1record_id,doi,title,year,venue,authors,abstract,citations,oa_pdf299094d1c4a802d09c48ab42b943130690d64f0f1,10.3390/buildings16122365,Indoor Environmental Quality as an Incremental Signal in Residential Valuation Using Hedonic Modeling,2026.0,Buildings,Shahrzad Sasani Babak; Saeed Malaekeh; Shadi Atalla; Amjad Gawanmeh; Saed Tarapiah,"This study presents an Indoor Environmental Quality (IEQ)-aware framework for residential valuation by integrating low-cost IoT sensing, transparent scoring, and hedonic price modeling. The analysis uses a dataset of 244 apartments across 12 districts in Tehran. It combines indicators of thermal comfort, particulate exposure, lighting, acoustics, stability, exceedance, and uncertainty with conventional housing covariates (area, age, bedrooms, floor level, renovation status, amenities, and accessibility proxies). Results show that pooled IEQ–price relationships are weak and confounded, whereas controlled specifications produce modest but consistent improvements in explanatory fit after IEQ features are introduced. Conventional location and structural attributes remain the dominant determinants of price per square meter. Still, IEQ contributes a non-redundant information layer that improves within-segment differentiation and interpretability for inspection and listing workflows. Methodologically, the framework extends beyond average comfort metrics by incorporating volatility, threshold exceedance duration, and sensor uncertainty, enabling uncertainty-aware reporting rather than sing",0.0,https://www.mdpi.com/2075-5309/16/12/2365/pdf?version=17813371713c911b3fd22af6e787ff69e7f09ef0ceca9cbebd6,10.5194/isprs-archives-xlviii-5-w4-2025-159-2026,Characterization of Surrounding Greenery and Housing Prices Using Street View Images Across Urban Local Climate Zones and Cities of Metro Manila,2026.0,"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences",Jeremiah L. Marimon; K. A. Vergara,"Abstract. Urban greenery is increasingly recognized as a factor that can influence residential property values. Despite this, few studies have explored this relationship using street-level perspectives or across diverse urban forms in developing megacities like Metro Manila. This study examines the relationship between visible greenery and housing prices in Metro Manila, utilizing Google Street View images sampled at 100-meter intervals and processed through a PSPNet-based semantic segmentation model pretrained on the ADE20K dataset to calculate the Green View Index (GVI). GVI values were averaged within 400-meter radius buffers around 1007 housing units sourced from Lamudi, with an 80-20 train-test split. Spatial autocorrelation analyses (Getis-Ord Gi* and Local Moran’s I) identified heterogeneous clusters of greenery and housing prices across the region. Hedonic pricing models, incorporating structural/housing attributes, location, proximity to amenities, facility density, and GVI, were estimated at three scales: the entire Metro Manila area, eight urban Local Climate Zones (LCZs), and individual cities. In the overall Metro Manila model, GVI exhibited a positive association with",0.0,https://isprs-archives.copernicus.org/articles/XLVIII-5-W4-2025/159/2026/isprs-archives-XLVIII-5-W4-2025-159-2026.pdf43f27945f1bec4deeef6b173dee1a3328ae4be2e6,10.15760/mem.14,"Understanding the Drivers of Forest, Residential, and Agricultural Land Values in Yamhill County Using Hedonic Models",2013.0,,Emily D. Dietrich,"Hedonic modeling is commonly used in land and property value estimations in an attempt to identify the impact that various attributes have on the market value of that property. The purpose of this study is to examine the factors contributing to land value of agricultural, forest, and residential properties in Yamhill County, as part of the Spatial Ecosystem Services Analysis, Modeling, and Evaluation (SESAME, http://www.pdx.edu/ecosystem-services/) project. This paper discusses the process and preliminary results of the development of hedonic models that will be utilized for predicting land value changes under future land conversion scenarios. Applying the models to future scenarios will provide insight into the effect that land conversion will have on market value of land in Yamhill County, in order to elucidate one component of the total land value in the area. Numerous studies have performed hedonic modeling in order to provide greater understanding of the non-market ecosystem service values that are contributing to land values, and it is necessary to have baseline information on the value of environmental attributes in order to identify potential policy and planning activities ",0.0,https://pdxscholar.library.pdx.edu/cgi/viewcontent.cgi?article=1001&context=mem_gradprojects5e336552beedf8dc351b10d3666b1cef39cb00bcc,10.12928/jampe.v5i2.12673,Defining and Measuring Housing Location in Appraisal and Hedonic Price Models: A Systematic Review,2026.0,JAMPE (Journal of Asset Management and Public Economy),Bagaskara Bagaskara; W. S. Ciptono,"Location is a complex, multidimensional aspect often highly preferential and dependent on personal preference. In general discussions, this may not pose a significant problem. However, in quantitative analyses such as housing appraisals (sales comparison approach) or applied research using the hedonic price model, the nature and characteristics of location can become a major issue. Even though location is often included in housing studies, there is no clear and straightforward way to measure it as a single variable. This challenge is exacerbated in Indonesia due to the lack of a valid and reliable property database. Therefore, this study conducts a systematic review that contributes to the understanding of how location can be measured objectively. The present study aims to propose an alternative method for defining and measuring the strategic location of housing in appraisal practice, particularly through the sales comparison approach. Based on the review, location is measured using two aspects: spatial aspects and circumstantial aspects. Generally, spatial aspects are much more dominant than circumstantial aspects. The identified location dimensions include distance to the Central",0.0,http://journal2.uad.ac.id/index.php/JAMPE/article/download/12673/68396a0a56967b97e63759cc23f57d3cd04c8bb94e7b0,10.53808/kus.2025.22.02.1340-ss,Assessing the Influence of Housing Attributes on Rent in the Urban Context of Khulna,2025.0,Khulna University Studies,M. Hasan; M. Hasan,"Rapid urbanization pressure is one of the major challenges of city corporation authorities in Bangladesh. House rents have become a major concern in Bangladesh. However, few studies have assessed the value of housing characteristics in the housing market in the southern region of Bangladesh. Hence, this study examines the value of housing characteristics on house rent in Khulna City, considering 180 respondents. The hedonic pricing method has been used to examine the value of four housing characteristics–structural, location, transportation, and neighborhood in the housing market. The study found that these housing characteristics explain the variation in housing rents significantly. Structural attributes–A shift of floor materials from tile to cement decreases house rent by 0.062 %, while a 1% increase in the number of rooms boosts house rent by 0.171%. Neighborhood characteristics–one discrete unit increase in a 5-point fire extinguishing system improvement scale from very poor to very good turnout, a 2.8% rent increase. Structural and neighborhood characteristics significantly influence the rental prices of both planned and unplanned areas. Further analysis showed that the ren",0.0,https://doi.org/10.53808/kus.2025.22.02.1340-ss7a25e8d966d143933dd0bc0cf6e8efd17d465c108,10.2139/ssrn.3803977,"The Housing Costs Associated with School Quality in the United States, 2009-2018",2021.0,Social Science Research Network,R. DiSalvo; Jia Yu,"In discussions of the barriers faced by the poor to accessing high-quality K-12 education, housing costs figure prominently. A common view is that housing costs more in school zones with higher quality schools. But is this view accurate? And if so, how much more does it cost? We investigate this question by relating two test-based school-level measures of educational quality, standardized test score levels and rates of student learning, with housing cost measures around the school based on homeownership, renting, or both. Our work contributes the first nationwide estimates of this relationship for rates of student learning, and to date the most comprehensive nationwide examination these associations for the levels of test scores. Using a model of choice, we justify our correlational analysis as reflecting the school quality cost curve faced by a household that strongly desires school quality at the expense of other amenities. We find that test score levels are strongly positively related to housing costs, and in particular exhibit a strongly convex (concave up) relationship when levels are measured in the conventional metric of student population standard deviations. Growth rates a",0.0,https://doi.org/10.2139/ssrn.38039778fb97de37e18676ad2491e0fc8a021a7274bffa4d,10.1177/00420980261456151,Gender homophily and rent premiums in platform-mediated shared housing: Evidence from Ziroom in urban China,2026.0,Urban studies,Weiyi Cao,"Digital platforms are increasingly reshaping how housing is accessed, priced, and experienced in cities. Platform logics, characterized by data-driven processes and algorithmic pricing, can reflect and reinforce existing social inequalities. This study examines how gender intersects with platform dynamics to shape rental outcomes in Nanjing, China, a major metropolis of nearly 10 million residents. Drawing on a year of data from 373,964 bedroom listings on Ziroom, the country’s largest shared rental platform, the study tests whether the gender composition of roommates influences rents. Hedonic regressions controlling for unit, building, and neighborhood characteristics show that all-female-roommate units command a rent premium, suggesting gender homophily is priced as a valued amenity. When interaction terms with room status are included, results show no initial rent difference under “reserve,” but a clear premium for all-female units under two leasing conditions: immediate move-in (“sign”) and subleasing (“sublease”). These findings suggest that the premium does not arise from platform-set base rents but from gendered preferences interacting with algorithmic pricing, whereby units",0.0,https://doi.org/10.1177/004209802614561519bb7951622c9d7100b8d94f5d590e8dc3dd6f4611,10.1007/s10901-024-10161-2,An approach for constructing spatially paired pseudo repeat-sales housing price indices in China,2024.0,Journal of Housing and the Built Environment,Haiyong Zhang; Zisheng Song; Zhuo Chen,"Constructing a reliable housing price index is crucial for accurately reflecting housing price dynamics and enhancing transparency in the housing market. However, existing methods for constructing housing price indices often confront many challenges, such as omitted variable issues in the hedonic model and constrained samples used in the repeat-sales model. To address these challenges, this study identifies a spatially paired relationship between complexes and develops a Spatially Paired Pseudo Repeat-Sales model to construct the housing price index. This approach offers two significant advantages: first, it enlarges the sample size used in the repeat-sales model at least 1.8 times; second, it effectively estimates the effects of spatial dependency and physical housing factors on prices while mitigating the impacts of unobservable factors through differentiation. The findings of this paper suggest that using the spatially paired pseudo repeat-sales model can significantly improve the estimation of housing price volatility, by approximately 13%. Moreover, the constructed housing price index model demonstrates significant robustness, even when the spatial weight settings are altered.",0.0,https://doi.org/10.1007/s10901-024-10161-210ccd9530d4678150bdec0d854811d6dbacc75ce4e,10.1007/s10901-026-10303-8,Housing market impacts of Urban Air Mobility in Seoul: evidence across district and parcel scales,2026.0,Journal of Housing and the Built Environment,Hanghun Jo; Gyuseon Kim; Minseok Kim; Hyounggeun Song; Yeolin Cho; Sungtaek Choi,"Urban Air Mobility (UAM) is emerging as a new layer of urban transport, yet its effects on housing markets remain unclear. This study examines how UAM deployment could reshape apartment prices and support more balanced urban development in Seoul. A scenario-based framework is developed to link reductions in generalized travel cost with spatial variation in housing values. A hedonic pricing model is estimated using 35,408 individual apartment transactions across 466 legal subdistricts, accounting for building characteristics, neighborhood amenities, socio-demographics, and accessibility to transport hubs. Six UAM scenarios, differing in network coverage and service performance, are simulated. Results show that housing price responses are not uniformly positive, but reflect net effects between accessibility gains and localized disamenities. Service quality improvements produce stronger housing price responses than network expansion alone, while integrated strategies generate the most widespread spatial effects. Relative gains expand toward peripheral districts where accessibility is currently constrained, whereas localized declines also emerge near vertiports, suggesting that noise-r",0.0,https://www.researchsquare.com/article/rs-7621928/latest.pdf11e656a737e981fa62b3e2abf991b986cfb8ca0266,10.61586/zoy7c,EVALUATING THE IMPACT OF LOCAL AMENITIES AND SPATIAL SPILLOVERS ON QUALITY OF LIFE,2025.0,"Mitteilungen Klosterneuburg : Rebe und Wein, Obstbau und Fruchteverwertung",Chich Ping Hu,"This article uses the Hedonic models proposed by Rosen 1979, Roback 1982, and Blomquist et12al. 1988 to establish the framework for calculating and evaluating inter-townships quality of life13in Taiwan. From view of local amenities, the results show that the quality of life index are less than14zero, which represents that compensation wage is higher than capitalized housing value from the15local amenities. The estimated quality of life by inference with the substitution of input data into16model is used as the dependent variable of spatial regression model to investigate the spatial effects.17The results show that the local amenities play various roles in the housing market and the labor18market. Quality of life is quite geographically characterized with spillover effects, which consists19with the Rosens report 1979. In Taiwan, quality of life index does not meet economic20development. Economic growth does not spill over completely to improve quality of life. Local21amenities factors are more of a threat to quality of life than value addition on quality of life. Many22natural disasters, unfavorable climate, unpleasant weather has been higher than positive23expectations. The distribution of qua",0.0,24f2060422567b2f0f0588497d67e536ce50a5a555,10.1515/ercl-2025-2009,"Contract, Property, and the Market: Regulating Short-Term Rentals in Comparative Perspective",2025.0,European Review of Contract Law,Alessio Sardo,"Abstract This article investigates the contractual and proprietary implications of short-term rental (STR) regulation in European cities. Focusing on Berlin, London, Milan, and Paris, it compares regulatory strategies ranging from targeted administrative restrictions to structural redefinitions of housing access. Drawing on private law theory and law-and-economics approaches, the article shows how STR regulation reconfigures the classical balance between contractual autonomy and property rights in light of urban policy goals. Empirical analysis complements the normative argument through a Hedonic Pricing Model estimated across the four cities. Using log-linear regressions with neighbourhood fixed effects and clustered standard errors on Inside Airbnb data, the model reveals robust and significant spatial price differentials. Entire flats and hotel-type listings command substantial premiums, while private and shared rooms are structurally penalized. These effects persist across specifications and point to a regressive structure in platform-mediated rental markets. By combining doctrinal and quantitative methods, the article frames STR regulation as a site of distributive recalibrati",0.0,https://doi.org/10.1515/ercl-2025-200925d502aa4f5b471e0f60cf0b9faa135be1c6b490dd,10.54254/2753-8818/2025.dl27981,Housing Value Drivers: OLS vs Random Forest,2025.0,Theoretical and Natural Science,Jingyu Zhang,"This study examines the determinants of California house prices using the 1990 census block-group dataset (n = 20,640) and a unified evaluation protocol with a fixed train/validation/test split (60/20/20). This study compares two linear hedonic baselines, OLS without distances (A1) and OLS with five geographic distances (A2), to a Random Forest (RF) trained on log prices and back-transformed to dollars via Duan smearing, while A1/A2 are estimated in levels (USD). Models are compared primarily by test-set R2in dollars. RF attains the highest accuracy (test R20.834, RMSE$47k), outperforming A2 (R20.648), while A2 improves modestly over A1, quantifying the incremental value of explicit geographic accessibility. Cross-method evidence converges on a stable core of determinants: median income and distance to coast rank first and second, followed by latitude/longitude and distances to major cities; structural count variables are comparatively weaker at the block-group level. Price-tier analysis (Low/Mid/High, defined at training P30/P70) shows stronger fit in the low tier and larger errors/heterogeneity at the high end. Robustness checks (Winsorization, Huber, dropping distances, higher-o",0.0,https://www.ewadirect.com/proceedings/tns/article/view/27981/pdf262a2afe89dae1a7c2843efc577b3513f4facba71e,10.1080/13467581.2025.2495898,Research on the spatial divergence characteristics and multi-scale influence of innovative industries and housing prices–the case of knowledge-intensive service industries in Guangzhou,2025.0,Journal of Asian Architecture and Building Engineering,Lu-Hui Qi; F. Wan; Yan Li; X. Pang,"ABSTRACT The impact of industries on housing prices has been a hot topic in urban geography research. The influence of knowledge-intensive business services (KIBS), as a representative of innovative industries, on surrounding housing prices has been understudied. This paper employs Spearman’s correlation analysis, Hedonic Price Model (HPM), Geographically Weighted Regression (GWR) and Optimal Parameters-based Geographical Detector (OPGD) to analyze the impact of Guangzhou’s knowledge-intensive industries on surrounding housing prices and spatial differentiation effects from multiple scales. The results indicate a significant spatial agglomeration and correlation between the two. From a meso-perspective, there is a critical value between industrial agglomeration and housing prices; beyond this threshold, central and peripheral areas begin to show negative correlation coefficients. Microscopically, there is a displacement effect between industrial agglomeration and housing prices, with the peak distance between the two exceeding 500–1000 m in the core urban area (Zhujiang New City) and even in the most industrially dense areas of the peripheral region (Nansha District), which also ap",0.0,https://doi.org/10.1080/13467581.2025.249589827ffac1b00cb130ff48266f9476aa638d75fe3e3cf,10.3390/su172411029,"Estimating the Economic Value of Blue–Green Spaces Generated by River Restoration: Evidence from Nanyang, China",2025.0,Sustainability,Yi-Nan Dong,"Urban river restoration provides significant ecological and social benefits, yet its market valuation remains underexamined in rapidly urbanizing inland cities. This study estimates the economic value of integrated blue–green spaces generated by the Bai River Ecological Restoration Project in Nanyang, China, using a spatially explicit hedonic pricing framework that links geocoded resale transactions with NDVI-based vegetation measures. Properties located within blue–green zones—areas jointly characterized by restored waterways and enhanced riparian greening—command an average price premium of 17.9% (CNY 1509/m2). Visual accessibility further increases housing values, although interaction effects indicate diminishing marginal premiums where multiple amenities co-occur. Quantile regressions show stronger capitalization effects in lower- and middle-priced segments, suggesting that ecological improvements may yield broad-based rather than elite-focused benefits. Spatial dependence diagnostics confirm significant autocorrelation, and Spatial Error Model estimates remain consistent with the baseline results. Overall, the findings provide robust evidence of supra-additive blue–green syner",0.0,https://www.mdpi.com/2071-1050/17/24/11029/pdf?version=1765290565289b7e497f7d5de0b8c09c2d7298d3ce1a0a551ae7,10.5505/jas.2021.30301,Determining the Economic Value of Historic Urban Districts through the use of the Hedonic Pricing Model: Ankara Castle District,2021.0,Journal of Ankara Studies,Leila Akbarishahabi,"Historic districts, which are an essential source of a society’s historical and sociocultural values, have a semantic value for urban residents. However, the cultural identity of these areas and the semantic values they offer to people are often ignored nowadays in urban design and planning studies. This study aims to reveal the desire of many people to live closer to historic districts, and to encourage local governments to be more aware of the need to conserve these urban areas due to their value as part of a local identity. As historic districts are not normally on the market, determining their semantic value is a complex process, but one that can be achieved with the Hedonic Pricing model. In this study, the effect on house prices of being close to the historic district of Ankara Castle was examined with the help of this Model. In the study, a total of 422 houses was examined, all of which were located within a radius of 1500 meters from the district of Ankara Castle, and the effect of the distance to Ankara Castle on the price of the houses was evaluated. According to the results, the desire to live close to the district was reflected in higher house prices. Houses located wit",0.0,https://doi.org/10.5505/jas.2021.303012941a24683a4b966679145f8c822178e61a9a339a4,10.56261/built.v24.266592,"A Comparative Hedonic Analysis of Condominium Asking Rents in Bangkok, Phuket, and Pattaya",2026.0,"International Journal of Building, Urban, Interior and Landscape Technology",Than Dendoung,"This study estimates condominium rental price differentials from online listings across Thailand’s three major tourist cities, using Bangkok as the benchmark for Phuket and Pattaya while controlling for observable unit characteristics. Intercity differentials are measured with a hedonic regression in which the dependent variable is the natural logarithm of monthly rent (in Thai baht). Model 1 controls for the number of bedrooms, while Model 2 adds unit size through log(size_sqm), allowing the effect of unit composition on estimated city effects to be assessed. Confidence intervals at 95% are based on heteroskedasticity-robust (HC1) standard errors. The main finding is the magnitude and persistence of city-level effects relative to Bangkok. In Model 1, Pattaya has a monthly rent 11.5% lower (95% CI -13.3% to -9.6%) and Phuket 23.8% higher (95% CI 21.4% to 26.3%). When apartment size is included in Model 2, the monthly rent in Pattaya is 16.8% lower (95% CI -18.3% to -15.2%) and in Phuket 14.3% higher (95% CI 12.5% to 16.2%), and the model fit improves as the adjusted R-squared rises from 0.491 to 0.663. These results indicate that factors beyond apartment size drive rental differenc",0.0,https://ph02.tci-thaijo.org/index.php/BUILT/article/download/266592/1745553075c78bcd5379d61a32a5887b3e2824eab05cb124,10.2139/ssrn.4229198,Does Working-From-Home Reshape the Urban Morphology? Early Evidence From Rental Gradient Analysis in Auckland,2022.0,Social Science Research Network,Ka-Shing Cheung; E. Yiu; D. Wong,"Since the outbreak of COVID-19, work-from-home (WFH) and e-commerce have become much more common in many cities. Many news reports have contended that households are leaving city centres and moving into bigger and better houses in the suburbs or rural areas. This emerging trend has been redefining the traditional theory of residential location choices. Proximity to CBD is no longer the most critical consideration in choosing one’s residence. WFH and e-commerce flatten the traditional bid rent curve from the city centre. This study is one of the earliest attempts to identify the pandemic’s impact on house rents by applying a rental gradient analysis to compare the pre-and post-COVID-19 periods in Auckland. We examined micro-level housing rental listings in 242 suburbs of the Auckland Region from January 2013 to December 2021 (108 months) and found that the hedonic price gradient models suggest that there has been a trend of rental gradient flattening and that its extent was almost doubled in 2021. Rents are also found to be increasing more in lower-density suburbs. The results imply that the pandemic has accelerated the trend of WFH and ecommerce. We also scrutinised this WFH trend ",0.0,https://doi.org/10.2139/ssrn.4229198317ae8515da5ca78a174cf983ae81cb942344a6e00,10.1108/pm-05-2025-0075,Valuation of the economic impact of a disaster event,2025.0,Property Management,M. Razali; K. Achu,"32 33 This study investigates the impact of environmental disasters on residential property values, focusing on the Putra Heights gas pipeline explosion and the Sungai Kim Kim River industrial waste pollution in Malaysia. It aims to develop and test a spatially explicit valuation framework that captures both tangible and perception-driven effects, enabling more accurate post-disaster property assessments.34 35 36 37 An extended hedonic pricing model, integrated with spatial econometric techniques – the spatial lag model (SLM) and spatial error model (SEM) – was applied to property transaction data before and after the disasters. Variables included structural and locational characteristics as well as disaster-specific factors such as hazard proximity, insurance accessibility, public perception indices and media coverage intensity. Geographic Information Systems (GIS) were used to quantify spatial spillover effects.38 39 40 41 Environmental disasters caused both direct and indirect devaluation of properties, with average losses per property ranging from RM 13,500 to RM 60,500, and total market losses in high-impact zones reaching RM 12–18 m. Spillover effects extended up to 800 m from hazard s",0.0,423083315dbf7ccb4707fcede5054b714edabae3de,10.21837/pm.v24i40.1962,ADVANCING MALAYSIAN HOUSE PRICE INDEX PREDICTIONS: THE POTENTIAL OF ARTIFICIAL NEURAL NETWORK,2026.0,PLANNING MALAYSIA,Aida Julia Aminuddin; N. H. Adi Maimun; Hishamuddin Mohd Ali; Shang-Yin Tan; Abdul Jalil Omar,"This study develops a localized house price index by employing an Artificial Neural Network (ANN) forecasting model to enhance the organization and efficiency of the Malaysian property market. Traditional Malaysian House Price Index (MHPI), based on a hedonic model, exhibits multicollinearity among house attributes, limiting its ability to accurately capture house price trends. While MHPI provides aggregate indices, the construction of disaggregate indices remains underexplored, potentially reducing the effectiveness of local housing market analysis and long-term planning. This research aims to identify key house attributes influencing prices and to evaluate the capability of ANN in forecasting the Johor Bahru house price index. The study applies ANN to disaggregate transaction data of double-story terrace houses in Taman Mutiara Rini and Taman Bukit Indah, comparing actual and forecasted prices using R-squared (R²), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), and Mean Absolute Deviation (MAD). Findings reveal significant differences between forecasted and actual indices, demonstrating ANN’s superior ability to capture local price variations. The study hig",0.0,https://www.planningmalaysia.org/index.php/pmj/article/download/1962/163943fd9e2d589e4cf3d85a4769aff0adb4062a87cf53,10.57199/jgcr.2026.5.2.439,"Analysis of Apartment Price Determinants Based on Differences in Characteristics of Regional Submarkets : Focusing on Haeundae-gu and Saha-gu, Busan",2026.0,Global Convergence Research Academy,Cheon-Woo Lee; Seongsoo Seo,"This study identified Haeundae-gu and Saha-gu in Busan Metropolitan City, which are expected to differ in regional characteristics, conducted a comprehensive survey of iapartment transaction data in 2025, and compared and analyzed price determinants using a hedonic price model. The key analysis results are summarized as follows. First, based on prior research, a total of 20 variables were included as explanatory variables. As a result, for Haeundae-gu, 18 variables were significant, excluding the number of rooms and the shortest distance to large marts, and the explanatory power was also high at R²=0.889. For Saha-gu, the significance of 15 variables was confirmed, excluding the number of rooms, entrance (mixed type), middle school accessibility, shortest distance to large hospitals, and gentle slope, and the explanatory power was also high at R²=0.869. In particular, as a result of testing using squared terms to verify the non-linear effects of the area and elapsed years variables, The estimated turning points were 224.6㎡ and 30.02 years in Haeundae-gu, and 163.2㎡ and 32.3 years in Saha-gu. In addition, significant differences were found in the degree of influence of brand value a",0.0,4492e7bed78640da66954d0cbce56d4e28bb729ba6,10.38100/jhuf.2026.11.2.61,"Effects of industrial heritage adaptive reuse on apartment prices:45 Evidence from F1963 in Busan",2026.0,Journal of Housing and Urban Finance,J. Jang; Yeol Choi,"Industrial facilities created through industrialization often become idle as urban economies restructure, leaving underused industrial sites as persistent spatial challenges. In this context, industrial heritage has been increasingly reframed as a resource for urban regeneration. Here, a key strategy is adaptive reuse: reprogramming existing industrial buildings while retaining historical and physical traces. However, empirical evidence on whether and how such projects generate neighborhood-level externalities that are capitalized into housing prices remains limited. This study examines F1963, an adaptive reuse project completed in 2016 in Busan, South Korea, and estimates its effect on nearby apartment prices. We analyze apartment transaction records from 2008 – 2022 using a hedonic pricing framework combined with a quasi-experimental propensity score matching – difference-in-differences design. We find a statistically significant post-reuse price premium within the treatment area, with an estimated magnitude of approximately 1.5% per square meter. Thus, the adaptive reuse of industrial heritage can generate measurable neighborhood benefits that are capitalized into housing values",0.0,http://www.ejhuf.org/download/download_pdf?pid=jhuf-11-2-614685ec88163a881d2f9a23ced6110d5e4e05b48d09,10.15760/etd.8061,Urban Traffic Arterials and the Sale Price of Single Family Houses in Portland: A Hedonic Analysis of Impacts,2022.0,,P. Wuest,"An abstract of the thesis of Philip Wuest for the Master of Urban Studies degree presented August 6, 1997. Title: Urban Traffic Arterials and the Sale Price of Single Family Houses in Portland: A Hedonic Analysis of Impacts. This thesis explores the hypothesis that the prices of single family houses are negatively influenced by proximity to urban arterial roadways. A hedonic price.model is developed that tests the effects of traffic volumes and proximity on sale price. Using a data set of sale records from Portland Oregon in 1994, a traditional hedonic model is developed based on housing and neighborhood characteristics. Using a geographic information system, each sale record is associated with the nearest arterial roadway, and the data on distance to the roadway and level of traffic is returned to the sale record. These data are then applied in the hedonic equation. The results indicate that distance to an arterial roadway has a much larger effect than traffic volume alone. It is also found that the effects of high traffic arterials diminish rapidly with distance, becoming difficult to distinguish beyond about 2/3 of a city block. The estimated effect on sale price of close proxim",0.0,https://pdxscholar.library.pdx.edu/cgi/viewcontent.cgi?article=7282&context=open_access_etds4738064fc5c9cbac2b1208cd20dae53602d642ec2c,10.3390/land15101839,Comparing Designated Green Areas and Satellite-Derived Vegetation Greenness in Housing Price Prediction Using Explainable Artificial Intelligence,2026.0,Land,Dongwon Ko; David Park; Junwoo Park,"The study examines how formally designated green areas and satellite-derived vegetation greenness, measured using the Normalized Difference Vegetation Index (NDVI), are associated with apartment prices in Seoul. Using 10,629 apartment transactions from 2022, we compare a semi-log hedonic price model with Random Forest, XGBoost, and LightGBM and apply explainable artificial intelligence techniques to interpret the best-performing model. The results show that a higher proportion of designated green area is generally associated with lower predicted housing prices, whereas higher NDVI values are associated with higher predicted prices, although this positive predictive relationship weakens at higher NDVI levels. These contrasting patterns indicate that planning-based green-area designations and satellite-observed vegetation greenness capture different dimensions of the residential environment. Because NDVI measures vegetation greenness and vigor rather than its maintenance, accessibility, usability, or perceived quality, the findings should not be interpreted as evidence of vegetation quality or residents’ preferences for particular types of green space. The study demonstrates the valu",0.0,https://doi.org/10.3390/land1510183948eb856d8727bb0ad0a99eb28933dbd04db3ee22b0,10.54254/2977-5701/2026.31822,Resource-residential dual drivers: an empirical study on regional heterogeneity in Beijing's secondary housing prices,2026.0,Journal of Applied Economics and Policy Studies,Jiayue Zhang,"This research explored the factors that determine housing prices and their regional differences in Beijing's second-hand housing market using complete transaction data from 2024 covering all 16 administrative areas, adopted the Hedonic Price Model and carried out separate Ordinary Least Squares (OLS) regressions for different sub-markets, the results showed a clear two-part difference in how prices were formed which was described as being ""resource-driven"" compared to ""residence-driven"", in central urban areas, housing prices were mainly influenced by proximity to top-quality public resources and there was a large price increase for apartments having three or more bedrooms, on the other hand, in suburban zones, market evaluations concentrated more on fundamental living features showing a definite preference for south-facing directions and medium to large sized units, moreover, the additional impacts of important structural elements varied significantly among these regions, the discoveries offered strong empirical proof to back location-specific regulatory measures for the existing housing supply in mega-cities such as Beijing and also provided useful information for market players ",0.0,https://jaeps.ewapub.com/article/view/31822.pdf49ec22772ca14f5506d3c84bededf6b90711878d36,10.21837/pm.v23i38.1886,QUANTIFYING NATURE'S IMPACT: FLOOD VULNERABILITY AND THE MALAYSIAN RESIDENTIAL MARKET,2025.0,PLANNING MALAYSIA,Siti Nur Husna Abd Rahman; N. H. Adi Maimun; Aida Julia Aminuddin; Umi Syahiidah Suhaidi; Umussaa’dah Adam,"Flooding, a frequent and devastating natural disaster, poses significant risks to residential property markets, including in Malaysia. This study aims to quantify the impact of floods on house prices in Johor Bahru, a region increasingly prone to flash floods. Approximately 468 property transactions from 2013 to 2022 were analysed using the Hedonic Pricing Model to determine how flood risk influences house prices. Contrary to the global consensus that flood exposure depresses property prices, the results indicates a modest price premium effect for properties located within flood-prone areas. This suggests that local market dynamics including strategic location, established neighbourhood amenities, and community risk adaptation offset the typical price discounts observed internationally. The findings offer new empirical insights for Malaysian urban studies and highlight that environmental risks may not be universally internalised in the same way across markets. The findings also offer insights for homeowners, buyers, planners, valuers, insurers, financiers, and policymakers, guiding informed decision-making in flood risk management and urban planning. Future research may explore oth",0.0,https://doi.org/10.21837/pm.v23i38.188650972e3c33bc16dcaeb5855c3af2beca214d69afa4,10.1108/ijhma-05-2025-0110,The avian influence: examining the impact of birds on house prices,2025.0,International Journal of Housing Markets and Analysis,Lei Zhang; Shan Zhang,"51 52 The purpose of this paper is to disentangle the often-overlooked relationship between biodiversity, measured by bird abundance and species richness, and residential property values.53 54 55 56 While conventional determinants such as location, amenities and economic conditions typically shape house prices, the ecological characteristics of a neighborhood – including its biological abundance and species richness – can also exert a significant influence. By integrating novel citizen science eBird data with housing sales records from the Hampton Roads region of Virginia, the authors employed a hedonic pricing model and a quantile regression approach to examine the impact of biodiversity on house prices.57 58 59 60 The analysis reveals a statistically significant positive association between bird biodiversity and house prices, with the strongest effects observed in close proximity to the properties. While avian presence at greater distances still influences property values, its impact diminishes with distance. The quantile regression results suggest that bird abundance has a more pronounced effect on higher-priced residences compared to lower-priced ones. It was also found that the relation",0.0,61bb6fb9c2e62bdab0a807879a1005180240426e3d,10.1108/ijhma-04-2026-0106,Stray dog density and residential property prices: a ward-level hedonic analysis from urban India,2026.0,International Journal of Housing Markets and Analysis,S. Walia,"62 63 This study aims to examine whether stray dog density, an urban environmental externality prevalent in developing cities, is negatively associated with residential property prices in Indian housing markets.64 65 66 67 A cross-sectional, zone-level hedonic analysis is conducted for 32 administrative wards and planning zones across Mumbai and Bengaluru. Residential price per square foot (Q4 2025) is regressed on stray dog density from municipal Animal Birth Control (ABC) program censuses and human population density. Linear and log–log ordinary least squares specifications are estimated, with standard error selection justified by Breusch–Pagan tests. Robustness is assessed through high-leverage observation exclusion and city fixed effects.68 69 70 71 A statistically significant negative association is observed between stray dog density and residential property prices in the pooled two-city sample. In the preferred log–log specification, a 1% increase in stray dog density is associated with a 0.39% decline in price per square foot. The coefficient retains most of its magnitude and sign under city fixed effects but is not conventionally significant (p = 0.148), while within-city regressions",0.0,725c3c1bbb5000f225cba78ab64204be9ba1ae6461,10.3390/buildings16061171,"Zoning Regimes, Official Land Values, and Housing Price Formation",2026.0,Buildings,Ya-Wen Wu; Wei-Hsi Hung; Chen-Yi Sun,"This study examines how zoning regimes mediate the capitalization of officially assessed land values into housing prices in a high-density metropolitan housing market. Using transaction-level housing data from New Taipei City, Taiwan, we estimate a hedonic pricing model combined with a boundary-based spatial comparison that restricts observations to properties located near zoning borders. The results indicate that official land values are significantly associated with housing prices but are only partially capitalized, with an estimated elasticity of approximately β ≈ 0.37 in the baseline specification. Interaction models further reveal that capitalization elasticities vary systematically across zoning regimes, suggesting that planning regulations influence how administratively determined land values are translated into market prices. These heterogeneous capitalization patterns remain stable across alternative boundary bandwidths and model specifications. The findings highlight the institutional role of zoning systems in shaping the relationship between administratively assessed land values and housing market outcomes. More broadly, the study contributes to the literature on housing",0.0,https://www.mdpi.com/2075-5309/16/6/1171/pdf73fc259a55d15c31e8e716a1ae0ef9c7196a48c4ec,10.21837/pm.v23i38.1887,EXAMINING THE TRANSIT ACCESSIBILITY PREMIUM OF BUS RAPID TRANSIT ON HOUSING PRICE,2025.0,PLANNING MALAYSIA,Chin-Tiong Cheng; Kai Tan; Alan Chong Kim Wing; H. Chin,"Public transportation system is crucial in supporting the urban mobility of a country including Malaysia. This system is built to alleviate the urban congestion in the cities. Good connectivity between locations can be achieved through a combination of bus and rail transit. Among these transit systems, Bus Rapid Transit (BRT) holds both characteristics of bus and rail transit. BRT not only operates on a specific express lane but also offers benefits such as ease of deployment and lower investment costs compared to rail transit systems. However, the impacts of BRT on residential prices has yet to be explored for Malaysian context. Understanding the response of residential market to BRT could provide valuable insights for stakeholders in formulating appropriate strategies and policies. This study applies the difference-in-differences (DiD) method and hedonic pricing model for assessing the Transit Accessibility Premiums (TAP) of BRT stations. The results reveal that residential prices increased by 6.06% after the government announced a new BRT in Bandar Sunway. The variation in premium is highly associated with the proximity to BRT stations. These insights serve as crucial informati",0.0,https://www.planningmalaysia.org/index.php/pmj/article/download/1887/156474c67ce856a98062e3ca8cde96abd879b34a2d52e2,10.4114/ia.v19i58.1156,Artificial Intelligence (AI) techniques to analyze the determinants attributes in housing prices,2016.0,,J. Núñez,"The econometric approach to obtain the value of a property began with hedonic modelling, which were based on a set of property attributes, internal or external, associated to each particular dwelling. The final sale value can be estimated, and also the marginal prices of each exogenous explanatory variable. A good alternative to the hedonic approach is based on several Artificial Intelligence (AI) techniques, such as artificial neural networks (ANN), these tend to be more precise. Both methodologies are compared, and a case study is developed using data from Seville, the larger town in the South of Spain. Resumen El análisis abordado tiene como objetivo la obtención de modelos econométricos de valoración de vivienda. Partiendo de una serie de atributos referidos al inmueble -internos y externosse pretende obtener el precio de venta del mismo, estimando además el peso marginal de cada uno de los atributos que explican el precio global. Debido al carácter heterogéneo de estos bienes se utiliza desde hace varias décadas la Metodología de Precios Hedónicos. Sin embargo, las técnicas de Inteligencia Artificial (IA), en especial las Redes Neuronales Artificiales (RNA) suelen ser más prec",0.0,http://journal.iberamia.org/index.php/intartif/article/download/37/8/47750b73ae4efcbfc1f6fb6c4aede6220c03499c9aef,10.15396/eres2019_306,Residential rent indices in a long-term trend for the french case: An application of the hedonic method,2019.0,26th Annual European Real Estate Society Conference,Alexis Pourcelot,"The purpose of this paper is to understand the housing rents formation and their dynamics over almost half century (1970-2013) by sector (private/public) and location (Paris region, big, medium and small urban areas). We underline the role played by physical and locational characteristics in the formation of rents. Dynamics and cycles in rents over the period are tackled using macro-economic factors as well as market variables and housing policy. Likewise, we are able to show the impact of specific housing policies such as APL on rents. This stratified approach, will give a relevant overview of the French market for international investors. Likewise, valuation of asset prices is relevant and useful for practitioners (appraisers, brokers, developers, investors, fund managers, analysts and market researchers) but also policy-makers. In order to conduct this analysis we will use the French Housing Survey from the French Statistical and Economic Study Institute (INSEE). This survey describes the French housing stock as well as the household tenure choice and their housing consumption. Physical characteristics and dwelling quality such as size, sanitary convenience, heating, location, e",0.0,769cf172e9f98dd8e4763e5e90a4b1cec2fc594c55,10.1177/23998083261460686,Scaling-informed natural submarkets: A bottom-up approach to segment housing markets in the Yangtze River Delta,2026.0,Environment and Planning B Urban Analytics and City Science,Zihan Xu; Yunjie Feng; Qimeng Song; Yao Shen,"Urban housing markets exhibit pronounced spatial heterogeneity shaped by multiple spatial factors, resulting in scaling characteristics and hierarchical structures typical of complex systems. These properties provide an alternative perspective for delineating housing market areas and interpreting inter-market linkages. This study introduces the concept of natural submarkets, defined as spatially contiguous housing clusters exhibiting both hierarchical scaling in price patterns and consistent hedonic price determinants. We implement this concept through a bottom-up segmentation framework that combines an improved head/tail breaks with hedonic model fit, enabling data-driven delineation of market boundaries and comparative regional analysis. Applied to 26 cities in the Yangtze River Delta (YRD), China, the proposed method yields a more objective and interpretable representation of price differentiation and scaling properties than conventional classifications. The results indicate that economically advanced cities may exhibit either multi-level submarket structures with well-defined hedonic relationships or more complex hierarchical structures with weakly defined pricing mechanisms. F",0.0,778d1c37ceefc6a51f84e7cd47fd691f63e86a4892,10.1186/s40537-020-00348-z,Impact of rail transit station proximity to commercial property prices: utilizing big data in urban real estate,2020.0,Journal of Big Data,M. Berawi; P. Miraj; G. Saroji; M. Sari,"Urban transport investments have contributed to the exponential increase of value from land and properties around the built infrastructure. Although literature had shown evidence of value uplift from the residential property due to transit development, little is known about the impact on commercial property values. This paper aims to evaluate the impact of rail transit proximity to the commercial property market by taking into account the pre-operation of the LRT project in Jakarta, Indonesia. This study utilizes a big data approach to accelerate research data processing by employing data mining method, as well as geographical information system (GIS) and hedonic price modeling (HPM) to investigate the property prices to formulate empirical evidence for the research. The results show opposite evidence compared to previous studies which argued that accessibility may contribute to the property price when closer to the transit station. The findings indicate that proximity to rail transit has an insignificant impact on the commercial property price compared to other variables such as building size, number of rooms, location, and hospitals. A comparison of the findings between this rese",0.0,https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-020-00348-z787f45f70c2c2271b7539c0915321311343666b384,10.1007/s11146-025-10026-7,The Grass Isn’t Always Greener: How Crime Influences Property Values Near Urban Greenlines,2026.0,Journal of real estate finance and economics,Jason De Freitas; Fatemeh Kamkar; Mark A. Sunderman; Velma Zahirovic-Herbert,"79 Green spaces, including greenlines and greenways, are widely regarded as amenities that enhance residential property values through aesthetic appeal, recreational opportunities, and improved community connectivity. However, these benefits may be offset by crime, which deters homebuyers and diminishes perceived safety. This study examines how proximity to greenlines affects property values in Memphis, Shelby County, Tennessee, and how this relationship is shaped by local crime conditions. Using a hedonic pricing model and a spatial Difference-in-Differences framework, we analyze property transactions alongside detailed measures of property, violent, and other crime types. We find that while greenlines are generally associated with increased property values, this effect is significantly moderated by crime—especially property crime. In high-crime neighborhoods, proximity to greenlines can decrease property values, suggesting that perceived safety concerns outweigh amenity benefits. Our findings suggest that perceived safety plays a central role in shaping the value residents place on green infrastructure. Although focused on Shelby County, the results offer broader insight into how ",0.0,https://link.springer.com/content/pdf/10.1007/s11146-025-10026-7.pdf80fabd38e3d684b3496fdc9802ac35009ea99845f2,10.37407/kres.2026.44.3.159,Reliability Assessment of Machine-Learning Automated Valuation Models : Apartment-Complex Holdout Validation in the Seoul Metropolitan Area,2026.0,Korea Real Estate Society,Jae H. Kim,"This study evaluates the reliability of machine-learning automated valuation models (AVMs) when repeated apartment-complex observations are explicitly controlled. AI-based AVMs refer here to random forest, LightGBM, and XGBoost, which are compared with an unpenalized hedonic OLS benchmark using 129,237 apartment transactions assigned to 2,371 composite complex groups. The source file combines 2021-2023 transactions with 2023 management-fee records, but transaction dates are unavailable; the temporal validity of some management-fee inputs therefore cannot be verified, and related results are interpreted as retrospective and conditional. Row-wise random splitting and apartment-complex holdout testing are treated as separate operational evaluation regimes with different test samples, not as a paired estimate of the pure effect of the split rule. Under row-wise random splitting, random forest yields the lowest log-price MAE (0.1026). Under complex holdout testing, OLS has the lowest point estimate (0.1839), but the difference from LightGBM (0.1960) is not statistically significant (Delta=0.0121, 95% CI [-0.0036, 0.0282], p=0.135); XGBoost and random forest have significantly larger err",0.0,8102eb974cc5cbf358d7efb5a03dba50558823408f,10.64361/14445921.2025.212322,"Evaluating Users’ Willingness to Pay for Private Sector Participation in Water Infrastructure Provision: Evidence from Lagos, Nigeria",2025.0,Pacific Rim Property Research Journal,T. Ayodele; A. Olaleye; Olayemi O. Olatunde,"The importance of water infrastructure to housing quality, enhanced property values and economic development cannot be overemphasized This study examined the investment potential inherent in private sector participation (PSP) in water infrastructure by evaluating users' willingness to pay for the private provision of water infrastructure in Lagos, Nigeria. The study collected primary data using a closed-ended questionnaire. With a focus on three local government areas in Lagos, 296, 172, and 57 buildings were selected in Ikeja, Surulere, and Shomolu respectively through multistage sampling. Selecting one adult resident in each building, 525 questionnaires were administered, and 450 (85.71%) questionnaires were retrieved and analyzed. Descriptive and inferential statistical techniques were used for data analysis. The results of the gap analysis between the users’ satisfaction and accessibility showed a negative mean difference, revealing a low level of satisfaction with the existing water supply options. The users’ willingness to pay for the benefits of private water provision showed that better quality of service to consumers (3.84), transparency in charges (3.78), improved service",0.0,8260dfdba30857ca7267b53c72edae402a2b06bc12,10.21834/ajbes.v3i12.125,GIS and Hedonic Pricing for Green Space in Housing Area,2018.0,Asian Journal of Behavioural Studies,Norzailawati Mohd Noor; M. Asmawi; Alias Abdullah,"This paper explores a framework that combines Geographic information System (GIS) with Hedonic pricing method in improving the analysis and determining the value of green spaces with housing prices in Subang Jaya, Malaysia. The previous study found that proposed combination between GIS and Hedonic pricing method for the same purpose has not been fully explored particularly in Malaysia. Findings show the proposed combined method leads to improved understanding and representation of urban dynamics and regeneration process, furthermore will encourage a sustainable setting of the environmental amenities in improving the geospatial technologies respectively.Keywords: GIS, Hedonic Pricing Method, green Spaces and urban regenerationeISSN 2398-4295 © 2018. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture,",0.0,https://ajbes.e-iph.co.uk/index.php/ajbes/article/download/125/pdf8397fda1ba42ae86574d254847d7472d9d602c0931,10.1108/ijhma-07-2026-0233,Housing price formation after the 2023 Türkiye earthquakes: hedonic and spatial evidence from the Iskenderun housing market,2026.0,International Journal of Housing Markets and Analysis,İsmet Demirağ; Murat Sağır; Mehmet Duruel,"84 85 This study aims to examine how the 2023 Türkiye earthquakes reshaped housing price formation and residential valuation patterns within the Iskenderun housing micro-market.86 87 88 89 This research uses publicly available micro-market listing data. This study applies hedonic pricing models combined with a Generalized Method of Moments Spatial Error Model to control for unobserved geographical spillovers.90 91 92 93 Post-disaster properties command a 16.7% price premium. A non-linear, U-shaped vertical price gradient emerged, where both lower and upper floors command premiums relative to middle floors. Additionally, the price advantage associated with centrally located properties declines as building age increases, indicating a horizontal revaluation of residential location after the earthquake.94 95 96 97 This research relies on public listing prices rather than final transaction data because of limited registry transparency, and it is geographically limited to a single micro-market.98 99 100 101 The findings of this study provide critical insights for urban planners, appraisers and policymakers to understand post-disaster market dynamics, support post-disaster housing policy and enhance market r",0.0,10204fde59cf7989359e7c12d59dbe1dae88b6021ef,10.14254/2071-789x.2026/19-2/6,"Hedonic pricing, rental yield and housing affordability: The Czech micro-apartment market and its lessons for Central and Eastern Europe",2026.0,Economics & Sociology,E. Hromada; Renata Schneiderova-Heralova; K. Čermáková; Ondřej Venhoda; Irina Alina Popescu,"Micro-apartments, the smallest self-contained dwellings, have expanded rapidly as a response to the housing affordability crisis, yet they remain almost unstudied in the Central European context. This paper analyses the micro-apartment segment (16-23 m²) in the Czech Republic and compares it with two larger categories of small apartments, using listing-level data from January 2018 to June 2026. It combines descriptive analysis with hedonic regression, quantile regression, an Oaxaca-Blinder decomposition, and a survival analysis of time on market. Micro-apartments are simultaneously the cheapest apartments in absolute terms and the most expensive per square metre; this unit-price premium of about 22 percent is genuine and structural rather than a product of location or composition, and it strengthens in the upper price bands. The premium is economically rational, underpinned by the highest gross rental yield of all categories, which makes the segment both an affordable outlet for budget-constrained buyers and an investment product for small landlords. Micro-apartment prices are also the most sensitive to mortgage rates, whereas the smallest units sell at least as quickly as larger o",0.0,https://www.economics-sociology.eu/files/6_1731_Hromada et al.pdf103b8a14343f047b4c80e9c247f7030152d5a952ddb,10.15793/kspr.2013.79..002,임대주택단지 입지여건이 주변 아파트 가격에 미치는 영향 분석,2013.0,,정훈 김,"The purpose of this study is to analyze empirically the effect of public housing complex’s location conditions upon the neighborhood apartment prices in Daegu. The dependent variable is the price per 3.3m² of Sales House, and for the independent variables this study identified the variable revealed by previous studies, with correlation analysis and selected it with household properties, complex properties, regional characteristics, and location characteristics. For research methods, this study used HPM (Hedonic Price Model) in statistical method to grasp the effect of public housing complex’s location conditions upon the neighborhood apartment prices from 25 public houses located in Daegu’s land development district. This study used statistical program of SPSS 18.0 for the empirical analysis by each model. The analysis resulted in that the normal public housing complex’s location conditions has the positive effect upon the neighborhood apartment prices. Just in the research result of this paper, it is judged to have a positive effect upon the surrounding condominium if traffic and education and culture and leisure facilities are built parallel for its surrounding to which would be ",0.0,https://doi.org/10.15793/kspr.2013.79..0021043ba18cfc830a3ff17d1287a7246a714df85b77b5,10.15396/eres2012_087,Additive hedonic regression models for the Austrian housing market,2012.0,,Wolfgang A. Brunauer; W. Feilmayr,"In this paper we derive hedonic regression models for single family homes that account for nonlinearity in price functions as well as spatial heterogeneity. House prices belong to four hierarchical levels of spatial units: Census tracts (level 1), municipalities (level 2), districts (level 3) and federal states (level 4). Additionally to individual house attributes, locational covariates are available on three of these resolutions. We apply a multilevel version of structured additive regression (STAR) model on this data, which allows for nonlinear covariate effects and time trends as well as spatial effects to capture unexplained spatial heterogeneity on every level of the hierarchy. The model proposed is particularly useful for automated valuation purposes, as the decomposition of spatial effects results in improved predictive quality even in the case of unobserved spatial units. Furthermore, external price information can be integrated on various levels of the model. The presented results include nonlinear covariate effects of house and locational attributes as well as the distribution of spatial heterogeneity over Austria on maps. We also show how the inclusion of external house",0.0,https://eres.architexturez.net/system/files/pdf/eres2012_087.content.pdf105ce99fea2df84a3db4ec858a1d9b09e166bf15099,10.12928/jampe.v3i2.9335,Application of Hedonic Pricing Model and Geographic Information System on Property Valuation in Yogyakarta,2024.0,JAMPE (Journal of Asset Management and Public Economy),Nurisqi Amalia; Nur Aini Yuniyarti; F. Prativi,"This study aims to: 1) identify the differences in housing choices between Generation Z (students) and the previous generation (parents or guardians); 2) determine the factors influencing housing purchase decisions; and 3) map the areas of interest for Universitas Gadjah Mada (UGM) students based on price. The research employs a combination of the Hedonic Pricing Model (HPM) and Geographic Information System (GIS), a method that remains limited in the field of property research. The findings reveal that significant factors affecting property prices are building area and location, with the majority of UGM students choosing to reside in Ngaglik District, Sleman Regency. Sleman Regency is also the predominant area where UGM students purchase housing in Yogyakarta. Key attributes influencing UGM students' housing decisions include a safe neighbourhood, residential environment, and distance from waste centers. This research contributes valuable information to property appraisers regarding property price distribution in Yogyakarta and its influencing factors, and provides crucial insights for effective decision-making and policy implementation in regional economic development planning, e",0.0,http://dx.doi.org/10.12928/jampe.v3i2.933510691c4d23f447eb6303b2fcc74d26c9eff18216fc2,10.24843/jekt.2026.v19.i01.p01,Affording Homes in Yogyakarta: An Empirical Analysis of Local Housing Market Affordability,2026.0,Jurnal Ekonomi Kuantitatif Terapan,Bagaskara; Yudistira Permana; M. Suwandi,"Issues surrounding the difficulty of buying a house for local people in the Special Province of Yogyakarta are undeniable. This raises the question: can local residents afford a decent house? This study aims to develop a framework to describe housing affordability using surveys and econometric methods. A hedonic price model was created based on data from 174 houses in urban areas in Yogyakarta. This model estimates house prices considered appropriate, derived from a survey of 283 local residents who do not own a house. The results indicate that local residents cannot afford to buy a house. The regression model estimates house prices higher than the mean or median values of respondents' perceptions of affordability. Surveyed respondents deemed houses with minimum specifications as follows: a lot size of 53.6 m², building size of 89.4 m², front road width of 4.4 m, and a distance of 2.7 km to shopping facilities. The estimated price for such housing ranges between IDR 300,000,000 and IDR 400,000,000. These findings highlight a gap between market prices and local affordability. The government can use these specifications as input to design policies that provide affordable housing for ",0.0,https://ejournal1.unud.ac.id/index.php/jekt/article/download/1921/2599107cb1bc7e2c84417458119d53a40d6ec9c84167bc6,10.30585/icabml-cp.v2i1.209,The House Price Dynamics and the Macro-Economy: an Empirical Perspective of UAE,2019.0,"International Conference on Advances in Business, Management and Law (ICABML)",Yahya Hamad Al Zaabi; Genanew Bekele,"Objective: The paper aims to examine house price drivers in Dubai, addressing the effect of internal and external factors afecting house prices 108 109Design/methedology/approach: Using the Hedonic price model, the study examined the implications of house size (space), the availability of bathrooms, bedrooms, waterfronts, and pool and cell phone towers within residential area as auxiliary determinant factors to housing price within developed cities by using the Hedonic Modelling. Also, study highlight the effect of the green strategies that been followed by developer on the housing prices. 110 111Findings: The study is expected to reveal results with significant ramifications for researchers, practitioners and policy makers. From a policy perspective, there is an obvious interest in understanding whether the price of housing is affected by different attributes differently along its distribution. 112 113Research limitations/implications: The data used in this study could be limited, and depends on information to be provided by the Dubai Land Department. There is a room for future research to include more data (such as on other house attributes such as house condition, plot numbers and config",0.0,http://publications.ud.ac.ae/index.php/ICABML-CP/article/download/209/7311464b2ef04150450815c46f32ceb5898434d4eaa4b,10.37407/kres.2023.41.3.173,Determinants of Housing Price by Region of Seoul,2023.0,Korea Real Estate Society,U.-Hui Lee; Hae Jung Chun,"This study conducted empirical analysis using the hedonic price model to examine regional differences in the determinants of housing prices among the representative examples of decoupling phenomena in inter-regional housing price movements, namely, “Gangnam 3-gu”, “Nodogang”, and “Mayongseong”, from 2017 to 2022. 115In the analysis results, the Gangnam 3-gu emerged as the region with the highest housing prices. It was observed that the longer the elapsed years, the more the anticipation of reconstruction was reflected in housing prices for older apartments. Additionally, a strong preference for convenient living facilities and an excellent educational environment was evident, indicating a dual focus on residential convenience and investment purposes. 116On the other hand, the Nodogang region had the lowest housing prices. The elapsed years were found to be significant only beyond a certain generational threshold. Preference for living convenience facilities showed contrasting results compared to the Gangnam 3-gu. Furthermore, the importance of proximity to subway stations was highlighted, indicating anticipation for reconstruction alongside the significance of convenient public transpo",0.0,117c912d674d814bd053c3466ceabb37019f159d2c1,10.1177/23998083251389078,"Impacts of bus rapid transit (BRT) on income-segmented housing markets in El Paso, Texas: A spatial hedonic and difference-in-differences analysis",2025.0,Environment and Planning B Urban Analytics and City Science,Young-Kyun Noh; Hanwool Lee; Yang Song; Chanam Lee; Wei Li,"This study evaluates the impact of introducing the Bus Rapid Transit (BRT) system on housing market dynamics across three diverse urban corridors in El Paso, Texas, utilizing spatial hedonic pricing and AITS-DID models. The research aims to understand how the BRT system influences property values, hypothesizing that the effects vary between developed and underdeveloped areas. Initial findings reveal an increase in property values in the affluent Mesa area until the BRT opening in 2014, followed by a decline, suggesting a shift in market perceptions post-implementation. Conversely, less affluent areas along the Alameda and Dyer corridors exhibit a reduction in the negative impact on property values over time, indicating growing appreciation for the BRT and associated urban improvements. The study contributes to urban planning and policy by highlighting the mixed impacts of BRT systems on property values across different urban fabrics and underscores the importance of context-sensitive transit planning. It also points to the necessity for comprehensive communication with stakeholders to ensure transit solutions meet community needs and support equitable urban development.",0.0,https://doi.org/10.1177/23998083251389078118b9aee40be8ba8be4fa1039744940423563423b07,10.32854/agrop.v15i10.2193,"Housing economic valuation in the metropolitan area of Puebla, Mexico",2022.0,Agro Productividad,Ramiro Torres Ramirez; M. Á. Martínez Damián; Ramón Valdivia Alcalá; Fermín Sandoval Romero,"Objective: The purpose of this research was to identify the sale value of homes in the metropolitan area of the city of Puebla, using the hedonic price technique to determine a model that takes into consideration relevant variables that explain the housing prices.Methodology: An overall problem is land mismanagement. The location of the homes can affect their price. A hedonic price model helps to determine the relative importance of the variables in the final price. This information provides an initial perspective to the people who are interested in acquiring a home in the study area. The model was built based on the information collected from 182 properties and it was analyzed using theSPSS software version 28.0.0.0.Results: The most significant variables that determine housing prices, which presented a multiple valuation coefficient of 64.3%. The effect of the variables on the housing value was determined by means of elasticities.Study Limitations: There were no limitations for this report.Conclusions: The following variables were significant: new home, number of bathrooms, built‐up area, private security, distance to the downtown of Puebla, and distance to a park.",0.0,https://revista-agroproductividad.org/index.php/agroproductividad/article/download/2193/1933119b6eb87efbbeb1d5e2145c1e6add65a91728ceb04,10.1108/ohi-12-2025-0426,Capitalization of urban nature quality versus quantity in housing markets: a global meta-analysis (1990–2023),2026.0,Open House International,Wuyao Li; Qingqing Zhou; Ying Zhou; Hui-Lin Liang,"120 121 This article critically evaluates the economic capitalization of urban nature within housing markets to inform residential planning. It addresses the limitation of strategies prioritizing green space “quantity” over “quality”, aiming to resolve inconsistencies in Hedonic Pricing Model (HPM) literature regarding environmental amenities.122 123 124 125 A rigorous three-level random-effects meta-analysis was conducted on 75 empirical studies (1990–2023). To ensure robustness, the study applied strict inclusion criteria, specifically filtering for research that quantified ecological quality metrics (e.g. vegetation health) rather than mere presence, ensuring a high-integrity dataset.126 127 128 129 The analysis reveals that ecological quality (e.g. vegetation condition) and spatial configuration (accessibility) are significantly stronger drivers of housing price premiums than mere quantity (size). Notably, this capitalization effect is context-dependent, showing significantly stronger impacts in developing countries and high-density regions compared to developed contexts.130 131 132 133 For rapidly urbanizing societies, particularly in the Global South, shifting focus from “large, distant parks” to “high-",0.0,1343229833cbf66f7437c3ccda763ab4938ba95a151,10.5194/agile-giss-7-15-2026,The value of where – quantifying location values with tabular transformer models,2026.0,AGILE: GIScience Series,Christian Mueller-Kett,"Abstract. Location is a key feature of urban spaces. It influences housing and land markets, social segregation, and decisions in urban planning and administration. Hedonic price models and, increasingly, machine learning (ML) methods are traditionally used for quantitative location valuation. At the same time, transformer architectures and their more recent adaptations for tabular data mark a methodological milestone. However, to date, tabular transformers have not been widely adopted in spatial analyses and, in particular, have not been systematically evaluated for location value assessments. This study addresses this gap by comparing classic ML methods with two tabular transformer approaches: TabNet and Mitra. In a case study, rents are used as the target variable, with property-specific characteristics being normalised using spatial regressions. Location-describing features include accessibility to POIs and areal variables such as imperviousness, noise, and population density. While a stacked ensemble of classical ML models achieved the lowest RMSE, TabNet and Mitra performed within a narrow margin, demonstrating that they can be used to map spatial patterns.",0.0,https://agile-giss.copernicus.org/articles/7/15/2026/agile-giss-7-15-2026.pdf1355b3bf7e5127cae6ae0e31174486c228a949c3bf6,10.22394/2079-1690-2022-1-2-272-280,VALUING THE ECOLOGICAL QUALITY OF THE URBAN ENVIRONMENT USING HEDONIC PRICING METHOD,2022.0,STATE AND MUNICIPAL MANAGEMENT SCHOLAR NOTES,Yi-Nan Dong,"Development of sustainable cities needs the natural and human living in a harmony way. River is an important natural attribute, which has a closed relationship with the development of the city. The purpose of the study is to use hedonic pricing method to assess the economic value of the river in Nanyang city. The novelty of the study lies in the development of econometric models, which use two explanatory variables as metrics of environmental quality – the distance from the residential property to the river and the beauty of the river landscape. Three hedonic pricing models using dummy variables to reflect distance and landscape were developed and analyzed. Simulation results showed that the distance to the river has a positive effect on property price when the distance between them is less than 200 meters. The price of property with river vision will be 9.8 % higher than the price of property without river vision. The results of the study demonstrate a fairly high economic value of the river and the need to implant economic assessments of the ecological quality of the urban environment into the strategic management of sustainable cities’ development.",0.0,https://doi.org/10.22394/2079-1690-2022-1-2-272-2801360ed03ed2dfe584b1a44e7edaadfa0391ad66c97e,10.62335/z3rf7r98,PENENTUAN HARGA JUAL PRODUK DENGAN PENDEKATAN MODEL HEDONIK: KASUS DI KOTA BANJARMASIN DAN KOTA SURABAYA,2024.0,Sinergi,Chairina Chairina,"This research aims to know at the factors that determine the selling price of houses in Banjarmasin City and Surabaya City. The Hedonic Price Method is used to evaluate environmental services, where the presence of environmental services directly influences the selling price. The selling price can be influenced by land area, building area, number of space (bedrooms and bathrooms), certificate of ownership, quality of building materials, security and access to public facilities. Research approach is used with quantitative statistics. Housing sales data of 50 samples were analyzed for each city obtained randomly. Total sample safety with 100 observations. Regression method with Principal Component Analysis (PCA) is used to test the research hypothesis and is processed with Minitab software version 19. Based on the results of the analysis, the factors that influence the selling price of houses in the city of Surabaya are land area, building area, number of rooms and number of bathrooms. While the factors that determine the selling price in the city of Banjarmasin are building area, certificates, quality of building materials and building facilities.",0.0,https://manggalajournal.org/index.php/SINERGI/article/download/662/8611379314c9c166f136ed55e2bf8c04077a539e1949dc,10.70675/959651b2z90cdz473az9c8dzf3d9e83780e5,L’influence de l’action publique sur la demande et l’offre de logement,2016.0,,J. Hubert,"Cette thèse porte sur les facteurs déterminant la demande et l’offre de logement, avec des applications dans l’ex-région Nord-Pas-de-Calais. Elle est constituée de cinq chapitres.Le premier propose une analyse de la littérature fondée sur les quelque 200 articles publiés dans la revue Journal of Housing Economics durant la période 2003-2012. Il met en lumière des résultats instructifs pour des chercheurs en économie du logement, novices et confirmés. Le second chapitre présente de manière détaillée et didactique la nouvelle base de données du service de « Demande de valeurs foncières » afin de rendre compte de la richesse de son contenu. Ce chapitre propose également quelques statistiques décrivant le marché du logement du Nord-Pas-de-Calais. Le chapitre 3 utilise une analyse hédonique des prix des transactions de logement pour expliciter les facteurs affectant leur prix. Hormis le service de « Demande de valeurs foncières », cette étude met en œuvre plusieurs bases spatialisées exploitées via un SIG. Le chapitre 4 utilise les résultats de ces estimations pour calculer la valeur du stock total de logements et de rente différentielle du Nord-Pas-de-Calais. Ces résultats apportent de",0.0,138fb64a5a8a50cc19b4056631efe79a96d1ca0ada1,10.21837/pm.v24i43.2118,IS GREEN A PREMIUM? AN INVESTIGATION ON THE IMPACT OF URBAN PARK ON HOUSING PRICE,2026.0,PLANNING MALAYSIA,Chin-Tiong Cheng; H. Chin; A. Azmi; P. Tedong; Ming-Yu Cheng,"Urban green spaces are increasing recognised as an important element of residential development. In line with this, this study aims to quantify the extent to which urban park landscape features contribute to housing prices. This study utilized residential transaction data spanning from 2016 to 2023 across three major housing areas, incorporating both conventional and modern landscape designs. This study employs hedonic price modelling to estimate the green premium via Ordinary Least Squares regressions. The findings suggest a positive correlation between housing prices and the presence of urban parks, indicating the existence of a “green premium”. The research contributes to the literature by providing empirical evidence of the urban park landscape's economic value in the housing market. It underscores the critical role of urban park landscape in shaping the economic dynamics of the housing market. It provides valuable insights for urban planners, valuers, financial institution and policymakers in advocating for a holistic approach to urban development that harmonizes economic objectives with environmental and aesthetic considerations.",0.0,https://www.planningmalaysia.org/index.php/pmj/article/download/2118/179013979f96b8c44ab08a687f21986600628b7cd6b1857,10.1108/ijhma-05-2025-0106,Is climate gentrification happening? Evidence from the effect of elevation and flooding risks on housing price dynamics in South Florida,2025.0,International Journal of Housing Markets and Analysis,Yanmei Li; Sumei Zhang; Serena Hoermann,"140 141 Using housing price and price appreciation as a proxy for gentrification, the purpose of this study is to explore whether climate gentrification exists in South Florida when new or redevelopment projects target areas with higher elevation and/or lower flooding risks.142 143 144 145 Existing literature lacks longitudinal comparisons to isolate the effect of climate change on the property market. This study uses spatial mapping and six hedonic pricing models to measure how elevation and flooding risks are associated with housing prices and price appreciation in 2016 and 2021, controlling for housing attributes, neighborhood demographic characteristics, changes and the interaction terms between elevation/flooding and neighborhood variables.146 147 148 149 The findings of this study reveal that elevation and flooding risks influence housing transaction prices differently in different periods, indicating the potential impact of the presence versus absence of hurricanes on short-term market corrections. When exploring the repeat sales data, the overall finding is that climate gentrification, manifested as climate retreat, may happen because higher elevation areas have seen higher housing price appre",0.0,1505df4f0fb35593013c2dd0be171965b34b8a99aa9,10.3390/realestate3010001,"Quality of School and Housing Prices: A Study for the Apartment Market in Porto Alegre, Brazil",2026.0,Real Estate,Luiz Andrés Ribeiro Paixão; C. Costa,"We use the hedonic price model to measure the effect of school quality on apartment rent prices in Porto Alegre, Brazil. A spatial autoregressive regression (SAR) was employed due to the spatial nature of the data. We estimated the effect of school quality on apartment prices for public and private schools separately. The results shed light on the relation between school quality and apartment prices in a Global South context. We showed that both public and private school quality is valued in Porto Alegre house markets, although the effect is quite different for each type of school. For public schools, the major effect comes from the distance of the nearest schools. An increase in test scores by one standard deviation raises apartment rent prices by 2.7% for the whole city. However, this effect is bigger for some submarkets, reaching 11.6% for the distant suburbs. For private schools, the same effect occurs but for a larger distance radius. The same increase in average test score out to a 2 km distance from private schools raised the apartment price by 1.0%. Nevertheless, this effect reaches 6.6% in one specific submarket.",0.0,https://www.mdpi.com/2813-8090/3/1/1/pdf?version=17695277721512ad2b9200c6291e5af67b2034d66bbdf2cfe9581,10.1111/1540-6229.70062,Graph‐Laplacian modeling of spatiotemporal effects for house price estimation,2026.0,Real Estate Economics,Willem P Sijp; Marc K. Francke,"152 Many variables involve the modeling of spatial effects, and their dynamics over time. This article presents a linear model in which spatiotemporal random effects are modeled by graph‐Laplacians. A graph‐Laplacian flexibly encodes adjacency in both space and time, in our case not depending on unknown parameters. The graph‐Laplacian can be input for a prior in a Bayesian estimation setup, or used as regularization term in a Ridge regression. A spectral decomposition of the graph‐Laplacian significantly reduces computation time for estimation. As an application, we estimate graph‐Laplacian hedonic pricing and repeat‐sales models on sales prices of Australian residential properties in the period from 1990 to 2024. Bayesian and Ridge regression estimation results are very similar, although the computation time for the Ridge regression is orders of magnitude faster, however at the expense of missing posterior density functions. Our results highlight the advantages of graph‐Laplacians for predicting individual property prices and for producing stable, granular price indexes, also in thin markets.",0.0,https://doi.org/10.1111/1540-6229.70062153aaf0e966df7ffb81b8eda5c4c1989af80e16cb3c,10.24215/16666038.26.e01,House Price Prediction in Andalusia: A Comparative Study of Hedonic and Machine-Learning Approaches Using Online Data,2026.0,Journal of Computational Science and Technology,Emilano Gutiérrez; Lorena Caridad-López del Río; Jose Mar'ıa Caridad Ocerín,"This study explores housing price prediction in six major cities of Andalusia using a combination of traditional and machine learning models. Online property listings were compiled to build a detailed dataset incorporating structural, socioeconomic, and locational variables. A traditional hedonic model was estimated using Ordinary Least Squares (OLS), and its performance was compared with that of Random Forest, K-Nearest Neighbours, and XGBoost. Results show that linear models tend to underperform, highlighting the relevance of non-linear approaches in capturing the complex dynamics of the housing market. To enhance interpretability, SHapley Additive exPlanations (SHAP) values were applied to the XGBoost model, enabling the identification of the most influential predictors in each city. While structural variables remained important across all models, socioeconomic and locational features exhibited varying effects depending on the city. These findings underscore the potential of combining rich data sources with interpretable machine learning techniques for urban housing market analysis.",0.0,https://journal.info.unlp.edu.ar/JCST/article/download/4338/2033154253da9d725f2e031b79e5ea196860c662831042d,10.1257/jel.47.4.1126.r16,Book Reviews,2009.0,Journal of Economic Literature,,"Raymond B. Palmquist of North Carolina State University reviews “Hedonic Methods in Housing Markets: Pricing Environmental Amenities and Segregation” by Andrea Baranzini, Jose Ramirez, Caroline Schaerer, Philippe Thalmann,. The EconLit Abstract of the reviewed work begins “Ten papers, resulting from a workshop held at the Geneva School of Business Administration in June 2007, consider the use and advancement of the hedonic approach to analyze and quantify the sources of rent and property price differentials in the housing market. Papers discuss theoretical foundations and empirical developments in hedonic modeling; hedonic modeling of the home selling process; hedonic property value studies of transportation noise--aircraft and road traffic; pricing the homebuyer’s countryside view; semiparametric tools for spatial hedonic models--an introduction to mixed geographically weighted regression and geoadditive models; estimating hedonic models of consumer demand with an application to urban sprawl; conceptual and operational issues in incorporating segregation measurements in hedonic price modeling; using hedonic models to measure racial discrimination and prejudice in the U.S. housing ",0.0,155696774cb19c9f037b7d2fbaa0fe86b00c842fa74,10.1177/00420980261483896,Impacts of new light rail investment on accessibility and housing markets: A difference-in-differences hedonic analysis in Amsterdam,2026.0,Urban studies,J. Claassens; Jan Rouwendal; E. Koomen; M. Lankhuizen,"In 2018, Amsterdam introduced the North-South Line (NZL), a metro connecting the city’s north and south via its historic centre. Using a spatially adjusted difference-in-differences approach, combined with hedonic modelling for the relevant submarkets, this study estimates the effects of accessibility improvements, measured as the change in the number of jobs reachable within a 30-minute trip, on housing prices, rents, social housing queues and housing density. Unlike most studies in this literature, which focus exclusively on transaction prices, we examine this broader set of outcomes, an approach of particular relevance in Amsterdam, where owner-occupied housing represents only around 30% of the total stock. We find modest housing market responses to the NZL around specific stations. Effects are strongest where accessibility improvements were most pronounced, but often small or statistically insignificant. While house prices show small capitalisation effects in some locations, private rents, social housing and housing density exhibit weak or largely insignificant changes.",0.0,https://doi.org/10.1177/00420980261483896156e8f48e7e91bb043c222f2cfbe026c67e0e422a5f,10.30541/v64i3pp.241-261,Valuing Neighbourhood Soundscapes in Urban Housing Markets: Evidence from Karachi,2026.0,Pakistan Development Review,Ghamz E. Ali Siyal; Heman Das Lohano; Johane Dikgang; Ayesha Zia,"Noise pollution in Karachi has already exceeded WHO-recommended environmental thresholds. It causes sleep disturbances, hearing impairment, stress, and anxiety. However, there is a lack of evidence on how these effects transferred into housing market. This study extends a conceptual framework and empirically explores household data on perceived neighbourhood soundscapes and self-reported housing values. We estimate hedonic pricing models to examine how the presence of natural and non-natural soundscapes around respondent’s residence affects housing values. This study conducted a primary data survey of 507 respondents affiliated with the Institute of Business Administration (IBA), Karachi. Using hedonic regression results, this study is the first to confirm the effect of natural and non-natural soundscapes on housing values, along with structural, locational, and neighbourhood attributes. The results recommend designing and installing soundproof windows in homes and developing better urban planning and management policies to ensure a good quality of life in Karachi. ",0.0,https://thepdr.pk/index.php/pdr/article/download/3322/30561573197c905065b4dc447853fe08d80877fce0c8c7e,10.54091/krepa.2024.25.3.22,Explainable Machine Learning for Housing Price Determinants: Focusing on Regional and Temporal Variation,2024.0,Korea Real Estate Policy Association,Jeongsik Park; Jihun Oh; Jaewoong Won,"The hedonic price model has long been a key method for predicting and explaining housing prices. Despite its widespread application, the model is limited by assumptions such as the normality of error terms and challenges like multicollinearity, which constrain its flexibility and predictive accuracy. Recently, machine learning techniques have emerged as powerful alternatives, demonstrating significant predictive capabilities while overcoming the limitations of traditional parametric models. Moreover, the advent of explainable machine learning methods has broadened their applicability across various domains, including housing price analysis. However, most existing studies on housing prices using machine learning have mainly focused on improving predictive performance with a limited set of variables, primarily emphasizing physical housing characteristics while overlooking the complex impact of locational factors. This study addresses this gap by leveraging actual transaction prices of apartments in Seoul between 2016 and 2018 to develop explainable machine learning models, specifically Random Forest and XGBoost. These models incorporate an extensive set of variables, including neighb",0.0,158ca7e6874d9bffb706c7e3ad2908432e3315ecd20,10.1111/geoj.70127,The Price of Cool: Using Hedonic Modelling to Assess Spatial Inequalities of Air Conditioning Access in Madrid,2026.0,Geography Journal,G. Kenyon; Caitlin Robinson; Elisabetta Pietrostefani; Olga Gkoutouna,"159 Air‐conditioned homes make hot summers more comfortable and can mitigate the effect of heat on health, which is a growing concern in increasingly hot urban areas. The following research uses a large property listings data set to investigate neighbourhood‐level spatial inequities in access to residential air‐conditioning (AC) in Madrid, Spain. A hedonic model is used to assess the effect of AC on housing prices and a multi‐level model to estimate how the effect varies between neighbourhoods. The paper shows the high housing value uplift of AC systems and, furthermore, key neighbourhood and district inequalities in access to, and the price of, air‐conditioned properties. The spatial interaction between AC access and socioeconomic and neighbourhood factors is further assessed to characterise the populations and areas deprived of cool. We identify vulnerable neighbourhoods characterised by a lower prevalence of AC, higher cost of this amenity in the housing stock and low incomes, contributing a new dimension to understandings of summer energy poverty.",0.0,https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/geoj.701271601143b63af6f53e6cd1a151f05169eebabb42425b,10.5465/ambpp.2020.21096abstract,The Social Value of a Ridesharing Platform: The Case of Uber,2020.0,Academy of Management Proceedings,Yongwook Paik; C. Makridis,"Ridesharing has become ubiquitous throughout the United States, leading to a proliferation of academic studies and policy debates about its welfare implications. However, the overall social value of a ridesharing platform is still unclear because prior literature focuses only on the supply side (i.e., drivers) or the demand side (i.e., passengers) of ridesharing when analyzing its welfare and does not consider non-users of the platform. In this study, we aim to quantify the social value of a ridesharing platform using a hedonic pricing model, exploiting plausibly exogenous variation in the staggered entry of UberX into different metropolitan areas between 2010 and 2016. We find that the entry of UberX into a metropolitan area leads to a 2.9% rise in median housing prices per square foot. A back-of-the-envelope calculation suggests that the entry of UberX is associated with a welfare gain of approximately $795 million. We also find substantial spatial heterogeneity, with benefits concentrated in areas with higher shares of college graduates, greater dependence on public transportation, and a lower value of vehicles per capita. By objectively computing the value of a ridesharing plat",0.0,161c186da01373d7305a1c7d1f43c3368e5f6a12afe,10.35136/krer.36.1.3,A Spatial Hedonic Analysis of the Impact of Lake Parks on Residential Property Values,2026.0,Korea Real Estate Institute,Sang-Jun Lee; Sang-Gun Lee; Wanhee Park,"This study empirically examines the impact of pedestrian accessibility to lake parks on apartment transaction prices in four major new towns (Gwanggyo, Dongtan, Unjeong, and Cheongna) in the Seoul metropolitan area. Using 1,180 actual transaction records aggregated into 80 apartment complexes, a hedonic price model or ordinary least squares (OLS) was initially estimated. Moran's Index test was then conducted to assess spatial autocorrelation in the residuals. The results indicated significant spatial clustering only in Gwanggyo, characterized by its high-density linear urban structure, leading to the application of the spatial error model (SEM). Conversely, the OLS model was found to be statistically appropriate for the other three cities. 162The findings confirm that apartment prices significantly decline as walking distance to lake parks increases, indicating that walking access to parks is capitalized into housing prices in the form of price premium. In Gwanggyo, the application of the SEM significantly improved model performance, as indicated by lower Akaike Information Criterion values, implying that proximity to lake parks and subway stations, as well as apartment age (newer bu",0.0,16374181ccff8d0d759fa695995114dce87df5f85a0,10.61225/rjrs.2025.04,"Criminality and apartment prices: A study for Rio de Janeiro, Brazil",2025.0,Romanian Journal of Regional Science,Luiz Andrés Ribeiro Paixão,"Violence is one of the biggest problems in Brazilian society, Brazil being one of the most violent countries in the world. Rio de Janeiro is the second largest Brazilian city both in economic and population terms and is the most famous Brazilian city in the world. Measuring the social cost of violence is an important task to understand the Rio de Janeiro reality. There is some consensus in literature that housing prices are very sensitive to environment changes and there is a negative relationship between violence rates and housing price. We developed a hedonic price model to quantitatively determine the effect of violence on apartments price in Rio de Janeiro, using homicide and robbery rates as criminality proxies. A set of control variables were included since these variables were relevant to Rio de Janeiro’s apartment market. We used spatial econometric frameworks to deal with the spatial nature of the data. Our results show that the increase in criminal violence is linked to the decrease in apartments prices in Rio de Janeiro.",0.0,https://doi.org/10.61225/rjrs.2025.04164b4a3796c49b63309644969e4f8cbb671392e85ec,10.37407/kres.2026.44.3.369,The Effects of Green and Blue Amenities on Apartment Prices in Songdo International City : Focusing on Accessibility and Views,2026.0,Korea Real Estate Society,Jae In Lee; B.-S. Byun,"As multi-unit housing is increasingly recognized as a complex good that combines various attributes, there is growing interest in the phenomenon whereby the economic value of environmental amenities is capitalized into housing prices. In particular, Songdo International City within the Incheon Free Economic Zone (IFEZ) is a prime example of a planned waterfront city that features a concentration of green and blue amenities, such as Central Park and the waterfront. This study aims to empirically analyze the impact of accessibility to and views of “parks (Green Space)” and “waterfront spaces (Blue Space)”— factors constituting environmental amenities—on the actual transaction price per square meter of multi-family housing. To this end, a hedonic price model was constructed, and multiple regression analysis was conducted using physical, locational, and environmental characteristics as explanatory variables. The results showed that access to and views of waterfront areas have a statistically significant impact on apartment prices; in particular, views were found to have a statistically significant positive effect on apartment prices after controlling for physical and locational charact",0.0,165d3e27cac15a096168d22a145ab49342c924dc96e,10.2478/fiqf-2025-0026,Bridging the information gap: what are the impacts of EPCs on Prague’s residential market selling prices?,2025.0,Financial Internet Quarterly,Tomáš Podškubka; Barbora Rýdlová; Josef Arlt,"Abstract It is assumed that energy performance certificates (EPC) can promote energy efficiency, increase property values, and improve market liquidity by providing trustworthy energy performance information. This article will provide a comprehensive study of the impact of EPCs on the residential selling prices in Prague, the capital of the Czech Republic. For the analysis, the original dataset was extracted from the publicly accessible sreality.cz portal. The hedonic regression model was applied to evaluate how the EPC influences the selling price of apartments in Prague. The regression analysis results are entirely in line with the analyzed current literature. EPC ratings have been proven to significantly affect the selling price in Prague and several other locations. In the most affluent locations of Prague, i.e., typically historical locations, the EPC ratings have not proved to be a statistically significant price factor because these locations suffer from excess demand and limited supply of properties.",0.0,https://reference-global.com/2/v2/download/article/10.2478/fiqf-2025-0026.pdf166257c937dbbf7f50cb8e416c822adc6d6dc825b02,10.15396/eres2019_12,Is access to public services valued differently in low- and high-end housing submarkets?,2019.0,26th Annual European Real Estate Society Conference,Wing-Chau Kwong; Lin-Chuan Yang; Zhu Yuan,"Previous research suggests that access to public services, generally, has a positive impact on housing prices. However, most, if not all, studies are silent on whether the effect varies across different housing submarkets. For example, wealthy households are likely to own cars and thus have high transportation mobility. Thus, they may not value access to public services in the same way as low-income households do. We use 22,586 second-hand housing data in Xiamen, China to test the differential impact of access to public services on housing prices in the high- and low-end submarkets. Low- and high-end housing submarkets are defined according to price. Results from estimating the hedonic pricing and spatial econometric models confirm several findings: (1) the benefits of access to most public services are capitalized in housing prices; (2) access to transit, commercial facility, education, and sports/cultural center has significantly positive impacts on house prices in the low-end housing submarket. Yet, this finding is less applicable to the high-end counterpart; (3) the effect of access to public services on housing prices varies across the two submarkets: typically, access to publ",0.0,167c37e5d25b99182845a215acb6e6fce1c77450b97,10.17160/josha.10.4.915,Modelling Spatial Scale and Heterogeneity in Rotterdam Housing Market Using Multiscale Geographically Weighted Regression,2023.0,Journal of Science Humanities and Arts - JOSHA,N. Feddes,": This study investigates the spatial heterogeneity of the Rotterdam housing market, as well as the spatial scale at which the processes that explain housing prices operate. I use data on 3632 residential properties that were sold in Rotterdam in 2018 provided by the NVM. Using a recently (2017) developed technique called Multiscale Geographically Weighted Regression (MGWR), I show that certain factors explaining residential housing prices operate on different spatial scales, indicating the existence of relatively local and more global effects. Lot size and the state of maintenance of the house exterior seem to operate on a local scale, whereas the degree of isolation and number of rooms appear to be global. Comparison of the MGWR model with a regular GWR with fixed bandwidths and a global hedonic model with location fixed effects, show that the MGWR best fits the data, i.e. a model that allows the bandwidths to vary for each parameter outperforms the models that do not allow this.",0.0,https://josha-journal.org/download_pdf/modelling-spatial-scale-and-heterogeneity-in-rotterdam-housing-market-using-multiscale-geographically-weighted-regression?locale=en168cbca708e6a3e8af63d629068afb1ef0a8bfdc148,10.54254/2753-7048/2024.19494,The Impact of Open Spaces on Residential Property Values,2025.0,Lecture Notes in Education Psychology and Public Media,Rui Wu,"The increasing population density in urban areas leads to further construction of houses, and less land is being distributed to open spaces. Thus, there are preservation efforts in many cities to preserve open spaces and maintain the benefits. Ultimately, people desire to live near open spaces to enjoy their benefits, impacting the residential property values. This study attempts to explore the relationship between open spaces and the effects on the values of its neighboring residential properties, specifically in the city of Shanghai, using the hedonic model. The study analyzed the impact through several aspects, including open space type, size, and proximity to residential properties. Results suggest that open spaces, in general, do have the impact of increasing residential property values, and the effect could vary according to the size, type, and distance to residential property. This study helps decision-makers better implement future housing policies and city planning models.",0.0,https://www.ewadirect.com/proceedings/lnep/article/view/19494/pdf1699abeb80f56e08c3e8e71b17f0ba39158f1e8083d,10.1080/09640568.2024.2322538,"Hedonic analysis of willingness to pay for dam removal: evidence from Plymouth, Massachusetts",2024.0,Journal of Environmental Planning and Management,M. Cahill; Nikolay Anguelov,"This study investigates how the removal of small dams, and subsequent river restoration investments, affect residential housing prices in Plymouth, Massachusetts, selected for its unusually high density of dam removals. From 2002 to 2019, 5 dams within 1.05 miles of each other have been removed. Following removal, riverine restoration was completed, leading to improved public safety for downstream infrastructure, fish passage, and better water quality. Yet, contention exists in local government decision-making from fear of loss of property values of homes that are no longer classified as “waterfront.” To examine that charge, we evaluate sale prices of 9,710 single-family homes from 1997 to 2021, in a comparative estimation of a hedonic regression and a difference in differences model. The results indicate that the price of homes sold in Plymouth after dam removal increased, with no impact on property values of waterfront and properties within 1 mile of riverine restoration locations. For properties within a 5-mile radius of a former dam, we observe comparative difference in price of a fraction of a percent for lots around 2 of the dams, in relation to all home lots in Plymouth. We ",0.0,17051b03fe73ab38a2429eea55ef9458519b31449c4,10.1080/02673037.2025.2552397,The willingness to pay and the willingness to stay in privately rented housing,2025.0,Housing Studies,Chris Leishman; Fentahun Abebe; Emma Baker; Sumin Kim; Alison Reid,"Abstract Previous research has explored and conceptualised private renting as a unitary sector, thus obscuring deeper understanding of the experiences of discrete groups in the private rental market. We draw on a large-scale Australian survey dataset to estimate two inter-linked econometric models—a hedonic and a logit—that let us analyse rental conditions, rent paid and intended mobility. We find evidence of a specific group of renters who are in a more marginalised position than other cohorts. We argue that that price (rent) paid is a function of tenant choice, in addition to physical and neighbourhood attributes. Meanwhile, tenants’ propensities to move home are a function of satisfaction with physical, neighbourhood, landlord behavioural factors, as well as rent paid. Our empirical evidence supports the idea that marginalised renters face poor physical dwelling and neighbourhood conditions, higher levels of rent and higher levels of intended mobility.",0.0,https://doi.org/10.1080/02673037.2025.25523971715bcd886348a12f52aa055354a9647ba5c4fa64c4,10.1007/s11146-026-10071-w,Giving Eyes to Automated Valuation Models: Computer Vision Assessment of Interior Home Condition,2026.0,Journal of real estate finance and economics,V. Almaas; A. Oust; A. J. Pollestad,"172 Housing condition is a key determinant of property value, yet it is often omitted from modern automated valuation models (AVMs). This study develops a computer vision framework to extract room-specific condition signals from listing images and examines their economic relevance for housing valuation. Using 15,702 condominium transactions from Oslo, Norway (2022–2023), matched with 393,914 images, we classify images by room type, estimate condition on a 1–5 scale, and incorporate these measures into hedonic linear regression and XGBoost AVMs. The results show that computer-vision-based condition improves predictive performance, with gains comparable to those from human-labeled condition. Moreover, housing condition is positively associated with sales prices, with stronger effects for kitchens and bathrooms and in lower-priced homes. Explainable AI analysis further indicates that the models rely on intuitive and economically meaningful visual patterns.",0.0,https://link.springer.com/content/pdf/10.1007/s11146-026-10071-w.pdf1731cb2244b68c3291edcf48ed0a573d6f0bb6e9245,10.3389/fams.2023.1133397,The value of being the decisive voter: Exploratory evidence from a hedonic model,2023.0,Frontiers in Applied Mathematics and Statistics,E. Peters; Joshua C. Hall,"In the field of public economics, there is a literature on calculating the probability of being a decisive voter. The raison d'etre of this literature is to explain voter turnout. In this short empirical paper, we look at the question from a different angle. Heterogeneity in voting preferences means that some individuals vote rationally, others instrumentally, and some individuals are marginal and respond to changes in the probability of being decisive. Individuals with a preference for instrumental voting might be willing to pay more to live in an area with a greater probability of being a decisive voter. If this is the case, housing prices should reflect this higher willingness to pay. We test our theory using hedonic data from Columbus Ohio and find suggestive evidence that voters are willing to pay for a greater likelihood of being a decisive voter. Our results, however, cannot rule out other interpretations.",0.0,https://www.frontiersin.org/articles/10.3389/fams.2023.1133397/pdf174e78cd9b05895215b36ad4dd4b759fbdf07a96918,10.5325/naturesopolirese.10.1.0047,Economic Benefits of Remediating the Ashtabula River Area of Concern,2020.0,Journal of Natural Resources Policy Research,G. Gardner,"175 This study uses hedonic modeling to estimate the economic benefits of remediation in the Ashtabula River Area of Concern (AOC) in Ohio. Data from residential single-family housing sales between 1997 and 2020 are used in a spatial difference-in-difference (DiD) analysis. The analysis compares housing price differences pre- and post-remediation between houses sold within 2000 m of the AOC and houses sold outside of this area. Rather than a recovery of housing prices after remediation, results indicate additional losses of 14%. Total property losses amount to $40.2 million. Past studies conducted using benefit transfers prior to remediation had predicted property value benefits of as much as $35.6 million. The contrast between predicted and observed impacts on property value highlights the need for more retrospective analysis to identify actions that will yield better predictions and outcomes.",0.0,https://scholarlypublishingcollective.org/psup/jnrpr/article-pdf/10/1/47/2021332/naturesopolirese.10.1.0047.pdf176f329415dedcfa87542be3a35868f12bbfc6d4ad5,10.1177/00420980261448667,Impacts of flood zoning policies on housing markets: Evidence from the national flood insurance program,2026.0,Urban studies,Pin Sun; Douglas S. Noonan; Lilliard E. Richardson,"Floods pose significant threats in the United States, and the National Flood Insurance Program uses Special Flood Hazard Area (SFHA) designations to guide regulations intended to reduce flood damage. Yet the effect of SFHA regulation on housing markets is difficult to identify because floodplain status is correlated with flood risk and unobserved amenities. This study estimates SFHA policy effects on assessed housing values by combining parcel-level flood risk data, property-level housing information, and Federal Emergency Management Agency (FEMA) SFHA boundaries in Texas. Using a regression discontinuity (RD) design, we compare single-family homes just inside and just outside invariant SFHA boundaries to better separate local policy effects from flood risk and other confounding factors. Relative to a standard hedonic model, the RD analysis yields different estimates. The hedonic model suggests lower assessed values for coastal-county properties inside floodplains and no significant effect inland. In contrast, the RD estimates show no significant boundary effect in coastal counties and about a 2% assessed-value premium for homes inside SFHAs in inland counties. These findings sugge",0.0,1779848e68efcee710bc05a55f8576e298c00f7e04b,10.1017/age.2022.26,"The effect of remediating PCB-contaminated sediments on home prices in Milwaukee, Wisconsin, USA",2022.0,Agricultural and Resource Economics Review,R. Wilkinson; Richard T. Melstrom,"Abstract This paper estimates the effect of environmental remediation on housing prices in the Milwaukee Estuary Area of Concern (AOC) using a hedonic analysis of individual arms-length sales before and after a major remediation action between 2011 and 2015. Our design leverages this before-after comparison as well as the proximity of homes to remediation and the AOC boundary. Measuring the effect of AOCs in the housing market has always been a difficult task, given that water in AOCs can provide a mix of amenities and disamenities. Indeed, we find little evidence of a negative proximity effect when applying hedonic analysis to cross-section data. However, when we apply the analysis to a repeated cross section in a quasi-experimental framework, we find statistically significant evidence that living near the affected part of the AOC became more desirable after cleanup.",0.0,https://www.cambridge.org/core/services/aop-cambridge-core/content/view/F3891A8BE6A3544390E0DA3BADEEDFF8/S1068280522000260a.pdf/div-class-title-the-effect-of-remediating-pcb-contaminated-sediments-on-home-prices-in-milwaukee-wisconsin-usa-div.pdf178e2ffb2f90fb1103bb936e2fe27f976d3cffc2a65,10.56409/kreis.2026.9.2.245,Analysis of Heterogeneity by Quantum of Apartment Price Determinants in Haeundae-gu,2026.0,KOREA REAL ESTATE INDUSTRY SOCIETY,Seongsoo Seo,"This study analyzed the actual transaction prices of apartments in Haeundae-gu, Busan Metropolitan City in 2025 based on hedonic price theory after conducting a full survey to identify the heterogeneity of submarkets within the region and the price determinants by apartment price level. The analysis methods utilized were OLS, quantile regression, and Shapley decomposition. The results can be summarized as follows: First, Haeundae-gu is differentiated into a heterogeneous submarket structure characterized by significant price disparities between neighborhoods even within the same district. Second, variables such as the number of parking spaces per household, brand value, slope, and accessibility to elementary schools showed significant differences in significance or influence depending on the level of housing prices. Third, through Shapley decomposition, the high explanatory power of variables such as exclusive area, building dummy variables, number of parking spaces per household, highest floor, and years of age can be confirmed. Based on the results of this study, companies can utilize market segmentation within the same region to formulate development plans and marketing strategi",0.0,179070e78f122bd87a03bcd33fe81ce29f9570b28a8,10.11113/intrest.v18n2.385,An Examination of the Influence of Housing Attributes on Residential Property Rental Value in South-western Nigeria Using the Hedonic Pricing Model,2024.0,International journal of real estate studies,A. Odebode; D. E. Oladimeji; O. T. Ogunbayo,"This study adopts the hedonic pricing model to examine the influence of housing attributes on residential property rental value in south-western, Nigeria. This is to provide information on the housing attributes that could increase residential property rental values based on the current market situation. The study used primary data and employed quantitative data analysis. The data obtained were analysed using descriptive and inferential statistics. The study revealed the significant factors that influence rental value across different residential property types in south-western Nigeria. The paper is significant because it provides the necessary information on the influence of housing attributes in the study area. Hence, it enhances increasing knowledge in profitability, which could shape both local and foreign investors' investment decisions.",0.0,https://intrest.utm.my/index.php/intrest/article/download/385/177180f8760f72ef0e86660f6413b70ff31c2d9ef67332,10.22313/reik.2022.20.4.21,The Effect of the Establishment of a School for Students with Developmental Disabilities: Focusing on Seojin School,2022.0,Residential Environment Institute Of Korea,Sang Min Lee; Seo-Young Cho; S. Shin,"Special schools are essential facilities to guarantee the right to education for students with disabilities. Still, it is not easy to establish those schools due to strong opposition from local residents. The main reason for the residents' resistance is the negative effect of the community image and the resultant decline in housing prices. By studying the case of Seojin School, this study attempts to examine the special school's external economic impact and explore strategies to respond to the NIMBY phenomenon of local residents effectively. 181This study analyzes the sale price of apartments in nearby areas, focusing on Seojin School, which opened in 2020. 2017 was the year when the “Second Resident Hearing” was held, and the residents' NIMBY demonstration was covered in the national news. Before and after the debate, the sale price of apartments around Seojin School for five years(2015~2019) is analyzed using a hedonic price function model. The polygonal model was set in consideration of the spatial research area based on our judgment of the impact zone of Seojin school. 182First, the location of Seojin School has a negative effect on the apartment sale price. 183Second, these negative",0.0,184fd28c218b98b3031b60851e331e028c04d6f39c5,10.1016/j.cstp.2026.101867,Congestion charges and property prices: The effects of congestion charges in Gothenburg,2026.0,Case Studies on Transport Policy,H. Andersson; Peter Karpestam; P. Molnár; M. Ögren,"We analyze how the introduction of congestion charges in Gothenburg, Sweden, in 2013 affected the prices of condominiums. Using both a hedonic difference-in-difference (DiD) price regressions and the regression discontinuity design (RDD) approach we find robust evidence that the congestion charges made condominiums inside the toll zone less attractive. For instance, the findings from the DiD suggest a negative price impact on condominiums within the zone by about 6 percent compared to the control group (condominiums in Gothenburg outside the toll zone). The conclusion is that there is strong evidence that the congestion charges had a negative effect on property prices within the toll zone in Gothenburg. This can be explained by relatively small positive effects on traffic volumes and the environment within the zone.",0.0,https://doi.org/10.1016/j.cstp.2026.1018671850523be630438c84c940e29cf2e7afd680debb837,10.3390/tourhosp7100338,Online Reputation and Observable Quality in the Short Term Hospitality Pricing Under High-Dimensional Machine Learning: A Case of Airbnb,2026.0,Tourism and Hospitality,Shao-Hui Gao; Yi-Ming He,"This paper shows that guests’ online reviews play a critical role in determining rental prices on the Airbnb platform. We identify this pricing mechanism by developing an information-cost-based hedonic machine learning approach that links guests’ online reviews, property amenities, and rental prices. We investigate the effects of guests’ online reviews and the capitalization effects of property amenities using low-dimensional versus high-dimensional regressions. We estimate those effects using U.S. Airbnb data and compute the guests’ online review sentiment scores. Our empirical findings show that, using high-dimensional amenity-vector-based hedonic regression and the double machine learning algorithms, the guests’ online review sentiment scores variable is statistically positively associated with rental prices.",0.0,https://doi.org/10.3390/tourhosp71003381867e996f814b72e80b4de3f1e836fe30324b1e2912,10.1007/s10640-014-9856-y,Hedonic Valuation with Translating Amenities: Mountain Pine Beetles and Host Trees in the Colorado Front Range,2014.0,Environmental and Resource Economics,J. Cohen; C. Blinn; K. Boyle; T. Holmes; K. Moeltner,"In hedonic valuation studies the policy-relevant environmental quality attribute of interest is often costly to measure, especially under pronounced spatial and temporal variability. However, in many cases this attribute affects home prices and consumer preferences solely through its impact on a readily observable, spatially delineated, and time-invariant feature of the physical landscape. We label such a feature a “translating amenity.” We show that under certain conditions changes in the marginal effect of such amenities on home values over time can be used to draw inference on the implicit price of the unobserved environmental quality of interest. We illustrate this approach in the context of a repeat-sales model and the recently intensified outbreak of the Mountain Pine Beetle in the Colorado Front Range.",0.0,https://vtechworks.lib.vt.edu/bitstream/10919/97895/1/Cohen2016_Article_HedonicValuationWithTranslatin.pdf18799a8ee7090d0d9110792636bc8c256959867cf89,10.1177/09731741261467139,‘Untouchable’ Housing? Caste and House Prices in Rural Nepal,2026.0,Journal of South Asian Development,Binod Khanal; W. Chang; Sunil P. Dhoubhadel,"Caste-based discrimination is prohibited by law in Nepal. However, it remains deeply entrenched in Nepalese society, leading to widespread discrimination against lower castes, particularly Dalits, in various social and economic activities. This research aims to examine disparities in house prices between Dalits and non-Dalits using a hedonic price model. To accomplish this, we utilize demographic data, self-reported information on house attributes and house prices from the 2018 wave of the Household Risk and Vulnerability Survey (HRVS). The findings indicate that Dalit-owned houses are priced significantly lower than houses owned by Kshatriyas and Brahmins, even after accounting for all relevant house characteristics. Propensity score matching analysis reveals that this Dalit discount ranges from 11% to 16%, translating to a reduction of NRs 123,000 to NRs 174,000 for Dalit-owned houses compared to non-Dalit-owned houses. Furthermore, the analysis across regions suggests that house price differentials between Dalits and non-Dalits are less prevalent in the southern plains and urban areas than in mountainous and rural regions. One possible explanation for this housing price differen",0.0,1885d97f7b57f1077093f12f7680af0d8d25a5b16bf,10.1080/08920753.2024.2431940,A Hedonic Approach to Coastal Resilience in Post-Hurricane Maria’s Puerto Rico,2024.0,Coastal Management,L. Santiago; Kevián Pérez; Aurelio Castro; Maritza Barreto; J. García,"Abstract Hurricane Maria devastated Puerto Rico in 2017, resulting in reduced beach width and dune flattening in certain coastal areas. Economic development activity observed in coastal regions of Puerto Rico after Hurricane Maria has partly focused on commercial and housing construction projects. The following study seeks to estimate the implicit value attributed by coastal homeowners to natural infrastructure attributes that may serve not only for recreation, but also as protection from future extreme weather events. We estimated a hedonic valuation model to assess the implicit value attributed by coastal homeowners to key natural attributes, emphasizing beach width and property elevation. Property owners sufficiently close to the coastline (1,000 m or less) implicitly assigned a positive value to beach width at their closest coastal location. An unexpected result was that elevation, when interacted with beach and human-made coastal types, was negatively associated with property prices, an indication of the importance of closeness to sea level. Given the impact of extreme weather events in coastal regions, hedonic valuation data on natural coastal attributes such as beach width c",0.0,189c88a2614bef72aae3b32c340c845a0dd22308dc0,10.54694/stat.2025.45,Analysis of the Heterogeneity of Apartments and Its Impact on Rental Prices in Prague Using Web Scraping and Hedonic Regression Model,2025.0,Statistika: Statistics and Economy Journal,Adam Slavíček; Stanislava Hronová; Richard Hindls,"The study analyzes the heterogeneity of the housing stock and its impact on rent levels in Prague. Using web scraping and hedonic log-log regression on data from the SReality portal (20 184 apartments offered), it quantifies the impact of layout, size, and amenities (elevator, terrace, garage, facilities, new construction) on the price per square meter and examines the spatial and temporal variability of these factors. It compares classic indices (Laspeyres, Paasche, Fisher) with their hedonic variants to assess whether changes in the structure of supply distort aggregate statistics. The results show significant spatial heterogeneity of parameters, but only slight differences between traditional and hedonic indices in short-term monitoring.",0.0,https://doi.org/10.54694/stat.2025.45190cedbbc51293d5a6c9b99369caba95cca6a4ecb3f,10.15396/eres2019_218,Heterogeneous Households and Market Segmentation in a Hedonic Framework,2019.0,26th Annual European Real Estate Society Conference,Steven C. Bourassa; M. Hoesli; Martijn Droes,This paper explores Rosen’s (1974) suggestion that within the hedonic framework there are natural tendencies toward market segmentation. We show that market segmentation can be estimated on the basis of an augmented hedonic model in which marginal prices are separated by household characteristics into different classes. The classes can either be exogenously defined or endogenously determined based on an unsupervised machine learning algorithm or a latent class formulation. We illustrate the usefulness of these methods using American Housing Survey data for Louisville and show that there are distinct housing market segments within the Louisville metropolitan area based on income and family structure.,0.0,https://eres.architexturez.net/system/files/P_20190131192341_3991.pdf1916a495d8ab790e7b73fb54b9626ebd07aecde747c,10.24957/hsr.2023.31.1.79,Price Effect Analysis by Improving the Qualitative Characteristics of Apartment Buildings by Period in Gangnam-gu,2023.0,Korean Association for Housing Policy Studies,Song-Jie Yu; Jae Hee Kim; Young-Sun Song; Chang-Moo Lee,"In the domestic apartment market, the quality enhancement and differentiated strategies of construction companies have been implemented since the 2000s. In many ways, the quality characteristics of apartment buildings that have been improved continuously provided a variety of choices in the criteria for housing buyers to purchase. This study empirically analyzed the effect of improving the quality characteristics of apartments by period among the determinants of housing prices on apartments in Gangnam-gu, Seoul through the Hedonic price model. The analysis showed that all the variables of qualitative characteristics, which are the core variables of this study, had a positive effect on apartment prices. It was confirmed that some of the variables corresponding to the qualitative characteristic factors showed higher estimation coefficient values than other variables, which had a greater impact on apartment price formation. In addition, it can be seen that a significant portion of the price effect due to aging, which has been measured as a quadratic function in many previous studies, is the result of overlapping effects due to the improvement of the qualitative characteristics of apar",0.0,192b8c37b8ea0a12e9cbed953c9880d16a2673b2159,10.18335/region.v7i1.261,Measures of labour market accessibility. What can we learn from observed commuting patterns?,2020.0,,Liv Osland; Arnstein Gjestland; I. Thorsen,"It is well known that measures of labour market accessibility explains spatial variation in housing prices even in markets with polycentric labour market structures. This paper examines whether data on observed commuting patterns can replace or supplement gravity-based measures representing the commuting potential at specific locations. We use data from a region in Western Norway,and we find that measures based on observed commuting flows and commuting time cannot replace a gravity-based measure of labour market accessibility. Based on, inter alia, the spatial Durbin estimator we find that measures of observed commuting flows increase the explanatory power of a hedonic house price model.",0.0,https://openjournals.wu.ac.at/ojs/index.php/region/article/download/261/339193512f0b7686fef267e1a38cf48bd25b833ac3e6a2,10.56902/etdcrp.2013.20,The Value of Proximity to External Amenities and Mountain Views in the Metropolitan Denver Residential Housing Market,2013.0,,Tabatha Rose Waldron,"This research examines how natural amenities, such as views of Colorado’s Front Range mountains and proximity to lakes, parks and recreational areas, as well as proximity to community amenities such as hospitals, active wastewater treatment plants, fire and a police stations impact residential housing prices in Adams, Arapahoe and Denver Counties using a hedonic pricing model. Views of the mountains produced the most impact on home sale value in 2000 followed by proximity to a lake of 250 feet. These results demonstrate the importance of environmental amenities to single-family home buyers and can be used to inform parties involved in the future development of the area.",0.0,https://digitalcommons.du.edu/cgi/viewcontent.cgi?article=1047&context=geog_ms_capstone1945497cdcb3bd85699f486a6e157628bf5cbdf57d7,10.2991/icassr-15.2016.14,Impacts of Housing Features on Home Prices in Chengdu: Logarithmic Linear Regressions,2016.0,,Gao-Lu Zou; Lu-guang Xu; Deng Pei,"This paper aims to analyse the effects of several housing features on home prices in Chengdu, China. These features include larger floor space and green coverage rate. There are 1006 samples. Sampling is focused on existing ordinary homes. Data were collected from metropolitan Chengdu. Utilizing log-linear hedonic techniques, the study suggests a nonlinear marginal effect of housing age on house prices. Green converge has a positive impact on prices. We suggest higher property tax rates applicable to units with larger floor space, higher green coverage rate and lower volume fraction. Index Terms - Home space, green coverage, housing feature, log-linear, marginal effect.",0.0,https://download.atlantis-press.com/article/25846540.pdf1953357e71759e69bc4a6191ef07fbebbf0c7b5fbc3,10.57178/jer.v8i2.1607,Analysis of the Application of the Hedonic Price Method in Setting House Rental Prices in the Coastal Area of Padang City,2025.0,JURNAL ECONOMIC RESOURCE,A. Putri; Tri Kurniawati,"This research investigates how structural, location, and environmental attributes impact residential rental rates in Padang City, a region challenges by disaster risks and limited facility access. The study aims to identify key determinants affecting rental costs. A quantitative research design was employed, utilizing questionnaires for data collection, followed by analysis through multiple linear regression. Finding reveal that all three independent variables significantly affect rental pricing, as reflected by an F-value of 61,607, substantially surpassing the critical threshold of 2,69. These insights are valuable for shaping more effective housing policy strategies.",0.0,https://jurnal.feb-umi.id/index.php/JER/article/download/1607/12121962bf7befeb78be2c9365a1d6179643a46fb465980,10.1080/00330124.2022.2148902,The Efficacy of Mortgage Lending on Geographically Disparate and Differently Priced Residential Neighborhoods in Shanghai,2023.0,Professional Geographer,Cheng-He Guan; Kelly Yan; Bo Zhang; Ying Li; Xiao-Ling Zhang,"As both a vibrant industry and necessity for people’s lives, housing has attracted much attention in recent years. This article examines the efficacy of both loosening and tightening policies on mortgage lending in different priced housing markets in Shanghai, China, from 2014 to 2018 using daily average sale prices across 1,824 neighborhoods, with price-classified cluster analysis and policy-informed hedonic regressions. The results show that (1) the effects of mortgage lending policy interventions varied significantly and the overall spatial distribution gravitated toward subway networks and varied throughout the years; (2) the effects of interventions were time lagged but varied by different priced neighborhoods; and (3) although the accumulated number of both loosening and tightening policies were both significant, only the effects of tightening policies were significant overall. This article contributes to the existing literature by combining the spatial-temporal component in policy studies, providing detailed mortgage lending policy intervention variables, and expanding the scope of study from housing prices to housing transaction frequencies.",0.0,19746ca9fdd13ccad0f4efeb349ea0fcd25702a960a,10.55463/hkjss.issn.1021-3619.64.12,"Determinants Influencing the Price of Second-Hand Condominiums in Bangkok’s Central Business District, Thailand",2024.0,Hong Kong Journal of Social Sciences,Pornraht Pongprasert,": This study aims to analyze the factors affecting the prices of second-hand condominiums in Bangkok’s central business district (CBD). After the COVID pandemic, new residential properties in urban areas of Bangkok have become more complicated to sell because of declining purchasing power among customers, with many new buyers turning to second-hand properties. In 2023, the sales growth of second-hand houses and condominiums in Bangkok increased by up to 2.6 trillion baht compared to 2022. Notably, second-hand condominium sales in Bangkok grew by approximately 36.7%. Additionally, the younger generations prefer to live in urban areas near public transport and their workplaces. In this study, 400 second-hand condominiums in Bangkok's CBD opened between 2018 and 2023 were surveyed, and data were collected. Twenty-four independent variables related to pricing factors, including locational and structural attributes and neighborhood environments, were examined. The hedonic price model investigated the factors influencing second-hand condominium prices. This study aims to highlight the importance of various physical attributes that affect",0.0,198d5b166d93b85d7f563ac3aa3093228d596231330,10.3917/reru.255.0745,Evaluation of local environmental factors using the hedonic price method: The case of Grand Tunis municipalities,2025.0,Revue d’Économie Régionale & Urbaine,Souha Temimi; Hanène B. Ouada Jamoussi; I. Ben Ammar,"Cette étude analyse les préférences résidentielles des ménages tunisiens à partir de modèles hédoniques intégrant les interdépendances spatiales. Elle s’appuie sur une base de données microéconomique géoréférencée couvrant 613 logements situés dans l’aire métropolitaine de Tunis. Les résultats soulignent l’importance des aménités locales dans la formation des prix immobiliers, en particulier la proximité des infrastructures scolaires, dont l’effet dépasse largement celui du littoral ou d’autres aménités naturelles ou structurelles. Les impacts indirects liés à l’accessibilité éducative s’avèrent plus déterminants que les effets directs dans les choix résidentiels. Par ailleurs, des facteurs socio-économiques comme le chômage et la pauvreté sont associés à une dévalorisation des biens immobiliers, notamment dans certains quartiers. Ces résultats plaident pour une meilleure coordination des politiques d’aménagement urbain et d’investissement social, afin de réduire les inégalités territoriales et renforcer l’attractivité résidentielle dans un contexte de croissance urbaine et de contraintes budgétaires.",0.0,199ab63cf056264801d0565c22b30ac506ba377c92b,10.1109/icaml51583.2020.00043,Study on Spatial Distribution of Housing Price and its Influencing Factors of Cities and Towns Peripheral to China (Hubei) Pilot Free Trade Zone Wuhan Area,2020.0,2020 2nd International Conference on Applied Machine Learning (ICAML),Ying-Juan Du; Wei Huang,"As a new Free Trade Zone in Wuhan, China (Hubei) Pilot Free Trade Zone Wuhan Area (hereinafter referred as WA) provides certain innovation and practical guiding significance for being researched on. This paper studies the spatial distribution of housing price and its impact factors of cities and towns around Wuhan Free Trade Zone, which has important reference value for the future development rural areas under construction. Kriging interpolation method and spatial autocorrelation analysis were adopted in this paper to explore the spatial distribution pattern of housing prices of the target cities and towns around WA, and it is found that the spatial differentiation of housing prices was highlighted with the center of Optics Valley of China as the core, and a significant spatial agglomeration mode was discovered. In addition, the construction of hedonic price model revealed that the main impact factors of residential price include plot ratio, property management fee, road accessibility, nearest distance to the park and the nearest distance to commercial network station.",0.0,200269081eefa7196b7a90126f2af94582c41238eba,10.22313/reik.2023.21.1.91,Effects of Direction of the Gaining Water and Draining Water on Apartment Sales Price,2023.0,Residential Environment Institute Of Korea,Gap Ju Son; Hae-jung Chun,"This study analyzed how the direction of the gaining water and draining water in the apartment along the Jeong-neung stream in Dongdaemun-gu affect the apartment sales price using the Hedonic Price model. In this study, the dependent variable was the actual apartment sales price. As independent variables, the direction of water extraction and draining water , elapsed years, the trading floor, the number of apartments building, the distance subway station, elementary school, and middle school were used. As a result of the analysis, it was analyzed that the direction of gaining water, the higher number of elapsed years, the higher number of apartments building and the higher the trading floor had a positive (+) effect on apartment sales prices. In addition, it was analyzed that direction of the draining water and the farther the distance to the subway station, elementary school, and middle school, the negative (-) effect on the apartment sales price.",0.0,201f3cd27354cf3a29a8ccb41a4aef3ae67a70ce98a,10.5604/01.3001.0054.8597,Price-setting factors or revealed preferences? How to understand the results of hedonic models and hedonic indices of the housing rental market that base on listings data?,2024.0,Bank i Kredyt,Michał Hebdzyński,"The problematic access to housing rental market transactional data forces the use of alternative sources. Using the observations of transactions and listings of apartments for rent located in Poznań, it was checked whether the fruits of hedonic models based on listings data may be treated as a proxy of consumers’ revealed preferences. Moreover, the study answered whether listings and transactions- -based hedonic rent indices show the same dynamics. Observing listings and transactions of the same apartments, it was concluded that the estimated determinants of listed rents may be considered a proxy of revealed preferences. Similarly, the listings-based hedonic rent indices proved to reflect well the dynamics indicated by market transactions. However, it is not the difference between the height of the listed and transacted rents that proved to be problematic in hedonic modelling, but the inequality of the quality structure of the analysed data types.",0.0,2027b3db83f17b60edf65e58e58daf2e4dc8f2af213,10.1108/ijhma-10-2020-0125,"Is HOA capitalized in housing price? Evidence from Chongqing, China",2021.0,,F. Deng,"203Purpose204International research has found that Homeowners Association (HOA) is capitalized in housing price in the West. Is that result applicable in Chinese cities? In China there is also widespread applause for HOA. Will that leave trail in the housing market? This paper aims to answers these questions by presenting empirical evidence from 113 private gated communities in Chongqing, China.205206207Design/methodology/approach208The data set comes from three different sources including a telephone survey. The research methodology includes hedonic models with an endogenous dummy variable of the presence of HOA in a community.209210211Findings212HOA is not capitalized in housing price.213214215Research limitations/implications216The empirical finding helps to explain why about 80% of private communities in big Chinese cities have not formed an HOA.217218219Originality/value220This is the first empirical study on HOA capitalization in housing price in China.221",0.0,2229f07012b239b72b0712dbbae066b72fc7f6b02fe,10.2139/ssrn.3474304,Residential Wealth and Its Interpersonal and Spatial Distribution in the Rio de Janeiro Metropolitan Region,2019.0,Social Science Research Network,D. Vetter; K. Beltrao; R. Massena,"October 22, 2019 Abstract: Given the importance of housing as a component of a household’s worth and of aggregate national wealth, we ask: What variables determine housing value in the Rio de Janeiro Metropolitan Region? What is Rio’s aggregate residential wealth (i.e., the sum of the values of all housing units) and its distribution among household income and tenure groups and in space? In other words, what generates residential wealth? How much residential wealth is there? Who holds it? Where is it located? To address these questions, we first calibrate a hedonic residential rent model with microdata from the 2010 Population Census. We then use this model to estimate the rents for homeowners and subsequently transform the actual and imputed rents into housing values. Finally, we analyze the distribution of residential wealth by household income and tenure and subregions and discuss the policy implications of our findings.",0.0,2234220f418775d026d963f88a95b6987fc1d3c6721,10.1111/jors.70066,Sweating Assets: The Effect of Extreme Heat on the Housing Market,2026.0,Journal of Regional Science,Jindong Pang; Jie Feng; Yuan Zhao,"224 This paper studies the impact of extreme heat on the housing market in 26 Chinese cities by analyzing more than 1.5 million second‐hand housing transaction records. Empirical results from hedonic regressions show that extreme heat significantly decreases housing prices and transaction volumes. This negative effect is concentrated in warm seasons and is substantially stronger for high‐end apartments, top‐floor units, and units in high‐rise buildings. Green spaces and water bodies are effective in mitigating the negative effect of extreme heat on the housing market. Mechanism analysis demonstrates that extreme heat significantly decreases the number of on‐site property visits before a transaction. These findings underscore the important influence of climate change on the housing market.",0.0,2259dfdb887833a47e99f41dbf967dee634121437ef,10.1111/ehr.70096,"Long‐run housing price indices and determinants: New data from Huizhou, China, 1570–1949",2026.0,The Economic History Review,Si-Yu Pan,"226 Economic studies on historical housing markets have gained increased popularity in recent years, yet remain limited by data scarcity. In this paper, a novel housing transaction dataset with more than 1000 observations from the historic Huizhou prefecture in south China is collected. This study develops housing price indices spanning the late Ming, Qing, and Republic of China eras (1570–1949). Results from hedonic ordinary and quantile regressions reveal unique housing price determinants tied to the region's cultural background: property orientation, proximity to ancestral halls and Buddhist temples, and seller's gender. Sellers being in urgent financial situations is positively correlated with the sales price.",0.0,2279caa3f75fb388144da165242da3e002177a38803,10.1111/irfi.70097,The Impact of Homeless Encampments on Housing Prices,2026.0,International Review of Finance,J. Kallberg; Yoshikiyo Shimizu,"228 A topic of intense and heated discussion in urban America is the impact of homelessness, yet the quantitative evidence is limited. This study examines how proximity to a homeless encampment influences housing prices. Analyzing home sale transaction data in Seattle from 2017 to 2020, our hedonic models reveal that houses within 0.75 miles of an encampment sell for about 2.0% less (equivalent to an average impact of $17,445). Quantile regressions show that this negative effect persists across most market segments and is most pronounced in 2018–2019, when Seattle recorded the highest number of encampment removals. Results remain generally robust after adjusting for spatial autocorrelation.",0.0,229f39eff943185bd0c72d9f537dd593309909e81c1,10.1007/s10109-017-0262-1,Erratum to: Housing price prediction: parametric versus semi-parametric spatial hedonic models,2017.0,Journal of Geographical Systems,J. Montero; R. Mínguez; G. Fernández-Avilés,,0.0,https://link.springer.com/content/pdf/10.1007%2Fs10109-017-0262-1.pdf2300bd5416ee79a0fb502afb9a45498e02d2b264a37,10.18397/kcgr.2011.15.1.159,The Comparison of Hedonic Housing Price Models in the Busan Housing Market using Spatial Econometrics Methodology,2011.0,,Kyoun-Sup Chung,,0.0,https://doi.org/10.18397/kcgr.2011.15.1.1592316d1a077c71600af2446bed1037c93ca304601894,10.2139/ssrn.4598682,Determinants of Hanoi Apartment Price Using Hedonic Approach,2023.0,Social Science Research Network,Thi Thanh Binh Dao; To Hoang Lan Linh,,0.0,https://doi.org/10.2139/ssrn.459868223251045ea77fa3c3143d1f66ad6f1044e00438ff72,10.19172/kreaa.30.3.4,The Effects of the Living-zone Park Types on the Housing Prices - Using Spatial Hedonic Model -,2024.0,Journal of the Korea Real Estate Analysts Association,Eunji Na; Dongwon Ko; Seung-Hoon Park,,0.0,2338079c987c374c2df518c5e529a25f614eb6a7291,10.2139/ssrn.4379221,"Spatially Heterogeneous Effects of Location, Amenity and Built Environment on the Rental Housing Market: A Geographically Weighted Hedonic Model",2023.0,Social Science Research Network,Jiajie Liu; T. Liu; Guang-Zhong Cao,,0.0,234doi_10_1007_978_3_032_06118_8_12,10.1007/978-3-032-06118-8_12,On the Performance of LLMs for Real Estate Appraisal,2025.0,arXiv,Margot Geerts; Manon Reusens; Bart Baesens; Seppe vanden Broucke; Jochen De Weerdt,"The real estate market is vital to global economies but suffers from significant information asymmetry. This study examines how Large Language Models (LLMs) can democratize access to real estate insights by generating competitive and interpretable house price estimates through optimized In-Context Learning (ICL) strategies. We systematically evaluate leading LLMs on diverse international housing datasets, comparing zero-shot, few-shot, market report-enhanced, and hybrid prompting techniques. Our results show that LLMs effectively leverage hedonic variables, such as property size and amenities, to produce meaningful estimates. While traditional machine learning models remain strong for pure predictive accuracy, LLMs offer a more accessible, interactive and interpretable alternative. Although self-explanations require cautious interpretation, we find that LLMs explain their predictions in agreement with state-of-the-art models, confirming their trustworthiness. Carefully selected in-context examples based on feature similarity and geographic proximity, significantly enhance LLM performance, yet LLMs struggle with overconfidence in price intervals and limited spatial reasoning. We off",,https://arxiv.org/pdf/2506.11812v1235doi_10_1177_23998083231213894,10.1177/23998083231213894,Extracting real estate values of rental apartment floor plans using graph convolutional networks,2023.0,arXiv,Atsushi Takizawa,"Access graphs that indicate adjacency relationships from the perspective of flow lines of rooms are extracted automatically from a large number of floor plan images of a family-oriented rental apartment complex in Osaka Prefecture, Japan, based on a recently proposed access graph extraction method with slight modifications. We define and implement a graph convolutional network (GCN) for access graphs and propose a model to estimate the real estate value of access graphs as the floor plan value. The model, which includes the floor plan value and hedonic method using other general explanatory variables, is used to estimate rents and their estimation accuracies are compared. In addition, the features of the floor plan that explain the rent are analyzed from the learned convolution network. Therefore, a new model for comprehensively estimating the value of real estate floor plans is proposed and validated. The results show that the proposed method significantly improves the accuracy of rent estimation compared to that of conventional models, and it is possible to understand the specific spatial configuration rules that influence the value of a floor plan by analyzing the learned GCN.",,https://arxiv.org/pdf/2303.13568v12362f03532299a505f55608166eb1824cff6a680e85,10.1016/s1051-1377(05)80028-2,Arithmetic Repeat Sales Price Estimators,1991.0,,R. Shiller,"Repeat sales price estimators are designed to infer price indexes of infrequently sold and unstandardized assets, such as houses, based only on changes in prices of those individual assets that are observed to be sold twice. Repeat sales price estimators are proposed here that are arithmetic, and either value-weighted or equally-weighted. Moreover, variants are proposed that are interval-weighted, i.e., that correct for a form of heteroskedasticity, and that include additional regressors representing changes in hedonic variables. Some of these methods are applied to data on house prices in Atlanta, Chicago, Dallas and San Francisco 1970-1986.",225.0,https://doi.org/10.1016/s1051-1377(05)80028-2237doi_10_1016_j_jtrangeo_2008_10_012,10.1016/j.jtrangeo.2008.10.012,Does high-speed rail accessibility influence residential property prices? Hedonic estimates from southern Taiwan,2010.0,Journal of Transport Geography,David Emanuel Andersson; Oliver F. Shyr; Johnson Fu,,153.0,238ddb3a8895ad5dfbe89c033d615bc7a80234d8c6c,10.1016/j.landurbplan.2016.06.010,Environmental externalities of urban river pollution and restoration: A hedonic analysis in Guangzhou (China),2017.0,,Wendy Y. Chen,"Abstract The degradation of urban river ecosystems presents a serious threat to sustainable urban development. Consequently, extensive efforts have been devoted to the ecological restoration of urban rivers worldwide. This study evaluates the environmental externalities associated with water pollution and river restoration in Guangzhou in southern China. A basic hedonic pricing model is applied to test hypotheses using a sample of 968 apartment transaction records during July-December 2013. Results show that river restoration could reverse negative externalities of polluted watercourses to positive externalities, especially for those apartments located on the 10th floor or lower. Water quality improvement from polluted non-recreational water (Grade V or worse) to non-body contact recreational water (Grade IV) could increase apartment values by 0.9%. River restoration (including river bank greening and water quality improvement) could increase property values by 4.61%, demonstrating a preference of Guangzhou residents for greening riverscapes. This study could hopefully provide a scientific basis for urban river governance for communities and decision-makers, and serve as a referenc",114.0,http://hdl.handle.net/10722/2454072394f4475636117754066fcc0578aecfcf69e646566,10.3846/1648-715x.2008.12.251-269,MODELLING THE IMPACT OF WIND FARMS ON HOUSE PRICES IN THE UK,2008.0,,S. Sims; P. Dent; G. Oskrochi,"This paper discusses the findings from a UK study to determine the likely impact of a wind farm on house prices using a hedonic pricing model. The Government's commitment to wind power has resulted in a massive increase in the number of wind farms sited in the UK. This has led to concerns that their visual and aural presence could have a negative impact on proximate house prices. This paper presents an analysis of 201sales transactions from houses situated within half a mile of a 16 turbine wind farm in Cornwall, UK. Whilst no causal link was established between the presence of the wind farm and house price, there was some evidence to suggest that both noise and flicker from the turbine blades could blight certain property and that the view of countryside enjoyed by the occupier had some value which may be affected by a wind farm.",107.0,https://journals.vilniustech.lt/index.php/IJSPM/article/download/6769/58492409851a7a479c8f65369fd38395b2a494dfb04e4b7,10.2139/ssrn.2171090,"Hedonic price–rent ratios, user cost, and departures from equilibrium in the housing market",2012.0,,R. Hill; Iqbal A. Syed,,105.0,https://doi.org/10.2139/ssrn.2171090241656690658486fd9be1f1d74ed0ac265211cea36a,10.2172/978870,The Impact of Wind Power Projects on Residential Property Values in the United States: A Multi-Site Hedonic Analysis,2010.0,,B. Hoen; R. Wiser; Peter A. Cappers; M. Thayer; Gautam Sethi,"This report uses statistical analysis to evaluate the impact of wind power projects on property values, and fails to uncovers conclusive evidence of the existence of any widespread property value impacts.",102.0,https://www.osti.gov/servlets/purl/978870242doi_10_1007_s10109_005_0011_8,10.1007/s10109-005-0011-8,Heterogeneity in hedonic modelling of house prices: looking at buyers’ household profiles,2005.0,Journal of Geographical Systems,Yan Kestens; Marius Thériault; François Des Rosiers,,96.0,2434016a68ad871f943235e95c02162687224352516,10.1016/j.reseneeco.2012.05.006,"A Hedonic Analysis of the Impact of LUST Sites on House Prices in Frederick, Baltimore, and Baltimore City Counties",2012.0,,Jeffrey E. Zabel; D. Guignet,,85.0,24458723b0a92c749942b72ca7c820ae13c20920cb2,10.3386/w22204,Who Wants Affordable Housing in their Backyard? An Equilibrium Analysis of Low Income Property Development,2016.0,,Rebecca Diamond; Timothy J McQuade,"We nonparametrically estimate spillovers of properties financed by the Low Income Housing Tax Credit (LIHTC) onto neighborhood residents by developing a new difference-in-differences style estimator. LIHTC development revitalizes low-income neighborhoods, increasing house prices 6.5%, lowering crime rates, and attracting racially and income diverse populations. LIHTC development in higher income areas causes house price declines of 2.5% and attracts lower income households. Linking these price effects to a hedonic model of preferences, LIHTC developments in low-income areas cause aggregate welfare benefits of $116 million. Affordable housing development acts like a place-based policy and can revitalize low-income communities.",80.0,https://doi.org/10.3386/w22204245https://openalex.org/W1541727578,10.1108/17538271011080655,Structural and temporal changes in the housing market and hedonic housing price indices,2010.0,International Journal of Housing Markets and Analysis,Chihiro Shimizu; Hideoki Takatsuji; Hiroya Ono; Kiyohiko Giichi Nishimura,"Purpose An economic indicator faces two requirements. It should be reported in a timely manner and should not be significantly altered afterward to avoid erroneous messages. At the same time, it should reflect changing market conditions constantly and appropriately. These requirements are particularly challenging for housing price indices, since housing markets are subject to large temporal/seasonal changes and occasional structural changes. The purpose of this paper is to estimate a hedonic price index of condominiums of Tokyo, taking account of seasonal sample selection biases and structural changes in a way it enables us to report the index in a manner which is timely and not subject to change after reporting. Design/methodology/approach The paper proposes an overlapping‐period hedonic model (OPHM), in which a hedonic price index is calculated every month based on data in the “window” of a year ending this month (this month and previous 11 months). It also estimates standard hedonic housing price indexes under alternative assumptions: no structural change (“structurally restricted”: restricted hedonic model) and different structure for every month (“structurally unrestricted”: u",74.0,2469bd20b61e5c7fa4aa4d2631c77ceb8c9e80ffe0d,10.1016/j.cities.2016.08.008,Defining Street-based Local Area and measuring its effect on house price using a hedonic price approach: The case study of Metropolitan London,2017.0,,S. Law,,73.0,https://discovery.ucl.ac.uk/10049564/3/Law_Street_Based_Loal_Area_SL.pdf247bd9daec586047735281c309ba315ffde35ffa3a5,10.3390/su9020185,Park Accessibility Impacts Housing Prices in Seoul,2017.0,,Jin Han Park; Dong-Kun Lee; Chan Park; H. Kim; T. Jung; Songyi Kim,"Housing prices are determined by a variety of factors, including the features of the building and the neighborhood environment, and a potential buyer decides to buy a house after reviewing these factors and concluding that it is worth the price. We used Hedonic Price Methods to find the relationship between monetary value of house and access conditions to urban parks. Two meaningful results were discovered in this study: first, as the distance from the park increases, the value of the park inherent in the housing price decreases; second, the greater walking accessibility, to the park, the higher the park value inherent in housing prices. Despite presenting shorter distances to walk and more entrances, poorly accessible zones were deemed as such due to the necessity of crossing an arterial road. This indicates that the results can define accessibility not as the Euclidian distance but as the shortest walking distance while considering crossroads and park entrances. The results of this study have significant implications for urban park economic impact analyses in Seoul. Also, the increase in housing prices closer to parks supports the idea that access is dependent on the residents’ s",72.0,https://www.mdpi.com/2071-1050/9/2/185/pdf?version=1485510518248617a0a763271a47069a8c5961c491dcb44392851,10.2139/ssrn.3678595,Estimating the Impact of Energy Efficiency on Housing Prices in Germany: Does Regional Disparity Matter?,2021.0,Social Science Research Network,Lisa Taruttis; C. Weber,"The German government aims at a climate-neutral building stock by 2050 to reach the goals defined in the Climate Action Plan 2050. Increasing the energy efficiency of existing buildings is therefore a high priority. For this purpose, investments of private homeowners will play a major role since about 46.5% of the German dwellings are owner-occupied. To identify potential monetary benefits of investing in energetic retrofits, we investigate whether energy efficiency is reflected in property values of single-family houses in Germany. Thereby we examine possible heterogeneous effects among regions. With 455,413 individual observations on a 1km²-grid level for 2014 to 2018, this study adds to the literature 1) by examining the effect of energy efficiency on housing values for Germany on a more small-scale level and specifically investigating regional disparities in this context and 2) by estimating an energy efficiency value-to-cost ratio. Applying a hedonic analysis, we find a positive relationship between energy efficiency and asking prices. We also find evidence for regional disparities. Effects are significantly weaker in large cities compared to other urban areas, whereas the im",65.0,https://doi.org/10.1016/j.eneco.2021.105750249cfd672ad9855be9ac99c22cd8049d89019f9c793,10.3390/su11133707,Urban Green Spaces and Housing Prices: An Alternative Perspective,2019.0,Sustainability,V. Liebelt; Stephan Bartke; N. Schwarz,"Urban green spaces (UGS) are essential components of sustainable cities that provide many benefits to urban residents, such as recreation or aesthetics. Urban residents may be willing to pay for some of these ecosystem services. Indeed, studies investigating the formation of housing prices through hedonic pricing analysis have shown that UGS can influence housing prices. Hedonic pricing analysis puts housing units at the center of analysis. In this study, we investigate whether an alternative perspective provides additional insights into the effects of UGS on pricing. The proposed approach puts UGS into the center of analysis by applying an analysis of buffer zones to housing prices, thus, linking approaches from urban economics and landscape ecology. Such an analysis could deepen our understanding of the effects of UGS on housing prices by analyzing price–distance slopes around UGS-thus supporting more informed decisions on efficient UGS management and urban planning. Our results using a case study on Leipzig, Germany, demonstrate that the size of UGS affects price–distance slopes around them. We conclude that further investigations should be fathomed to unleash the potential of a",60.0,https://www.mdpi.com/2071-1050/11/13/3707/pdf?version=1562395888250bca96be32bc6ec554c1a92328b0350115c15432c,10.2139/ssrn.960422,The Effect of the Theo Van Gogh Murder on House Prices in Amsterdam,2007.0,Social Science Research Network,Pieter A. Gautier; A. Siegmann; A. van Vuuren,"Does Islamic terrorism have an effect on the general attitudes towards Muslim minorities? We use the murder of Theo van Gogh as an event study to address this question. Specifically, we use the hedonic-market model and test for an effect on listed house prices in neighbourhoods where more than 25% of the people belong to an ethnic minority from a Muslim country (type I). Relative to the other neighbourhoods, house prices in type I neighbourhoods decreased in 10 months by about 3%, with a widening gap over time. We use a unique weekly data set from a multi listing service that contains over 70% of all houses for sale and obtain the actual transaction prices from the registers office. Our results are robust to several adjustments including changes in the control group. There is no significant difference in the time it takes for houses to be sold in type I versus other neighbourhoods. Finally, we find evidence that segregation increased. People belonging to the Muslim minority were more likely to buy and less likely to sell a house in a type I neighbourhood after the murder than before.",59.0,https://doi.org/10.2139/ssrn.9604222511d237b2ed7c862832a45adce8c950b6e84279ada,10.1093/jof/103.3.146,The Impact of Forest Density on Property Values,2005.0,Journal of Forests,Y. Kim; A. Wells,"252 We applied a simple hedonic price model to determine the benefits of fuel reduction treatments reflected in residential housing values in Flagstaff, Arizona, in hopes of finding a way to address increasing treatment costs. Results show that the fuel reduction treatments that convert high canopy closure would increase property values significantly ($190 per 1,000 m2 per home). The treatments that lower forest density are not only one means to reduce wildfire hazard but also to enhance scenic beauty and improve residential property values.",54.0,https://academic.oup.com/jof/article-pdf/103/3/146/22614421/jof0146.pdf25377c19717dd7dc4037a2b4a8c854ef558d56021c0,10.1016/j.ecolecon.2020.106692,"Hedonic Price Estimates of Lake Water Quality: Valued Attribute, Instrumental Variables, and Ecological-Economic Benefits",2020.0,,M. Moore; J. Doubek; Hui Xu; B. Cardinale,"We estimate the effect of lake water quality on residential housing prices using cross-sectional data on water clarity from 113 lakes across the United States. An instrumental-variables approach is developed to address potential endogeneity bias in the water-clarity variable. Three lake-based physical variables serve as instrumental variables: total nitrogen concentration in lake water, total phosphorus concentration in lake water, and water temperature near the lake surface. The econometric results include three methodological findings: the instruments are valid and strong; the ordinary-least-squares estimate of the coefficient on the water-clarity variable is unbiased; and water clarity is the attribute of water quality valued in the housing market. The estimated water-clarity effect shows that a one-tenth of a meter change in water clarity leads to a one-percent change in housing price, or an elasticity of 0.20 at mean clarity. Coupling this effect with estimates of an ecological production function, a lake-specific benefit index is developed that shows the effect on housing values of bringing lakes into compliance with the US Environmental Protection Agency's regional recommend",49.0,https://www.osti.gov/biblio/178763925480f7cd67d50e334ac02491c841b6eda68cdc9948,10.2139/ssrn.2785137,Rent Indices for Housing in West Germany 1985 to 1998,2002.0,Social Science Research Network,Johannes Hoffmann; C. Kurz,"In several studies, hedonic methods have been used successfully for the ex post assessment of the accuracy of inflation measurement. Most of these studies relate to high-tech products, with respect to which traditional methods of compiling price indices often fail. We apply hedonic methods to rental housing services, which display less quality progress. However, as German households spend about 10 % of total expenditure on housing rents, even a small bias in this field might induce a substantial distortion in overall inflation measurement. Based on data from the German Socio-Economic Panel, we per- form an hedonic analysis of housing rents and compile different price indices. Overall, we conclude that there is some evidence of an understatement of rent inflation in the official rent index for West Germany at the beginning of the 1990s.",47.0,https://doi.org/10.2139/ssrn.2785137255433fc152c87a1e087157e21d8f30cf502674a58c,10.1016/j.habitatint.2015.08.036,"Housing valuation of different towns using the hedonic model: A case of Faisalabad city, Pakistan",2015.0,,Ghaffar Ali; M. Bashir; H. Ali,,45.0,256e4f33aca0968c7c930129cd6f3fbf32507e5ac89,10.3846/ijspm.2019.6360,THE EFFECTS OF A SHOPPING MALL ON HOUSING PRICES: A CASE STUDY IN HANGZHOU,2018.0,International Journal of Strategic Property Management,Ling Zhang; Jiantao Zhou; E. Hui; Hai-Zhen Wen,"There are few studies on the externalities of shopping malls affecting the housing market. This study aims to discuss two issues: (1) What is the intensity of the impact of a shopping mall? (2) When does the external influence of a shopping mall begin to reveal itself? The West Intime Shopping Mall in Hangzhou offers a unique situation to research the questions. By dividing the study area into nine blocks, using hedonic price theory, and the price gradient approach with housing price data from 2011 to 2015, we found that in the space dimension, the mall exerted a significantly positive effect on the housing prices of nearby blocks. With the increase in distance from the mall, the positive effect decreased. There were more significantly positive effects in blocks far away from the city center. In the time dimension, the effects of West Intime did not reveal themselves until the mall had started to operate and gradually matured over time, implying that the mall did not have the obvious expected impact on housing prices before the mall had begun operating.",44.0,https://journals.vgtu.lt/index.php/IJSPM/article/download/6360/5556257dc7af9635b44a955a97c00b64b679a047f2f9a2f,10.1016/j.jenvman.2019.05.144,Impacts of environmental disturbances on housing prices: A review of the hedonic pricing literature.,2019.0,Journal of Environmental Management,S. Nicholls,"The global environment is susceptible to many types of change, including alterations to the world's climate. Climate change has been linked to a host of modifications to the natural environment, including the increasing frequency and severity of disturbances such as pest outbreaks, invasions by non-native species, and wildfire. These in turn pose substantial risks to human wellbeing and health. Estimates of the direct and indirect costs of these events are important prerequisites to well-rounded cost-benefit analyses of preventative or control measures, themselves essential components of appropriate education, policy and management responses. This review brings together the evidence with respect to the impacts of disturbances such as pests, invasive species and wildfire on residential property values as measured using the hedonic pricing method. It demonstrates that whilst most disturbances have the expected negative or an insignificant house price impact, in some cases disturbances can lead to housing price rise. The possible causes and implications of these unanticipated positive price responses are discussed. Broader consequences of all directions of price impact are also consid",43.0,258fdea450f2dc45c56b781a13d9e1a25b7cc317419,10.1016/j.chieco.2017.04.007,"Unequal school enrollment rights, rent yields gap, and increased inequality: The case of Shanghai",2017.0,China economic review,Muyang Zhang; Jie Chen,"This paper first builds a simple theoretic model to explore how a special feature of enrollment policy of public primary schools in urban China, the unequal enrollment right between home owners and tenants, would produce rent-yields gap between different housings. The model also predicts that an enrollment policy featuring with tenant discrimination, accompanying with strict credit constraint, would reduce the chance of kids from middle-income families to attend better public schools while allow families with high initial wealth to access better high-quality public education at a lower cost. Using a hedonic pricing model, we find that, in Shanghai, rental yields of housings in neighborhoods associated with reputed public primary schools is on average 0.1–0.35 percentage-point lower than those associated with ordinary ones. We also explore how the rent-yields-gap varies across housing types, locations and changes over time. Nonetheless, our simulation computation suggests that the estimated opportunity cost of holding such schools in Shanghai is generally not a big amount and affordable for many families. Overall, the high entry costs of owing a housing is the major obstacle to acce",42.0,259a7994232e9de0d259914c149f19b3754a7f3b324,10.3233/sju-1985-3301,The application of hedonic indexing methods: A study of house prices in the United Kingdom,1985.0,,M. Fleming; J. Nellis,,42.0,260c92f6dd86a2220a544310471aaec06b7d66f2b88,10.1111/pirs.12003,A Bayesian approach to hedonic price analysis,2014.0,,D. Wheeler; A. Páez; Jamie E. L. Spinney; L. Waller,"type=""main"" xml:lang=""es""> Dos objetivos importantes en el analisis de precios hedonicos son la prediccion de los precios de venta y la delimitacion de submercados basada en consideraciones geograficas y funcionales. Para hacer frente a estos objetivos, en este articulo se han aplicado modelos bayesianos con coeficientes espacialmente variables para realizar un analisis de los precios de venta de la vivienda en la ciudad de Toronto (Ontario). Se evaluo el desempeno del modelo y se determinaron los patrones de los submercados indicados por los procesos de coeficiente espacial. Los resultados muestran que los modelos de proceso espacial bayesiano predicen bien los precios de venta de viviendas, proporcionan inferencias utiles con respecto a la heterogeneidad de precios dentro de un mercado, y pueden especificarse de modo que incluyan las opiniones de los expertos del mercado.",40.0,https://doi.org/10.1111/pirs.12003261b74d93f9fabc2a91919abdebe4d39182e2434094,10.1093/jeg/lbw040,"The impact of aircraft noise on apartment prices: a differences-in-differences hedonic approach for Frankfurt, Germany",2017.0,,Tim Winke,,40.0,26288985cc55defaaf2667566d4c6729c872cdceff5,10.1016/j.erss.2018.11.014,Energy next door: a meta-analysis of energy infrastructure impact on housing value,2019.0,Energy Research & Social Science,C. Brinkley; A. Leach,"Abstract The decision to site energy facilities occurs largely at the local level, requiring community support for permitting and construction. Biomass and waste incineration have been broadly adopted in European and Asian countries. Yet, combustion and the placement of affiliated smokestacks are often contentious. Similarly, wind turbines, large photovoltaic arrays, and transmission lines are often criticized for disturbing viewsheds. As communities consider energy production, they often weigh benefits against concerns for how facilities may impinge on the local quality of life. This review of 54 studies spanning over forty years of statistical multi-variate housing price assessments in relation to energy supply infrastructure provides a comparative meta-analysis of both the negative and positive local impacts of siting energy infrastructure. The oldest studies in the 1960s investigated powerlines and waste-to-energy facilities, both with mixed results. A surge of studies in the 1990s assessed renewable energy infrastructure, including hydropower, wind, and rooftop solar, concluding that of all energy infrastructure only rooftop solar consistently positively impacts home value. Tr",38.0,263ede799d5a89d38a16239a4734a2cb00510a8c501,10.13060/23362839.2021.8.1.524,"The COVID-19 Pandemic, Airbnb and Housing Market Dynamics in Warsaw",2021.0,Critical Housing Analysis,R. Trojanek; Michał Głuszak; Michał Hebdzyński; Justyna Tanas,"In this study, we analyse the impact of COVID-19 on house rents and prices in Warsaw, the capital of Poland. Hedonic indexes indicate a slight increase in prices (ca. 1.2%) and a substantial drop in long-term rents (ca. -7.7%) between March 2020 and December 2020. The largest decline in rents occurred in centrally located neighbourhoods, which was largely due to the inflow of new housing supply from the short-term rental market (the Airbnb Warsaw market shrank by almost 30% in December 2020 y/y). Using hedonic methods, we show the effect of the shrinking Airbnb market on the drop in long-term rents. The study indicates the elasticity of rents with respect to Airbnb supply, with a 1% change in Airbnb listings leading to a 0.031% change in rents.",37.0,https://www.housing-critical.com/data/USR_057_DEFAULT/The_COVID_19_Pandemic__Airbnb_and_Housing_Market_Dynamics_in_Warsaw(1).pdf264cbbbfe27d3d53c6d8b11cd72d705360f6429c554,10.1108/jfm-05-2013-0027,Hedonic values of physical infrastructure in house rentals,2014.0,,F. Famuyiwa; G. Babawale,,31.0,2654c7bba90de5240a5d03b2c0871f812ea4526af2e,10.1086/702540,Valuation of the External Costs of Unconventional Oil and Gas Development: The Critical Importance of Mineral Rights Ownership,2019.0,Journal of the Association of Environmental and Resource Economists,Andrew J. Boslett; Todd Guilfoos; Corey Lang,"We quantify the externalities associated with unconventional oil and gas development using hedonic valuation. One complication in determining local impacts is that some but not all properties are unified with mineral rights, which enable the residents to financially benefit from drilling, and this information is typically unobserved by researchers. To overcome this issue, we exploit the mineral severance legacy of the homestead act extensions of the twentieth century to identify properties in western Colorado that do not have mineral rights and are therefore only impacted negatively by drilling. We find housing prices decline about 35% when drilling occurs within 1 mile. Treated properties are affected by highly intensive drilling (∼16 wells drilled within a mile, on average), and there is suggestive evidence of nonlinear impacts on a per-well basis. Our estimate of local costs is larger than those found elsewhere in the literature, which demonstrates the critical importance of mineral ownership.",22.0,https://digitalcommons.uri.edu/enre_facpubs/56266f1ecd58db64dc3a4367edd5cafba5abcb4c51b8d,10.1007/s10640-022-00682-1,Air Pollution and Housing Values in Korea: A Hedonic Analysis with Long-range Transboundary Pollution as an Instrument,2022.0,Environmental and Resource Economics,K. Nam; Yifu Ou; Euijune Kim; Si-Qi Zheng,"We estimate the degree and scope of PM2.5-induced negative price shock in Korea’s local housing markets, taking a two-stage hedonic approach. For the analysis, Korea’s local PM2.5 levels are treated as endogenous and are instrumented with regional air pollutants from China. We find that a unit µg/m3 PM2.5 level increase in a Korean city is associated with a 3.7% decline in local residential property value. Long-range transboundary pollution has significant effects on Korea’s local PM2.5 levels with an elasticity of 0.05. These results enrich the sparse hedonic literature on local air-quality valuation in connection to long-range transboundary pollution in East Asia. The advanced methodological features presented in our two-staged identification strategy with a novel instrument is another contribution of this paper.",22.0,https://hdl.handle.net/1721.1/14256326747143c59c718d87faa93857d725c9033dfecda1d,10.1086/704755,A New Approach to Estimating Equilibrium Models for Metropolitan Housing Markets,2020.0,Journal of Political Economy,D. Epple; L. Quintero; Holger Sieg,"We provide a new estimator for a broad class of equilibrium models of metropolitan housing markets with housing differentiated by quality. Quality is a latent variable that captures all features of a dwelling and its environment. We estimate the model for Chicago and New York, obtaining hedonic housing price functions for each quality level for each metropolitan area, stocks of each quality, and compensating variations required for a household of a given income in Chicago to be equally well off in New York.",22.0,https://doi.org/10.2139/ssrn.321620726858a9ab2513035056fdc6d56cafc04ae9d61a0955,10.14246/irspsd.6.1_45,Willing to pay more for high-quality schools?,2018.0,,Lin-Chuan Yang; Bo Wang; Yunyi Zhang; Zi-Wei Ye; Yu-Zhuo Wang; Peng-Fei Li,": Principally, the enrolment of elementary school in China is solely based on residential location. Due to the scarcity of prestigious schools, the household registration (or hukou in Chinese) and the territorial-based school admission policy, a feasible approach for parents to provide the children with good education is to purchase the house in the attendance zone of a high-quality school (or xuequfang in Chinese). The supply-demand imbalance gives rise to the xuequfang phenomenon (much higher prices of xuequfang relative to non xuequfang) . Based on 1250 housing samples in 286 multi- or high-storey residential districts, this paper firstly develops two basic and four Box-Cox transformed hedonic price models to estimate the effect of high-quality schools on residential property prices. The consistency of six models greatly enhances the credibility of this study. Moreover, complementary, the propensity score matching technique is used to estimate the treatment effect. The two methods consistently suggest that residential property values are affected by top-tier schools. They reveal that xuequfang exhibit values that are between 9.3% and 12.1% higher than non- xuequfang , ceteris pa",20.0,https://www.jstage.jst.go.jp/article/irspsd/6/1/6_45/_pdf26911150b500c450a47d8a9b6ac00ae7d6522f6fae7,10.1016/j.jeem.2019.06.006,Environmental regulation as a double-edged sword for housing markets: Evidence from the NO Budget Trading Program,2019.0,Journal of Environmental Economics and Management,Sumit Agarwal; Yong-Heng Deng; Teng Li,"Abstract We investigate the effects of environmental regulations on housing markets using a quasi-experimental setting—the NOx Budget Trading Program (NBP). Hedonic theory predicts that house prices should rise as pollution levels decrease. However, environmental regulations may also affect labor markets, and thus housing demand. Employing a difference-in-differences framework, we find that house prices shifted up in the regulated areas with low manufacturing intensity, whereas in the areas with high manufacturing intensity, housing markets were weakened. We also find that in high-manufacturing-intensity areas, loan application volume declined, rejection rate augmented, and the probability of loan default increased.",20.0,2700539758cbc1492190975b2900d11f2e8eb552429,10.1016/j.jenvman.2022.115012,Rethinking urban park irrigation under climate change.,2022.0,Journal of Environmental Management,Claire A. Doll; M. Polyakov; D. Pannell; M. Burton,"Climate change is forcing cities to reassess their water management practices, particularly for water-intensive applications like park irrigation. If water scarcity requires governments to deviate from current park management norms and allocate less water towards parks, it is essential that park managers design spaces that maintain community wellbeing. We apply the hedonic pricing method and use detailed park management information to assess the value of parks in a region where local climatic conditions require extensive irrigation to keep turf green, and where climate change is further constraining water supplies. Here we show that the impacts of irrigation on the value of parks differ depending on the dwelling types of the nearby housing populations that they serve. In most cases, the convention that parks have to be irrigated to deliver ecosystem services to the public is supported. However, we find that non-irrigated park areas are also valued positively by nearby apartment dwellers. Accelerating rates of urbanization and shifts towards high-density living may support the development of more diverse park options that are less water-intensive. Increased visibility of these alter",19.0,271c9cc0d0978a1981e9d35395a8e50d6c0cec5afd5,10.3368/le.94.3.386,Incomplete Information and Adverse Impacts of Environmental Cleanup,2018.0,Land Economics,Corey Lang; P. Cavanagh,"We use the hedonic method to examine the external effects of Rhode Island’s voluntary brownfield program. We hypothesize that housing price impacts are a combination of valuation of environmental improvement and response to information disclosure initiated by remediation. The results indicate that housing prices decline after nearby remediation, suggesting incomplete information about the presence of risk. Further, we find empirical evidence that price impacts and the degree of incomplete information are different across neighborhoods. Specifically, low-housing-value neighborhoods experience price declines following remediation, while high-value neighborhoods experience price increases, leading to an overall regressive impact. (JEL D63, Q51)",19.0,https://digitalcommons.uri.edu/enre_facpubs/2527291ee2f7cf11b2d742696808a9e79600b39d9c89b,10.1108/ijhma-10-2015-0066,A hedonic house price index in continuous time,2016.0,,S. Waltl,,19.0,http://www100.uni-graz.at/vwlwww/forschung/RePEc/wpaper/2015-04.pdf2732ebf2fc45e1ff6345856c5a09a6850dcf3fc21ca,10.1108/jerer-11-2019-0042,NIMBYs for the rich and YIMBYs for the poor: analyzing the property price effects of infill development,2020.0,,Fredrik Brunes; Cecilia Hermansson; Han-Suck Song; Mats Wilhelmsson,"A combination of strong urbanization and shortage of land in many European city areas prompts an impetus of infill development, with current residents often raising concerns that infill development leads to lower nearby property prices. The aim of this paper is to analyze how nearby property prices are affected by new construction projects in Stockholm, Sweden. We use a difference-in-difference specification in a hedonic model, and our sample consists of more than 40,000 observations over the period 2005–2013. Our results are robust and indicate that house prices in nearby areas increase following the completion of infill development. Our results also indicate that infill development only has a positive spillover effect on nearby house prices only in areas with lower incomes, more public housing units and more inhabitants born abroad.",18.0,https://www.emerald.com/insight/content/doi/10.1108/JERER-11-2019-0042/full/pdf?title=nimbys-for-the-rich-and-yimbys-for-the-poor-analyzing-the-property-price-effects-of-infill-development274750f4ab28d99634c98324e9a9a91d8b26549aadf,10.1016/j.tranpol.2021.04.016,"Same, same but different? Neighbourhood effects of accessibility on housing prices",2021.0,Transport Policy,Helena Bohman,"Abstract A growing research literature is focusing on how effects from increased accessibility may differ according to socio-economic aspects of neighbourhoods and households. This has raised concerns of whether areas with high accessibility may became unaffordable for low-income households, who, at the same time, may depend on public transport accessibility more than average households. We use difference-in-difference estimates of hedonic price models to study the distribution of effects around the new stations provided by a railway tunnel in Malmo, Sweden. The study finds that the lower-price segments are the most affected by the improved accessibility, which becomes clearer when different control groups are used for different market segments. Accessibility is therefore interpreted as highly important for households in the lower-price segments. From a housing accessibility perspective, this is described as a double-edged sword. On the one hand, the owners of the apartments in these neighbourhoods, who benefit from the price increase, are typically low-income households. On the other hand, low-income households who are not owners may find the area prohibitively expensive due to pr",17.0,https://www.sciencedirect.com/science/article/pii/S0967070X21001116/pdf275949c048d3c329f94c1584bfeb8d6b26cae2ad1d2,10.1108/17538271011063889,The Ghanaian transaction‐based residential indices,2010.0,,Wilfred Anim-Odame; T. Key; S. Stevenson,"Purpose – The purpose of this paper is to provide technically robust indicators of housing market performance from the records held by the Ghana Land Valuation Board, through the construction of the first ever residential price and rent indices for the aggregate and disaggregate markets.Design/methodology/approach – The approach involved time series produced from hedonic models using 3,250 transaction‐based data, running from 1992 to 2007, and documents on movements in capital and rental values in Accra and Tema, the dominant commercial conurbations in the country.Findings – The paper makes a major contribution to knowledge and understanding of housing market dynamics in Ghana. The results suggest that the derived price and rent indices look, at first sight, reasonably plausible with cyclical trends showing weak and strong patches.Originality/value – The paper focuses on the development of formal housing markets through a detailed case study of Ghana, and provides findings and models of a wider applicatio...",17.0,https://figshare.com/articles/journal_contribution/The_Ghanaian_transaction-based_residential_indices/2084447827619859aaff14033f9d01240e5e3e584aa8306d70a,10.2139/ssrn.1972111,A New Way of Monitoring the Quality of Urban Life,2011.0,,Eduardo Lora; Andrew P. Powell,"This paper proposes a methodology to resolve the problems that result from using a combination of objective and subjective information in evaluating urban quality of life. The paper further suggests techniques to identify and rank issues of potential importance for urban dwellers. In order to combine objective and subjective information in a coherent manner and focus on the most relevant dimensions of the quality of life in a city or neighborhood, the paper attempts to exploit the complementary nature of two approaches: the ""hedonic"" approach, which employs market prices for housing, and the ""life satisfaction"" approach, which addresses subjective well-being. Results using both approaches in selected Latin American cities are discussed and compared. The paper concludes with a discussion of potential uses of the two-pronged methodology for policy analysis.",17.0,https://doi.org/10.2139/ssrn.197211127756bd301809d93ede3431c8385c488354b3ce02cf,10.2139/ssrn.610942,Hedonic Estimates of the Cost of Housing Services: Rental and Owner-Occupied Units,2004.0,,Theodore M. Crone; Leonard I. Nakamura; R. Voith,,17.0,https://doi.org/10.21799/frbp.wp.2004.2227829439c4be2e71dfd6b435bb42d3f625e33687e1e,10.15396/eres2018_201,An evaluation of the methods used by European countries to compute their official house price indices,2018.0,Economie et Statistique / Economics and Statistics,R. Hill; Michael Scholtz; C. Shimizu; Miriam Steurer,"Since 2012 Eurostat requires the national statistical institutes (NSIs) in all European Union (EU) countries to compute official House Price Indices (HPIs) at a quarterly frequency. Eurostat recommends computing the HPI using a hedonic method. Most NSIs have followed this advice, although they differ in their choice of method. Some NSIs use stratified medians instead of hedonic methods. We evaluate the theoretical and empirical properties of these methods. Of particular concern is the comparability of the HPIs across countries when computed using different methods. Our empirical comparisons use detailed micro-level data sets for Sydney and Tokyo, containing about 867,000 actual housing transactions. All the hedonic methods perform better than stratified medians. The hedonic methods generate quite similar results, except when applied to new dwellings in Tokyo. This finding shows that the choice of hedonic method can become important for smaller data sets. Also, the widely used hedonic repricing method becomes unreliable when the reference shadow prices are not updated frequently.",16.0,https://eres.architexturez.net/system/files/P_20180131121448_65.pdf279f7bf1bf2b5fcfa358119ca80cfff5ccbd3748824,10.1108/jerer-03-2017-0014,Developers’ price setting behaviour in urban residential redevelopment projects,2018.0,,Rolf Barlindhaug; B. Nordahl,"Purpose 280 281 282 283 284This paper aims to investigate whether developers’ ask lower prices on homes in redevelopment sites than they do on similar units in smaller developments completed over a shorter time span. It also investigates whether developers price units differently at different stages of the redevelopment process. The development of designated redevelopment areas often consists of multiple projects spread across several years, some in parallel, some sequential. New units are put on the market in a piecemeal fashion, and infrastructure, shared green spaces and shared facilities are installed successively. 285 286 287 288 289Design/methodology/approach 290 291 292 293 294A hedonic price model is used to analyse sales prices of 7,000 new apartments in Oslo sold between 2011 and 2015, all else being equal. The paper distinguishes between infill as one-stage projects, and multi-staged competitive and multi-staged monopolistic redevelopments. 295 296 297 298 299Findings 300 301 302 303 304Dwellings in redevelopment projects sell at a lower price than similar dwellings in infill projects. In competitive redevelopments, those in charge of the last projects put a slightly higher price on apartments. In redevelopments involvi",15.0,https://www.emerald.com/insight/content/doi/10.1108/JERER-03-2017-0014/full/pdf?title=developers-price-setting-behaviour-in-urban-residential-redevelopment-projects305bec2dc3e4e4990aeac6f447c7c11ec0f4caca588,10.4314/ejesm.v8i5.4,"Using Hedonic price model to estimate effects of flood on real property value in Lokoja, Nigeria",2015.0,,Ir Egbenta; G. Udo; A. Otegbulu,"The perceived risk associated with flood hazard has increased its awareness especially among those living within the flood prone areas. There is paucity of information on the effects of flood hazard on property values in Nigeria. The aim of the study is to assess the effects of flood on property value in Lokoja using hedonic price model with a view to contributing to the existing literature. The study uses a total of 50 residential homes that were sold in Lokoja, Nigeria between 2010 and 2012. The study used quantitative data from property transactions before and after the floor disaster and related them with the affected properties to estimate the average effects of the disaster on property value. Data from the Ministry of Lands and Urban development as well as the State Emergency Management Agency were used. Distances were measured in metres from the centroid of the building to the edge of the river and roads using Global Positioning System. The result of the estimation shows that property located within the floodplain are lowers in value by an average of N 493, 408 which represents 6.8 percent reduction in sales price for an average value house. The study adds to the understandi",15.0,https://doi.org/10.4314/ejesm.v8i5.430618e9db169b7915e1c47f388741b5a11c0648949e,10.1016/j.cbrev.2021.03.001,Do regional house prices converge? Evidence from a major developing economy,2021.0,,Aytül Ganioğlu; Ünal Seven,"Abstract This paper analyzes the long-run convergence of regional house prices in a major developing country, Turkey. Using a non-linear time-varying factor model and quarterly hedonic house price data from 2010 to 2018, we find that house prices do not converge across 26 regions of Turkey. Results reveal that the regions can be grouped into seven convergence clubs and one divergent club, confirming the Turkish housing market’s heterogeneity and complexity. We extend the analysis to explore the possible factors driving the convergence clubs. We find that income, population, education, unemployment, being in an earthquake zone, and inflow of Syrian refugees are significant driving forces in explaining convergence club formation. These outcomes will benefit home buyers/sellers, investors, regulators, and policymakers interested in analyzing the dynamic interlinkages among house prices and the effects of shocks originating from the regional housing markets in developing countries.",15.0,https://www.sciencedirect.com/science/article/pii/S1303070121000020/pdf3071c8f190855ce2647f711abf1b1cb77ab5af068a2,10.1080/10511482.2019.1661266,The Effect of Credit Supply on House Prices: Evidence From Turkey,2020.0,Housing Policy Debate,Cengiz Tunç,"ABSTRACT This article examines the effect of exogeneous credit supply shocks on house prices in an emerging economy, Turkey, using bank deposits, the number of branches, and financial literacy as instruments to estimate exogenous credit supply. Utilizing data for 26 regions and from 2010 to 2017, I find that an exogenous expansion in housing credits as well as consumer credits utilized has a large and significant effect on prices. A similar effect holds for quality-adjusted hedonic house prices. The results have important policy implications for credit-driven emerging economies.",15.0,308d3cc2b5ffbf39645fc47562257a85c240474e3d7,10.1111/1540-6229.12478,Investment incentives of rent controls and gentrification: Evidence from German micro data,2024.0,Real Estate Economics,Vera Baye; Valeriya Dinger,"We empirically document that the effectiveness of the German rent control introduced in 2015 in achieving rental housing affordability is limited. Exploring the reasons for this limited effectiveness, we focus on the impact of the rent control on the yield on rental housing investments proxied by rent‐price ratios, which we derive by predicting sale prices to rental objects based on a hedonic model using micro‐level quotes on rental and sale listing. Exploiting the temporal, regional, and object‐specific variation generated by the design of the rent control, we identify a causal negative effect of the rent control on the yield of rental objects subject to the regulation. Furthermore, we zoom into the spillovers across regulated objects and objects in the affected markets that were exempt from the regulation and find rising yields for the exempted objects, suggesting that the regulation contributed to gentrification via a shift of rental housing supply away from the regulated segment.",14.0,https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/1540-6229.124783093004e298a11f9a5054040b9877af438600d59ebb,10.5539/jms.v2n1p128,Neighborhood Quality and Housing Value: Evidence from Urban Micro Data,2012.0,,Yi Wang; Rui-Ping Ran; Guo-Ying Deng,"Using urban residential micro data from CHNS, this paper employs Hedonic Pricing Model to investigate the impact of Neighborhood Quality on housing value and its mechanism. We find that, Human Capitals measured by average schooling years and occupational diversity have significant positive effect while cultural capitals such as Ethnic Diversity have significant negative effect on housing value. Compared with the empirical results from developed counties, Social Capitals measured by length of tenure and own room rate have insignificant effect on housing value. In addition, having Kindergarten and Hospitals near the communities are positively correlated with the housing value while Internet cafe or transportation services are negative. We believe that these facts are closely related to the stage of economy transition and rapid urbanization in current China. The conclusions have important implications for the effective construction of harmonious commodities.",14.0,https://ccsenet.org/journal/index.php/jms/article/download/11793/10531310d3f8adaf294c99687cf12ec7755231bf0c933456,10.3390/su14159283,Nexus between Housing Price and Magnitude of Pollution: Evidence from the Panel of Some High- and-Low Polluting Cities of the World,2022.0,Sustainability,R. Das; Tonmoy Chatterjee; Enrico Ivaldi,"With the growing environmental pollution and adverse climatic conditions, it is now a globally vibrant topic whether housing prices should be associated with the quality of the environment in a particular region. From the microeconomic approach to environmental economics, it is proposed that property prices in any region should be associated with the environmental quality-the concept of hedonic pricing. A negative association between low magnitudes of pollution and high house prices is a precondition to achieving the aim of sustainable development. The study thus starts with the objective of investigating whether there are long-term relations and short-term dynamics between the magnitudes of pollution and house price in the panel of the world’s high-polluting and low-polluting cities for the period of 2012–2021 across 30 cities. Using appropriate time-series econometric procedures such as panel cointegration, panel VECM, and the Wald Test, the study arrives at the conclusion that magnitudes of pollution and house prices in the cities are cointegrated with a stable long-term relationship in all panels. Further, there are strong causal interplays in both the long- and short-term betw",13.0,https://www.mdpi.com/2071-1050/14/15/9283/pdf?version=1659015639311597ef587e683d1905752466a088ae7a4872d4acf,10.1016/j.cesjef.2015.10.002,Formación de los precios de alquiler de viviendas en Machala (Ecuador): análisis mediante el método de precios hedónicos,2016.0,,Manuel A. Zambrano-Monserrate,"En Ecuador, los precios de la vivienda se han incrementado considerablemente en los ultimos anos debido a la existencia de factores externos e internos de la region. En este estudio se analiza el mercado inmobiliario en la ciudad de Machala. A traves del metodo de precios hedonicos se explica la formacion de los precios de alquiler de las viviendas en la localidad en 2013. Para amortiguar el problema de las variables omitidas, se utiliza el modelo de frontera heteroscedastica. Se incluyen variables sociales, ambientales, demograficas y estructurales. Se encontraron resultados significativos en variables ambientales, como el tipo de abastecimiento de agua, la distancia al parque central con areas verdes y la eliminacion de desechos. Se encuentra que los precios de alquiler de las viviendas con abastecimiento de agua irregular son inferiores en un 5,79% a los de aquellas con un abastecimiento regular. Ademas, los hogares cuyo metodo de eliminacion de desperdicios es a traves del servicio municipal pagan en promedio un 3,58% mas de alquiler que aquellos que no lo poseen. Mas aun, las viviendas cercanas al parque tienen una mayor renta: por cada 100 m adicionales entre la vivienda y el",13.0,https://doi.org/10.1016/j.cesjef.2015.10.00231254e73d2ff5b4ffb16abb8067ff70f3d5994515b9,10.1108/jhti-09-2022-0468,"Do sustainability motivations drive satisfaction and engagement in the sharing economy, or is it just price and convenience? Some answers in a collaborative housing context",2023.0,Journal of Hospitality and Tourism Insights,M. Alarcón-del-Amo; C. Lorenzo-Romero; Miguel-Ángel Gómez-Borja,"PurposeThis study aims to understand the motivations behind using Airbnb as a collaborative housing platform brand, their impact on satisfaction and engagement, and how the latter affects brand electronic Word of Mouth (eWOM) and brand loyalty. It also analyzes the potential moderating effect of the use intensity of collaborative housing platforms for the proposed causal relationships.Design/methodology/approachAn online survey was addressed to active users of Airbnb with a final sample of 405 users. Data were analyzed using a covariance-based structural equation modeling (SEM) to test the causal model and a multigroup SEM to test the moderator effect of the intensity of use.FindingsThe results show that convenience affects brand satisfaction and hedonic motivation influences brand engagement, and both affect return intention and eWOM. In contrast, sustainability motivations seem unrelated both with satisfaction and engagement. Furthermore, the mechanism by which people reach loyalty in terms of return intention varies according to their usage intensity. Thus, the engagement–intention way is stronger for more intensive brand users. In contrast, the satisfaction–intention mechanism ",11.0,313a95339a5c99dc5d2632f98b99afd0a0e5baec8fc,10.1093/epolic/eiac039,Neighbourhood stigma and place-based policies,2022.0,Economic Policy,H. Koster; J. V. van Ommeren,"314 We analyse the effects of the Dutch Act on Extraordinary Measures for Urban Problems. This allows local governments to prohibit non-employed households from entering into public housing in targeted neighbourhoods to improve social mixing. We show that the Act is largely ineffective in changing the demographic composition of neighbourhoods. At the same time, due to prominent advertising of targeted deprived neighbourhoods, a stigma may have been created. We adopt a hedonic price approach and use a boundary-discontinuity (within 100m of neighbourhood borders) to quantify the overall effect of the policy. We thus exploit spatio-temporal differences in house prices and find a sizeable price reduction of about 3-5%. The magnitude of this effect is confirmed for two other national place-based policy programmes, adding to the external validity of these findings. Our results suggest that neighbourhood stigma is important, which implies that individuals living in deprived neighbourhoods experience dis-utility from living in a place with a low status.",11.0,https://academic.oup.com/economicpolicy/advance-article-pdf/doi/10.1093/epolic/eiac039/45189347/eiac039.pdf315f5ac9225c0dca0528e64d005f6ee97c2578e1b19,10.2478/jos-2022-0007,"Rolling-Time-Dummy House Price Indexes: Window Length, Linking and Options for Dealing with Low Transaction Volume",2022.0,Journal of Official Statistics,R. Hill; Michael Scholz; C. Shimizu; Miriam Steurer,"Abstract Rolling-time-dummy (RTD) is a hedonic method used by a number of countries to compute their official house price indexes (HPIs). The RTD method requires less data and is more adaptable than other hedonic methods, which makes it well suited for computing higher frequency HPIs (e.g., monthly or weekly). In this article, we address three key issues relating to RTD. First, we develop a method for determining the optimal length of the rolling window. Second, we consider variants on the standard way of linking the current period with earlier periods, and show how the optimal linking method can be determined. Third, we propose three ways of modifying the RTD method to make it more robust to periods of low transaction volume. These modifications could prove useful for countries using the RTD method in their official HPIs.",11.0,https://sciendo.com/pdf/10.2478/jos-2022-0007316fa202e59c6c5e1d237f19c1d1ac165980674e008,10.1016/j.chieco.2019.04.003,Home value misestimation and household behavior: Evidence from China,2019.0,China economic review,Nan Gao; Ping-Han Liang,"Abstract Households often make errors when self-assessing their housing wealth. By using the Chinese Households Finance Survey, we show that Chinese urban households systematically overestimate their home value. This bias is significantly related to household consumption: a one standard deviation increase in the extent of estimation bias is associated with a 10% increase in household consumption. Our main results are robust against a variety of robustness checks, e.g., taking into account the expectations of future home price, using the interviewee's estimation as the instrumental variable for the household self-estimation, implementing the hedonic model on an external data source to assess real homevalue, etc.. Further, we show that overestimated households are more likely to take risk in financial market, and have a larger amount of immediate and conspicuous consumption. These findings have policy implications for the recent debate about property tax, indicating the unintended consequences of property tax through providing more precise information about home value.",11.0,3179562a7b440fd126686a824fdd76f1d890164482f,10.1080/13504851.2020.1853665,Estimating the impact of pollution on wages and housing prices using satellite imagery,2020.0,Applied Economics Letters,M. Goodwin; Matías Fontenla; Fidel Gonzalez,"ABSTRACT Air pollution is a global concern. However, research and policy addressing the problem remains hampered by a lack of ground-level air quality data. We estimate the value residents of Mexico City place on clean air using aerosol optical depth (AOD) from satellite imagery as a proxy for air pollution. We employ a unique dataset that combines actual household-level data with AOD and rainfall within a hedonic model focusing on people’s decisions regarding where to work and live in a developing nation. We address endogeneity and simultaneity concerns by using a 3SLS-IV estimation. Results suggest that residents place significant value on clean air, with a 10% increase in AOD leading to a 1.3% decrease in home prices and a 2.3% increase in wages.",11.0,318303ea90781c2348f2adddfafd9879967a27e6976,10.1080/19498276.2024.2432758,The Impact of Urban Green Space on Housing Value: A Combined Hedonic Price Analysis and Land Use Modeling Approach,2024.0,The Journal of Sustainable Real Estate,Jianfei Li; I. Ossokina; Theo A. Arentze,,11.0,https://doi.org/10.1080/19498276.2024.243275831979a0d9c686d244487edd3cf606ffe1b9d876303c,10.5821/ace.v2i6.2427,LA INCIDENCIA DE LAS EXTERNALIDADES AMBIENTALES EN LA FORMACIÓN ESPACIAL DE VALORES INMOBILIARIOS: EL CASO DE LA REGIÓN METROPOLITANA DE BARCELONA,2008.0,,Jesús Manuel Fitch Osuna; Pilar García Almirall,"Esta investigacion se inscribe en la linea de la valoracion ambiental, y se fundamenta en la economia ambiental, urbana y la organizacion territorial. La hipotesis central es que la 320poblacion aprecia la calidad ambiental al momento de realizar su eleccion residencial en 321funcion del nivel de ingresos, costumbres y estilo de vida. Para comprobar dicha hipotesis se 322propone un modelo de precios hedonicos donde la variable dependiente es el precio de 323tasacion de un conjunto de viviendas localizadas en la Region Metropolitana de Barcelona 324(RMB) y las independientes son los diversos factores que inciden en la formacion espacial de 325dicho valor. 326El estudio, entre otras cosas, permite detectar, a escala metropolitana, cuales son los factores 327locacionales que se valoran positiva y negativamente. Esta informacion objetiva es importante 328para tomar decisiones sobre proyectos de inversion en vivienda de proteccion oficial y libre, 329para comprender las decisiones de ubicacion y crecimiento metropolitano, para facilitar a las 330entidades financieras, aseguradoras y consumidores potenciales comprender las diferencias en 331las tasas de apreciacion entre las diferentes zonas metropolitanas mini",10.0,https://upcommons.upc.edu/bitstream/2099/4488/1/4_FITCH.pdf3321d57857811e3f735e7c7dfe3dfb0c766f1aba868,10.1007/s11146-020-09798-x,Adaptive Reuse of Religious Heritage and Its Impact on House Prices,2020.0,Journal of real estate finance and economics,Caixia Liu; Xiaolong Liu,"Due to social demographic change and secularization, religious heritage sites in Europe are on the verge of losing their original functions. While the adaptive reuse seems to be a proactive strategy to preserve the historical and cultural value embedded in religious heritage sites, little is known concerning its external impact. This paper aims to fill this gap by investigating the external effect of reusing religious heritage on surrounding house prices. Employing both the parametric and non-parametric difference-in-differences hedonic model on a sample of 42 projects of reusing religious heritage and a rich dataset of housing transactions in the Netherlands, we find significant positive externality of reusing religious heritage on local house prices. The external effects are heterogeneous across differentiated project size and monumental status. Larger religious heritage reuse projects and those listed as national monuments exert greater influence on surrounding house prices.",10.0,https://link.springer.com/content/pdf/10.1007/s11146-020-09798-x.pdf333527549ae967cd285e82137d9247b9adbcda78354,10.1016/j.cities.2020.103043,Homevalue misestimation and household leverage: An empirical study of Chinese urban households,2020.0,,Ping-Han Liang; Nan Gao,"Abstract Households often make errors in assessing homevalue. By merging representative Chinese urban household survey data with web-scraped housing price data, we estimate a hedonic model to assess the real value of homes and calculate the extent of homevalue misestimation. We show that homevalue misestimation is significantly related to household leverage: a 10% increase in the extent of homevalue misestimation is associated with a 1.88 percentage increase in household leverage, in terms of debt-to-income ratios. Moreover, both formal and informal borrowing are increasing with respect to homevalue misestimation. A variety of robustness checks and heterogeneity analyses further support our main results. The correlation between misestimation and leverage is even larger for households who underestimate their homevalue. It's demonstrated that the lack of housing market information and endowment effect both contribute to misestimation. However, there is no evidence that overconfidence, risk attitude, or anchoring effect significantly affect misestimation. These findings have policy implications for the recent debate on property taxes, indicating the unexpected consequences of property",10.0,334f5f366b2d367f60b497b4077f135578116ab9799,10.1007/s10901-014-9403-8,"Creating sustainable urban built environments: An application of hedonic house price models in Wuhan, China",2014.0,Journal of Housing and the Built Environment,Hao-Cheng Huang; Yin Li,,10.0,335c1f24bb5d22e9fec525b1905b6cfa6b1126498e8,10.1108/ijhma-07-2020-0084,Economic policy uncertainty and house prices in Germany: evidence from GSADF and wavelet coherence techniques,2020.0,,D. Kırıkkaleli; K. Gokmenoglu; Siamand Hesami,"PurposeThis study aims to answer the following questions which have not been investigated in the literature to the best knowledge: Is there any bubble in the German housing sector between 2005–2009 and 2012–2017? and Is there any linkage between economic policy uncertainty and the housing sector price index?Design/methodology/approachThis study aims to shed some light on the German’s housing sector by investigating the housing sector bubble and the causal link between the housing sector index and economic policy uncertainty in Germany, using GSADF, Granger causality, Toda Yamamoto causality and wavelet coherence tests.FindingsThe findings reveal that there are some bubbles in the housing sector in Germany for the periods investigated, there is a positive correlation between economic policy uncertainty and housing sector price index at different frequencies and different periods and between 2008 and 2009 and between 2011 and 2013, economic policy uncertainty leads housing sector price index. The consistency of the findings from wavelet coherence is confirmed by the outcomes of Granger causality and Toda Yamamoto causality tests.Originality/valueTo the best knowledge, this is the fir",9.0,https://hdl.handle.net/11129/148333360bc1fdb226dd86dfbdc941ce7dd8e45cacef3a9f,10.4067/s0718-915x2011000100008,El impacto del policentrismo sobre la distribución espacial de los valores inmobiliarios: un análisis para la Región Metropolitana de Barcelona,2011.0,,Carlos Aguirre-Nuñez; Carlos Marmolejo,"La teoria de la renta ofertada, que prevalece en el ambito de la economia urbana, establece un trade-off entre los costes de transporte y la renta que se transfiere al suelo, de manera que cuanto mayor es la distancia entre un punto determinado del sistema urbano y el CBD, menor es la renta transferible al suelo. Sin embargo, esta teoria, en su acepcion original, parte del supuesto de un sistema monocentrico, en el cual todos los empleos estan situados en el centro, un paradigma, por tanto, alejado del actual. En este articulo se propone: 1) un conjunto de metodos que permiten detectar subcentros de empleo, para 2) probar hasta que punto estos ejercen una influencia en el valor inmobiliario de su entorno. A partir de datos de empleo de la Region Metropolitana de Barcelona (RMB) y de valores residenciales, se detectan entre 15 y 26 municipios como potenciales subcentros; a partir de aqui, mediante un modelo de precios hedonicos, se prueba la influencia de estos sobre la distribucion espacial del valor de las viviendas. Los resultados destacan la presencia de problemas de multicolinealidad, entretanto, la distancia al CBD y a algunos subcentros esta correlacionada. Sin embargo, el mo",9.0,http://www.scielo.cl/pdf/rconst/v10n1/art08.pdf337f1de5144add391092d7f2b74c8c0f99e10eee0f7,10.1016/j.cbrev.2019.06.002,An analysis to detect exuberance and implosion in regional house prices in Turkey,2019.0,Central Bank Review,Evren Ceritoğlu; S. Cilasun; U. Demiroğlu; Aytül Ganioğlu,"Abstract The aim of this paper is to find out whether there is exuberance in regional house prices in Turkey. For this purpose, we analyze real hedonic house prices and price to rent ratios countrywide as well as for 26 geographic regions at the NUTS2 level from January 2010 to January 2019. We perform the right-tailed unit root testing procedures developed by Phillips et al. (2015) and Phillips and Shi (2018) and use their real time date-stamping strategy to determine periods of explosiveness and implosion. Our empirical findings indicate that there were exuberance episodes in house prices in Turkey for multiple periods, where an important contributor to these dynamics was the largest housing market, Istanbul. We also detect exuberance in some other regions, particularly in the neighboring NUTS2 regions of Istanbul and in Izmir after around 2014. However, we find out that explosive price behavior turned into implosion in many regions starting from 2018.",9.0,https://www.sciencedirect.com/science/article/pii/S1303070119300678/pdf338c6d212544d7de195ef420feb4b3a0321a1536079,10.20875/sb.76010,Isparta İlinde Konut Fiyatlarını Etkileyen Faktörlerin Hedonik Fiyat Modeli İle Analizi - Factors Affecting Housing Prices In Isparta Analysis Using Hedonic Price Model,2016.0,,Uğur Çiçek; Selim Adem Hatırlı,"Konut heterojen bir maldir ve bircok ozelligi icinde barindirmaktadir. Bu calismada Isparta Ilinde konutun sahip oldugu farkli ozelliklerin konutun fiyatini ne derece etkiledigi hedonik fiyat modeli ile tahmin edilmistir. Isparta Belediye’sinin kayitlarina gore, 2012 yili Ekim ayi itibariyla, Isparta Ili kent merkezinde 44 mahallede toplam 78.492 adet konut bulunmaktadir. Orneklem hacmi, gayeli orneklem yontemine gore hesaplanmis ve bu baglamda 368 hanehalki ile anket gorusmesi yapilmasinin Isparta il merkezini temsil edecegi kabul edilmistir. Model log-lin formunda olusturulmus ve degisen varyansi sinamak icin White Testi uygulanmistir. Modelde, 26 bagimsiz degisken kullanilmis ve bunlardan 13 tanesi istatistiksel olarak 0,01 onem duzeyinde anlamli bulunmustur. Tahmin sonuclarina gore, konutun fiyatini etkileyen en onemli unsurlar; sehir merkezine uzaklik, hava kirliligi, konutun muhiti, konutun yasi, konutun buyuklugu, oda sayisi, kaloriferli olmasi, otoparkinin olmasi ve guney cephede olmasi olarak belirlenmistir.",8.0,https://dergipark.org.tr/tr/download/article-file/181872339a2ef3af6fec31c6b4435e4e791241cb9998f5aa7,10.1080/13657305.2020.1869857,Do oyster farms actually reduce the property values? Empirical evidence from Rhode Island,2021.0,,P. Sudhakaran; G. Puggioni; H. Uchida; J. Opaluch,"Abstract While there in general appears to be public support for shellfish aquaculture operations, the construction of oyster farms often meets opposition where an important argument is devaluation of housing property. This makes it important to study the effect of construction of oyster farms on property value. In this paper house sales data from Rhode Island between 2000 and 2013 is analyzed to evaluate the effect of oyster farm construction on property values using a difference-in-difference (DiD) approach within a hedonic price model (HPM). Given the use of sales data this study focuses on the perceptions of people in the housing market. We found that the impacts are more nuanced and complex: overall on average the construction of oyster farms increased the value of the houses located closer to the farm. When the houses are grouped by their value category, however, our results show that the value of luxury houses decreased significantly.",8.0,https://digitalcommons.uri.edu/cs_facpubs/13234097b159d806d36e4800edf348bbe9683aca20ebe6,10.7290/pur31elus,The Impact of Surface Coal Mining on Residential Property Values: A Hedonic Price Analysis,2011.0,Pursuit: The Journal of Undergraduate Research at the University of Tennessee,A. Williams,"The use of certain surface mining techniques is currently a heavily-debated environmental issue and one where consideration of non-market values is likely to lead to the creation of better public policy. This study uses the hedonic pricing method to investigate the impact that surface coal mines have on residential property values. The results of this statistical analysis show that as the number of surface mines and their average production increases, the median value of housing units in a county significantly decreases. In particular, for the three model specifications explored, it is estimated that the addition of a surface mine to the average county decreases aggregate property values by between $7,949,363.77 and $40,146,061.87.",8.0,3411c6bf9be1758fab4d0d1723cb5c7fc8b1defd63a,10.1061/(asce)up.1943-5444.0000564,Impacts of an Urban Environmental Event on Housing Prices: Evidence from the Hangzhou Pesticide Plant Incident,2020.0,,W. Yue; Chaoran Ni; Chuan-Hao Tian; Hai-Zhen Wen; Li Fang,Abstract Environmental pollution incidents affect urban residents and the natural environment. This article employs hedonic price models and a difference-in-difference (DID) approach to examine how...,8.0,3423f2d10c5d6d3d089c494489695293c13e38d7090,10.1007/s00181-019-01804-3,A hedonic approach to the valuation of the effect of criminal violence on housing prices in Acapulco City,2019.0,Empirical Economics,J. Delgado; Giovanni Wences,,8.0,343b35e7dcac822195de7f0c39ec744471b30928422,10.30784/epfad.747705,Determining Housing Prices Using The Semiparametric Estimation Within The Hedonic Price Model Framework: Case Study of Istanbul Housing Market Example,2020.0,,Tuğçe Acar,"Konutlarin sahip olduklari birbirinden farkli ozellikler, konut piyasalarina heterojen yapi kazandirmistir. Dolayisiyla konut piyasasi hedonik fiyat modeli ile analiz edilebilir. Bu dogrultuda calisma, heterojen yapiya sahip olan konut piyasasindaki fiyat degisimlerini takip edebilmek amaciyla, konutlarin sahip oldugu farkli karakteristik ozelliklerin konut fiyatlari uzerindeki etkilerinin ortaya cikarilmasi bakimindan onem tasimaktadir. Bu calismada amaclanan ise Istanbul ili icin apartman dairesi turundeki konut ozelliklerinin fiyat uzerindeki etkisinin hedonik fiyat modeli kapsaminda incelenmesidir. Bu amacla 974 daire, konut fiyatlari ve fiyatlari etkileyen faktorler icin semiparametrik regresyon modelleri ile tahmin yapilmistir. Cunku semiparametrik tahmin, veri setini belirli varsayimlara zorlamamasi ve bagimli degisken uzerinde dogrusal olmayan etkiye sahip degisken yapisi soz konusu oldugu durumda bu yapiyi dikkate almasi bakimindan parametrik tahmine gore daha ustundur. Elde edilen bulgulara gore satilik konut fiyatlarini (apartman dairesi) en cok etkileyen ozellikler olarak sirayla otopark degiskeni, krediye uygunluk degiskeni ve asansor degiskeni olarak belirlenmistir. N",7.0,https://dergipark.org.tr/en/download/article-file/11352003443408dba77389bdfbd3095c8b514c5c95c3dddc66,10.3390/econometrics10010004,The Age–Period–Cohort Problem in Hedonic House Prices Models,2022.0,Econometrics,Chung Yim Edward Yiu; Ka-Shing Cheung,"The age–period–cohort problem has been studied for decades but without resolution. There have been many suggested solutions to make the three effects estimable, but these solutions mostly exploit non-linear specifications. Yet, these approaches may suffer from misspecification or omitted variable bias. This paper is a practical-oriented study with an aim to empirically disentangle age–period–cohort effects by providing external information on the actual depreciation of housing structure rather than taking age as a proxy. It is based on appraisals of the improvement values of properties in New Zealand to estimate the age-depreciation effect. This research method provides a novel means of solving the identification problem of the age, period, and cohort trilemma. Based on about half a million housing transactions from 1990 to 2019 in the Auckland Region of New Zealand, the results show that traditional hedonic prices models using age and time dummy variables can result, ceteris paribus, in unreasonable positive depreciation rates. The use of the improvement values model can help improve the accuracy of home value assessment and reduce estimation biases. This method also has important",7.0,https://www.mdpi.com/2225-1146/10/1/4/pdf?version=16431179883455b7fdd77ea672cc550e45d2f7bbc171920de19ca,10.69554/yzcu7790,Investigating the differences in the impacts of redevelopment and building rehabilitation on house prices: A Hong Kong case study,2012.0,"Journal of Building Survey, Appraisal & Valuation",Y. Yau,"While redevelopment is a common approach to housing improvement or urban renewal, increasing numbers of scholars, urban managers and sociologists started promoting the use of building rehabilitation, which is more sustainable. In Hong Kong, public administrators have been facing challenges in choosing between redevelopment and building rehabilitation when executing urban renewal projects. For more informed policymaking, it is necessary to know and compare the benefits generated from different housing improvement projects. The literature suggested that redevelopment and rehabilitation could add values to the nearby properties, yet it is still unclear whether there are any differences in the positive externalities posed by the two processes, for example in terms of magnitude of price change and affected distance. In this regard, this study aims to investigate the differences in the effects between redevelopment and building rehabilitation on house prices in Hong Kong. Two housing improvement projects in the old urban area are targeted for investigation, using hedonic price analysis. Yet no significant positive net externalities are identified from both redevelopment and rehabilitatio",7.0,34687b010de156e63c9c351d7c1b248e4b57346941c,10.1061/(asce)up.1943-5444.0000734,"Purchase Motivation, Landscape Preference, and Housing Prices: Quantile Hedonic Analysis in Guangzhou, China",2021.0,,Hai-Zhen Wen; Shu-Yuan Li; E. Hui; Shi-Jun Jia; Wenjun Cui,,7.0,http://ira.lib.polyu.edu.hk/bitstream/10397/97513/1/Hui_Purchase_Motivation_Landscape.pdf347faf116e3bdb264262e2ca66f5fcdcf119569a05e,10.1007/s10901-022-09990-w,Impact of different ecological landscapes on housing prices—empirical evidence from wuhan through the hedonic pricing model appraisal,2022.0,Journal of Housing and the Built Environment,Xiao-Ling Ke; Chang Yang; Wei Shi; A. Mougharbel; Haixiang Guo; Mo Zheng,,7.0,3480c8c5070b6bb8c0d1ecb35c68d9149a06021183a,10.5821/ace.11.32.4834,El valor de la centralidad: un análisis para la Barcelona Metropolitana,2016.0,,C. Duarte; J. C. Ochoa; R. Arenas,"Es ampliamente aceptado que la accesibilidad es uno de los pilares basicos en la formacion espacial de los valores inmobiliarios. Sin embargo, en la literatura especializada, esta ha sido reducida a la medicion de la distancia o coste generalizado para acceder, desde una localizacion cuyos valores inmobiliarios son estudiados, a un centro o conjunto de centros.En este articulo se propone un enfoque que incide en dos puntos: 1) se parte de la hipotesis de que la centralidad es un atributo multidimensional (i.e. formado por diferentes variables), 2) cuya distribucion espacial es continua y no dicotomica (i.e. centro/no centro). Con dichas premisas se calibra un modelo de precios hedonicos en el que la variable a explicar es el precio de oferta de una muestra de viviendas plurifamiliares en la Region Metropolitana de Barcelona, y las variables explicativas se refieren a los atributos arquitectonicos y locativos, dentro de los cuales se incluye el nivel de centralidad. Por su parte, el indicador de centralidad reviste interes en si mismo, ya que se construye a partir del analisis del comportamiento espacio-temporal de la poblacion a partir de las cadenas-de-viaje/actividad de la encues",6.0,https://upcommons.upc.edu/bitstream/2117/91359/5/4834-1905-1-PB.pdf34917f8f1569fa95f6eb5e22b566b1a1962d7ce1a43,10.1111/roiw.12692,"OBJECTIVE HOUSING SALES AND RENT PRICES IN REPRESENTATIVE HOUSEHOLD SURVEYS: IMPLICATIONS FOR WEALTH, INEQUALITY, HOUSING MARKET, AND AFFORDABILITY STATISTICS",2024.0,The Review of Income and Wealth,M. Naidin; S. Waltl; Michael H. Ziegelmeyer,"Many economic analyses require hypothetical but realistic sales and rent prices for properties representative of the housing stock and reflecting current market conditions. To achieve this, we replace subjectively reported prices in a representative household survey in Luxembourg with objectified hedonic imputations informed by observable market data. Thus, we propose a powerful tool for assessing the health and affordability of housing markets, compiling housing‐related statistics and simulating hypothetical scenarios. This approach also enables us to test for the reliability of survey responses. When switching to objectified values, we detect shifts in the wealth distribution, large regional variation in market indicators, and striking affordability concerns: only 18 percent of Luxembourg's renters could theoretically afford to purchase their inhabited dwellings given current market conditions. Further, participants' tendency to mis‐estimate market values strongly correlates with tenure length and type, dwelling type, income, and wealth.",6.0,https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/roiw.126923500a760d7b1fcddbe65211845d40a4fca4d87a859d,10.19052/ed.140,Una aproximación hedónica al efecto de las preferencias por segregación en el precio del suelo urbano en Bogotá,2011.0,,L. Viloria; Liliana Núñez Camargo,"El valor del suelo urbano se fija en funcion de variables de localizacion y entorno, pues su precio aumenta en la medida en que exista mayor acceso a vias principales, centros de comercio y servicios urbanos. Sin embargo, la busqueda de distincion, expresada como preferencia por segregacion socioeconomica, es otra variable que tiene incidencia en este valor. El presente articulo busca comprobar que esta preferencia es una variable significativa en la determinacion del valor del suelo urbano residencial, usando la distancia a estratos socioeconomicos como una variable proxy de la preferencia por segregacion, y estimando un modelo hedonico con herramientas de econometria espacial. Se encuentra que efectivamente existe una relacion significativa entre el valor por metro cuadrado del suelo urbano y la distancia de una vivienda a diferentes estratos socioeconomicos. Entre mas lejos se encuentre de estratos 1, 2 y 3, y mas cerca de estratos 4, 5 y 6, mayor sera el valor por metro cuadrado del suelo.",6.0,https://ciencia.lasalle.edu.co/cgi/viewcontent.cgi?article=1013&context=eq351bc94abcd65ab917e7b6873d218a74dde73c7125d,10.3390/buildings12030286,Impact of Induced Seismicity on the Housing Market: Evidence from Pohang,2022.0,Buildings,Jengei Hong; Hyun-kuk Jo; Ducksu Seo; S. You,"In this study, we analyze the case of induced seismicity in Pohang, South Korea, in 2017 to investigate the effect of seismic risk perception on the local residential property market. Based on a hedonic pricing model with a difference-in-differences method, we examine the geographic distribution of the effects of unexpected earthquake hazards. Our results indicate an overall reduction in local property values, but the magnitudes of negative externality for housing prices decrease with respect to the distance from the epicenter. In areas within 3 km of the epicenter, the asset value reduced by approximately 20% after an earthquake event, but if the distance from the epicenter was higher than 12 km, the negative effect on the price was not significant. In addition, we examine how the experience of seismic events affect the preference on the anti-seismic building structure. The results show that the market valuation on the anti-seismic system significantly escalated after the earthquake.",6.0,https://www.mdpi.com/2075-5309/12/3/286/pdf?version=1646211070352c13111d7f015de35ef032b5f6b389d707ddb8bee,10.3846/ijspm.2023.20563,HOW DO DIFFERENT NOISE POLLUTION SOURCES AFFECT APARTMENT PRICES?,2023.0,International Journal of Strategic Property Management,R. Trojanek,"The paper analysed the impact of different noise sources on the residential market. This research used the hedonic method in OLS, SAR and SEM models based on the data set containing geocoded 16,247 apartments in Poznan. Strong evidence was found that noise is negatively linked with apartment prices. The apartment prices were the most significantly influenced by railway noise – an increase of 1 dB above 55 dB causes a 1.79% decrease in the value of an apartment. For other noise sources, aviation noise had the most significant impact with a 0.59% decrease in value per dB, tram noise with a 0.32% decrease and road noise with a 0.12% decrease. The influence of different noise levels on apartments is not constant and does not assume a linear relationship. For road noise, noise below 60 dB and tram noise below 65 dB were statistically insignificant. This may indicate that these noise levels are acceptable and are compensated by better access to public roads or urban transport.",6.0,https://doi.org/10.3846/ijspm.2023.2056335313f6f587afd8db71d0ff7eb4ce4861d5767f9aa9,10.17233/sosyoekonomi.2022.04.20,Determining the Factors Affecting House Prices in Erzurum Using Hedonic Analysis,2022.0,Sosyoekonomi,Cansu Güller; Çiğdem Varol,"The study aims to determine the factors that cause the differentiation of house prices and rents according to different locations of settlements in Erzurum. As the study area, three regions with the highest housing density in Erzurum were determined: Erzurum city centre (Yakutiye), urban development area (Palandöken) and satellite city settlement area (Aziziye). The hedonic price analysis method was used to analyse house prices. Within the scope of the study, building typologies, which are thought to be important in the differentiation of house prices and rent in the city, were analysed, and the variables affecting the housing prices were interpreted together with the urban development dynamics in this study different than the previously conducted housing studies in the region.",6.0,https://dergipark.org.tr/tr/download/article-file/218098835456bc5ebd8542dd52cd905ef715e1fbdd106f4b0a,10.1007/s10037-013-0074-9,Hybrid multilevel STAR models for hedonic house prices,2013.0,,Wolfgang A. Brunauer; S. Lang; W. Feilmayr,,6.0,3557795a2c292ccad4719f593f78952039641270a5e,10.1142/9789814723237_0006,IMPACT OF NATURAL DISASTERS ON RESIDENTIAL PROPERTY VALUES: EVIDENCE FROM AUSTRALIA,2018.0,Economics of Natural Disasters,W. Athukorala; W. Martin; P. Neelawala; D. Rajapaksa; J. Webb; C. Wilson,"One of the most prominent casualties of a natural disaster is the property market. The private and social costs from such events typically run into millions of dollars. In this chapter we use a dataset to examine the impact of natural disasters on residential house prices using a hedonic property (HP) values approach. Data before and after both a wildfire and floods, which affected Rockhampton in central coastal part of the state of Queensland, Australia are used. The data is unique because one of Rockhampton’s suburb was affected by wildfires and another by floods. For the analysis, three suburbs namely Frenchville, Park Avenue and Norman Gardens are used. Frenchville was significantly affected by wildfires in the latter part of 2009 and to a lesser extent in 2012, while Park Avenue was affected by floods at the end of 2010, January 2011, 2012 and 2013. Norman Gardens, which was relatively unaffected, is used as a control site. This enables us to examine the before and after effects on residential property values in the three suburbs. The results confirm that in the aftermath of a natural disaster property prices in affected areas decrease even though the large majority of individ",5.0,356316e372bb24c3d2d7b06318ad6a908525f9cadfd,10.17163/lgr.n36.2022.08,"Contrasting Effects of Air Pollution Assessment in two Areas of the Quito Metropolitan District, Ecuador",2022.0,La Granja,Daniel Cornejo-Vásconez; F. Rodríguez-Espinosa; Alejandra Guasumba; T. Toulkeridis,"One of the main factors of air contamination within urban areas is burning gasoline by cars, light trucks and motorcycles. Gasoline burning liberates pollution gases such as Nitrogen dioxide, Sulfur dioxide, Carbon monoxide, benzene, besides others. Among these, Nitrogen dioxide (NOx) is the one that stands out for the people’s awareness of such contamination. We used the Hedonic Price Method (HPM) in order to determine people’s perception of air quality as a proxy and estimate the effect of gases on the housing market. We selected two areas of Quito Metropolitan District in order to evaluate contamination effects on properties. One with a higher concentration of gases located within the historic district of Quito. The other with better air quality called the Bellavista district. The results of three different models indicated that a reduction of 1 (µg/m3) of NOx would increase an average of 4.54% of the housing market value, which it represents 2,032,326.24 USD in value for sample properties. A decrease of 5 µg/m3 will increase in 22.7% of properties value.",5.0,https://doi.org/10.17163/lgr.n36.2022.083578b40d59c2cf1fb45e2898b8a9d2bc70967606aa7,10.1007/bf03399268,Indirect Construction of Hedonic Price Indexes for Private Properties,2008.0,,S. Fahrländer,"SummaryThis paper analyzes the construction of price indexes for condominiums and single family houses in Switzerland over the period 1985 to 2004 using the indirect method. We find, that the pooling of the data, i.e. direct indexes with fixed hedonic prices, are good models for average properties but can be biased for the indexation of non-average properties. Therefore indirect index construction using predictions for specific properties based on annual equations is recommended.Based on differentiation of forty regions it is shown, that indexes vary from region to region, but show a comparable general path between 1985 and 2004. In recent years prices for single family houses raised in the large urban areas and tourist resorts but, due to big land reserves, were stable or even declined in smaller urban and semi-urban as well as in rural areas. Price paths for condominiums are generally comparable to those of single family houses with the big difference, that over the last three years prices were raising in most of the regions.",5.0,https://sjes.springeropen.com/counter/pdf/10.1007/BF03399268358bdabc5cf4f046fd4ae9fea57fc3e1d2c42d268cb,10.1007/s11146-023-09949-w,Tracking Home-Owners’ Sentiments: Subjective Indices and Convergent Validity,2023.0,Journal of real estate finance and economics,S. Waltl; Anthony Lepinteur,"Surveys regularly ask home-owners to guess what their property might be worth in the current housing market. We develop suitable statistical techniques to construct hedonic and repeat-sales style house price indices from these owner-estimated values (OEVs). The resulting series are then linked to a large set of quality-adjusted residential property price indices estimated from transaction data allowing us to perform a variety of convergent validity tests. Based on results for 20 countries, several decades and different OEV elicitation techniques, we conclude that the “wisdom of the home-owner crowd” is sufficient to study objective house price dynamics. Yet, surveys fail to accurately measure house price levels.",5.0,https://link.springer.com/content/pdf/10.1007/s11146-023-09949-w.pdf359a9abf0950b66976858510543546f2f1a44f16566,10.1111/1540-6229.12298,Hedonic Price of Housing Space,2019.0,Real Estate Economics,S. Agarwal; Yan-Ying Chen; Jing Li; Yi-Jin Tan,"This article estimates hedonic prices for different levels of housing space, by exploiting a unique space‐adding project in Singapore that added a uniform amount of space to each existing housing unit regardless of the original size. This space adding program was carried out if sufficient residents vote in favor of space adding. Using a difference‐in‐differences (DiD) strategy after restricting our sample to narrow margins around the voting cutoff, we find that the additional space increased the resale price of a housing unit by 7% on average, and the extent of price appreciation varied significantly across the original size of the units.",5.0,https://doi.org/10.2139/ssrn.344044836080203e432f645fd5aa6cbd7349189256b149ca4f,10.1111/1540-6229.12360,"Rental equivalence, owner‐occupied housing, and inflation measurement: Microlevel evidence from Ireland",2020.0,Real Estate Economics,C. Coffey; K. McQuinn; C. O'Toole,"In this paper, we use unique supervisory property-level rental data to estimate a rental equivalence (RE) measure for owner-occupied housing (OOH) for the Irish housing market. Our data from the o cial, domestic rental regulator allow us to simultaneously address three signi cant issues which have arisen in the empirical application of rental equivalent measures. First, we are able to consider the di erences in using data on both new and existing rent levels in the analysis, we can also control for other utility costs and nally we are able to estimate a RE measure in the absence of rent controls. To better approximate the OOH structure of the Irish residential market, we also avail of regional data to estimate 32 separate hedonic rent models and use the results to reweight the RE index. We nd that our subsequent estimate of RE results in a reduction in the Irish headline rate of consumer price in ation by 0.4 percentage points. Furthermore, we show there are considerable di erences in the in ation rate if new relative to existing rents are used in the rental equivalence measures with measures based purely on existing rents biasing downwards both the rental equivalence measure and t",4.0,https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/1540-6229.12360361807335511e2617caa1df375cccf38a79763acb45,10.24957/hsr.2020.28.2.113,A Study on Gender Difference of Housing Costs: Focusing on Single-Person Household,2020.0,Korean Association for Housing Policy Studies,Mihwa Lim,"In terms of housing selection, women prefer to live in a house that is comfortable, convenient, and safe from crimes despite their lower income compared to men. Considering this, the housing cost of single-woman households may be higher than that of single-man households. This study estimated and compared the user costs and rental fees as the self-resident cost, using the hedonic price model for housing in single-woman and single-man households. As a result, it was found that the user cost of single-woman households is approximately 20,000 won higher than that of single-man households while the user cost per area (m2) of single-woman households is approximately 3,000 won higher than that of single-man households. Based on the age and gender analysis of the user cost per area (m2), the housing cost ratio of single-woman households is higher than that of single-man households. In the case of rental fee per area (m2), the housing cost ratio of single-woman households is 1.0 or higher than that of single-man households in the 20s, 30s, and 40s age groups. In conclusion, the housing cost ratio of single-woman households is 1.0 or higher than that of single-man households in terms of use",4.0,3621eaeb6cb4ceafec197ee2c50fee42cb09556c6d0,10.1108/jpif-12-2020-0138,Property valuation: the hedonic pricing model: the application of search-and-matching models,2021.0,Journal of Property Investment & Finance,G. Lisi,"PurposeThe aim of this education briefing is to comment upon how basic hedonic pricing models for the valuation of property can be expanded and developed. In this case, the briefing illustrates the use of the new economic approach to the analysis of housing markets, namely the search-and-matching models.Design/methodology/approachThis education briefing discusses the connection of two important economic theories: the hedonic price theory and the search-and-matching theory.FindingsThis education briefing gives an example of a (non-linear) form of the hedonic price function.Practical implicationsIn cases of mass appraisals, hedonic pricing models can provide a broad indication of value across submarkets and this education briefing demonstrates a theoretical model that can be used to provide a theoretical groundwork for the use of a concave hedonic price function in empirical estimates.Originality/valueThis education briefing shows how basic hedonic pricing models can be enhanced by a search-and-matching approach to determine property values.",4.0,363117ece8d9f6f27eb3420fceece83b4d2ea4c9e8c,10.1111/jors.12381,Economic Valuation of a Rise in Ambient Radiation Risks: Hedonic Pricing Evidence from the Accident in Fukushima,2018.0,Social Science Research Network,A. Munro,"Using a combined data set of radiation levels and property prices from Fukushima and Miyagi prefectures that runs from 2009 to early 2017, the economic impact of radiation from the Fukushima nuclear accident is assessed. A 1 percent rise in radiation is associated with approximately 0.051 percentage drop in housing prices and though the level of radiation falls substantially after 2011, the estimated elasticity is broadly stable. The associated estimate of VSL (value of a statistical life) is in the region of US$4.5–6.4 million, which suggests no strong element of dread or overestimation of risks is present.",4.0,3647b68afecbfc93575ac1643d681165f9749189fe6,10.19030/jabr.v28i4.7048,The Housing Price Bubble In A Suburban Georgia Setting: Using The Hedonic Pricing Model In The New South,2012.0,,Jason Beck; Joshua Fralick; Michael Toma,,4.0,https://doi.org/10.19030/jabr.v28i4.70483655d2c053894e7bd8f9d2bd969084ad2f043953e14,10.4028/www.scientific.net/amm.587-589.2285,The Analysis of Second-Hand Housing Price Influencing Factors Based on Hedonic Model and WEB Information,2014.0,,Hui-Rong Li; Yu-Mei Sun,,4.0,366b8757da465da4bd490ab004e3c10d0ecb61e91bd,10.15396/eres2022_186,Proposing a global model to overcome the bias-variance tradeoff in the context of hedonic house price models,2022.0,28th Annual European Real Estate Society Conference,S. Lang; Wolfgang A. Brunauer; Julian Granna,,4.0,36711b7372d2d38c8a6031a4ac3d5c8f83360e3c972,10.2478/remav-2023-0003,Architectural Factors Influencing a Housing Market Value: A Theoretical Framework,2023.0,Real Estate Management and Valuation,Tomas Skripkiūnas; V. Navickas,"ABSTRACT A housing price, not considering its change over time, is widely determined by hedonic properties. This is common in literature; however, there is a significant part of a price, the so-called unexplained variance, that is not captured by hedonic models. The scientific problem of this research is how to classify and visualize architectural factors that might have an influence on the market value of a dwelling. The object of the research are architectural factors in a housing market value analysis and the aim of research is to describe the theoretical framework that defines the structure and scope of architectural variables influencing a housing market value. Not all architectural factors described in the literature review are equal in terms of scale, measurability, public or private context, aesthetic or functional priority. A systematic approach would be to classify architectural factors as a matrix of built environment properties. Two orthogonal dimensions can be identified: architectural factors spanning from non-design (functional, utilitarian) to design (abstract, unexplained) and factors spanning from architectural design (private) to urban design (public). A multidim",3.0,https://sciendo.com/pdf/10.2478/remav-2023-0003368367e2b3c9a2b81d9f08952da7fb022c6c1ccc9e7,10.46849/guiibd.1060105,INVESTIGATION OF FACTORS AFFECTING HOUSING PRICES IN ORDU PROVINCE BY USING CROSS-SECTION ANALYSIS,2022.0,Giresun üniversitesi iktisadi ve idari bilimler dergisi,Burhan Mağden,"The approach that states that the value of heterogeneous goods results from the sum of the prices of all the different features that make it up is called the hedonic price model approach. In this study, it is aimed to determine the most important features that determine the housing prices in Altınordu district of Ordu province and the features that affect the housing prices of different income groups by using the data set from www.sahibinden.com site for the month of December 2021. For this purpose, 13 neighborhoods according to income groups were divided into three as upper, middle and lower income groups and tested with semi-logarithmic models using data from 558 houses. According to the results of this model, it has been determined that there are significant relationships on the housing prices of the different properties of the houses in terms of income groups. The results of the analysis show that the square meter size affects the housing price positively whilst the age of the building negatively affects all income groups.",3.0,https://dergipark.org.tr/tr/download/article-file/2201106369c2020efe69de94e5f2b73057150b6da505d6d03b,10.15446/bitacora.v32n1.87760,Modelo de estratificación como generador de segregación en Bogotá,2021.0,Bitácora Urbano Territorial,Julián Alberto Gutiérrez López; Lina Fernanda Quenguan López; Héctor David Nieto Martínez,"Este trabajo evidencia que, en contra de los deseos de la política pública, el mercado inmobiliario, por medio de las rentas de segregación, hace que la mezcla socioeconómica resulte cada vez más difícil. Por medio de un modelo de precios hedónicos, en donde se toma como base el estrato socioeconómico y las variables urbanas más relevantes, encontradas en los modelos de precios urbanos que configuran los precios del suelo de la ciudad, se evidencian las rentas de segregación que algunos agentes dentro del mercado de vivienda deciden pagar por obtener los beneficios más altos (mejores localizaciones, mejores vecinos, mejores productos inmobiliarios).370Se encontró que existe una relación significativa entre el valor del metro cuadrado de terreno y la distancia a estratos socioeconómicos considerados bajos (para Bogotá estratos 1 y 2), evidenciando que los agentes económicos de estratos altos pagan precios altos por localizaciones que se encuentren alejadas de los estratos bajos.",3.0,https://doi.org/10.15446/bitacora.v32n1.877603719a7554c578a086f14bafb130c8e3c82b8514c22d,10.32468/be.1016,¿Está Afectando el Impuesto Predial el Precio de la Vivienda en Bogotá? Un Análisis Basado en la Econometría Espacial,2017.0,,Ignacio Lozano-Espitia; D. Ricciulli-Marín,"Este documento provee evidencia sobre los efectos del impuesto predial en los precios de la vivienda nueva en Bogota para el periodo 2009-2016. Se utiliza informacion fiscal y de los atributos fisicos y de localizacion de 6.013 predios residenciales de estratos medios y altos, ubicados en las tres localidades de mayor urbanizacion y contribucion al fisco (Chapinero, Suba y Usaquen). Mediante el uso de modelos espaciales para datos de panel, el trabajo encuentra que los aumentos registrados en la tarifa efectiva del predial han impactado negativamente los precios de los inmuebles y que dicho efecto ha venido aumentando en los ultimos anos. Los resultados son robustos tanto a cambios en la matriz de pesos espaciales como a cambios en las metodologias de estimacion. Los ejercicios controlan por los impactos sobre los precios debidos a los atributos fisicos de las viviendas, su estrato y ubicacion, con resultados coherentes con la evidencia internacional sobre precios hedonicos.",3.0,https://doi.org/10.32468/be.10163725c1ce232e30e4794f1218b36f5a568103751acad,10.12775/aunc_econ.2014.001,INDEKS HEDONICZNY MALARSTWA POLSKIEGO DLA NAJBARDZIEJ POPULARNYCH AUTORÓW NA RYNKU AUKCYJNYM W LATACH 2007-2010,2014.0,,K. Kompa; D. Witkowska,Situation at financial markets tend investors to look for alternative investments to diversify their portfolio. The aim of our research is evaluation of hedonic price index for selected Polish painters based on data from auctions of paintings held by auction houses and foundations in the years 2007–2010. The criterion of artworks selection is popularity of authors that is measured by the number of paintings sold in analyzed period. We construct and estimate several models for different sets of hedonic variables. On the basis of models parameter estimates the hedonic quality adjustment for the art price index is evaluated.,3.0,https://apcz.umk.pl/czasopisma/index.php/AUNC_EKON/article/download/AUNC_ECON.2014.001/471737363d3e41634a76fe68a3edb5f056b73b7098ad523,10.3368/le.99.4.041322-0030r1,The Impact of Water Body Restoration on the Sales and Rental Markets in Beijing,2023.0,Land Economics,Ying-Dan Mei; P. Liu; Li Gao,"Black and odorous water bodies (BOWBs) are increasingly common in cities worldwide. This article evaluates the impact of an urban water bodies restoration program in Beijing, China, based on detailed housing sale and rental transaction data. We implement a hedonic price model with a difference-in-difference and a triple-difference approach and find that listing and restoring a BOWB significantly increase house prices by 2.2%–3.9% and 2.3%–4.9%, respectively, and increases rents by 11.3%–13.7% and 13.4%–16.9%, respectively.",3.0,https://le.uwpress.org/content/wple/early/2023/03/14/le.99.4.041322-0030R1.full.pdf374dba4a79632ce16ef969c1186a72550e41ec13165,10.1111/asej.12169,Monetarizing Spillover Effects of Soil and Groundwater Contaminated Sites in Taiwan: How Much More Will People Pay for Housing to Avoid Contamination?,2019.0,Asian Economic Journal,Je-Liang Liou; A. Randall; Pei-Ing Wu; Hanhui Chen,"This study monetizes spillover effects of soil and groundwater contaminated sites using a quantile hedonic price model for different site types in Taoyuan City in Taiwan, which has 1664 sites, the highest number for any city in Taiwan. The results show that except for those living in the cheapest housing, most residents are willing to pay a higher price to live farther away from contaminated sites. Farmland makes up the largest share of the total contaminated site area and has the highest per square monetary spillover effects in Taoyuan City; remediation of farmland is one of the most urgent missions for the city. Overall, a NIMBY effect is found to exist for soil‐ and groundwater‐contamination in this city.",3.0,375703d4f4902dbf48a8a55665e5f59734351adda33,10.5505/megaron.2017.35582,Examination of house price differentiation in Ankara with the help of hedonic analysis,2017.0,MEGARON / Yıldız Technical University Faculty of Architecture E-Journal,Leyla Alkan Gökler,Ankara'da konut fiyatlar farkl alanlara gre eitlilik gstermektedir,3.0,https://doi.org/10.5505/megaron.2017.35582376f00d413d1fc1aec9c71401512c0a45076cbdd8bf,10.1007/978-3-319-54873-9_12,The Statistical Basis of Valuation: The Hedonic House Price Model,2017.0,,C. Price,,3.0,3770b89e623e0b05b7c8f536f0cfe2f7928ae52db92,10.56712/latam.v5i6.3110,"Determinación de la influencia de la contaminación acústica generada por el flujo vehicular, en la valoración económica de viviendas en el distrito de Arequipa, 2018",2024.0,LATAM Revista Latinoamericana de Ciencias Sociales y Humanidades,Treyzy Fransheska Loza Osorio; Digmar Arturo Loza Alcalde; Yoana Alexandra Portugal Cano,"La presente investigación busca determinar la influencia de la contaminación acústica en la valoración económica de viviendas en el distrito de Arequipa generada por el flujo vehicular, el cual, El desarrollo de la investigación se realizó a través de un estudio empírico con 72 mediciones de ruido en diferentes puntos del distrito, mismas que fueron comparadas con los ECA (Estándares Nacionales de Calidad Ambiental) establecidos para ruido, dando como resultado que el 33.3% (24 mediciones) no superan los ECA; mientras que el 66.6% (48 mediciones) superan los ECA. Como resultado se obtuvo que el modelo econométrico de la función de precios hedónicos utilizados en el estudio es adecuado para medir la capacidad explicativa del modelo en su conjunto, donde el coeficiente de determinación R² dio un valor de 0,95. Se muestra que el ruido se convierte en una externalidad negativa en el valor comercial de las viviendas, puesto que a medida que se encuentran expuestos a altos niveles de ruido, su precio disminuye; es decir, su valor comercial se deprecia en un 0,96% por el incremento de 1 decibel (dB). Esta investigación se realizó con el fin de que sirva como instrumento para aplicar polít",2.0,https://doi.org/10.56712/latam.v5i6.31103787e1fb30ea0df3365f3fc36da9a0ba3d2741cb1a8,10.3846/ijspm.2021.14570,NET BENEFITS OF URBAN SLUMS REDEVELOPMENT POLICIES ON THE VALUE OF ADJACENT RESIDENTIAL PROPERTY,2021.0,,Touseef Hussain; Wei Zou,"Over time, the government of Pakistan introduced several strategies to deal with the issue of slums in its capital city, Islamabad. Contrary to the traditional strategies that primarily focus on the tenure security of occupants, the strategy of slum redevelopment is more composite. It involves the up-gradation of slums in their existing sites as well as the demolition of slums from the posh areas. The present study is first to empirically investigates the outcomes of the slums redevelopment policies on the value of adjacent residential properties. Using a rental valuation based hedonic price model, the study examined the spillover effects of an urban slum up-gradation and eviction projects on the nearby housing values. The results show that the redevelopment of slums reduces the adverse effects on residential value. It is essential for the urban planners to cautiously include the slum redevelopment projects spillover effects on the adjacent property value in different geographical locations, to maximize the net positive effects of improvements on the neighborhood.",2.0,https://journals.vgtu.lt/index.php/IJSPM/article/download/14570/10474379eeb49dbdc07f45aba3683bea434eb0bb041bdc8b,10.3390/buildings15071156,Urban Megaprojects from Isolation to Integration: A Property Market Perspective on Flagship Buildings,2025.0,Buildings,Maximilian Neuger; Connie Susilawati,"This study investigates how the simultaneous development of multiple urban megaprojects creates synergistic effects in residential property markets, with significant implications for urban planning and policy. Through an enhanced hedonic pricing model incorporating inter-project interaction terms, the research quantifies both individual and collective impacts of concurrent developments on property values. Analysis of comprehensive transaction data (2016–2022) reveals complex patterns of complementary and competing effects between proximate megaprojects, demonstrating that their combined impact differs substantially from the sum of their individual effects. The findings highlight the critical importance of coordinated planning approaches that consider inter-project dynamics when designing urban regeneration strategies. This research provides the first empirical measurement of megaproject synergy effects, offering valuable insights for policymakers and investors in optimizing the economic outcomes of transformational flagship buildings.",2.0,https://doi.org/10.3390/buildings15071156380a4d41fae49ce23763e2570510944942df5f51e00,10.1111/ecca.70008,Energy price shocks and the demand for energy‐efficient housing: evidence from Russia's invasion of Ukraine,2025.0,Económica,Nils Braakmann; Bahadır Dursun; Harry Pickard,"This paper examines how the energy price shock post Russia's invasion of Ukraine in 2022 affected property transactions. Using administrative data on transaction price and energy efficiency in the UK, we explore if buyers adjust behaviour in response to greater energy costs. Using hedonic difference‐in‐differences models, we find that prices increase by £1000 for high‐rated energy efficiency properties and decrease by £2400 for low‐rated ones. Properties with higher potential energy efficiency also see value upticks. We also find that high gas‐consuming neighbourhoods experience fewer house sales post‐invasion. The size of the effect is explained by buyers perceiving the energy price hike as temporary. Our results shed light on the interplay between energy prices and the property market, offering insights into buyer behaviour and the valuation of energy efficiency.",2.0,https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/ecca.700083815cf0e2b30c228ce0f66b63e399dd288439b123ba,10.1108/ijhma-01-2021-0005,A housing price index with the improvement-value adjusted repeated sales (IVARS) method,2021.0,International Journal of Housing Markets and Analysis,C. Yiu; Ka-Shing Cheung,"382Purpose383The repeat sales house price index (HPI) has been widely used to measure house price movements on the assumption that the quality of properties does not change over time. This study aims to develop a novel improvement-value adjusted repeat sales (IVARS) HPI to remedy the bias owing to the constant-quality assumption.384385386Design/methodology/approach387This study compares the performance of the IVARS model with the traditional hedonic price model and the repeat sales model by using half a million repeated sales pairs of housing transactions in the Auckland Region of New Zealand, and by a simulation approach.388389390Findings391The results demonstrate that using the information on improvement values from mass appraisal can significantly mitigate the time-varying attribute bias. Simulation analysis further reveals that if the improvement work done is not considered, the repeat sales HPI may be overestimated by 2.7% per annum. The more quality enhancement a property has, the more likely it is that the property will be resold.392393394Practical implications395This novel index may have the potential to enable the inclusion of home condition reporting in property value assessments prior to listing op",2.0,39689e86c34d31d60b83fe1893b6d6fc9985407503c,10.3389/frsc.2025.1522520,From industry to center for arts and culture: the impact of industrial heritage transformation on neighborhood house prices,2025.0,Frontiers in Sustainable Cities,Lasse Læbo Matthiesen; Marie Lautrup; T. Panduro,"We examine how converting an industrial heritage site in Aarhus, Denmark, into a center for arts and culture affects nearby residents’ welfare. Using a hedonic house‑price model and a difference‑in‑differences design, we track apartment prices before and after the conversion. Prices within the neighborhood rose by 2.3–3 % relative to the rest of the city. This uplift represents a welfare gain of €17.5–21 million for the local community. As one of the few quasi‑experimental evaluations of creative‑led heritage revitalization, our study provides rigorous causal evidence of substantial indirect economic benefits. This evidence can guide future investments to convert disused industrial buildings into cultural and recreational spaces that serve local communities.",2.0,https://www.frontiersin.org/journals/sustainable-cities/articles/10.3389/frsc.2025.1522520/pdf3978a131d87888c091e6a09db7ad502ed1c9e466beb,10.32866/001c.16628,"Did the A Line Arterial Bus Rapid Transit Affect Housing Values in Ramsey County, MN?",2020.0,,Jack Benson; Jason Cao,"As arterial bus rapid transit (BRT) has become popular in the Twin Cities, local residents worry about the housing value uplift associated with these investments and the potential displacement of poor residents. Using a before-after treatment-control design, this study developed a difference-in-difference hedonic model to examine the effects of the A Line BRT on station-area housing values. After the funding announcement and opening, housing sales prices increased slightly. However, neither effect is statistically significant. The A Line encouraged ridership but had no effect on housing values. We will explain why the Green Line light rail increased property values whereas the arterial BRT did not.",2.0,https://findingspress.org/article/16628.pdf398011bb69dea5394989740ba269b46216fb1f69a8d,10.33358/jfea.112406,The anticipation effect of a light rail transit line on housing prices in the Helsinki region,2021.0,Journal of the Finnish Economic Association,Eetu Kauria,"I analyze how housing markets in Espoo and Helsinki anticipate the construction of a new light rail transit connection called Jokeri Light Rail. I use geocoded micro-level housing transaction data from 2003–2019. As an econometric identification strategy, I utilize difference-in-differences estimation with a hedonic price model. My main result is that, on average, apartment prices increase by 5 percent more within 800 meters of the Jokeri Light Rail stops than apartments farther away. A rough estimate of the total windfall for homeowners indicates that the anticipated benefits exceed the cost estimate for the investment five to eight years before the Jokeri Light Rail becomes operational.",2.0,https://journal.fi/jfea/article/download/112406/6605939928e30fd142283c88cda58781490c077681d90293,10.3390/jrfm15020087,Urban Leverage and Housing Price in China,2022.0,Journal of Risk and Financial Management,Wanying Lu; Jianfu Shen,"This paper examines whether urban leverage, defined by the bank loan-to-deposit ratio in a city, affects housing prices in China. Using a panel dataset of 236 cities and hedonic models, we find a depressing effect of urban leverage on housing price in first- and second-tier cities while leaving third- and fourth-tier cities unaffected. Urban leverage negatively affects housing prices by influencing credit supply. Moreover, the difference-in-differences analysis indicates that purchase restriction policies amplify the depressing effect of urban leverage on housing prices. Overall, we show that urban leverage is an important determinant of housing prices in China.",2.0,https://www.mdpi.com/1911-8074/15/2/87/pdf?version=1645178659400568f3f03d522b02d12944fb42fafa6e08764e3b4,10.1177/0160323x241252584,A Regional Analysis of the Impacts of Changes in Housing Values on Property Tax Assessment During and After the 2008 Financial Crisis,2024.0,State and Local Government Review,Yun-Ni Deng; Mark Skidmore,"This study examines the relationship between changing house prices and assessed value in the Detroit Michigan region. Using parcel-level data from 2008 through 2016, we construct a Hedonic Housing Price Index and an Assessed Value Index for 120 Michigan assessing jurisdictions in the five-county region surrounding Detroit (Macomb, Monroe, Oakland, Washtenaw, and Wayne). Our findings are consistent with the literature, indicating at least a three-year lag between changes in house prices and changes in property assessments. Communities considered to be distressed tended to over-assess properties before the crisis, but these communities recalibrated assessments to better align with market conditions after the financial crisis. Our evaluation also shows that while assessed values decreased more slowly than housing prices fell during the crisis, assessed values tended to fall to even deeper levels than housing prices over a longer time horizon. JEL Codes: H71, H83, G01",2.0,4012863159db1d9a7be0915495677fb30e9725f2212,10.1080/13547860.2019.1664534,"Wages, house prices and industry composition: an empirical analysis of cities in China",2019.0,Journal of the Asia Pacific Economy,Jing Wang; Li-Fen Zhu; Jing Li,"Abstract Wages and house prices are two of the hottest public issues in China today. Whether and how the change in industry composition affects them? These issues have received widespread public attention. This study is dedicated to analysing the effects of industrial composition, which is measured by an index calculated using 19 2-digit industries, on wages and house prices using a modified hedonic price model and prefecture-level city data from China between 2005 and 2013. The main findings indicate that (1) an increase in industry composition index will drive up wages and house prices. The increment of wages surpasses that of house prices, showing that the house-purchasing burden decreases as the index increases; and (2) the effects of industry composition on wages and house prices differ between high-, middle- and low-income cities. The change in industry composition may increase the wage and house price gaps between cities of different income levels.",2.0,402b5f540312d535081cc599b12ca82c2c4d7e86656,10.15604/ejef.2017.05.02.004,Determinant of Housing Rents in Urban Albania: An Empirical Hedonic Price Application with NSA Survey Data,2017.0,,Mustafa Kahveci; Ernil Sabaj,,2.0,https://doi.org/10.15604/ejef.2017.05.02.004403c737648e1f43f7a824388474c3b1fd82a37e4636,10.2139/ssrn.2841730,Impact of the Economic Crisis on House Prices in the Czech Republic Measured on Hedonic Price Index on Bank Data,2014.0,,Martin Lux; Petr Sunega,,2.0,https://doi.org/10.2139/ssrn.284173040483ad512586a8602964d721ee086178a111e4b4e3,10.3828/jtep.1996.30.1.15,The Impact of a Light Rail System on the Structure of House Prices: A Hedonic Longitudinal Study,1996.0,Journal of Transport Economics and Policy,D. Forrest; J. Glen; R. Ward,Two conventional railway lines in Greater Manchester were replaced by a new light rail system. This paper uses hedonic price methodology to examine whether any of the claimed benefits were capitalised in house prices. No discernible effect was found. This finding contrasts with claims made for the urban transit schemes in other countries. Reasons for the differences and methodological problems with the current literature are discussed.,2.0,405dc8e95a42e4f28c5d406942223769fbfcaa06f54,10.4324/9780203799833-24,The impacts ofland use on nearby property values: estimates from a hedonic house price model,2004.0,,J. Bergstrom; S. Goetz; J. Shortle,,2.0,406babc83ff8ba37ccca49ba0e923a16f989bf653cd,10.15396/eres2013_233,Measuring Dwelling Price Changes in Poland with the Application of the Hedonic Methods,2013.0,,R. Trojanek,,2.0,4071db7cc73a8606e5ba21dfac1f5a0da6d535e3f89,10.5821/dissertation-2117-93437,"Espacio ""privatizado"". El valor de privatizar un espacio público en zona urbana",2007.0,,José Refugio Rojas Lopez,"A través de la historia de la ciudad se vienen contemplando diferentes ideas, propuestas de solución al problema de la vivienda y su forma de ordenarla dentro del territorio urbano. En la actualidad una de las formas de presentarse estos modelos de urbanización son los fraccionamientos cerrados. Esta urbanización tiene como característica principal o singular el muro que delimita la zona de vivienda con el resto de la ciudad.El crecimiento en distintos países de la topología denominada en el presente trabajo como Ciudad Privatizada, llama a la reflexión sobre el tema y a conocer mas sobre el. Si bien, se establecen las características de estas topologías, se hecha en falta estudios que permitan conocer como afecta a los distintos sectores de la ciudad, así como los beneficios y obligaciones de las mismas.La Ciudad Privatizada, es una propuesta, cuyos inicios aparecen a principios del siglo XX, y evoluciona hasta llegar a los años 80 donde se presenta como la conocemos hasta hoy día. Actualmente se ha convertido en una alternativa importante para el desarrollador inmobiliario. Además, ha logrado tener una importante penetración en el urbanismo de países tan diversos como distintos.E",1.0,https://upcommons.upc.edu/bitstream/2117/93437/2/02JRrl02de10.pdf4082266514b15119ed8cecc8c68920cfbe50b13b29d,10.14744/megaron.2019.78700,The Effect of Housing Properties in Törekent Neighborhood On Housing Prices in the Context of the Development in the Western Corridor of Ankara,2019.0,,K. Özcan,"Yerel ve bölgesel olarak alınan planlama kararları ile birlikte hızla gelişen sanayileşme, gayrimenkul piyasalarının gelişimini de etkilemiştir. Bu bağlamda, tarihsel gelişim içerisinde Sincan İlçesi’ndeki, Ankara Sanayi Odası 1. Organize Sanayi Bölgesi ve Ankara Merkez Dökümcüler Sanayi Sitesi ile çevresi bir çekim merkezi olarak gayrimenkul sektörünün gelişimini de etkilediği için bu bölgeye yakın olan Törekent Mahallesi çalışma alanı olarak seçilmiştir. Yıllar içerisinde İlçe’de oluşan söz konusu cazibe merkezi ile artan istihdam sonucu gayrimenkul alanında faaliyet artışı gözlemlenmiş ve dolayısıyla, konut fiyatlarını etkileyen çeşitli mekânsal ve çevresel faktörler de oluşmuştur. Çalışmanın amacı; Ankara’nın batı koridorunda bilhassa planlama kararları ile meydana gelen gelişme çerçevesinde gayrimenkul alanındaki gelişmeyi ortaya koymak olup; bu doğrultuda konut fiyatlarını etkileyen özellikleri analiz etmektir. Çalışmanın yöntemi ve metodolojisi; literatür taraması, Sincan İlçesi’nin mekânsal gelişiminin incelenmesi, Sincan İlçe Belediyesi’ndeki konuyla ilişkili çalışanlarla yüz yüze görüşmelerin yapılması, çalışma alanı içerisindeki 50 adet kiralık ve 50 adet satılık konuta ",1.0,https://doi.org/10.14744/megaron.2019.78700409ed853c400bd0f80e1b2a68df8f46a4da0e00a204,10.1108/ijhma-05-2025-0123,"Investigating the spillover effects of neighbouring housing rents on housing prices: evidence from Beijing, China",2025.0,International Journal of Housing Markets and Analysis,Zisheng Song; Mats Wilhelmsson; A. Zalejska-Jonsson,"410 411 The purpose of this paper is to investigate the spillover effects of neighbouring rents on housing prices.412 413 414 415 Treating neighbouring rents as a locational attribute, the authors estimate a price–rent hedonic model using owner-occupied and rental housing transactions from Beijing (2016–2018). In addition, the empirical model shows substantial robustness using instrumental variable-two-stage least squares estimation, Oster’s selection-on-unobservables test and placebo tests.416 417 418 419 The authors find that a 1% increase in one-quarter-lagged neighbouring rents raises sale prices by about 0.35% in OLS estimation, while the spillover is around 0.23% in instrumental variable (IV) estimation. Furthermore, rental spillovers are heterogeneous – stronger for mid-sized and newer housing units, outside school-district zones and in Chaoyang, Haidian and Shijingshan, while weaker in new-town areas. In addition, exploiting a late-2017 tightening of rental supply, the authors further show that the spillover intensifies thereafter.420 421 422 423 The findings highlight the interconnectedness of the rental and ownership markets and underscore the need for urban housing policy to consider the signals of",1.0,https://doi.org/10.1108/ijhma-05-2025-01234240a4937b08535504a0947151b89978ab85fcc8f00,10.15396/eres2013_59,How Can One Tell When the Housing Market Is Out of Equilibrium,2013.0,,R. Hill,"Purpose - One way of detecting departures from equilibrium is by comparing house prices and rents. Here I assess the viability of this approach.Design/methodology - Error-correction models (ECMs) based on price and rent indexes can be used to forecast movements in house prices. The short-term forecasting ability of ECMs is limited though due to the long persistence of departures from equilibrium. ECMs also suffer from the limitation that they do not tell us whether the price-rent ratio is above or below its equilibrium level at any given point in time. To answer this question it is necessary to make cross-section comparisons of prices, rents and user cost (i.e., the cost incurred by owning a house).Findings - A meaningful cross-section comparison requires that prices and rents are quality adjusted. This may require the use of hedonic methods. The equilibrium price-rent ratio (which is derived from the user cost) is difficult to compute since it depends on the expected capital gain. Also, both the actual and equilibrium price-rent ratios differ depending on which segment of the housing market is considered. Originality/value - The housing market, which is prone to booms and busts, c",1.0,https://eres.architexturez.net/system/files/pdf/eres2013_59.content.pdf425eeeb80738d277fb610c4a79f5dd1b93a1a96c684,10.3390/realestate2040019,"Transactional (Case–Shiller) vs. Hedonic (Zillow) Housing Price Indices (HPI): Different Construction, Same Conclusions?",2025.0,Real Estate,Mark Rzepczynski; Wei Feng,"Housing price indices (HPIs) are employed to assess the impact of the business cycle, monetary policy, housing policies, and local market dynamics. However, comparative empirical analysis of different HPI methodologies has not been conducted to measure why or when they may diverge and whether these differences are meaningful. Two leading US HPI choices, the repeat-sale transactional (S&P Case–Shiller) and characteristic-based hedonic (Zillow) indices, although highly correlated, generate different distributions and time-series properties primarily at the city level. The spread between these two HPI choices measures the difference between housing market transaction intensity and a willingness-to-pay characteristic valuation. We find that transactional indices are more volatile, with HPI spreads associated with both macro and local drivers. The transactional index will rise more rapidly in a market with increased buying (positive macro and local market conditions) and fall further in a market with increased selling (negative macro and local market conditions) relative to a hedonic index. A buyer- or seller-biased spread between a transactional and hedonic housing price index (HPI) ma",1.0,https://www.mdpi.com/2813-8090/2/4/19/pdf?version=17623316464268fbc4962e2e912946d9d1ab4a59608223046ca05,10.21837/pm.v21i27.1280,CONCERN OVER PROPERTY VALUE: WILL THE SITTING OF PETROCHEMICAL HUB INFLUENCING HOUSING PRICE?,2023.0,PLANNING MALAYSIA,Chin-Tiong Cheng; H. Chin,"Malaysia is a major exporter for petrochemical products. In line with this, the petrochemical industry is experiencing continuous growth and expansion. This study intends to examine the effect of the establishment of petrochemical hub on nearby housing price. Using residential transaction data of year 2016-2022 nearby Gebeng Industrial Area, we analyse the effect of the sitting of petrochemical hub via hedonic models. Our result indicates that the sitting of petrochemical hub will influence the housing price in which those located nearby will experience higher appreciation in property prices. This study is essential in clearing the doubt that housing price will be negatively influenced by petrochemical hub. Our findings further indicate that there is a need to educate local residents on the impact of the industry cluster on their house, in mitigating local opposition due to concern over declination of housing price due to the sitting of petrochemical hub.",1.0,https://www.planningmalaysia.org/index.php/pmj/article/download/1280/961427fbd86333a5340517442d9e35f3aa3cc5cd40aaae,10.2478/remav-2018-0024,Ruin Pubs in Budapest: Blessing or Curse?,2018.0,Real Estate Management and Valuation,I. Hajnal,"Abstract One of the most prominent tourist attractions in Budapest is the ruin pub district. Here, in ruined, rundown buildings, clubs that are mainly aimed at young foreigners, participants in party tourism, have sprung up like mushrooms. In Inner Erzsébetváros, the housing prices have significantly risen, since investors see the short- or long-term renting of the apartments as a good opportunity. Those who live in the district, however, find the noise of parties to be too loud, while the crowd and the dirt reduces their quality of life. The apartments located near these pubs are so-called “stigmatized properties”, since their value is shaped by the - positive or negative - opinion of the community. Using the method of hedonic analysis, this article examines the question of whether ruin pubs are a blessing or a curse to surrounding apartments, whether their effect increases or, on the contrary, decreases the apartments’ values.",1.0,https://content.sciendo.com/downloadpdf/journals/remav/26/3/article-p51.pdf428eef294febe6df66d6680721daf3b75ab6cacba65,10.1080/00036846.2024.2388308,Estimation of tax incidence in Beijing housing market,2024.0,Applied Economics,Ge-Ran Tian; Chongqi Sun; Wei-Xing Wu; Xiao Bai,"ABSTRACT Capital gains tax (CGT) in China charges 20% of the profit from home resale, exempted only if the seller owns only one home and the seller has owned it for more than five years. This work estimates how CGT is shared between seller and buyer. By calculating the price differential between similar CGT-accrued housing units and CGT-exempt housing units and estimating CGT accrued, we find that approximately 50% of CGT is in fact transferred to the buyer. It should be noted that 50% is a lower bound of actual buyer incidence due to data limitations. Appreciating, liquid, quality housing units are associated with higher tax incidence for buyers. To address non-hedonic motives to sell, it is also shown that the price differential between CGT- accrued and CGT-exempt housing units is not a result of demand for liquidity or out of market conditions. This work suggests that regulators should be prudent in utilizing such tax as tools to deter speculation in the housing market.",1.0,42927ef0dbd5725e37ff03a7aad4ac9f3ffc2e04b2b,10.22423/kreus.2023.15.2.23,"The Impact of New Town Development Plan on Apartment Prices: Focusing on the Case of Changneung District, Goyang-si",2023.0,Konkuk Research Institute of Real Estate and Urban Studies,Y. Jung; J. Jeon,"This study analyzed the effect of the announcement of new town development in Goyang Changneung district on the prices of surrounding apartments using the difference in difference model based on the Hedonic model. Research that affected the existing development of new cities in the Seoul metropolitan area was limited to the land market. Therefore, for the first time, this study analyzes the Changneung district in Goyang to analyze the impact of the new city on the surrounding apartment market. it was analyzed that the announcement had a negative effect on the price increase in the area near the Changneung district in Goyang, Seoul. On the contrary, it was analyzed that apartments located in Goyang-si had a positive effect of increasing prices unlike the Seoul influence area. Through the analysis results, it was suggested that the influence of the presentation had different effects on apartment sales prices in Seoul and Goyang, respectively.",1.0,43084b7bf33afb0d9db53c8731cb363f31c12f1a416,10.1016/j.sftr.2025.101586,"Building value: Hedonic pricing analysis of energy performance ratings and house prices in Dublin, Ireland",2026.0,Sustainable Futures,J. Clinch; C. Deegan; J. Kelly,,1.0,https://doi.org/10.1016/j.sftr.2025.101586431e6a1a7456694e4d82f53e60d41336f947a438dda,10.37956/jbes.v6i2.286,Estimation of housing prices in Ecuador using hedonic and geostatistical models: A comparative analysis,2022.0,Journal of business and entrepreneurial studies,,,1.0,https://www.journalbusinesses.com/index.php/revista/article/download/286/638432840280365ad310c2e59263058ae245276553cc36,10.18170/dvn/dhz9vy,Seattle House Prices Hedonic Model,2018.0,,戴 浩然,,1.0,433abb7fb5e60edb4e86a12cac01b1fd4aee8679c01,10.4324/9781315235134-2,The Hedonic House Price Function,2017.0,,S. Orford,,1.0,434d64e03ae20c0baa03afff75285d892dc57b793a8,10.4324/9781315743035-11,Negative environmental externalities and housing price: a Hedonic model approach,2016.0,,R. Li; Wing-Chau Kwong; Ming-Hon Li; Tat-Ho Leung,,1.0,4352fb170701e6c89f3f66a97c144a15143ec1a3cae,10.1002/pu.31087,"Brain stimulation, tDCS, and the Update",2023.0,The Brown University Psychopharmacology Update,L. Price,"T hese commentaries have never addressed studies focused on brain stimulation. Since this newsletter is about psychopharmacology, that’s not surprising. We sometimes have covered such studies in our pages, however, if they have also considered issues involving psychotropic drugs, such as: efficacy of a brain stimulation technique compared with a drug (e.g., electroconvulsive therapy [ECT] vs. ketamine in depression, in our September 2023 issue); effects of preceding drug treatment on brain stimulation treatment outcomes (e.g., prior pharmacotherapy and transcranial magnetic stimulation [TMS], covered in October 2023); use of a drug to boost brain stimulation efficacy (e.g., ketamine augmentation of ECT, July 2017); or viceversa (ECT augmentation of clozapine in schizophrenia, February 2014). This commentary concerns one of those “viceversa” studies. Before we get to that, let’s define some terms. “Brain stimulation therapy” encompasses techniques that activate or inhibit the brain with some form of energy (mostly electricity or magnetic fields, although ultrasound and intracranial light are also being investigated). Another, probably more accurate, term often used interchangeably i",0.0,436e73f6a1e55ae17fd5454f734e83e9cd883b8cdcb,10.18235/0007174,Medición de la calidad de vida en la ciudad de Guatemala y su importancia en el diseño de una política pública municipal,2014.0,,José Larios; Juan Robalino,"La ciudad de Guatemala ha crecido rápidamente y de forma desordenada, lo cual implica que no todas las zonas o los barrios de la ciudad reciben o se benefician de los servicios prestados por el gobierno municipal. A fin de determinar el impacto de la provisión o ausencia de servicios municipales en los hogares en diferentes zonas de la ciudad, estudiamos la calidad de vida en la ciudad de Guatemala de modo de ver cómo esta puede apoyar la definición de políticas públicas tanto en materia de inversión como de provisión de servicios municipales. Para ello, utilizamos dos métodos complementarios: precios hedónicos y preguntas de satisfacción. El método de precios hedónicos se basa en los precios o rentas de las viviendas para inferir la contribución de las características de los vecindarios y la ciudad sobre la calidad de vida. Para complementar este método se emplearon preguntas de satisfacción enfocadas en la vida, el vecindario y la ciudad. Al igual que en estudios previos, encontramos que la satisfacción en la vida aumenta significativamente con los ingresos, pero que el nivel de ingresos no afecta la satisfacción de vida, aun cuando la desigualdad de ingresos en la ciudad es alta",0.0,https://publications.iadb.org/publications/spanish/document/Medición-de-la-calidad-de-vida-en-la-ciudad-de-Guatemala-y-su-importancia-en-el-diseño-de-una-política-pública-municipal.pdf437c5003629ff0bd51b59df134c629afdb9ce6c8fb2,10.70675/83eb908dz3eb5z4b0az84bfz2da3dbe7e506,Three essays on housing markets and housing policies,2018.0,,Zhe-Jin Zhao,"438 Cette thèse contient trois essais empiriques sur les marchés du logement et les politiques de logement. Dans le premier essai, nous étudions les effets du contrôle des loyers sur les loyers en utilisant des données historiques de panel sur une période de 78 ans à Lyon. Nous utilisons des régressions multiples avec des effets fixes comme principale forme d’analyse. Nos résultats montrent que l’effet causal du contrôle des loyers sur les loyers à Lyon est significativement négatif. Dans le deuxième essai, j’étudie l’influence de l’âge du chef de famille sur la demande de logements grâce à des données sur les ménages en Chine. Le modèle de prix hédonique en deux étapes, utilisé dans cet essai, me permet d’estimer l’effet de l’âge du chef de famille sur la demande de logements, en contrôlant la qualité du logement et les caractéristiques des autres ménages. Les résultats montrent que la disposition à payer, à qualité constante de la maison, diminue légèrement ou reste constante lorsque le chef de famille vieillit, une fois contrôlé le niveau d’instruction du chef de famille. En revanche, il diminue rapidement si le niveau d’instruction du chef de famille n’est pas contrôlé. Par consé",0.0,https://theses.hal.science/tel-02097496v1/file/These-ZHAO-Zhejin-2018.pdf4399bbf39dfd7043e0e1a2872c7abad6d0f7f5d33bf,10.11361/journalcpij.54.1153,Impact of Disaster Risks on Rental Housing Market in Kanto Major Metropolitan Area,2019.0,Journal of the City Planning Institute of Japan,Haruki Kubota; U. Hiroi,*学生会員 東京大学大学院工学系研究科(University of Tokyo) **正会員 東京大学大学院工学系研究科(University of Tokyo) 1. 研究の背景・目的 危険な地域に市民を住まわせないよう適切な規制誘導施 策を立案することは、都市計画に期待される重要な役割の 一つである。この際、人々が災害リスクをどのように評価 するか知らなければ、効果的な取り組みを行うことは困難 である。 近年、災害リスクが不動産市場に与える影響についてヘ ドニック・アプローチを用いて分析した研究成果の蓄積が 進んでいる。中川ら 1)は東京都の賃貸住宅を対象にした分 析で、地震災害危険度が賃料を有意に下落させ、その効果 は旧築年の物件でより高くなる可能性を示した。また、直 井ら 2)は慶應義塾家計パネル調査(KHPS)の結果を用いて日 本全国における借家・持ち家住宅価格と地震リスクの関係 を分析し、地震発生確率が家賃を有意に下落させるという 結果を得た。これに対し佐藤ら 3)は、全国の不動産を対象 に地震リスク・床上浸水リスク・土砂災害リスクが不動産 価格に与える影響を分析し、市区町村レベルで災害リスク を集計した分析からは地震リスクが高いほど価格が高くな る関係を示し、公示地価の住所データを用いた分析からは 災害リスク評価が地価を下落させる効果を持つまでに高い 閾値が存在する可能性を示した。 他方で、既往研究には災害リスクの回避行動が世帯の社 会属性によって異なる可能性がうかがえる報告もいくつか 存在する。石野・瀬古 4)は東日本大震災後に家計における 自然災害への備えの意識がどのように推移したかを分析し、 世帯年収が低い家計ほど災害に対する備えの意識が低下し やすいことを示した。また、大石 5)は大阪市淀川区の単身 世帯用と家族世帯用の賃貸マンション物件それぞれヘドニ ック分析を行ない、単身世帯用物件と家族世帯用物件のヘ ドニック関数の間に顕著な違いがあることを示した。 石野・瀬古4)と大石 5)の成果から、災害リスクと不動産市 場の関係についても、年収や家族構成といった各住宅に居 住する世帯の社会属性による市場区分が存在する可能性が あると言える。しかしながら、既往研究の中に住宅の特性 とそこに住まう世帯の社会属性に注目して災害リスクと不 動産市場の関係について論じたものはなかった。 加えて、首都直下地震に関する報道や建物密度の高さな どから、東京都の賃貸住宅への移転を検討する世帯は、他 の地域の賃貸住宅への移転を検討する世帯と比べて災害リ スク回避傾向が大きくなっている可能性がある。このよう に、人々の災害リスク回避傾向を調べる際は、地域特性に よる差異の存在を念頭に置きながら分析を行うのが望まし いが、災害リスクと不動産市場の関係について分析した,0.0,https://www.jstage.jst.go.jp/article/journalcpij/54/3/54_1153/_pdf440b7a37c3fdc9ccb44fb8205496626f43ca065d0fa,10.37407/kres.2024.42.2.71,Analyses of the Three Environmental Factors Affecting Apartment Prices: Focusing on Gyeongsangnamdo,2024.0,Korea Real Estate Society,Y. Jo; Jae-Wook Park; Dong-Keun Lee,"The purpose and significance of this study is to analyze the impact of complex environmental factors on apartment prices across the country based on actual transaction prices. For this, based on the actual transaction prices of apartments in four complexes within △△ district in ○○-si, Gyeongsangnam-do, which are all affected by three environmental factors: exposure to open spaces (neighborhood parks and natural mountainous areas), exposure to Nimby facility (livestock barn), and exposure to traffic noise. The influence of each factor was estimated through three-pair two-apartment correlation analysis and hedonic modeling. Three pairs of two apartments were selected for correlation analysis, and they have the same or similar physical factors such as exclusive use area, construction year, construction company, and orientation. However, the first pair of two apartments differs only in exposure to open space. The second pair of two apartments differs only in exposure to Nimby facilities. and the final pair of two apartments differs in simultaneous exposure to both open space and traffic noise. In addition, the actual transaction prices of 300 apartments in 4 complexes were investigated",0.0,4415072f40152b58baf769c095eb24879124e8191ee,10.1007/s10901-009-9156-y,"Kauko Tom and d’Amato Maurizio (Eds.): Mass Appraisal Methods. An international perspective for property valuers, 2008, Wiley-Blackwell, pp. 319, ISBN: 978-1-4051-8097-9",2009.0,,C. Schaerer,"The book Mass Appraisal Methods—An international perspective for property valuers presents and reviews the techniques of mass appraisal that are currently used in different countries. In addition to the rather traditional techniques, it also discusses innovative and emerging methods. Aside from reviewing their relative performances, the book reveals that the development and the choice of the optimal appraisal method for property valuations should be based on criteria reflecting the particular property market environment where the valuation takes place. Indeed, due to countries’ specific institutional contexts and regulations, a mass appraisal methodology that is pertinent in a given property market situation may not be suitable for other property markets. Given that the different appraisal methods apply to different contexts, none of the proposed mass appraisal methods can be said to be more efficient than another. The different methods of mass appraisal reviewed in the book are subdivided into two groups: the traditional property valuation methods, referred to as the orthodox methods; and the emerging methods, referred to as heretic techniques. The most popular and commonly used m",0.0,44242a036736f1195f1e9a9b2a76fc8cfb8ce4b9fa6,10.15396/eres2019_51,Assessing the investment performance of residential suburbs subject to aircraft noise,2019.0,26th Annual European Real Estate Society Conference,C. Eves,"An increasingly important issue facing developing cities is the requirement for more airports or more development of existing airports to cater for the increasing level of business, leisure and tourism air travel.In several major international cities, the airport is located in residential areas that have developed after the construction of the airport, with development further from the actual airport now under aircraft flight paths. In such residential affected suburbs, the issue of aircraft noise is raised, with an emphasis on the impact on property prices and values.There have been numerous research papers addressing the impact on price based on hedonic price models, with most of these studies showing a decline in prices for affected houses, and a smaller number of studies showing that location close to a major airport can result in higher prices due to the employment opportunities provided by major airports such as Heathrow, London.Although these studies have focussed on possible decreases or increases in house prices due to aircraft noise, there have been limited studies in relation to the long-term investment performance of houses under, adjoining or in view of aircraft flight",0.0,4430b0a57d06a03b332d0b188c717eb0544e13f9340,10.15396/eres2013_32,Valuing the Risk of Imperfect Information: Christchurch Earthquake,2013.0,,Callum Logan,"Purpose - This is a background discussion and literature review relating to the application of methods to measure the impact of a significant earthquake event on house prices. The purpose of this review is to select an appropriate methodology to be applied to the assessment of earthquake impacts on Christchurch house prices. The results of this review will form part of a further research paper.Approach - Previous literature specific to hedonic modelling of earthquake events and their impact on housing is limited. Therefore, a wider review of natural disaster events and types of methodologies used are undertaken in this paper.Findings - The Christchurch earthquake land zoning process combined with government compensation that followed the 2010 earthquake is unique. The literature review suggests that a hedonic pricing modelling using a Difference-in Difference specification may be the most appropriate model for an event of this nature. Value of research - It is anticipated that the outcomes of the proposed further research will assist in the identification of risk management strategies for the insurance industry, central and local governments. This type of research also has relevanc",0.0,https://figshare.com/articles/conference_contribution/Valuing_the_Risk_of_Imperfect_Information_Christchurch_Earthquake/30132724444d62ac3975fa321d7d6d3d543757398e5c945afcd,10.32469/10355/4785,"Family structure, residential area and housing demand : evidence from micro-data for the U.S.",2007.0,,M. Kim,"Existing literatures emphasize the estimates of price and income elasticities for housing demand over the whole population. This dissertation analyzes and quantifies different responses of whole population and subgroups for housing demand categorized by family structure and residential area. Micro data for the U.S. are used to analyze the effects of family structure and residential area on tenure choice and housing demand. This data is used to model hedonic house price, tenure choice and housing demand. This dissertation presents the significant differences in the housing demand between the subgroups. First, the effect of family structure on tenure choice and housing consumption is very significant. Single person and single parent households are less likely to own their house, while couples with children are likely to consume more housing. Second, the location of households affects tenure choice significantly. The households living in the center of a big city are less likely to own than the households living small urban and rural areas. Third, each family structure has different income and price elasticities of housing demand. Single parent households are more responsive to change ",0.0,https://mospace.umsystem.edu/xmlui/bitstream/10355/4785/1/public.pdf445e9c32c6209faf427aa9659131eb00161a4e56abe,10.1080/00036846.2024.2334768,The reverse mortgage market in New Zealand: key drivers of loan determination,2024.0,Applied Economics,Norman E. Hutchison; Bryan MacGregor; T. Ngo; Graham Squires; Don J. Webber,"ABSTRACT This paper examines the drivers of loan principals in the reverse mortgage and equity release market in New Zealand using a hedonic price model (HPM) approach. Our analysis using reverse mortgages data between 2004–2021, sourced from one major reverse mortgage bank, provides four key findings. First, the term of payment for repaid reverse mortgages is positively associated with loan principals, implying that longer repayment terms allow applicants who were able to repay mortgages to borrow more. Second, there is partial evidence to suggest the presence of a positive linear impact of the value of the current property on its loan principal, in line with previous house price modelling studies. Third, older applicants (age 75+) borrow less than younger applicants, which may be due to their repaying ability. Fourth, we confirm a positive effect of interest rates on reverse mortgage amounts but reject the positive association between wider loan-to-value policy restrictions and equity release lending amounts. The results broadly highlight that the house price is more relevant than any individual characteristic of a property in determining loan principals, and that all drivers are",0.0,https://doi.org/10.1080/00036846.2024.23347684460a320b8539445f20868d08159fe3b23f0fa9aa64,10.70675/b95b9923zc4c4z45a4za28fz9f233e41403b,Social interactions and energy-efficiency investments in the building sector,2021.0,,Nathaly Cruz Garcia,"447 Les stratégies de lutte contre le changement climatique et en faveur du processus de transition énergétique soulignent l'importance de la rénovation des bâtiments dans la réduction de la consommation d'énergie mondiale et des émissions de gaz à effet de serre. Néanmoins, le potentiel de ce secteur est limité par différents facteurs identifiés notamment dans la littérature sur le Gap d'Efficacité Energétique (EEG) [Jaffe and Stavins,1994 ] [Hirst and Brown, 1990] [Allcott and Greenstone, 2012] [Gerarden et al., 2017]. Ainsi, la transition vers un parc de bâtiments plus durables est confrontée à différentes défaillances de marché et autres qui, combinées, peuvent faire obstacle aux investissements en efficacité énergétique. Dans le cas du logement collectif, les enjeux de coordination, la complexité du processus, et le positionnement des individus vis-à-vis du marché jouent un rôle supplémentaire dans les décisions d'investissement. Dans cette thèse, nous postulons que les investissements en efficacité énergétique sont affectés, d'une part, par l'écosystème des acteurs du marché de la rénovation, et d'autre part, par le fait que les individus peuvent inclure la dynamique du marché ",0.0,448d45fbe91f4dbcf8135e008d7dcadb6a059fca632,10.11113/sh.v8n4-3.1078,Determining Temporal Aggregation And Seasonality Problems In Malaysia Housing Index,2016.0,,Chin-Tiong Cheng; J. Lee; H. Ali,"Nowadays, housing index not merely act as housing performance indicator but also been transformed into financial product that based on housing index. There are two issues to be considered in this paper which are temporal aggregation and seasonality problem in housing index. Seasonality appeared in time series when the price or index movement is repetitive around the trend line. If the housing index consists of seasonal effect it will mislead measurement on real housing performance based on economic situation. In other words, cyclical effect should be avoided in measuring housing performance. Temporal aggregation in constructing house price index may lead to missing information for certain periods and variability in house price is smooth. As a result, the evaluation on housing performance becomes unrealistic. In order to investigate these problems quality adjusted index will be developed by hedonic model based on Laspeyres, Paasche, Fisher and time dummy price index formula. The case study to be investigated is housing index of double storey houses in Plentong Johor. This study found that house price index that developed from different level of temporal aggregation will lead to diff",0.0,https://sainshumanika.utm.my/index.php/sainshumanika/article/download/1078/63744916450ba2a7dfb82072fb5763d23397a048b00289,10.1177/23998083261418330,The housing market value of public transport accessibility to employment in post-pandemic England,2026.0,Environment and Planning B Urban Analytics and City Science,Michail Georgiou; N. Bailey; Annamaria Nizi; Jose Rafael Verduzco Torres,"The rise in home/hybrid working post-pandemic across multiple countries has been linked to significant shifts in housing demand away from urban centres. This paper explores evidence for this shift through changes in the value placed on public transport services in house prices. We analyse changes across 74 travel-to-work areas in England using data from 2.6 million house sales listings combined with novel measures of public transport accessibility to employment (PTAE). Multilevel hedonic models capture changes in willingness-to-pay for PTAE at the Travel-to-Work Area level with meta-analysis models used to analyse variations between and within cities. Overall, there was a reduction in willingness-to-pay for PTAE post-pandemic but this was confined to smaller cities and those with lower housing affordability. Within cities, reductions were greater in locations better served by public transport and with greater potential for home/hybrid working though the latter was also confined to smaller cities and those with lower affordability. Results align with evidence on increasing trends of counter-urbanisation in the UK and Europe and pose challenges for future sustainable urban developmen",0.0,https://doi.org/10.1177/23998083261418330450dfd836c56fd33dc021acfdf9971e3bbd78377b82,10.26871/killkanasocial.v9i1.1581,Costos de contaminación ambiental en la valoración de inmuebles en la ciudad de Cuenca: estudio de la depreciación en sectores de alta contaminación,2025.0,Revista Killkana Sociales,Wilson Fernando Cueva Vera; Fanny Cabrera-Barbecho; Juan Pablo Sarmiento Jara; Jorge Luis Palacios Riquetti,"En las metrópolis modernas, la contaminación ambiental, especialmente la generada por el tráfico vehicular, emerge como un problema crítico. Este trabajo se enfoca en la ciudad de Cuenca y explora cómo la contaminación, específicamente las emisiones de dióxido de nitrógeno (NO2), afecta el valor de las propiedades inmobiliarias. Adoptando el modelo de precios hedónicos, se utilizó un enfoque integrado para el análisis, combinando datos sobre las características estructurales de las viviendas, aspectos del entorno vecinal, y mediciones específicas de emisiones de NO2. Los resultados revelan una relación negativa y significativa entre la contaminación atmosférica y el valor de las propiedades por metro cuadrado. Asimismo, se destaca que el impacto de la contaminación varía considerablemente entre diferentes tipos de viviendas, las cuales se categorizan según su tipo, el costo del suelo y el nivel de exposición a la contaminación. Este análisis proporciona un marco para entender cómo la contaminación ambiental no solo degrada la calidad de vida, sino que también influye en el valor del mercado inmobiliario, sugiriendo la necesidad de políticas enfocadas en la mitigación de la contamin",0.0,https://killkana.ucacue.edu.ec/index.php/killkana_social/article/download/1581/1771451672272b616b4feefd55d35741ca3e516c02677c4,10.52344/hfr.2026.10.1.133,"Apartment Transaction Volume and Price Volatility: Construction and452 Application of a Transaction-Volume-Based Price Uncertainty453 Index",2026.0,Housing Finance Research,Chunil Kim,"Observed housing price volatility comprises both fundamental value changes and sampling noise arising from transaction scarcity; however, conventional indicators fail to distinguish between these two components. This study aimed to addresss this problem by constructing a novel transaction-volume-based price uncertainty index (PUI), defined as the rolling standard deviation of hedonic model residuals divided by the square root of the number of transactions. Using apartment transaction records and building registry data, a quarterly panel of 93 districts across the Seoul metropolitan area and five major metropolitan cities was constructed. The correlation between the PUI and realized volatility (RV) was only 0.38, confirming that the two indicators captured distinct information. The explanatory power of transaction volume on volatility operated through time-varying pricing noise, and the PUI significantly predicted future transaction volume changes that RV failed to capture. Asymmetric analysis revealed that additional transactions had no effect on volatility during boom periods, whereas volatility amplification was pronounced during market contractions; this asymmetry was more clear",0.0,https://www.e-hfr.org/download/download_pdf?pid=hfr-10-1-133454531226d59e644f9f5350979931980531a8c04aed,10.65864/mha53d3bsk,The Price of Regulatory Risk in Housing Markets: Evidence from Berlin,2026.0,CESifo working papers,Mathias Dolls; Clemens Fuest; David Gstrein; Carla Krolage; Florian Neumeier,"We study how regulatory risk affects housing markets in the aftermath of rent control. Our setting is Berlin, where a stringent rent cap introduced in 2020 was repealed in 2021, but was followed by continued political debate over expropriation of housing companies and further intervention. Using micro-level listing data and a hedonic difference-in-differences design comparing Berlin to other major German cities, we show that Berlin’s price-rent ratio remained 10–15 percent below its pre-intervention trend three years after repeal. To interpret this persistence, we develop a simple model in which institutional investors face greater exposure to future regulation. The model predicts lower asset prices, reduced institutional ownership, and partial crowding-in of private investors. Consistent with these predictions, we document a sharp rise in housing policy uncertainty after repeal and show that large housing companies reduced their Berlin portfolios, accepted lower sale prices, and sharply cut construction activity. The results imply that credible threats of future intervention can depress housing valuations and reshape market structure even in the absence of binding regulation.",0.0,https://www.ifo.de/sites/default/files/docbase/docs/cesifo1_wp12851.pdf455447fa1aa5275bfa2aa380a321e8296a1dffa299a,10.61173/4jbm2j10,Does the Eutrophication Control Improve People’s Utility: Evidence from the Second-Hand Housing Market and the Taihu Lake Sludge Removal Project,2024.0,Finance & Economics,Junyi Wang,"Addressing water body eutrophication often requires substantial and long-term public expenditure. However, due to the public good (PG) nature of water management policies, there is limited research estimating the level of public support for such policies. In 2020, the Chinese government implemented a closed dredging project around the Taihu Lake basin in Wuxi, creating a potential natural experiment. This paper uses second-hand housing transaction data from Wuxi from 2017 onwards. By employing revealed preference and hedonic pricing models, to construct a difference-in-differences (DID) model, the paper evaluates the causal effect of the dredging policy on second-hand housing prices in the Binhu District, aiming to reflect the impact of the dredging policy on residents. The study finds that the eutrophication dredging policy significantly increased the second-hand housing prices by 8% on average in the affected areas, though the duration of this effect appears to be limited. This research provides valuable insights into the economic effects of environmental governance policies and considerations for future water quality management decisions by governments.",0.0,https://www.deanfrancispress.com/index.php/fe/article/download/1955/1991456a14233ed745154acdd94225f1db0275e7381b56f,10.4236/jss.2020.83029,An Analysis on Influence of the Realty Rents Brought by Urban Railway System: A Case Study of Guangzhou MTR 2nd Line,2020.0,Open Journal of Social Sciences,Q. Deng,"This 457paper took 215 samples along the Guangzhou metro line 2 as an example to 458research the impact of urban rail system 459on realty rental prices. Method of hedonic price model was employed to 460calculate the range of subway influencing the surrounding reality rental. Three conclusions can be drawn 461up: 1) Metro has 462no influence on the samples of the central zone, while it contributes to 463surrounding realty rental prices increment of the peripheral area; 2) For the peripheral area, rental houses are 464influenced within 1.5 km. 465Realty rental prices have a significantly positive correlation with the 466distance of rental house away from the 467nearest subway station; 3) Average appreciation rate of monthly rents in the impact range reaches to 52.37%. Furthermore, residential monthly 468rents of house within 0.5 km, 0.5 - 1 km, and 1 - 1.5 km of 469subway stations are separately 56.9%, 49.2%, and 51% higher than monthly rents 470of houses located outside the affected area. Based on the result above, several 471points of tactic advice to generate higher return in rentals for investors and to 472rent a proper house for tenants have been put forward.",0.0,http://www.scirp.org/journal/PaperDownload.aspx?paperID=990784737bb59640e8b0c5941b5c038236ccbf2b6ff2ff0b,10.5007/2175-8085.2021.e81978,"Determinantes do preço do aluguel de apartamento residencial na cidade de Porto Alegre, Rio Grande do Sul (2020)",2021.0,Textos de Economia,Diego De Vasconcelos Souza,"O preço do aluguel residencial pode ser influenciado por diversos fatores, intrínsecos ou extrínsecos. Neste contexto, o presente artigo tem como objetivo estimar os determinantes do preço do aluguel residencial na cidade de Porto Alegre, Rio Grande do Sul. A construção teórica do artigo tem como base abordagem de preços hedônicos. A amostra utilizada contém 994 imóveis residenciais. A análise foi feita através de uma regressão múltipla estimada via estimadores robustos, sendo os determinantes utilizados: Área m2, Andar, Nº Quartos, Nº Banheiros. Vagas de Estacionamento, se o imóvel aceita animal ou não, e se o imóvel é mobiliado ou não. Os resultados encontrados corroboram com estudos anteriores, reafirmando que variáveis utilizadas no modelo estimado impactaram positivamente no preço do aluguel dos imóveis. Vale destacar que a variável mobília foi a que mais impactou no preço do aluguel, a presença de mobília impacta em 25,80% o preço do aluguel. A variável referente à permissão de animais de estimação foi a única que afetou negativamente o preço dos imóveis segundo o modelo estimado.",0.0,https://periodicos.ufsc.br/index.php/economia/article/download/81978/483704746803fe8650135bde41c935a035f4bf371779ace0,10.3846/ijspm.2025.23638,A study on house price index performance: Mix adjustment and hierarchical linear growth repeat-sales models,2025.0,International Journal of Strategic Property Management,Chung-Chang Lee; Cheng-Yen Chuang; Wen-Chih Yeh; Pei-Syuan Lin,"In this study, we examined the differences between three house price indexes constructed using hedonic price, mix adjustment, and hierarchical linear growth repeat-sales modeling. The data consisted of housing sales across 13 administrative districts in Kaohsiung City from the third quarter of 2013 to 2022. The predictions were compared using the mean standard error, mean absolute percentage error, mean absolute error, and root-mean-square error. The results revealed that the hedonic price index performed the best; its prediction scores, as reflected by the four aforementioned metrics were 0.072, 1.176, 0.181, and 0.181, respectively. The index with the second best performance was the mix adjustment model, with scores of 0.154, 1.905, 0.293, and 0.293. The worst-performing index was the repeat-sales model, with scores of 0.309, 2.804, 0.439, and 0.439. After comparing the annual prediction errors of the three models, it became apparent that the hedonic price index had the best performance, followed by the mix adjustment index, and then the hierarchical linear growth repeat-sales index.",0.0,https://journals.vilniustech.lt/index.php/IJSPM/article/download/23638/12856475f0d5e67adfb32d53ffee933112b354c3e46ab6a7,10.1051/e3sconf/202561801004,A study of the impact of the resource thermal power plants with ‘de-industrialised design’ on the NIMBY effect,2025.0,E3S Web of Conferences,Qiuyang Li; Rui-Feng Tian,"The construction of the resource thermal power plant has negative impacts on the surrounding residents and it causes the NIMBY effect. The “de-industrialized” design can alleviate the NIMBY effect of the power plant to a certain extent. This paper quantifies the degree of impact of resource thermal power plant with“de-industrialization design” to the NIMBY effect from the perspective of housing prices. It takes Shenzhen Eastern Energy Eco-Park as example to analyze the changes in price of the Second-hand Properties around Power Plants by Hedonic-Price Models and Kriging Interpolations. The results of the study show that the resource thermal power plants with ‘de-industrialised design’ can effectively mitigate the NIMBY effect. Within a certain range, the magnitude of the impact decreases with distance. So it is suggested that the construction of the resource thermal power plant should be adapted to the local conditions, and the application of the “de-industrialization” design should be used to improve the acceptance of the residents of the plan to create a good human environment.",0.0,https://doi.org/10.1051/e3sconf/202561801004476636b1788d572877a163b21c5dd25ade6a7f74b29,10.18361/2176-8366/rara.v8n2p128-143,IMPACTOS DOS ATRIBUTOS NA PRECIFICAÇÃO DE IMÓVEIS RESIDENCIAIS DE MOSSORÓ/RN A LUZ DO MODELO HEDÔNICO,2016.0,,Fábio Chaves Nobre; Adail José de Sousa; Eduardo Vieira do Prado; L. Nazareth; Daniel Basso Polezi; M. I. Montebello,"Trata-se de estudo transversal que tem por objetivo avaliar as caracteristicas do imovel e estimar a influencia das caracteristicas no seu valor, como destaca o sistema de precos hedonicos. O universo compoe-se dos imoveis da cidade de Mossoro/RN e foram utilizados dados secundarios, com base nos registros disponibilizados pelo site www. mossoro imoveis com. br no ano de 2012. A pesquisa abrange uma amostra dos bairros de Mossoro/R com 512 imoveis diversos que se compoe em apartamentos, casas e casas duplex de diferentes tamanhos, , a amostra 111 unidades residenciais. Foi realizada a regressao multipla com a utilizacao do procedimento Stepwise. Os resultados apontam que as variaveis “numeros de suites” e “numeros de quartos”, o “tamanho do imovel” e “numeros de quartos”, bem como, o “tamanho do imovel” e “numeros de suites” evidenciaram forte correlacao positiva entre si. Outro resultado e o preco do imovel (variavel dependente) esta diretamente correlacionado com as demais variaveis (independente) estudadas, agregando valor aos imoveis.",0.0,https://doi.org/10.18361/2176-8366/rara.v8n2p128-1434775e86be2f1dcb54aa7364538ff75ad2281d35a673,10.35808/ersj/1538,A Hybrid Property Pricing Model: The Case of Apartment Residents in Jakarta Indonesia,2020.0,EUROPEAN RESEARCH STUDIES JOURNAL,Eris Sudariswan; E. T. Sule; Sucherly; Sulaeman Rahman,"Purpose: This research initiates a property pricing model that involves various perspectives and consumer considerations in selecting properties, including aspects of sales comparison, investment, hedonic life style, brand equity, and digital life style. Design/Methodology/Approach: The study investigates 222 residents of middle class apartments in Jabotadebek (Great Jakarta). The study employs Structural Equation Modelling (SEM) to test the research hypotheses. Findings: The research found that the price of apartments in the region is strongly influenced by a combination of multi aspects of sales comparison, investment, hedonic life style, brand equity, and digital life style. Practical Implications: The research has implications for investment shows the weakest contribution to the apartment price. Originality/Value: This study found that the price of apartments in the region is strongly influenced by a combination of multi aspects of sales comparison, investment, hedonic life style, brand equity, and digital life style.",0.0,https://www.ersj.eu/journal/1538/download47886b8521d3a99f193f08be234733ca2c586408989,10.15396/eres2019_111,The value of energy efficient housing - is there an incentive to make houses more energy efficient?,2019.0,26th Annual European Real Estate Society Conference,G. Maier,"The basic question of this paper is the following: 'Do energy efficient appartments generate higher rents for their owners than comparable appartments with lower levels of energy efficiency?' This is an important question for environmental policy because if it is ansered positively, it generates an economic incentive for landlords to invest into the energy efficiency of buildings. We use data from the EU-SILC survey for Austria and a hedonic price approach to determine the marginal rent of more energy efficiency (measured in the form of lower heating costs). In this paper we revisit a topic that we have already discussed in a presentation eight years ago. At that time the results were very disappointing. The analysis produced a significant coefficient but with the reverse than expected sign. In the meantime, more waves of the EU-SILC survey have become available and the pool of respondents has been turned over. This allows us to revisit this question and to produce an answer with more empirical support.",0.0,https://eres.architexturez.net/system/files/P_20190708153657_8664.pdf479033fac32027cbb4440e5d28f6e08e5f48854ac0d,10.36253/techne-12870,The regenerative project for hybrid evolutionary buildings’ Active Resilience Convertibility Enhancement,2022.0,Techne : Journal of Technology for Architecture and Environment,Giulia Vignati; G. Pozzi; Leopoldo Sdino; Marta Dell'Ovo; E. Ginelli,"This paper deals with the enhancement of the project for the intervention on existing disused buildings with three sequential objectives: converting tertiary buildings to the hybrid housing function; regenerating buildings, providing them with continuous transformative capacity and making them functionally convertible; providing a housing model of temporary uage duration, according to the principle of House as a Service. Considering the temporal variable, the proposal defines criteria that guide the reconversion of buildings in relation to the dynamic needs of the different categories of users and stakeholders who are involved in the decision-making process and, through the hedonic price method, investigates the influence that the qualities attributed to the performance of the building have on the formation of their value, highlighting the perception of value and the acceptance of green performances.",0.0,https://oaj.fupress.net/index.php/techne/article/download/12870/11327480c646465e9f77eefafb4c78dcbe542c8db4feabd4,10.1108/ijhma-04-2023-0055,"Impact of decentralized long-term rental apartments on the value of community housing--taking Tianjin, China, as an example",2023.0,International Journal of Housing Markets and Analysis,Guang-Ping Liu; Guo Zhang,"481Purpose482This study aims to explore the impact of decentralized long-term rental apartments on the value of in-community housing from two perspectives of housing price and rent.483484485Design/methodology/approach486This study uses the hedonic model to identify the factors affecting the housing value, and the influence of distributed long-rented apartments on the housing value in the community is analyzed from two aspects of housing price and rent by using the ordinary least square method and propensity score matching method.487488489Findings490The primary finding indicates that decentralized long-term rental apartments increase housing prices while decreasing general rental housing rents in the community, with the average degree of increase ranging from 0.93% to 2.59% and the average degree of decrease ranging from 2.23% to 4.34%. According to additional research, the prices of houses within communities rise by 0.042% for every 1% increase in the share of decentralized long-term rentals, while the rents for other types of rental property fall by 0.162%.491492493Practical implications494The government can regulate the housing market by regulating the access and layout of distributed long-rent apartments.495",0.0,496a8dc6e5d1f57e3ecbb8de52c7d58727bfcb7784c,10.1080/09599916.2024.2339813,"Changes in risk appreciation, and short memory of house buyers when the market is hot, a case study of Christchurch, New Zealand",2023.0,Journal of Property Research,E. Mendoza; Fabian Dunker; M. Reale,"ABSTRACT In this paper, house prices in Christchurch are analysed over three distinct periods of time: post-2011 earthquake, pre-COVID-19 lockdown, and post-COVID-19 lockdown. The first method used is the well-established hedonic price model, additionally a second method incorporates random effects into the model to capture unobserved heterogeneity in buyers’ preferences for certain features of a house. Results show that buyers, in periods that are temporally distant from the 2011 Christchurch earthquake, underappreciate the risk of potential earthquake damage to a property. We find that there are observable shifts in buyer preference across the different time periods, specifically in terms of section size. We also examine heterogeneity and correlations in buyers’ preferences for floor area, land area, and age of a property.",0.0,http://dx.doi.org/10.1080/09599916.2024.23398134976481f1f8d65c07367d4022422049962c3c9f8f0c,10.5194/agile-giss-6-18-2025,Characterising neighbourhood dynamics through social media anlaysis and house sales transactions,2025.0,Agile Conference,Alexis J. Comber; Molly Asher; Yiyu Wang; Minh Kieu; Quang-Thanh Bui; T. Nguyen; P. Hoang; Nick Malleson,"Abstract. This paper describes a two stage approach for identifying neighbourhood areas that may be undergoing gentrification related changes. It summarises classic hedonic house price data over time (2014–2023) for each neighbourhood, and compares neighbourhood average price with those of local nearby areas. This enables neighbourhoods experiencing high relative increases in price to be identified as potentially gentrifying areas. Social media data for these areas were extracted and analysed using a large language model which scored each individual social media post by the degree to which their content indicated that the neighbourhood is experiencing change, potentially providing confirmatory evidence or not of gentrification. A number of areas of further work are identified.498",0.0,https://doi.org/10.5194/agile-giss-6-18-20254995ad1c5878e340e91ed961ab6a35a6161756fbdd0,10.1108/ijhma-09-2024-0134,The impact of the COVID-19 market shock on residential buyer preferences,2024.0,International Journal of Housing Markets and Analysis,Christopher N. Cain; Daniel Huerta; Norman Maynard; Bennie D. Waller,"500Purpose501This paper aims to investigate the effect of the COVID-19 pandemic market shock on house pricing, time-on-market (TOM) and probability-of-sale functions using local multiple listing service data from Richmond, Virginia, USA.502503504Design/methodology/approach505The empirical analyses use a two-stage residual inclusion model to simultaneously address endogeneity and nonlinearity in modeling sales price and TOM, and a Heckman two-stage procedure to account for sample selection bias in estimating the probability-of-sale.506507508Findings509The pandemic shock not only directly impacted average home prices, TOM and probability-of-sale, but it also caused the coefficients of some of the factors that influence these metrics to change while others were stable to the exogenous shock of the pandemic. The authors find that coefficients in the hedonic pricing, TOM and probability-of-sale models did not shift instantaneously; instead, the impact evolved over several months at the beginning of the pandemic until stabilization.510511512Originality/value513The results should be of interest to buyers and sellers of residential properties, agents specializing in residential properties and researchers looking to b",0.0,51490d6296abb636382aad54ee7be58c96bd3083519,10.24201/ee.v20i2.163,Contaminantes locales malolientes y valores de propiedades residenciales: un análisis hedónico de cuatro ciudades del Condado de Orange (California),2005.0,Estudios Económicos de El Colegio de México,Jean-Daniel Saphores; Ismael Aguilar Benítez,Proponemos un enfoque que combina el uso de sistemas de información geográficos (GIS) y el método de regresión hedónica para evaluar el impacto de los malos olores producidos por la industria local en el precio de viviendas en cuatro ciudades del sur de California. Al utilizar GIS se identificaron las viviendas localizadas a diferentes distancias de talleres automotrices y plantas contaminantes. Resultados estadísticamente significativos indican que los precios de las casas se reducen hasta en un 3.4% debido a la contaminación del aire. Este resultado tiene importantes implicaciones para el diseño de políticas de control de emisiones industriales.,0.0,https://estudioseconomicos.colmex.mx/index.php/economicos/article/download/163/165515dda7c152f667a493da84064be856365a57a8e8b9,10.53383/100370,Aging City and House Prices: Impact of Aging Condominium Stock on the Housing Market in the Tokyo- Metropolitan Area,2023.0,International Real Estate Review,Masayuki Nakagawa; C. Shimizu,"Based on an analysis of the housing market in the Tokyo metropolitan area, this study focuses on the external diseconomies of aging condominiums. It is possible that the quality of the condominium stock deteriorates more rapidly than that of ordinary housing. This deterioration in quality leads to a reduction in the quality of housing services received by residents. Furthermore, this worsening of the residential environment may lead to external diseconomies. We run hedonic models to identify the external diseconomies of aging condominiums in the residential market of the Tokyo metropolitan area. The results of our estimated models indicate that such external diseconomies occur for detached housing in areas where detached houses and condominiums coexist. These external diseconomies exert downward pressure on prices. Specifically, detached housing prices are lowered by around 3.2% for each 1% increase in the proportion of total building floor area in neighborhoods where condominiums were built before 1990. In other words, aging condominiums begin to generate diseconomies in their vicinities approximately 20 years after they were built.",0.0,516bf21046a0230c693f3d63aa0c0d68175c4934aa3,10.30845/jbep.v8n2p1,Mismeasurement of Housing Services in the Pandemic,2021.0,Journal of Business & Economic Policy,P. D'Antonio,"The 2020 COVID-19 pandemic has brought to light a flaw in the accounting and pricing of housing services in517consumer spending (PCE) and the consumer price index (CPI). The dramatic shifts in housing usage caused by the518pandemic have not registered at all in PCE. This paper takes a fresh look at the use of opportunity costs to measure519housing services. It shows how the current gauge can miss real changes in services flows. The paper proposes that520housing services be measured instead by hedonic methods, using new survey questions added to the Consumer521Expenditure Survey (CES) and the CPI",0.0,https://jbep.thebrpi.org/journals/Vol_8_No_2_June_2021/1.pdf52273ce45f1c8beb34fc288b6e7e99a78f64f4e05f7,10.37407/kres.2022.40.3.75,The Effect of 2030 Housing Project for Young People on Nearby Housing Prices,2022.0,Korea Real Estate Society,Gi-hun Lee; Kang-Rae Ma,"It has been proven from the previous research that rising housing prices affect not only timing of the first marriage, but also family planning of young people. In response to housing shortage for young people, the Seoul Metropolitan Government came up with ‘the 2030 Housing Project for young people’ designed to supply social rental housing to young people in areas close to subway station. However, the project had been faced with the opposition from the nearby residents who are concerned with a decline of property value. 523The main purpose of this study is to analyze the impact of the 2030 Housing Project for young people on the nearby housing prices using a hedonic-based difference-in-difference analysis. The main finding of this research is that the supply of the 2030 Housing Project for young people has a negative effect on the nearby housing prices at first, and then turned into a positive effect over time. Such a result might be related to the fact that young people have a key role to play in fostering local economies and vitalizing commercial districts in the community.",0.0,52431e4d7cc7597aa4c29e9b8b07db00cea4522bf07,10.22313/reik.2022.20.3.203,A Study on the Factors of Rising in Apartment price: Focused on Jeju Special Self-Governing Province,2022.0,Residential Environment Institute Of Korea,Young-Jun Yang,"This study analyzed the factors of price rise in apartments traded in Jeju Special Self-Governing Province from 2019 to 2021 using the Hedonic price model. There are 486 apartments subject to analysis and 526 types based on area. In 2019, 2026 transaction cases were applicable, and in 2021, 2907 transactions were applicable. In summary, the high price increase rate is based on the size of the exclusively used area, whether large, medium or small. The larger the remaining building-to-land ratios and the longer the elapsed years, the better the return on reconstruction can be expected, indicating that the high price rise rate. The higher the number of households, the higher price rise rate. In addition, the price rising rate of entrust management apartments is higher than that of the autonomous management apartments. Compared to the Dong area of Jeju-si, the price increase rate of apartments in the Dong area of Seogwipo-si is the lowest, followed by Eup·Myeon area of Seogwipo-si. It was analyzed that the farther away from the market, the lower the price rise rate.",0.0,5259cbbab3049e758845d304b20e1b79c767c9c518c,10.54097/ijeh.v4i2.1529,The Influence of Policy for School District Housing,2022.0,International Journal of Education and Humanities,Xiaohan Zhang,"High rate of housing price of school district house has led to serious social phenomena such as buying a house for school, which increase the financial burden of some families. Thus, in order to relief those phenomena, government impose some policies. This paper used Hedonic Price Model to test what factor will affect housing price change and use dummy variable to test whether the policy is efficiency. The results show a 12.8% decrease in the rate of change from school district houses to regular houses.",0.0,https://drpress.org/ojs/index.php/ijeh/article/download/1529/15585262f318628db92fce923a15e7097c70c30bbbe9474,10.31908/grafias.v0i19.1470,Efecto de la distancia al acceso de trasporte masivo megabús sobre el valor de la propiedad en la zona sub-centro del barrio cuba,2012.0,Grafías disciplinares de la UCPR,Laddy Katherin Quintero García; Leidy Johana Rivera Grajales; Nury Marín Berrío,"En este documento se pretende analizar cuál es el efecto de la distancia al acceso de transporte masivo “Megabús” sobre el valor de la propiedad en la zona sub centro Cuba (Pereira); la metodología empleada es la de precios hedónicos, ya que esta reúne los diferentes atributos de la vivienda que determinan su valor en el mercado. Se concluye que el sistema de transporte masivo Megabús genera externalidades que hacen especular a los propietarios sobre la valorización de los predios.",0.0,https://revistas.ucp.edu.co/index.php/grafias/article/download/1470/14765275ccbd6be6e707fff68fcc3a8c75830f909304004,10.54091/krepa.2025.26.2.158,The Impact of Green Building Certification(G-SEED) of Apartments on Transaction Prices,2025.0,Korea Real Estate Policy Association,S.-H. Bae; Byungkyoo Jeon; Hyungkyoo Kim,"This study analyzes the actual transaction prices of apartments with and without green building certification located in the Seoul Metropolitan Area over a three-year period from 2021 to 2023. Employing an independent samples t-test and hedonic price models, we quantitatively assessed the effect of green building certification on apartment prices and examined annual variations. The results indicate that in general green building certification has a statistically significant positive impact, Our findings suggest that certification can influence how market participants perceive and evaluate property value, although its impact may be attenuated under conditions of heightened market uncertainty. This study offers empirical evidence of the market value of green building certification and underscores the need for policy measures to sustain its effectiveness across market cycles.",0.0,52843c23442058a0195604af9e5f00d0be406723522,10.1111/ehr.70088,"Measuring the interwar housing boom: House prices and rents in England, 1913–39",2026.0,The Economic History Review,Antoninus M. Samy,"529 Existing statistics about England's interwar housing market are sparse and based on outdated sources and methods. This article seeks to improve upon them by drawing on mortgage data from a major London‐based building society and using the hedonic method of price index measurement to construct house price and rent indices for residential houses that are robust to intertemporal sampling differences. It is found that house prices and rents in England both rose significantly between 1919 and 1926 but moderated thereafter and declined throughout the 1930s housing boom. Further evidence indicates that there was excess supply in the housing market during the boom, driven by cheap money and a deliberate strategy by building societies of ‘making the market’ by fuelling private house construction.",0.0,5300be4a3931ac33c8d0aa23ef9660c3c8ea28c41c7,10.29121/ijetmr.v8.i1.2021.849,"AN ANALYSIS OF COMMON APPLICATIONS ON HEDONIC PRICING MODEL IN VALUING ECOSYSTEM SERVICES: SIMILARITIES AND DIFFERENCE BETWEEN EUROPE, US, AND CHINA",2021.0,,Xuan Zhang,"The study made a comparison with the common applications on the hedonic pricing model that valuing ecosystem services between Europe, the United States, and China. By analyzing various reasons impacting housing prices, cultural and historical backgrounds played roles in the real-world applications.",0.0,https://www.granthaalayahpublication.org/ijetmr-ojms/index.php/ijetmr/article/download/IJETMR21_A01_2505/705531e9a02d61989547662ea5aa06c195e4dd5fe044a5,10.15396/eres2013_182,A Hedonic Model of House Prices in the Greek Islands,2013.0,,Dimitra Kavarnou; Anupam Nanda; Sotiris Tsolacos,,0.0,https://eres.architexturez.net/system/files/pdf/eres2013_182.content.03428.pdf5321aaa8e934d42c945f9880796705cdce7b8fecea9,10.2139/ssrn.2841734,The Hedonic Housing Price Index For Poland – Modelling on NBP BaRN Data,2014.0,,Marta Widłak,,0.0,https://doi.org/10.2139/ssrn.28417345337c12a9637ff27f08d70bb302dbc921076dda88c4,10.19172/kreaa.24.1.4,Spatio-temporal dependence in a hedonic house price model,2018.0,,Dongwoo Hyun,,0.0,5341937b683a495134a543a3557ef595ac54491948c,10.14445/22315373/ijmtt-v56p527,Development of Mathematical Modeling using Hedonic Price Method to Establish Relation between Housing Price and Air Pollution,2018.0,,R. Yadav; Magan Grover,,0.0,535066ac27074c172c571a2e49aedd294be24f80b38,10.1007/978-981-16-3587-8_51,"The Analysis of Second-Hand Housing Prices in Jiangmen City, Based on Semi-structured Interview and Hedonic Model",2021.0,Proceedings of the 25th International Symposium on Advancement of Construction Management and Real Estate,J. Liao,,0.0,536559f5a0be29385181368bf25513d2969cd4a4397,10.26118/5792.2025.66.34.006,Hedonic pricing as a tool for analyzing price differentiation in the secondary housing market (regional perspective),2026.0,"СБОРНИК МАТЕРИАЛОВ XXXXII МЕЖДУНАРОДНОЙ НАУЧНО-ПРАКТИЧЕСКОЙ КОНФЕРЕНЦИИ «Развитие науки и практики в глобально меняющемся мире в условиях рисков» (шифр –МКРНП) 16 декабря 2025г., г. Москва",Ю. Ю. Казанцев; A. Samuseva,,0.0,5373c72e72b55a4ca070873d9ffdd425dbb521c7db7,10.15396/eres2022_111,The hedonic house price index for Poland in years 1996-2021,2022.0,28th Annual European Real Estate Society Conference,R. Trojanek,,0.0,538b28e4c322c0b376810e95bff886bda3dec8a683e,10.1016/j.compenvurbsys.2009.10.007,"Integrating lidar, GIS and hedonic price modeling to measure amenity values in urban beach residential property markets",2010.0,"Computers, Environment and Urban Systems",S. Hamilton; Ash Morgan,,104.0,http://libres.uncg.edu/ir/asu/f/Morgan_Ashton_2010_Integrating_Lidar_GIS_Hedonic.pdf53955d4a458373c49e75daaea02131c23ea61886693,10.1016/0140-9883(86)90011-3,Housing market capitalization of thermal integrity,1986.0,,J. Laquatra,"Abstract The extent to which housing markets capitalize investments in energy efficiency is important to observe. The uncertainty now associated with this process can lead households to allocate resources inefficiently in the production of thermal comfort, by substituting more fuel inputs for less capital. From a policy perspective, the end result of this is the continued construction of units in the housing stock with sub-optimal levels of energy efficiency. This study is a cross-sectional analysis of houses constructed through the Energy Efficient Housing Demonstration Program of the Minnesota Housing Finance Agency. Values of investments in energy efficiency are derived from a hedonic regression which includes a vector of thermal integrity factors as an independent variable.",71.0,https://www.sciencedirect.com/science/article/pii/0140988386900113/pdf540668f045adfd0488efe88950eac2f8843da52c7ec,10.1177/0042098011429486,"A Spatial Hedonic Analysis of the Value of Urban Land Cover in the Multifamily Housing Market in Los Angeles, CA",2012.0,,Wei Li; J. Saphores,,50.0,5412db3ff90fef8790d00b80b5962cdd08304f33637,10.1068/b38093,Local Hedonic House-Price Modelling for Urban Planners: Advantages of Using Local Regression Techniques,2013.0,,R. Crespo; A. Grêt-Regamey,,48.0,5425286e629bbf1b4ef8286132cbf7dd5ae979b923a,10.1016/j.econmod.2019.03.011,"Art in Africa: Hedonic price analysis of the South African fine art auction market, 2009–2014",2020.0,,J. Fedderke; Kai Li,"Abstract Real asset markets are characterized by illiquidity and heterogeneous assets, presenting challenges to price estimators. Use of a new dataset of 7,553 auction fine art lots brought to market in South Africa, for 2009–14, allows us to examine the full sales hedonic price estimator over a wide set of characteristics. Results validate full sale hedonic pricing: Identities of artists, medium and genre, dating characteristics, and physical characteristics of artwork are significant. External validity of hedonic pricing is supported by out-of-sample price prediction for 40 individual artists. Auction house catalogue presentation of art work also proves correlated with realized auction prices. Art as an asset finds support: art prices move countercyclically with GDP and domestic equity markets, pro-cyclically with off-shore equity markets, implying a risk diversification role. JEL Codes: D1, L8. Keywords: hedonic price equation, art market, South Africa Word Count: 9467 (including all Tables, Figures, References).",32.0,5436755b33aebe85f33284871490a049fe4f6f9d9d2,10.1007/s00181-011-0485-9,Nonparametric neural network modeling of hedonic prices in the housing market,2011.0,Empirical Economics,M. Landajo; C. Bilbao; A. Bilbao,"This article addresses the contribution to hedonic modeling of a nonparametric approach based on artificial neural network (ANN) regressions. ANNs provide consistent estimates for the hedonic price of each attribute and permit a number of hypotheses on the hedonic price relationship to be tested nonparametrically. In particular, we exploit results by Stinchcombe and White (Econom Theory 14:295–324, 1998) in order to carry out misspecification testing in linear and semiloglinear hedonic models. The same approach directly applies to testing misspecification of any parametric specification for the hedonic relationship. A nonparametric significance test for the variables in the hedonic model is also proposed. The test extends the approach developed by Racine (J Bus Econ Stat 15(3):369–378, 1997) in kernel-based nonparametric testing to ANN-based inference. The finite sample performance of the proposed tests is analyzed through Monte Carlo experiments, and simulation-based algorithms for computation of the null distribution of the tests are proposed. Then, the performance of three classes of regression models—linear, semi-log, and ANNs—applied to hedonic price modeling in a Spanish regi",28.0,http://hdl.handle.net/10651/710454445534596a3dd27c2a8412e2bf1c3524a7f490b2b,10.1016/j.scs.2018.05.022,How residential compactness and attractiveness can be shaped by environmental amenities in an industrial city?,2018.0,Sustainable cities and society,B. Mondal; Dipendra Nath Das,"Abstract At a time when rapid urbanization and environmental degradation continue to be serious issues of concern, there is an escalating need to promote sustainable living across the world, with due emphasis on environmental amenities. The economic value of these amenities cannot be overlooked either, as they are inevitable in undertaking compact city plan. However, due to inadequate understanding of economic and aesthetic value of environmental amenities developers, decision-makers and policy makers ignored its importance, resulting in massive exploitation. This study conducted in the city of Ahmedabad in India, explores the significance of local environmental amenities and residential attractiveness to elicit an urban expansion pattern. The geographically weighted hedonic regression is employed in this research to estimate the value of local amenities and spatial clustering is used to examine the environment induced residential pattern. Outcome shows that in addition to structural attributes, local residents are willing to pay for LST, NDVI, air quality, and tree cover, in spite of these services being exceedingly location-specific. Besides, widespread residential spillover is o",26.0,545e30104e7ef08f7b1c21960e51befeb5b10faf3b9,10.1016/j.sbspro.2016.05.497,"Measuring Structural, Location and Environmental Effects: A Hedonic Analysis of Housing Market in Wroclaw, Poland☆",2016.0,,Magdalena Ligus; Piotr Peternek,"Abstract This study aimed to investigate the home-buyers’ preferences and assess marginal values of improvements in structural, location and environmental attributes for Wroclaw, Poland. The AMRON database of Polish Banks Association is used with observations between 2013-2014 years. The GIS technique is applied for implementation to the database location and environmental attributes. Results of the hedonic regression analysis for linear, semi-log and model with Box-Cox transformation give good explanatory power (adjusted R square more than 0,7). Most of structural and location attributes occurred statistically significant with expected signs of influence on prices, nevertheless analyzed environmental attributes occurred to be statistically insignificant.",26.0,https://www.sciencedirect.com/science/article/pii/S1877042816305985/pdf546da7effef3a32d52f3b378ea61e8580591f12254c,10.1590/s1413-80502007000200004,Avaliação de imóveis: a importância dos vizinhos no caso de Recife,2007.0,,Rubens Alves Dantas; A. Magalhães; José Raimundo de Oliveira Vergolino,"Traditionally, in the assessment of real state values it is assumed that the observations are independent. However, data associated with the position that they occupy in the space are characterized by the spatial dependence. Following the recent international literature, this paper recognizes the importance of the space and shows how it can be incorporated in the specification of hedonic model at the same time it analyzes the real state market of the city of Recife. The data for the empirical test are derived from the IBGE Demographic Census (2000) and from the Caixa Economica Federal database. The results indicate that considering space with base in distances to influence poles is not enough to completely explain the price variations in relation to the location, once there is a true interaction among the data, so that each building influences its neighbors' price. This means that, contrary to the traditional models hypothesis, the apartment transactions do not occur in an independent fashion. The solution for this problem is to estimate the model using the spatial econometric tools and taking into consideration all possible spatial interactions in the data.",19.0,https://www.scielo.br/j/ecoa/a/RQyK5WbPJhhXtkmD5dy4TWb/?lang=pt&format=pdf5475be5e3ecc7dc58a071c4cdd27c791610b4a69d44,10.2139/ssrn.1313693,Flexible Spatial and Temporal Hedonic Price Indexes for Housing in the Presence of Missing Data,2008.0,,R. Hill; Daniel Melser; Iqbal A. Syed,,16.0,https://doi.org/10.2139/ssrn.1313693548dbd9f52fd5e148e861110627905494c38f0d5068,10.1016/j.landusepol.2017.12.045,Does where you live influence your socio-economic status?,2018.0,,Tony Lockwood; N. Coffee; Peter Rossini; T. Niyonsenga; S. McGreal,"Abstract The relationship between the wellbeing of society and understanding of land market structure and behaviour is an important research theme for understanding socioeconomic status (SES). Traditional SES area based measures of income, occupation and education are generally applied in the examination of a broad spectrum of societal issues. This paper examines the contribution of understanding the spatial variation of SES based upon residential property sales data unrestricted by the traditional artificial geographic boundaries in which SES is assumed uniform. Originality lies in identifying the locational component of residential property wealth as a proxy for SES. It includes market behavioural characteristics that reflect both the context and composition at particular locations. This provides a broader understanding of SES than income, occupation and education. The analysis uses a hedonic regression model based on transactions of detached housing. The model is specified using only available property attributes as independent variables and is therefore blind to location.. The residuals from this hedonic model are used to calculate the relative location factor (RLF) for each tr",15.0,https://pure.ulster.ac.uk/en/publications/4defec39-0f32-46ec-9d8f-a445bdb55efa5495478d72ee4159711f4ccdfa9e3f81d76fa9a9858,10.1111/jors.12162,Residential Sorting and Environmental Externalities: the Case of Non-linearities and Stigma in Aviation Noise Values,2015.0,Social Science Research Network,Sotirios Thanos; A. Bristow; M. Wardman,"type=""main""> This paper explores the sorting process in response to differing levels of aviation noise exposure in a housing market. Spatiotemporal hedonic pricing (HP) and stated choice (SC) results reflect nonlinearities and stigma. The HP models reveal nonlinear noise depreciation increasing from 0.40 to 2.38 percent per decibel as noise increases, while the SC noise values are lower in an area with high long-term noise exposure. These nonlinearities are attributed to the spatial sorting of noise tolerant individuals. HP results from the same “noisy” area show a “stigma” from noise during the first year after the complete removal of aviation noise.",14.0,https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/jors.1216255024822ae2a93f1303b44de60033d420a7ed3883d4,10.2139/ssrn.4466492,Quality Adjustment at Scale: Hedonic vs. Exact Demand-Based Price Indices,2023.0,Social Science Research Network,Gabriel Ehrlich; J. Haltiwanger; Ron S. Jarmin; David Johnson; E. Olivares; Luke Pardue; M. Shapiro; L. Zhao,"This paper explores alternative methods for adjusting price indices for quality change at scale. These methods can be applied to large-scale item-level transactions data that includes information on prices, quantities, and item attributes. The hedonic methods can take into account the changing valuations of both observable and unobservable characteristics in the presence of product turnover. The paper also considers demand-based approaches that take into account changing product quality from product turnover and changing appeal of continuing products. The paper provides evidence of substantial quality-adjustment in prices for a wide range of goods, including both high-tech consumer products and food products. ∗Ehrlich: University of Michigan; Haltiwanger: University of Maryland and NBER; Jarmin: U.S. Census Bureau; Johnson: University of Michigan and National Academies of Sciences, Engineering and Medicine; Olivares: University of Maryland; Pardue: University of Maryland and Gusto; Shapiro: University of Michigan and NBER; Zhao: Bank of Canada and University of Maryland. Luke Pardue and Laura Zhao worked on this project as doctoral students at the University of Maryland (and Laura ",12.0,https://doi.org/10.2139/ssrn.4466492551259691c3c6d22570f891346ba4a60239cd3de4ae,10.1017/s1355770x18000542,Are land values related to ambient air pollution levels? Hedonic evidence from Mexico City,2019.0,Environment and Development Economics,L. Chakraborti; D. Heres; D. Hernandez,"Abstract This article investigates whether residents of Mexico City value air quality. Our results suggest that air quality improvement in PM10 is equivalent to a marginal willingness to pay (MWTP) of US$440.31 per property for the period 2006–2013. The corresponding MWTP for PM2.5 is US$880.63, for O3 is US$623.78, and for SO2 is as much as US$2091.50. These estimates are considerably larger in magnitude compared to the few other studies in similar settings. As a percentage of annual household income, these represent 2.44 per cent for PM10, 4.88 per cent for PM2.5, 3.46 per cent for O3 and 11.59 per cent for SO2. Our estimates of land value–pollution elasticities for PM10 (−0.26 and − 0.58) are within range of hedonic estimates for total suspended particulate matter in US cities around the 1970s. The corresponding elasticities range from − 0.55 to − 0.84 for PM2.5, from − 0.06 to − 0.49 for O3 and from − 0.11 to − 0.34 for SO2.",12.0,552580b976304e7483e7fa6141851796e9cab03fc45,10.1177/0042098019895774,What’s so special about character?,2020.0,,M. Fernandez; Shane L. Martin,"Special Character Areas (SCAs) in Auckland, New Zealand, are areas with distinctive aesthetic, physical and visual qualities. Preservation policies entail controls on the design and appearance of new buildings, and on demolition, additions and alterations to existing buildings. To promote densification of the city, the Auckland Unitary Plan (AUP) removed SCA preservation rules in certain areas. This article assesses the trade-off between SCA preservation and housing development. We employ hedonic prices models to about 85,000 sale transactions between 2012 and 2016 and find that in 2012, the SCA price premium was 11.4% whereas the premium on upzoned properties (those with increased development allowances under the AUP) was zero. Over time, the SCA premium decreases, and by 2016 it was down to about 4.3%. At the same time, upzoning premiums increased to about 5% in 2016. These results reveal a demand shift from the protections of SCA towards flexibility on the development options of land.",11.0,553ec91d407567c6eda16be3e8788f2ee2b70efe006,10.1016/j.jhe.2021.101764,The illusion of a hedonic price function: Nonparametric interpretable segmentation for hedonic inference,2021.0,,Hayato Nishi; Yasushi Asami; C. Shimizu,"Abstract In housing markets, one bundle of characteristics is regarded as corresponding to a single price via a hedonic function. However, under the conditions of market mixture, the correspondence can be multi-valued and the existence of a single function is an illusion. The market segmentation approach decomposes a complex correspondence into simple functions. In this paper, we propose an automatic segmentation method that satisfies the submarket’s equilibrium and substitutability conditions. Our empirical results show that our method provides a reasonable segmentation.",11.0,554eef11908028461ab626e640dcf594a97750ab5a6,10.1016/j.sbspro.2011.07.021,"Addressing Structural Instability in Housing Market Segmentation of the Used Houses of Tokyo, Japan",2011.0,,Kazi Saiful Islam; Yasushi Asami,"Hedonic price is the most popular determinant of housing market segmentation. Nonetheless, hedonic regression is often criticized for not being able to tackle heterogeneity of hedonic price of urban scapes, which creates structural instability in the regression. Spatial switching regression is used in this paper to develop localized hedonic regression ensuring constancy of the parameters within each localized regression. Central Tokyo and the outskirts are clearly divided into two segments. This research provides a new dimension to the existing methods of housing market segmentation. Additionally, this research also improves the predictive capability and model fitting statistics of hedonic regression.",10.0,https://www.sciencedirect.com/science/article/pii/S1877042811013449/pdf555669fd3cf45964262c8e4571e8a3166d8c2ed6530,10.1017/bca.2015.49,Hedonic Vices: Fixing Inferences about Willingness to Pay in Recent House-Value Studies 1,2015.0,Journal of Benefit-Cost Analysis,John Yinger; Phuong Nguyen-Hoang,,10.0,5568237fc4226cd717f9dd489412630c15b0a48c7f7,10.1108/f-04-2016-0039,A market-oriented model for the independent-living retirement village industry,2018.0,,Le Ma; R. Reed,"Purpose 557 558 559 560 561As the “baby boomer” generation continues to enter their senior post-retirement years, the provision of affordable retirement housing has become increasingly important for the community, practitioners and policymakers. However, relatively little attention has to date been placed on identifying an effective market mechanism for the industry of the independent-living retirement villages to meet this increased and unprecedented demand. This study aims to develop an innovative and affordable retirement village development model which meets the needs of all stakeholders including seniors, retirement village residents, the retirement village industry and government. 562 563 564 565 566Design/methodology/approach 567 568 569 570 571The attributes of this study are as follows: structure of individual living units, retirement village characteristics, retirement village facilities and services and support mechanisms. The analysis was undertaken based on data relating to independent-living retirement villages in five Australian states. A hedonic pricing model was used where the price distributions relating to these four aspects were estimated. 572 573 574 575 576Findings 577 578 579 580 581The results confirmed the",9.0,https://figshare.com/articles/journal_contribution/A_market-oriented_model_for_the_independent-living_retirement_village_industry/208093425821c730a20c7eb1ac7838746b8ac6b68fe6d7ced3f,10.1257/pandp.20231131,Racial Gaps in Federal Flood Buyout Compensations,2023.0,AEA Papers and Proceedings,Kay Jowers; La-La Ma; Christopher Timmins,"In a managed retreat, or “buyout,” program, homeowners are offered their property's fair-market value to relocate from a flood-prone area. Using a nationwide sample of federal buyout acquisitions and the universe of US housing transactions over the last two decades, we estimate whether the discount in buyout price compensation, calculated using a hedonic prediction model, depends on a homeowner's race. We provide the first systematic evidence of inequitable compensation in a federal buyout program using nationwide administrative data. Disproportionate compensation, in an attempt to adapt to a warming climate, may further widen the wealth and social mobility gaps.",9.0,583a90efa2e2b4a4c7fde54cbffdb07fb2a1d2e8ed7,10.1186/s41937-021-00080-2,Examining the vintage effect in hedonic pricing using spatially varying coefficients models: a case study of single-family houses in the Canton of Zurich,2022.0,Swiss Journal of Economics and Statistics,Jakob A. Dambon; Stefan S. Fahrländer; Saira Karlen; M. Lehner; Jaron Schlesinger; Fabio Sigrist; Anna Zimmermann,"This article examines the spatially varying effect of age on single-family house (SFH) prices. Age has been shown to be a key driver for house depreciation and is usually associated with a negative price effect. In practice, however, there exist deviations from this behavior which are referred to as vintage effects. We estimate a spatially varying coefficients (SVC) model to investigate the spatial structures of vintage effects on SFH pricing. For SFHs in the Canton of Zurich, Switzerland, we find substantial spatial variation in the age effect. In particular, we find a local, strong vintage effect primarily in urban areas compared to pure depreciative age effects in rural locations. Using cross validation, we assess the potential improvement in predictive performance by incorporating spatially varying vintage effects in hedonic models. We find a substantial improvement in out-of-sample predictive performance of SVC models over classical spatial hedonic models.",8.0,https://sjes.springeropen.com/counter/pdf/10.1186/s41937-021-00080-25842a05a8c2b9969019e34c5dbefb462e28c7218932,10.3390/land8100147,"Valuing Environmental Amenities across Space: A Geographically Weighted Regression of Housing Preferences in Greenville County, SC",2019.0,Land,J. Hiebert; Karen Allen,"As global consumption and development rates continue to grow, there will be persistent stress placed on public goods, namely environmental amenities. Urban sprawl and development places pressure on forested areas, as they are often displaced or degraded in the name of economic development. This is problematic because environmental amenities are valued by the public, but traditional market analysis typically obscures the value of these goods and services that are not explicitly traded in a market setting. This research examines the non-market value of environmental amenities in Greenville County, SC, by utilizing a hedonic price model of home sale data in 2011. We overlaid home sale data with 2011 National Land Cover Data to estimate the value of a forest view, proximity to a forest, and proximity to agriculture on the value of homes. We then ran two regression models, an ordinary least squares (OLS) and a geographically weighted regression to compare the impact of space on the hedonic model variables. Results show that citizens in Greenville County are willing to pay for environmental amenities, particularly views of a forest and proximity to forested and agricultural areas. Howeve",7.0,https://www.mdpi.com/2073-445X/8/10/147/pdf?version=1571741902585b57c3a75fc6f8929009a6e0fb90c9649b6c36f7f,10.1007/s00181-009-0267-9,The welfare loss associated to characteristics of the goods: application to housing policy,2010.0,,C. Bilbao; A. Bilbao; J. Labeaga,"The subsidies in kind aimed at heterogeneous goods do not merely generate the traditional excess burden: there is an alternative welfare loss as the distortion also affects non-price characteristics of the good. The reason is that the beneficiary of this type of subsidy has to consume a good with some given characteristics which do not necessarily agree with his choice in the market. The welfare loss analysed here tries to overcome the lack of a correct measure of excess burden in the situations indicate above. Therefore, the paper constitutes an empirical novelty in the theory of excess burden. Moreover, we provide empirical evidence of the welfare loss after estimating a hedonic price model and using predicted prices in a quadratic almost ideal demand system for housing characteristics. The new excess burden is computed under standard assumptions from the theory of rationing. We identify the sources of the losses and we also provide a monetary measure suggesting that, under plausible parameter values, it can be quantitatively high.",7.0,http://hdl.handle.net/10651/8509586488210c141acbeeb9555857923d916a80eb94e8d,10.1108/ohi-04-2022-0091,"Housing demand of urban fringe residents and underlying causes: example of Ankara, Türkiye",2022.0,Open House International,Gizem Hayrullahoğlu; Yeşim Aliefendioğlu (Tanrivermis),"Purpose This study aims to explore the housing demand of urban fringe residents in southwest Ankara. Two subquestions were developed: What are the respondents’ perceptions of Ankara city center and which characteristics do they prioritize for living in the urban fringe? Data were collected through a face-to-face household survey, and a hedonic regression model was developed based on responses.Design/methodology/approach Increasing housing demand, lifestyle change and faulty housing policies in Ankara have triggered urban sprawl along fringe areas, which causes several urban problems. Considering that urban sprawl is related to housing demand, it is essential to examine the structure of housing demand and the preference to live near the urban fringe.Findings According to the survey results, security, crime, noise pollution, traffic congestion and parking problems that reduce the welfare of Ankara city center encouraged expansion toward the rural–urban fringe, in addition to low-quality or traditional housing attributes. The urban core became unattractive to the respondents for being insecure, chaotic and down-market. The hedonic model showed that seven variables, all related to hous",5.0,587067ff6512972482e0f5d95e3fea249fec204b375,10.1016/j.landusepol.2020.105150,Integrated hedonic-utilitarian valuation of the built environment by neutrosophic INVAR method,2020.0,,E. Zavadskas; A. Kaklauskas; R. Baušys; A. Naumčik; I. Ubarte,"Abstract Hedonic valuation models enable us to make relevant decisions concerning the equipage of the built environment amenities and to establish more correct price zoning and land use management. These studies examining the utilitarian and hedonic aspects of property often face issues: how can we measure and assess multisensory experiences of property buyers (their affective attitudes, emotional states and physiological parameters) in an integrated manner and make a decision? This fact was a vital goal of the integrated Neutrosophic Degree of Project Utility and Investment Value Assessments along with Recommendation Provisions (INVAR) method. About 200 million multisensory data points have been collected so far and, as a result of their correlation analysis, several tens of thousands of average and robust correlations were determined. The new Neutrosophic INVAR method offers a bigger, more detailed picture of the hedonic-utilitarian value of the property. Another benefit of the Neutrosophic INVAR method is its ability to assist in assessing any project, determining its integrated hedonic-utilitarian value and offering tips on ways to make the project better. The Neutrosophic INVA",5.0,58882059a10f1fa1cee49466f170f0137de8e27ad3e,10.17261/pressacademia.2020.1304,Spatial heterogeneity in Istanbul housing market: a geographically weighed approach,2020.0,Pressacademia,Orcun Morali; Neslihan Yılmaz,Purpose - This study examines and documents spatial heterogeneity in Istanbul housing market using Geographically Weighted Model (GWR). Methodology - A GWR model with a Gaussian kernel and an adaptive bandwidth based on cross-validation is employed on a cross-sectional housing listing data set. Additional analysis is provided using geographically weighted Spearman’s rank correlation measure between prices and variables. Findings- GWR model substantially boosts goodness of fit in our pricing model compared to a standard hedonic regression model. The variation within GWR coefficients is high and of micro nature. Median GWR coefficients often differ from standard hedonic regression coefficients. The variability of coefficients is plotted on map. Conclusion- Findings suggest the existence of spatial non-stationarity in standard hedonic regressions and favor the use of models appropriate for spatial heterogeneity. Findings encourage further research in hedonic models applications such as in quality adjustments to price indices.,5.0,https://doi.org/10.17261/pressacademia.2020.130458978f72b2a9956e95ecbe8f75ccf7ca82a896bda27,10.3390/agriculture14081259,Hedonic Pricing Models in Rural Tourism: Analyzing Factors Influencing Accommodation Pricing in Romania Using Geographically Weighted Regression,2024.0,Agriculture,Marius-Ionuț Gordan; V. Tudor; C. Popescu; T. Adamov; Elena Peț; I. Milin; Tiberiu Iancu,"This study investigates the factors influencing pricing in Romanian rural tourism using a hedonic pricing model through a hybrid LASSO-OLS regression and geographically weighted regression (GWR). By analyzing data from 5028 unique accommodation units across 1170 local administrative units, we identify some key pricing determinants, including accommodation size, capacity, facilities, and environmental attributes. The results reveal that larger accommodations and those with higher guest capacities command higher prices. Luxurious facilities, such as massage services, pools, and fireplaces, significantly increase pricing, although the impact of such features varies by region, as do accommodation type and natural scenery, with agritouristic boarding houses and proximity to natural attractions like water bodies and forests being more valued in certain regions. These factors can aid rural entrepreneurs in optimizing pricing to enhance competitiveness and profitability.",5.0,https://doi.org/10.3390/agriculture14081259590c87e18b4f3713d41492be844a7d389e9e25b2b22,10.2139/ssrn.1909374,Tacit Collusion in the Santiago Housing Market,2011.0,,M. Vargas; F. Lefort,"Given the numerous and widely acknowledged benefits of a well-functioning housing market, it is vital to understand the degree of competition in that market, which is the starting point for undertaking any policy tool aimed at improving its efficiency. This paper tests the extent of competition in the housing market in Santiago, Chile using a two-step methodology. In the first step, using a hedonic price model, the Santiago housing market is divided into sub-markets, which are analyzed separately. The second step is the tacit collusion test itself, which compares the industry markup with the business cycle in each sub-market using panel data regression models. Evidence of collusion is found in certain sub-markets.",5.0,https://doi.org/10.2139/ssrn.1909374591f82feef6610d5bc6fce2af26cee5230d5729dcaf,10.1108/arla-05-2021-0110,"Color intensity, luminosity, contrast and art prices: the case of Jean-Michel Basquiat",2022.0,Academia : Revista Latinoamericana de Administración,Urbi Garay; E. Pérez; J. Casanova; Michelle Kratohvil,"PurposeThe price of a painting is determined by multiple variables, including color-related variables. Colors are important in an economic analysis. This study aims to analyze the paintings executed by Jean-Michel Basquiat (the famous street artist from the 1980s' New York City) and sold at auction to study the potential effect of color intensity, luminosity and color contrast on the prices of his paintings. The authors also study the case of the op art master, Carlos Cruz-Diez, as a robustness analysis to the main results. The analysis that the authors present may be of interest to academicians and to participants in the art market.Design/methodology/approachThe authors run a hedonic regression model considering 306 paintings (executed by Basquiat alone), and 41 works painted collaboratively between Basquiat and Warhol and sold at auction (2003–2017). The data and the images corresponding to each painting were hand-collected from the websites of several auction houses and complemented with information obtained from the Artprice and Blouin websites.FindingsIncreases in color intensity, luminosity and color contrast have a positive effect on art prices. The authors also find that co",4.0,https://hdl.handle.net/10818/62564592529cf89c004b0b15709fa7a01fee2a8e3c44c1b8,10.3390/su162310612,The Urban Park Green Spaces Landscape Premium Functional Value Accounting System: Construction and Application,2024.0,Sustainability,Lingling Duan; X. Niu; Bing Wang,"Urban park green spaces have the functions of improving the urban ecological environment and providing recreational services, and at the same time, they have a certain effect on the value of the surrounding residential property. To quantitatively assess the value of the landscape premium function of park green space, many scholars have carried out research exploration and adopted a variety of methods (such as the contingent valuation method (CVM), travel cost method (TCM) and hedonic price method (HPM)), which have developed from simple theoretical models with single factors to complex empirical models with multiple factors. Among them, the hedonic price method has become the mainstream research method, and in recent years, it has been widely adopted in combination with GIS technology. In terms of research objects, single park green space or multiple park green spaces in large cities are the main focus, while there are fewer studies on park green spaces in built-up areas of small and medium-sized cities. In terms of research content, there are more studies on the value-added coefficient of landscape premium and influence distance, and there are fewer studies on the total value of l",4.0,https://www.mdpi.com/2071-1050/16/23/10612/pdf?version=173324074659384238faa2528e0ae6be3c77816706d06f777b7ff,10.17016/feds.2024.075,Explaining Machine Learning by Bootstrapping Partial Marginal Effects and Shapley Values,2024.0,Finance and Economics Discussion Series,Thomas R. Cook; Zach Modig; Nathan M. Palmer,"Machine learning and artificial intelligence are often described as “black boxes.” Traditional linear regression is interpreted through its marginal relationships as captured by regression coefficients. We show that the same marginal relationship can be described rigorously for any machine learning model by calculating the slope of the partial dependence functions, which we call the partial marginal effect (PME). We prove that the PME of OLS is analytically equivalent to the OLS regression coefficient. Bootstrapping provides standard errors and confidence intervals around the point estimates of the PMEs. We apply the PME to a hedonic house pricing example and demonstrate that the PMEs of neural networks, support vector machines, random forests, and gradient boosting models reveal the non-linear relationships discovered by the machine learning models and allow direct comparison between those models and a traditional linear regression. Finally we extend PME to a Shapley value decomposition and explore how it can be used to further explain model outputs.",4.0,https://doi.org/10.17016/feds.2024.075594b97fa02fdc8b48e3425f91802b06711e1a40bb8c,10.5075/epfl-thesis-4186,Assessing environmental amenities and testing for discrimination in housing markets using hedonic price models,2008.0,,C. Schaerer,,4.0,595eba338cf34039bebab5da264e85e1f19be450eaa,10.1177/02762374241267105,The Death of the Author: The Case of art Market,2024.0,Empirical Studies of the Arts,A. Pimenov; V. Kolycheva; Alexander Semenov; Dmitry Grigoriev,"Recent evidence suggests that the artwork of an experienced artist is usually more expensive than that of a beginner. Additionally, the artwork of a man is often more expensive than that of a woman, and a painting is typically more expensive than graphics. However, this research aims to contrast the influence of the author's age and sex on the price with the influence of the artwork's material and technique. This idea is based on Roland Barthes’ famous philosophical doctrine about the death of the author, which appeared in 1968 and remains relevant today. In our article, this doctrine is tested for the art market. The research question posed is whether the author's influence dies in relation to their artwork after its creation or whether the artwork begins to live its own life without the author. To answer this question, a study was conducted comparing the impact on auction prices of the artist's biography and the characteristics of the artwork. The artist's biography inevitably determines their creativity and affects their art, while the characteristics of the artwork are not directly related to the personality of the author but are important from a consumption standpoint. Several",3.0,59671c0af0abf1d51882d86d0043ba62ffb7ae12d8f,10.1111/1467-8489.12533,Capitalised nonmarket benefits of multifunctional water‐sensitive urban infrastructure: A case of living streams,2023.0,Australian Journal of Agricultural and Resource Economics,Saloomeh Akbari; M. Polyakov; M. S. Iftekhar,"Living streams are an important element of decentralised stormwater management solutions. They are actively promoted due to their ability to generate multiple ecosystem services, including water quality improvement, biodiversity protection and aesthetics. However, a lack of monetised values of ecosystem services of living stream projects makes it difficult to assess the net benefits of investing in such projects. This study uses the hedonic pricing method to estimate the capitalised amenity values of living streams and other public open spaces (POS) in housing and lot markets for the first time. The study area includes two newly greenfield‐developed suburbs in the Perth metropolitan area. We find the positive impact of living streams and other POS on the house and lot prices. However, living streams generate greater value than other types of POS. Furthermore, the POS (including living streams) that support active recreation are valued more than basic POS without active recreation features. Finally, we observe, for the first time, that the benefits of planned but not yet constructed POS (including living stream) are similar to the completed POS (including living stream) in both hous",3.0,https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/1467-8489.12533597285caab90381290dfb23f34ba340c2ab7a4de02f,10.1108/jerer-02-2023-0008,Quantifying the drivers of residential housing demand – an interpretable machine learning approach,2023.0,Journal of European Real Estate Research,Marcelo Cajias; Joseph-Alexander Zeitler,"PurposeThe paper employs a unique online user-generated housing search dataset and introduces a novel measure for housing demand, namely “contacts per listing” as explained by hedonic, geographic and socioeconomic variables. Design/methodology/approachThe authors explore housing demand by employing an extensive Internet search dataset from a German housing market platform. The authors apply state-of-the-art artificial intelligence, the eXtreme Gradient Boosting, to quantify factors that lead an apartment to be in demand.FindingsThe authors compare the results to alternative parametric models and find evidence of the superiority of the nonparametric model. The authors use eXplainable artificial intelligence (XAI) techniques to show economic meanings and inferences of the results. The results suggest that hedonic, socioeconomic and spatial aspects influence search intensity. The authors further find differences in temporal dynamics and geographical variations.Originality/valueTo the best of the authors’ knowledge, it is the first study of its kind. The statistical model of housing search draws on insights from decision theory, AI and qualitative studies on housing search. The econome",3.0,598c5bef05231fadf1fa9b2e50fafac775d4c27308c,10.1109/iscid.2018.00010,Air Quality Prediction Method in Urban Residential Area,2018.0,International Symposium on Computational Intelligence and Design,Rui-Jun Yang; Hailong Zhou; Dan Ding,"According to hedonic price theory, using classification algorithm of the machine learning which include SVM, Naive Bayesian and KNN, establish the internal mapping relationship between feature variables that include prices of housing and air quality. Air quality in urban residential district is predicted by feature variables. Finally, experiments have conducted on the data set of residential district In Tianhe, Guangzhou city, showed that the most accuracy. The method is very practical and stable for air quality in urban residential district prediction. The new method has a strong practical value as reference methods for buyers.",3.0,599fbe5a95570d731f0284b4497cee23648ad6cd685,10.3390/su16114768,Analysis of the Location Factors Affecting the Price of Tourist Houses: The Role of Accessibility to Public Transport Stations in Madrid,2024.0,Sustainability,Patricia Valenzuela; Armando Ortuño; M. Flôr; Begoña Guirao,"The location of tourist properties is a fundamental aspect in the determination of price, but in cities with dense and efficient public transport systems, the location being in the periphery can offer alternative advantages to central locations (such as better accessibility by private vehicles). This study analyses how the price of tourist housing is influenced by the characteristics of the accommodation itself and its location, using a hedonic pricing regression model estimated by ordinary least squares (OLS) in two periods of time: the high season (October 2022) and the low season (February 2023). The obtained results suggest that the characteristics of the properties, the local environment and the elements in the area influence the price of tourist accommodation. Similarly, the proximity to public transport stations and stops has a relevant influence on the choice of tourist properties. This latter factor is highly important for designing public policies that favour a denser public transport network in peripheral areas of the city. This would increase the number of tourist properties in these areas further away from the centre and, therefore, the number of reservations. In turn,",2.0,https://www.mdpi.com/2071-1050/16/11/4768/pdf?version=17174305496008e17140968f66d2c7e738948fbddd23eef074754,10.1108/jefas-02-2024-0065,Categorizing world regional art prices by artistic movement: an analysis of Latin American art,2025.0,Journal of Economics Finance and Administrative Science,Urbi Garay; Fredy Pulga,"PurposeThe literature on the potential benefits of art investing has yet to consider the effects of categorizing world regional art markets (e.g. Latin American art) by artistic styles or movements (e.g. Latin American surrealism, Latin American conceptual art, etc.). We propose that such categorization should be carried out and analyze the Latin American art market as an example.Design/methodology/approachEleven artistic style price indices within the Latin American art market (30,288 artworks created by 293 artists and sold at auction between 1970 and 2014) are estimated using hedonic regressions: Abstract-geometric, abstract-informal, conceptual, costumbrismo, cubism, figurative, muralism, landscape, surrealism, nineteenth century and avant-garde. We find that several variables that rely on the corresponding Latin American art movement index have a significant relationship with painting prices.FindingsThere is significant variation in the financial performance of the various price indices for Latin American art styles: the conceptual (10.33% annual real return), abstract geometric (1.97%), cubism (0.97%) and costumbrismo (0.91%) movements overperformed a market that exhibited an",1.0,https://doi.org/10.1108/jefas-02-2024-0065601926750010b8904428cdd986aaf4615c97c0ae06b,10.15611/aoe.2025.2.07,The regression model of the art market in Poland,2025.0,Argumenta Oeconomica,Anna Lucińska,"Aim: The aim of the article was to study the impact of the functional form of the regression model, i.e. the set of explanatory variables, on the rates of return. The assessment of the investment effectiveness in the Polish art market required building a regression model to determine price indices and rates of return. The knowledge of price-forming factors can be used to build a hedonic regression model that maps the dependence of painting prices and their characteristics. Methodology: The purpose of the article was achieved by analysing the sales records from Polish auction houses, for the most sold painters in the period 2007–2022. On this sample of 7,442 records, the parameters of nine hedonic regression models were estimated with the LSM using many combinations of explanatory variables. Results: The research results indicate that the form of the regression model is crucial for the value of indices and affects the rates of return with differences in examined models ranging from 3.71 p.p. to 13.71 p.p. Although the selection of explanatory variables affects the value of the indices and the rates of return, the variability of the average index values remained within the limits of ",1.0,https://dbc.wroc.pl/Content/140280/Lucinska_The_regression_model_of_the_art_market_in_Poland.pdf602889935bd7b158fedf9c366949573a1091ee525d2,10.5194/ica-proc-2-47-2019,Spatial Analysis to Identify Factors Affecting Residential Land Prices in Disaster Areas,2019.0,Proceedings of the ICA,Keiko Inagaki; S. Sadohara,"Abstract. On March 11, 2011, a catastrophic earthquake struck Japan’s Tohoku area, which faces the Pacific Ocean. In this study, a multivariate spatial analysis was conducted to analyse the factors affecting residential land prices in the disaster-stricken area using the Hedonic Price Method. For the analysis, we first, collected spatial data, including land price maps, tsunami damage area map, flood hazard map, landslide hazard map, railway map, zoning map, and public building map of Miyagi prefecture. Second, we examined the extent to which the damage caused by the tsunami inundation can influence land prices, in order to clarify the relationship between natural disasters and land price fluctuations. The results of the multivariate analysis concluded that the tsunami inundation affected the price of land, particularly after the Great East Japan Earthquake (2011) in Miyagi prefecture. Furthermore, the degree of the tsunami inundation and the distance from public housing constructed after the disaster influenced land price fluctuations after the earthquake. In other words, the human settlements have been affected by disaster damage and reconstruction plan. Present studies have demo",1.0,https://www.proc-int-cartogr-assoc.net/2/47/2019/ica-proc-2-47-2019.pdf603c667868a7e0326ec0a1185f939ca2c0d317ee130,10.1016/j.jue.2026.103830,The topography of regulatory costs: The shadow cost-gradient of parking standards,2026.0,Journal of Urban Economics,W. Cutter; Sofia Franco; W. Lewis,"Building and zoning regulations such as minimum parking requirements (MPRs) limit the ability of a developer to fully use a parcel of land to its unregulated level, potentially resulting in distortion in commercial development. In the case of MPRs, such regulation requires either the allocation of land for parking, or very costly substitution of structured parking for land. Therefore, MPR distortions are likely to increase with the value of land. A steep enough gradient in the cost of the MPRs could then displace development from dense, high land-value areas to outlying areas, reducing agglomeration economies. We use a Mixed Geographically Weighted Regression (MGWR) approach to estimate a hedonic specification using sales of office properties in Los Angeles County. This approach allows local variation in the estimates of marginal values of key parameters, including the value of on-site parking. To control for unobservables, we use the Linn (2013) method to incorporate pre-period prices into the MGWR estimator. We use these hedonic estimates plus locally-specific estimates of parking costs to estimate the cost of MPRs on a property-by-property basis. For completeness, we also test t",1.0,604f46aba4ac7687e2c0f6f1bcf3eac74d6d9ff02ce,10.2991/emcm-16.2017.205,The Analysis on Spatial-Temporal Evolution and Impacting Factors of Residential Land Price in Hangzhou: Evidence Based on Spatial Econometric Model,2017.0,,Hai-Zhen Wen; Luhong Chu,"In the context of rapid urbanization in China, the land market has become one of the focuses of the whole society. Based on the residential land transaction data from May 2006 to March 2010 in Hangzhou, this paper applies the hedonic price model of spatial econometrics to study the evolving trend and the influencing factors of land prices from two aspects of time and space. The results show that, compared with OLS estimation result, the estimated results of spatial econometric model improve significantly. And floor area ratio and land grade have a significant impact on land prices. At the spatial level, there is a significant spatial dependency between the error terms of land prices, and the price fluctuation between the adjacent lands is significant, besides the distance to the urban landscape center West Lake has a significant negative impact on the land price. In temporal dimension, land prices have an obvious rising trend, but the rising degree of land prices declines evidently in the period of international financial crisis.",1.0,https://download.atlantis-press.com/article/25870585.pdf60554d5d54390ccc641a2ae74b805d72c1a07781973,10.1007/978-3-030-74544-8_4,The Role of Migration Costs in Residential Sorting,2021.0,The Urban Book Series,Wenquan Liang; Ran-hee Song; Christopher Timmins,"Economistsgenerallyemploytwo ‘revealed preference’ approaches to measure households’ preferences for non-market amenities—the hedonic and equilibrium sorting models. The conventional hedonic model assumes free mobility across space. Violation of this assumption can bias the estimates of household willingness to pay for local amenities. Mobility constraints are more easily handled by the sorting framework. In this chapter, we examine the role of migration costs in household residential sorting and apply these two models to estimate the willingness to pay for clean air in the USAand China. Our results demonstrate that ignoring mobility costs in spatial sorting will underestimate the implicit value of non-market amenities in both countries. Such a downward bias is larger in developing countries, such as China, where migration costs are higher.",1.0,https://link.springer.com/content/pdf/10.1007%2F978-3-030-74544-8_4.pdf60625fa6df045a52c37dbe7df7f65c703e1d394c443,10.2139/ssrn.1150998,Measuring the Value of a Moscow Apartment: a Spatial Approach to the Hedonic Pricing of Attributes,2008.0,,Alexandre Repkine,,1.0,https://doi.org/10.2139/ssrn.1150998607aa13b4577518f8ee70386247019e5dfbcb0f0616,10.22437/ppd.v2i3.2271,Estimasi Nilai Basis Pajak Bumi dan Bangunan di Kota Jambi: Pendekatan Hedonic Price Function,2015.0,Jurnal Perspektif Pembiayaan dan Pembangunan Daerah,Arman Delis; Siti Hodijah,"Abstrak Penelitian ini bertujuan untuk mengidentifikasi faktor-faktor yang paling dominan yang menentukan tingkat harga tanah dan bangunan dan untuk mengukur rasio antara harga tanah dan bangunan berdasarkan harga yang ditetapkan pada Surat Pemberitahuan Pajak Terhutang (SPPT). Estimasi tingkat harga dan nilai wajib pajak atas tanah dan bangunan didasarkan pada fungsi harga hedonis. Data yang digunakan adalah data kerat-lintang dari hasil survei lapangan 100 pemilik tanah dan bangunan di wilayah Kecamatan Telanaipura, Pelayangan, Pasar Jambi dan Kota Baru. Hasil penelitian menunjukkan bahwa tingkat harga tanah dan bangunan yang tertinggi ada di Pasar Jambi dan yang terendah di Pelayangan. Variabel yang paling dominan yang menentukan tingkat harga tanah adalah kepadatan penduduk, jarak tanah ke lokasi pusat kota dan jenis jalan yang melewati lokasi tanah, sedangkan tingkat harga bangunan ditentukan oleh luas lantai bangunan, jenis rumah dan ketersediaan garasi. Secara rata-rata, rasio harga tanah pada NJOP terhadap harga tanah aktual yang dikehendaki pemiliknya dan harga prediksinya masing-masing adalah 29,30 persen dan 44,13 persen. Rasio rata-rata yang relatif rendah ini menunjukk",0.0,https://doi.org/10.22437/ppd.v2i3.2271608c561b6f62e3567245fe8a196863f9f40523be96b,10.5821/dissertation-2117-95032,"Modelo para maximizar ingresos de nuevos proyectos inmobiliarios, por medio de la selección de la mejor combinación de atributos y características de las viviendas, para una determinada localización.",2013.0,,Roberto Schovelin Surhoff,"The thesis goal is to build a model that defines the characteristics that a Residential Real State Project and the houses in it must have in order to get the highest income possible at the moment of getting it into the market. The design model defines for each house type, according to the constructed surface, the land surface if it is a house; the amount of units and the unit price planned for each one. This depends on the combination of the location characteristics. 609These relations are obtained from hedonic projects carried out in apartments, detached houses and condominiums. 610The design model is an optimized model that maximizes the residential project¿s income allowing the variable characteristics to be adjusted and delimited according to physical, legal, architectural and economic restrictions. 611The design model was build at Concepcion City, Chile for three types of houses. The apartment model was build based on 37 projects and 201 house types. The price was calculated based on 34 variables and gives the Real State Developer 21 design characteristics. The condominium house model was build with 12 projects and 32 house types. 612The hedonic models were tested for 6 projects alrea",0.0,https://upcommons.upc.edu/bitstream/2117/95032/1/TRSS1de1.pdf6134ede38c9861f1847575845f74e5e437914e67329,10.5821/ctv.8245,"The marginal price of housing energy-efficiency in Metropolitan Barcelona: issues of sample614 selection biases",2018.0,International Conference Virtual City and Territory,Ai Chen; Carlos Ramiro Marmolejo Duarte,"Proposito: La eficiencia energetica de la vivienda se ha convertido en un problema desde la obligatoriedad impuesta por la EPBD de exhibir un certificado de eficiencia energetico (EPC) al realizar transacciones de bienes raices. Numerosos estudios se han centrado en precios marginales de la eficiencia energetica utilizando modelos de precios hedonicos. Sin embargo, en algunos mercados como el espanol, una importante proporcion de propiedades en alquiler o venta no exhiben los EPC en el anuncio inmobiliario. Al no considerar este tema, el impacto de las EPC en los precios de la vivienda puede resultar sesgado. En otras palabras, estos casos sin etiquetas EPC no pueden ser considerados. Este desconocimiento del sesgo de la seleccion de la muestra puede reducir la precision de los resultados, o incluso dar una estimacion adversa. En este caso, el objetivo de este trabajo es explorar la presencia del sesgo en la seleccion de la muestra y corregirlo, para mejorar los siguientes estudios.MetodologiaSe utilizan, como principal fuente de informacion, los listados de propiedades inmobiliarias de Habitaclia, empresa lider en Internet en Cataluna y se aplica el modelo de Heckman para identifi",0.0,https://upcommons.upc.edu/bitstream/2117/132263/1/8245-5959-1-SM.pdf61550e6c80c5cbd52ae27b5aa077dc5fa305fdca8e6,10.15396/eres2019_131,Estimating the HARA land-use model for housing planning based on hedonic price analysis,2019.0,26th Annual European Real Estate Society Conference,I. Ossokina; Theo A. Arentze; Jian-Fei Li,"HARA is a land-use model that uses a search algorithm to find the optimal spatial allocation of new housing demands in an urban plan area. In the model, the plan area is represented as a grid of cells. A core element of the algorithm is a function that is used to evaluate the value of a cell for each possible land-use given its location. An optimum is found by stepwise improving an initial allocation based on the value function. In this paper we show that the value function can be specified as the net value of a (housing) development given the land costs, the construction costs and the market value of the development at a location. Specified in that way the solution generated represents an optimum as well as a market equilibrium (maximum net value for developers). A critical prerequisite for this is, however, that the value-function is specified such that it accurately represent buyers’ willingness-to-pay for dwelling and location characteristics in the housing market. In the paper, we show how the value function can be estimated using hedonic price analysis. The analysis is carried out based on a large housing transaction data set from The Netherlands. The trade-off between living",0.0,https://eres.architexturez.net/system/files/P_20190710151755_8247.pdf616ed35b9f1d9f0b487b254782f291698d7664e0b6b,10.15396/eres2011_277,Using a CAMA approach to model energy efficiency in housing,2011.0,,P. Davis; W. Mccluskey; M. McCord; M. Haran,"Computer Assisted Mass Appraisal (CAMA) utilising hedonic and spatial analysis is well established in the field of property valuation for taxation purposes. In this role these approaches are deployed on large datasets of property attribute data and use prices in a sold sample to estimate value in the general population. With the emergence of the green agenda, much effort has been put into improving the energy efficiency of housing. A key policy has been the introduction of energy ratings which have become mandatory in several jurisdictions, with the aim of informing market choices. Many jurisdictions have also made efforts to improve knowledge of energy efficiency of housing stock, to better target funding and awareness campaigns aimed at encouraging upgrades. Some jurisdictions are now seeking to reward / encourage such activity via tax incentives. This research is based upon a project to bring together several large databases of property based data, held by a tax authority, an energy saving trust and a major social housing provider to establish a basis for statistical analysis. The aim is to estimate the energy efficiency of the entire housing stock of a jurisdiction using the ty",0.0,https://eres.architexturez.net/system/files/pdf/eres2011_277.content.pdf6177951fc0d34a7324edacf2a63c5f4c669589fecf8,10.3390/econometrics13040049,Choosing Right Bayesian Tools: A Comparative Study of Modern Bayesian Methods in Spatial Econometric Models,2025.0,Econometrics,Yuheng Ling; J. le Gallo,"We compare three modern Bayesian approaches, Hamiltonian Monte Carlo (HMC), Variational Bayes (VB), and Integrated Nested Laplace Approximation (INLA), for two classic spatial econometric specifications: the spatial lag model and spatial error model. Our Monte Carlo experiments span a range of sample sizes and spatial neighborhood structures to assess accuracy and computational efficiency. Overall, posterior means exhibit minimal bias for most parameters, with precision improving as sample size grows. VB and INLA deliver substantial computational gains over HMC, with VB typically fastest at small and moderate samples and INLA showing excellent scalability at larger samples. However, INLA can be sensitive to dense spatial weight matrices, showing elevated bias and error dispersion for variance and some regression parameters. Two empirical illustrations underscore these findings: a municipal expenditure reaction function for Île-de-France and a hedonic price for housing in Ames, Iowa. Our results yield actionable guidance. HMC remains a gold standard for accuracy when computation permits; VB is a strong, scalable default; and INLA is attractive for large samples provided the weight m",0.0,https://www.mdpi.com/2225-1146/13/4/49/pdf?version=1764818843618aacf1da2f2c282d86f6907614f853ed1c1c7ce56,10.3390/a19020098,Machine Learning Applications for Sustainable Housing Policy: Understanding Price Determinants to Inform Affordable Housing Strategies,2026.0,Algorithms,Fan Zhang; Yi-Fang Luo; Yuqing Dong; Qi-Kai Zhang; Aihua Han,"Understanding how housing attributes are capitalized into prices is central to addressing urban affordability challenges. Using 2799 second-hand housing transactions from Wenzhou, China, this study examines residential price formation under pronounced spatial and structural heterogeneity. Multiple predictive models are evaluated within a unified 10-fold cross-validation framework. Results indicate that Random Forest delivers the strongest predictive performance, achieving a normalized mean squared error below 0.10 and explaining over 90% of out-of-sample price variation, substantially outperforming hedonic regression, regression trees, bagging, boosting, and support vector models. Permutation-based importance analysis identifies district location, building scale, and floor area as the dominant price determinants, while the influence of renovation quality, transportation access, and educational amenities varies across districts and dwelling types. These findings reveal strong nonlinearities and heterogeneous valuation mechanisms in rapidly urbanizing housing markets. Methodologically, the study demonstrates how interpretable machine learning complements traditional hedonic analysis,",0.0,https://www.mdpi.com/1999-4893/19/2/98/pdf6199911cd2df0a920ddd8b7ea871690b493064d3325,10.35649/kubr.2023.18.1.3,Estimating the Drivers of Urban Apartment Valuation by Using Hedonic Pricing Models: A Study on Dhaka City,2024.0,Khulna University Business Review,M. I. Alam,"Considering the population and land scarcity of Dhaka city, understanding the accommodation preferences as per the price has become a complex issue. This study has tried to investigate the drivers that shape the valuation of apartments in Dhaka city. To do that, Numerous articles have been studied and the number of bedrooms, bathrooms, balconies, apartment size, land price, the proximity of the city center and green spaces are considered as the predictors. A structured questionnaire was generated and data were obtained from a convenience sample of 265 consumers living in various locations of Dhaka city. The Multiple Regression Analysis was performed to test the research hypotheses where the apartment size, land price, and proximity to green spaces were found as the key predictors and the rest were found to be insignificant. Guidelines for the stakeholders were also provided as per the research outputs. Finally, the limitations of the research and future research avenues have been discussed.",0.0,https://kubusinessreview.com/download/v18/KUBR.2023.18.1.3.pdf6202dbb6fabdb868ab58b639471ad3818c1c52cb77c,10.24302/drd.v15.5426,Análise da relação entre criminalidade e valor por metro quadrado dos imóveis residenciais no município de Belo Horizonte,2025.0,DRd - Desenvolvimento Regional em debate,Iago Miranda Soares; Evandro Camargos Teixeira; I. S. Tupy,"The disorderly expansion of cities increases regional inequalities and contributes to the rise of crime in large urban centers. In view of this, this study investigated the relationship between the average homicide and robbery rates per 100,000 inhabitants and the value per square meter of residential property in Belo Horizonte in the period 2017-2021, using hierarchical models with spatial lag. As a result, the Exploratory Analysis of Spatial Data (AEDE) indicated distinct patterns of agglomeration for crime rates between the regions of the municipality of Belo Horizonte. In addition, the econometric results revealed that properties located in regions with higher homicide rates have lower square meter values in their built-up areas. On the other hand, the opposite is true for theft and robbery rates, which show a positive relationship with the square meter value of the properties.621Keywords: crime; regional inequalities; hedonic prices; spatial hierarchical model; Belo Horizonte.",0.0,https://www.periodicos.unc.br/index.php/drd/article/download/5426/25986220a697f89e5e39f76c324ec05106a344262ea7673,10.46553/ensayos.3.2.2020.p129-152,Noise pollution and housing markets: A spatial hedonic analysis for La Plata City,2020.0,,Juan Ignacio Zoloa,"Several cities around the world are affected by high levels of noise pollution. In fact, noise pollution is one of the main problems affecting the quality of life in cities. In this sense, noise, understood as an environmental stressor, can cause significant health problems, including sleep and learning disorders, memory troubles, lack of motivation and increase in irritability and aggressiveness. This work analyzes the value that individuals place on living in quieter areas. Using hedonic price models, we obtained an accurate assessment of the marginal willingness to pay of individuals to reduce noise pollution. The main result highlight the relevance of this topic: a buyer is willing to pay around 1.9% less for each decibel of noise around the house. Such result is especially relevant in the design of noise mitigation policies, as it determines whether the benefits of the policies designed to reduce noise pollution exceed their implementation costs.",0.0,https://erevistas.uca.edu.ar/index.php/ENSAYOS/article/download/3215/3159623d96426f104b748c11e43d1ddaad12a6aac560442,10.1016/j.ecolecon.2025.108791,The information value of energy labels: Evidence from the Dutch residential housing market,2020.0,Ecological Economics,Lennart Stangenberg; Sjors van Wickeren; Lu Zhang,"Do energy labels contain extra information that buyers cannot observe themselves? Which labeling scheme is more effective: a voluntary or a mandatory one? In this paper we examine the information value of voluntary and mandatory energy labels using administrative data on all transactions in the Dutch residential housing market. Employing a combination of hedonic price models, matching and a sharp Regression Discontinuity Design (RDD), we show that voluntary labels introduced in the period 2008-2014 contain limited information value. The information value of mandatory labels that are adopted since 2015 is less clear-cut. We observe that better-labeled dwellings were transacted with significant price premiums before obtaining labels. This implies that at least part of the premiums cannot be attributed to mandatory labels.",0.0,https://doi.org/10.1016/j.ecolecon.2025.108791624f92c8bf0532cc999532654fb7fb56d5c31157c84,10.22452/ijps.vol6no1.1,The Price Impact of House Refurbishment Estimated by Geographically Weighted Regression and Hedonic Pricing Model,2016.0,,P. Lai; D. Fischer,"Geographically Weighted Regression (GWR) is a technique that extends the traditional regression framework by allowing spatial parameters to be explicitly estimated. This paper provides a brief description of the Geographically Weighted Regression used here to value the effect of residential housing refurbishment in the City of Kaohsiung (Taiwan). The GWR results are then compared to a standard hedonic pricing estimation model applied to the same data set. What is intended here is to illustrate the use of a better tool for the identification of the spatial price impact of housing improvement investments in the metropolitan area. More generally, the paper confirms that spatial-adaptable models are required to measure the impact of investments in mixed and fuzzy goods.",0.0,https://ijps.um.edu.my/article/download/4123/1983625d1741eec20826e39eeff8da3a181e72d31eb1259,10.3905/jai.2026.011,Analysis of Malaysian Art Market Returns: A Hedonic Price Index Method,2026.0,The Journal of Alternative Investments,A. Shahrin; Karyn Anne Krishnan,"This article investigates determinants of price and returns for paintings sold within Malaysia. An annual hedonic price index is constructed from 3,541 paintings sold by three local auction houses over eight years (2010–2017). The results show an arithmetic mean return of −11.41% and a standard deviation of 14.21% within the Malaysian art auction market. The heterogeneous nature of paintings includes the artist’s nationality and living status, auction houses, year of sale, size of painting, and medium of painting. The result indicates whether the artist was deceased when the auction sale was conducted. The Edge Auction, larger paintings, and batik1 have a premium over other attributes. However, the artist’s nationality, Malaysian or otherwise, does not influence the price of paintings.",0.0,6268d6ee38b69ae5a8fddf4e870776a92c2d71461d0,10.1080/13658810802672469,Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices,2010.0,International Journal of Geographical Information Science,Bo Huang; Bo Wu; M. Barry,,1403.0,627933948fe04429611a2ee0c834dcb142aab5f5fb3,10.1257/aer.101.5.2108,Forced Sales and House Prices,2011.0,,John Y. Campbell; Stefano Giglio; Parag A. Pathak,"This paper uses data on house transactions in the state of Massachusetts over the last 20 years to show that houses sold after foreclosure, or close in time to the death or bankruptcy of at least one seller, are sold at lower prices than other houses. Foreclosure discounts are particularly large on average at 28% of the value of a house. The pattern of death-related discounts suggests that they may result from poor home maintenance by older sellers, while foreclosure discounts appear to be related to the threat of vandalism in low-priced neighborhoods. After aggregating to the zipcode level and controlling for regional price trends, the prices of forced sales are mean-reverting, while the prices of unforced sales are close to a random walk. At the zipcode level, this suggests that unforced sales take place at approximately efficient prices, while forced-sales prices reflect time-varying illiquidity in neighborhood housing markets. At a more local level, however, we find that foreclosures that take place within a quarter of a mile, and particularly within a tenth of a mile, of a house lower the price at which it is sold. Our preferred estimate of this effect is that a foreclosure at",891.0,https://doi.org/10.3386/w14866628b71e405cf455eb19f021ab99955d83dcf1123a60,10.1007/s11146-007-9032-z,The Impact of Railway Stations on Residential and Commercial Property Value: A Meta-analysis,2007.0,,G. Debrezion; E. Pels; P. Rietveld,"Railway stations function as nodes in transport networks and places in an urban environment. They have accessibility and environmental impacts, which contribute to property value. The literature on the effects of railway stations on property value is mixed in its finding in respect to the impact magnitude and direction, ranging from a negative to an insignificant or a positive impact. This paper attempts to explain the variation in the findings by meta-analytical procedures. Generally the variations are attributed to the nature of data, particular spatial characteristics, temporal effects and methodology. Railway station proximity is addressed from two spatial considerations: a local station effect measuring the effect for properties with in 1/4 mile range and a global station effect measuring the effect of coming 250 m closer to the station. We find that the effect of railway stations on commercial property value mainly takes place at short distances. Commercial properties within 1/4 mile rang are 12.2% more expensive than residential properties. Where the price gap between the railway station zone and the rest is about 4.2% for the average residence, it is about 16.4% for the ave",757.0,https://link.springer.com/content/pdf/10.1007/s11146-007-9032-z.pdf629a40c062cbe482f0eaf30c4dbbfd0e91036ceb7b0,10.3982/qe82,Dating the Timeline of Financial Bubbles During the Subprime Crisis,2011.0,,Peter C. B. Phillips; Jun Yu,"A new recursive regression methodology is introduced to analyze the bubble characteristics of various financial time series during the subprime crisis. The methods modify a technique proposed in Phillips, Wu and Yu (2010) and provide a technology for identifying bubble behavior and consistent dating of their origination and collapse. The tests also serve as an early warning diagnostic of bubble activity. Seven relevant financial series are investigated, including three financial assets (the Nasdaq index, home price index and asset-backed commercial paper), two commodities (the crude oil price and platinum price), one bond rate (Baa), and one exchange rate (Pound/USD). Statistically significant bubble characteristics are found in all of these series. The empirical estimates of the origination and collapse dates suggest an interesting migration mechanism among the financial variables: a bubble first emerged in the equity market during mid-1995 lasting to the end of 2000, followed by a bubble in the real estate market between January 2001 and July 2007 and in the mortgage market between November 2005 and August 2007. After the subprime crisis erupted, the phenomenon migrated selective",571.0,https://doi.org/10.3982/qe82630b531cfecedebdd4e4baa6ecc54f4ca643a46f7de,10.1016/j.regsciurbeco.2006.03.007,"Open Space, Residential Property Values, and Spatial Context",2006.0,,S. Anderson; Sarah E. West,,565.0,http://www.feem-web.it/ess/ess05/files/Anderson.pdf631bc51eddf83e750938b5e38b5cafb9eaf4e26022a,10.2139/ssrn.2092662,The Determinants of International Mobility of Students,2012.0,Social Science Research Network,Michel A. R. Beine; R. Noël; L. Ragot,"This paper analyzes the determinants of the choice of location of international students. Building on the documented trends in international migration of students, we develop a small theoretical model allowing to identify the various factors associated to the attraction of migrants as well as the costs of moving abroad. Using new data capturing the number of students from a large set of origin countries studying in a set of 13 OECD countries, we assess the importance of the various factors identified in the theory. We find support for a significant network effect in the migration of students, a result so far undocumented in the literature. We also find a significant role for cost factors such as housing prices and for attractiveness variables such as the reported quality of universities. In contrast, we do not find an important role for registration fees.",415.0,https://doi.org/10.2139/ssrn.2092662632df0f929e07c1e0b6cb236f2013e4727005866c72,10.1057/palgrave.ces.8100221,Determinants of House Prices in Central and Eastern Europe,2007.0,,Balázs Égert; D. Mihaljek,,403.0,https://repozitorij.uni-lj.si/IzpisGradiva.php?id=33324633c45231b7ac7a7cbd2e2642784b9201cb06506098,10.1016/j.amepre.2020.06.006,The Impact of Social Vulnerability on COVID-19 in the U.S.: An Analysis of Spatially Varying Relationships,2020.0,American Journal of Preventive Medicine,Ibraheem M. Karaye; J. Horney,"Introduction Because of their inability to access adequate medical care, transportation, and nutrition, socially vulnerable populations are at an increased risk of health challenges during disasters. This study estimates the association between case counts of COVID-19 infection and social vulnerability in the U.S., identifying counties at increased vulnerability to the pandemic. Methods Using Social Vulnerability Index and COVID-19 case count data, an ordinary least squares regression model was fitted to assess the global relationship between COVID-19 case counts and social vulnerability. Local relationships were assessed using a geographically weighted regression model, which is effective in exploring spatial nonstationarity. Results As of May 12, 2020, a total of 1,320,909 people had been diagnosed with COVID-19 in the U.S. Of the counties included in this study (91.5%, 2,844 of 3,108), the highest case count was recorded in Trousdale, Tennessee (16,525.22 per 100,000) and the lowest in Tehama, California (1.54 per 100,000). At the global level, overall Social Vulnerability Index (eβ=1.65, p=0.03) and minority status and language (eβ=6.69, p<0.001) were associated with increased ",398.0,https://europepmc.org/articles/pmc7318979?pdf=render634673016620a9520f1bfa0c857a9cd68179d007e38,10.17016/feds.2004.50,The long-run relationship between house prices and rents,2004.0,,J. Gallin,"I show that when house prices are high relative to rents (that is, when the rent-price ratio is low) changes in real rents tend to be larger than usual and changes in real prices tend to be smaller than usual. Standard error-correction models provide inconclusive results about the predictive power of the rent-price ratio at a quarterly frequency. I use a long-horizon regression approach to show that the rent-price ratio helps predict changes in real rents and real prices over three-year periods. This result withstands the inclusion of a measure of the user cost of capital. I show that a long- horizon regression approach can yield biased estimates of the degree of error correction if prices have a unit root but do not follow a random walk. I construct bootstrap distributions to conduct appropriate inference in the presence of this bias. The results lend empirical support to the view that the rent-price ratio is an indicator of valuation in the housing market.",384.0,https://doi.org/10.17016/feds.2004.506354adeeb79b828aef5199a576106ce47a6b4d67563,10.1109/tgrs.2013.2265295,Direct Georeferencing of Ultrahigh-Resolution UAV Imagery,2014.0,IEEE Transactions on Geoscience and Remote Sensing,D. Turner; A. Lucieer; L. Wallace,"Micro-unmanned aerial vehicles often collect a large amount of images when mapping an area at an ultrahigh resolution. A direct georeferencing technique potentially eliminates the need for ground control points. In this paper, we developed a camera-global positioning system (GPS) module to allow the synchronization of camera exposure with the airframe's position as recorded by a GPS with 10-20-cm accuracy. Lever arm corrections were applied to the camera positions to account for the positional difference between the GPS antenna and the camera center. Image selection algorithms were implemented to eliminate blurry images and images with excessive overlap. This study compared three different software methods (Photoscan, Pix4D web service, and an in-house Bundler method). We evaluated each based on processing time, ease of use, and the spatial accuracy of the final mosaic produced. Photoscan showed the best performance as it was the fastest and the easiest to use and had the best spatial accuracy (average error of 0.11 m with a standard deviation of 0.02 m). This accuracy is limited by the accuracy of the differential GPS unit (10-20 cm) used to record camera position. Pix4D achieved ",373.0,https://figshare.com/articles/journal_contribution/Direct_georeferencing_of_ultrahigh-resolution_UAV_imagery/22907072636528f0ce730b0607cc6107d672aec344aaaae1b24,10.1016/j.eswa.2014.11.040,"Using machine learning algorithms for housing price prediction: The case of Fairfax County, Virginia housing data",2015.0,Expert systems with applications,Byeonghwa Park; J. Bae,,367.0,637b4c611206b0349365515001b524c17231bee0d41,10.1016/j.landurbplan.2020.103919,Which communities have better accessibility to green space? An investigation into environmental inequality using big data,2020.0,,Yang Chen; W. Yue; D. La Rosa,"Abstract Green space accessibility is widely acknowledged as a crucial aspect of a livable environment and human well-being. Whether green space accessibility is equitable among communities is increasingly considered as an issue of environmental justice. Therefore, this study focuses on the possible environmental inequality of green space accessibility that can be found among residential communities in the context of Chinese booming housing market. The case study of Shanghai, China was conducted with the use of big data. A real-time navigation route measurement based on Amap application programming interface (AAPI) was developed to calculate green space accessibility, and housing price was used to indicate dwellers’ socioeconomic status. Bivariate Moran’s I, multiple regression, and spatial lag regression were adopted to explore inequality of green space accessibility among residential communities. The results reveal a spatial inequality of green space accessibility between communities in central portion of the city and those in peri-urban areas. We further found a spatial mismatch between green space accessibility and housing price. Environmental inequality is evident within the i",329.0,63830fca19560538122f42c52cdce315257f9fb7b30,10.1145/2783258.2783313,Network Lasso: Clustering and Optimization in Large Graphs,2015.0,Knowledge Discovery and Data Mining,David Hallac; J. Leskovec; Stephen P. Boyd,"Convex optimization is an essential tool for modern data analysis, as it provides a framework to formulate and solve many problems in machine learning and data mining. However, general convex optimization solvers do not scale well, and scalable solvers are often specialized to only work on a narrow class of problems. Therefore, there is a need for simple, scalable algorithms that can solve many common optimization problems. In this paper, we introduce the network lasso, a generalization of the group lasso to a network setting that allows for simultaneous clustering and optimization on graphs. We develop an algorithm based on the Alternating Direction Method of Multipliers (ADMM) to solve this problem in a distributed and scalable manner, which allows for guaranteed global convergence even on large graphs. We also examine a non-convex extension of this approach. We then demonstrate that many types of problems can be expressed in our framework. We focus on three in particular --- binary classification, predicting housing prices, and event detection in time series data --- comparing the network lasso to baseline approaches and showing that it is both a fast and accurate method of solv",322.0,6396f96a2cabeed11a465645475296302fc8b60370f,10.1177/0042098019849380,"Green gentrification or ‘just green enough’: Do park location, size and function affect whether a place gentrifies or not?",2020.0,Urban studies,A. Rigolon; Jeremy Németh,"Recent research shows that the establishment of new parks in historically disinvested neighbourhoods can result in housing price increases and the displacement of low-income people of colour. Some suggest that a ‘just green enough’ approach, in particular its call for the creation of small parks and nearby affordable housing, can reduce the chances of this phenomenon some call ‘green gentrification’. Yet, no study has tested these claims empirically across a sample of diverse cities. Focusing on 10 cities in the United States, we run multilevel logistic regressions to uncover whether the location (distance from downtown), size and function (active transportation) of new parks built in the 2000–2008 and 2008–2015 periods predict whether the census tracts around them gentrified. We find that park function and location are strong predictors of gentrification, whereas park size is not. In particular, new greenway parks with an active transportation component built in the 2008–2015 period triggered gentrification more than other park types, and new parks located closer to downtown tend to foster gentrification more than parks on a city’s outskirts. These findings call into question the ",307.0,640df2c6c14cf5ff301ab5eeeabc8990f18e6094eae,10.1007/s11146-008-9159-6,A Spatial Autocorrelation Approach for Examining the Effects of Urban Greenspace on Residential Property Values,2010.0,,D. A. Conway; Christina Q. Li; J. Wolch; Christoph Kahle; M. Jerrett,,301.0,6415b4c415dd04c3c0d04702d6c70ceb02830ce4280,10.1111/1468-0084.00061,"Regional migration in Spain: the effect of personal characteristics and of unemployment, wage and house price differentials using pooled cross-sections.",1997.0,Oxford Bulletin of Economics and Statistics,P. Antolin; O. Bover,"""The purpose of this paper is to identify which regional economic factors influence male migration decisions [in Spain], taking into account personal characteristics....[We present] evidence on the importance...of the person's situation, in particular: (i) family characteristics, such as being married to a working woman, having children, or living with relatives (ii) personal factors such as education or age, and (iii) own employment situation such as being registered as unemployed as opposed to non-registered, or being self-employed.""",292.0,https://repositorio.bde.es/handle/123456789/650164225971e1916a3636f73b7657b730f00c4e2c08842,10.1111/jems.12017,"Entrepreneurship, Economic Conditions, and the Great Recession",2013.0,Social Science Research Network,R. Fairlie,"The “Great Recession” resulted in many business closings and foreclosures, but what effect did it have on business formation? On the one hand, recessions decrease potential business income and wealth, but on the other hand they restrict opportunities in the wage/salary sector leaving the net effect on entrepreneurship ambiguous. The most up-to-date microdata available – the 1996 to 2009 Current Population Survey (CPS) – are used to conduct a detailed analysis of the determinants of entrepreneurship at the individual level to shed light on this question. Regression estimates indicate that local labor market conditions are a major determinant of entrepreneurship. Higher local unemployment rates are found to increase the probability that individuals start businesses. Home ownership and local home values for home owners are also found to have positive effects on business creation, but these effects are noticeably smaller. Additional regression estimates indicate that individuals who are initially not employed respond more to high local unemployment rates by starting businesses than wage/salary workers. The results point to a consistent picture – the positive influences of slack labor m",287.0,https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdocs.iza.org%2Fdp5725.pdf;h=repec:iza:izadps:dp5725643dd16dfd2ad00bae7aeaef2bf028f271f88a08b81,10.1007/s11146-007-9036-8,"Spatial Dependence, Housing Submarkets, and House Price Prediction",2007.0,,Steven C. Bourassa; E. Cantoni; M. Hoesli,,266.0,https://access.archive-ouverte.unige.ch/access/metadata/02eb05f3-2b51-4249-b83a-fd04a016f17f/download6442523787661a067c5969467f26013e12bda9fde53,10.1080/00420987320080311,Recent Empirical Work on the Determinants of Relative House Prices,1973.0,,M. Ball,,261.0,645ba2a9e6448271b83880e6cb2b007e142588aa58b,10.1016/j.jue.2008.09.001,Why do households without children support local public schools? Linking house price capitalization to school spending,2002.0,,Christian A. L. Hilber; C. Mayer,,254.0,https://www.nber.org/papers/w10804.pdf6466cafeb257f033fbe978e0b286044d2132f71a431,10.1016/j.jpubeco.2009.01.001,The Effects of Low Income Housing Tax Credit Developments on Neighborhoods,2009.0,Journal of Public Economics,Nathaniel Baum-snow; J. Marion,"This paper evaluates the impacts of new housing developments funded with the Low Income Housing Tax Credit (LIHTC), the largest federal project based housing program in the U.S., on the neighborhoods in which they are built. A discontinuity in the formula determining the magnitude of tax credits as a function of neighborhood characteristics generates pseudo-random assignment in the number of low income housing units built in similar sets of census tracts. Tracts where projects are awarded 30 percent higher tax credits receive approximately six more low income housing units on a base of seven units per tract. These additional new low income developments cause homeowner turnover to rise, raise property values in declining areas and reduce incomes in gentrifying areas in neighborhoods near the 30th percentile of the income distribution. LIHTC units significantly crowd out nearby new rental construction in gentrifying areas but do not displace new construction in stable or declining areas.",252.0,https://www.ncbi.nlm.nih.gov/pmc/articles/382496664737643b06c7ecb224773fb8206b909413003da2bb,10.1080/09599916.2020.1832558,Predicting property prices with machine learning algorithms,2021.0,,Winky K.O. Ho; B. Tang; S. Wong,"ABSTRACT This study uses three machine learning algorithms including, support vector machine (SVM), random forest (RF) and gradient boosting machine (GBM) in the appraisal of property prices. It applies these methods to examine a data sample of about 40,000 housing transactions in a period of over 18 years in Hong Kong, and then compares the results of these algorithms. In terms of predictive power, RF and GBM have achieved better performance when compared to SVM. The three performance metrics including mean squared error (MSE), root mean squared error (RMSE) and mean absolute percentage error (MAPE) associated with these two algorithms also unambiguously outperform those of SVM. However, our study has found that SVM is still a useful algorithm in data fitting because it can produce reasonably accurate predictions within a tight time constraint. Our conclusion is that machine learning offers a promising, alternative technique in property valuation and appraisal research especially in relation to property price prediction.",249.0,https://doi.org/10.1080/09599916.2020.1832558648300314f5e798dd5e59d8480f3d23264d2f2edfa5,10.3386/w9262,Determinants of Real House Price Dynamics,2002.0,,D. Capozza; P. Hendershott; C. Mack; Christopher J. Mayer,,241.0,https://doi.org/10.3386/w9262649fcc48db9f06bf2932df2d4bb864a9a5223d315b2,10.1016/j.tra.2020.06.022,A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data,2020.0,,Xinwei Ma; Yanjie Ji; Yu-Fei Yuan; N. van Oort; Yuchuan Jin; S. Hoogendoorn,"Abstract The co-existence of traditional docked bike-sharing and emerging dockless systems presents new opportunities for sustainable transportation in cities all over the world, both serving door to door trips and accessing/egressing to/from public transport systems. However, most of the previous studies have separately examined the travel patterns of docked and dockless bike-sharing schemes, whereas the difference in travel patterns and the determinants of user demand for both systems have not been fully understood. To fill this gap, this study firstly compares the travel characteristics, including travel distance, travel time, usage frequency and spatio-temporal travel patterns by exploring the smart card data from a docked bike-sharing scheme and trip origin–destination (OD) data from a dockless bike-sharing scheme in the city of Nanjing, China over the same spatio-temporal dimension. Next, this study examines the influence of the bike-sharing fleets, socio-demographic factors and land use factors on user demand of both bike-sharing systems using multi-sourced data (e.g., trip OD information, smart card, survey, land use information, and housing prices data). To this end, geogr",237.0,http://resolver.tudelft.nl/uuid:fbc59458-3398-45ef-bc36-b3fb99de20e7650f697988873fe97ba107099f9d2826bf630e534a5,10.1289/ehp898,"Race/Ethnicity, Socioeconomic Status, Residential Segregation, and Spatial Variation in Noise Exposure in the Contiguous United States",2017.0,Environmental Health Perspectives,Joan A. Casey; R. Morello-Frosch; D. Mennitt; K. Fristrup; E. Ogburn; Peter James,"Background: Prior research has reported disparities in environmental exposures in the United States, but, to our knowledge, no nationwide studies have assessed inequality in noise pollution. Objectives: We aimed to a) assess racial/ethnic and socioeconomic inequalities in noise pollution in the contiguous United States; and b) consider the modifying role of metropolitan level racial residential segregation. Methods: We used a geospatial sound model to estimate census block group–level median (L50) nighttime and daytime noise exposure and 90th percentile (L10) daytime noise exposure. Block group variables from the 2006–2010 American Community Survey (ACS) included race/ethnicity, education, income, poverty, unemployment, homeownership, and linguistic isolation. We estimated associations using polynomial terms in spatial error models adjusted for total population and population density. We also evaluated the relationship between race/ethnicity and noise, stratified by levels of metropolitan area racial residential segregation, classified using a multigroup dissimilarity index. Results: Generally, estimated nighttime and daytime noise levels were higher for census block groups with hi",237.0,https://doi.org/10.1289/ehp898651b6940ef9a423f22a3e755460fdfba329dd5276c8,10.1111/1468-2427.12740,Contradictions of the Climate‐Friendly City: New Perspectives on Eco‐Gentrification and Housing Justice,2019.0,International Journal of Urban and Regional Research,J. Rice; D. Cohen; Joshua Long; Jason R. Jurjevich,"Abstract As local governments and corporations promote ?climate friendliness?, and a low-carbon lifestyle becomes increasingly desirable, more middle- and upper-income urban residents are choosing to live near public transit, on bike- and pedestrian-friendly streets, and in higher-density mixed-use areas. This rejection of classical forms of suburbanization has, in part, increased property values in neighborhoods offering these amenities, displacing lower-income, often non-white, residents. Increased prevalence of creative and technology workers appears to accelerate this trend. We argue that a significant and understudied socio-environmental contradiction also occurs where the actual environmental outcomes of neighborhood transformation may not be what we expect. New research on greenhouse gas emissions shows that more affluent residents have much larger carbon footprints because of their consumption, even when reductions in transportation or building energy emissions are included. We describe an area in Seattle, Washington, the location of Amazon's headquarters, experiencing this contradiction and show a distinct convergence of city investments in low-carbon infrastructure, signi",235.0,https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/1468-2427.1274065262aa64d9f931279cff0fd84a3cc10c02b2b33828,10.1016/j.ijinfomgt.2020.102072,China's prefectural digital divide: Spatial analysis and multivariate determinants of ICT diffusion,2020.0,International Journal of Information Management,Zhou-Ying Song; Chen Wang; Luke Bergmann,"Abstract Much research has made efforts to elaborate upon different dimensions to the digital divide, including informational and communications technology (ICT) access, ICT usage, and ICT outcomes. We assess the utility of such perspectives for studying digital inequality across prefectural cities in China. China is the world's largest ICT market in terms of the number of mobile devices in use, internet users, and broadband subscriptions, yet it has notable digital inequality within and between provinces, prefectural cities, and counties. In this study, we built a conceptual framework of digital divides for prefectural cities in China, examined spatial agglomeration using cluster analysis, and explored the leading correlates using a geographically-weighted regression (GWR) model. A large digital divide among the prefectural cities in China was revealed, with cities with a high administrative level having a relatively high digital development index(DDI) score. Prefectural cities with high DDI levels are mainly agglomerated in large metropolitan areas, such as Beijing–Tianjin–Hebei, the Yangtze River Delta, the Pearl River Delta, and the West Coast Economic Zone of the Taiwan Strait",227.0,65364265d2ad7835e3be4855ed60dd439671b2397b0,10.1016/j.trd.2020.102387,"Accessibility to transit, by transit, and property prices: Spatially varying relationships",2020.0,,Lin-Chuan Yang; K. W. Chau; W. Szeto; Xu Cui; Xu Wang,"Abstract Accessibility to transit facilities is perceived to affect property prices. However, accessibility by transit has rarely elicited adequate scholarly attention in property price analyses. Additionally, previous studies on how transit accessibility affects property prices mainly focused on rail and bus rapid transit systems, while conventional bus transit, which is very popular in many contexts, has seldom been investigated. Moreover, whether there is spatial heterogeneity in the price (or capitalization) effects of conventional bus accessibility remains to be explored. To fill these gaps, this study aims to investigate the role of accessibility to and by bus in determining housing prices in a bus-dependent city where urban transit service is offered mainly by a bus system rather than other transit systems. Using a database of 4966 condominium units in Xiamen, China, this study develops a battery of spatial econometric models to estimate global and local relationships between to-bus and by-bus accessibility and housing prices. The findings are as below: (1) to-bus accessibility (measured by the number of nearby bus stops) is positively associated with nearby housing prices; ",225.0,65450e7b0d8e722b27bc7683ded32aa91e97444bca0,10.1038/s41467-021-24638-z,A generalizable and accessible approach to machine learning with global satellite imagery,2020.0,Nature Communications,Esther Rolf; J. Proctor; T. Carleton; I. Bolliger; Vaishaal Shankar; Miyabi Ishihara; B. Recht; S. Hsiang,"Combining satellite imagery with machine learning (SIML) has the potential to address global challenges by remotely estimating socioeconomic and environmental conditions in data-poor regions, yet the resource requirements of SIML limit its accessibility and use. We show that a single encoding of satellite imagery can generalize across diverse prediction tasks (e.g., forest cover, house price, road length). Our method achieves accuracy competitive with deep neural networks at orders of magnitude lower computational cost, scales globally, delivers label super-resolution predictions, and facilitates characterizations of uncertainty. Since image encodings are shared across tasks, they can be centrally computed and distributed to unlimited researchers, who need only fit a linear regression to their own ground truth data in order to achieve state-of-the-art SIML performance. This paper presents MOSAIKS, a system for planet-scale prediction of multiple outcomes using satellite imagery and machine learning (SIML). MOSAIKS generalizes across prediction domains and has the potential to enhance accessibility of SIML across research disciplines.",219.0,https://www.nature.com/articles/s41467-021-24638-z.pdf65590d123d23d3a8056f93170c4c292f2a2aead40ec,10.1023/b:real.0000035309.60607.53,Modeling Spatial and Temporal House Price Patterns: A Comparison of Four Models,2004.0,,B. Case; J. Clapp; R. Dubin; Mauricio Rodríguez,,214.0,6564acd3ea1b225db4078b10d54b4e10b55d5e86b0c,10.1016/j.habitatint.2017.03.010,"Spatial effects of accessibility to parks on housing prices in Shenzhen, China",2017.0,,Chao Wu; Xin-Yue Ye; Qingyun Du; P. Luo,,209.0,657293598d214c9c0cbe70f29732ad1e246e3ad58a2,10.1016/j.regsciurbeco.2017.08.006,Spatial-difference-in-differences models for impact of new mass rapid transit line on private housing values,2017.0,,M. Diao; Delon Leonard; T. Sing,,207.0,658b095d5a8a3646874672556964a170e5f163f6172,10.1016/j.econlet.2021.110010,The impact of the COVID-19 pandemic on the demand for density: Evidence from the U.S. housing market,2020.0,Economics Letters,Sitian Liu; Yichen Su,"We study the impact of the COVID-19 pandemic on the location demand for housing. We find that the pandemic has led to a shift in housing demand away from neighborhoods with high population density. The reduced demand for density is driven partially by the diminished need for living close to telework-compatible jobs and the declining value of access to consumption amenities. Neighborhoods with high pre-COVID-19 home values also see a greater drop in housing demand. Moreover, we find a significant shift in housing demand away from large cities, though the magnitude is smaller.",206.0,https://doi.org/10.24149/wp2024659d19eb4a611bab60f837d920bc857c17cb54e7e4c,10.1111/0017-4815.00135,The Impact of Airport Noise and Proximity on Residential Property Values,2000.0,,M. Espey,,206.0,https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2474636606d0d022c3468648830de11a1dfa8a2063899800e,10.1016/j.aap.2009.12.008,"The risk of pedestrian injury and fatality in collisions with motor vehicles, a social ecological study of state routes and city streets in King County, Washington.",2011.0,Accident Analysis and Prevention,A. Moudon; Lin Lin; J. Jiao; P. Hurvitz; P. Reeves,"This study examined the correlates of injury severity using police records of pedestrian-motor-vehicle collisions on state routes and city streets in King County, Washington. Levels of influence on collision outcome considered (1) the characteristics of individual pedestrians and drivers and their actions; (2) the road environment; and (3) the neighborhood environment. Binary logistic regressions served to estimate the risk of a pedestrian being severely injured or dying versus suffering minor or no injury. Significant individual-level influences on injury severity were confirmed for both types of roads: pedestrians being older or younger; the vehicle moving straight on the roadway. New variables associated with increased risk of severe injury or death included: having more than two pedestrians involved in a collision; and on city streets, the driver being inebriated. Road intersection design was significant only in the state route models, with pedestrians crossing at intersections without signals increasing the risk of being injured or dying. Adjusting for pedestrians' and drivers' characteristics and actions, neighborhood medium home values and higher residential densities increa",205.0,https://ink.library.smu.edu.sg/context/cis_research/article/1516/viewcontent/1_s2.0_S0001457509003224_main.pdf661725517c0f26df639a7e692031d664c717c34f19f,10.1111/1540-6229.00745,"New Place-to-Place Housing Price Indexes for U.S. Metropolitan Areas, and Their Determinants",1996.0,,S. Malpezzi; Gregory H. Chun; Richard K. Green,,201.0,6626aa1db4bcb1766c9d956578c29ac1dc094fc19fe,10.1080/01621459.2013.766613,Robust Variable Selection with Exponential Squared Loss,2013.0,Journal of the American Statistical Association,Xueqin Wang; Yun-Lu Jiang; Mian Huang; He-Ping Zhang,"Robust variable selection procedures through penalized regression have been gaining increased attention in the literature. They can be used to perform variable selection and are expected to yield robust estimates. However, to the best of our knowledge, the robustness of those penalized regression procedures has not been well characterized. In this article, we propose a class of penalized robust regression estimators based on exponential squared loss. The motivation for this new procedure is that it enables us to characterize its robustness in a way that has not been done for the existing procedures, while its performance is near optimal and superior to some recently developed methods. Specifically, under defined regularity conditions, our estimators are -consistent and possess the oracle property. Importantly, we show that our estimators can achieve the highest asymptotic breakdown point of 1/2 and that their influence functions are bounded with respect to the outliers in either the response or the covariate domain. We performed simulation studies to compare our proposed method with some recent methods, using the oracle method as the benchmark. We consider common sources of influen",200.0,https://europepmc.org/articles/pmc3727454?pdf=render66328dc1a03820c12eca42272a624bf4f0d55143309,10.1201/9781420057744.ch9,Spatial data analysis,2024.0,ACM SIGSPATIAL International Workshop on Advances in Geographic Information Systems,Tobias Rüttenauer,"This handbook chapter provides an essential introduction to the field of spatial econometrics, offering a comprehensive overview of techniques and methodologies for analysing spatial data in the social sciences. Spatial econometrics addresses the unique challenges posed by spatially dependent observations, where spatial relationships among data points can be of substantive interest or can significantly impact statistical analyses. The chapter begins by exploring the fundamental concepts of spatial dependence and spatial autocorrelation, and highlighting their implications for traditional econometric models. It then introduces a range of spatial econometric models, particularly spatial lag, spatial error, spatial lag of X, and spatial Durbin models, illustrating how these models accommodate spatial relationships and yield accurate and insightful results about the underlying spatial processes. The chapter provides an intuitive guide on how to interpret those different models. A practical example on London house prices demonstrates the application of spatial econometrics, emphasising its relevance in uncovering hidden spatial patterns, addressing endogeneity, and providing robust esti",200.0,66492d7ef83720ccbc959e3aa190d5c3dc6c0554545,10.1046/j.1080-8620.2003.00079.x,Modeling Spatial Variation in Housing Prices: A Variable Interaction Approach,2003.0,,T. Fik; David C. Ling; Gordon F. Mulligan,,200.0,665a289a62de4e9f34c166950d208e0878d2e993527,10.1016/j.landurbplan.2011.11.012,"Estimating the value of urban green areas: A hedonic pricing analysis of the single family housing market in Los Angeles, CA",2012.0,,J. Saphores; Wei Li,,197.0,666f4317b518c1f9f9fafd4a71cb0a32fe40b2b9f24,10.1016/j.euroecorev.2009.12.005,"Asset Prices, Exchange Rates and the Current Account",2007.0,Social Science Research Network,M. Fratzscher; Luciana Juvenal; Lucio Sarno,"This paper analyses the role of asset prices in comparison to other factors, in particular exchange rates, as a driver of the US trade balance. It employs a Bayesian structural VAR model that requires imposing only a minimum of economically meaningful sign restrictions. We find that equity market shocks and housing price shocks have been major determinants of the US current account in the past, accounting for up to 30% of the movements of the US trade balance at a horizon of 20 quarters. By contrast, shocks to the real exchange rate have been less relevant, explaining about 9% and exerting a more temporary effect on the US trade balance. Our findings suggest that large exchange rate movements may not necessarily be the key element of an adjustment of today's large current account imbalances, and that in particular relative global asset price changes could be a potent source of adjustment.",192.0,https://s3.amazonaws.com/real.stlouisfed.org/wp/2008/2008-031.pdf667b7e7ef7a7371520eb3b29e1eff2990ea7d611ed8,10.1016/j.landusepol.2020.104919,Understanding house price appreciation using multi-source big geo-data and machine learning,2020.0,Land Use Policy,Yu-Hao Kang; Fan Zhang; Wenzhe Peng; Song Gao; Jin-Meng Rao; Fábio Duarte; C. Ratti,"Abstract Understanding house price appreciation benefits place-based decision makings and real estate market analyses. Although large amounts of interests have been paid in the house price modeling, limited work has focused on evaluating the price appreciation rate. In this study, we propose a data-fusion framework to examine how well house price appreciation potentials can be predicted by combining multiple data sources. We used data sets including house structural attributes, house photos, locational amenities, street view images, transportation accessibility, visitor patterns, and socioeconomic attributes of neighborhoods to enrich our understanding of the real estate appreciation and its predictive modeling. As a case study, we investigate more than 20,000 houses in the Greater Boston Area, and discuss the spatial dependency of house price appreciations, influential variables and their relationships. In detail, we extract deep features from street view images and house photos using a deep learning model, merging features from multi-source data and modeling house price appreciation using machine learning models and the geographically weighted regression at two spatial scales: fi",190.0,66884b875c83cbfda9867894fd542d13cad33554a68,10.1080/13658816.2018.1545158,Multiscale geographically and temporally weighted regression: exploring the spatiotemporal determinants of housing prices,2018.0,International Journal of Geographical Information Science,Chao Wu; F. Ren; Weinbin Hu; Qingyun Du,"ABSTRACT Understanding scale effects is important and indispensable for geography studies. However, spatial and spatiotemporal statistical tools for measuring the operational scales of different processes are rather limited. This article extends the popular geographically and temporally weighted regression (GTWR) model to consider operational scale effects by proposing multiscale GTWR (MGTWR), which offers a flexible and scalable framework for identifying and analysing multiscale processes by specifying flexible bandwidths for various covariates. Then, MGTWR is employed to explore spatiotemporal variations and how influential factors are associated with housing prices in Shenzhen. This article attempts to extend GTWR to MGTWR in consideration of scale effects, thereby highlighting the importance of different levels of spatiotemporal heterogeneity. Furthermore, the empirical results of this study can provide valuable policy implications for real estate development in areas where urban planning should address multiscale effects in both temporal and spatial dimensions.",190.0,6696d69cd4c520c1d55a76d180563d89196fe959c0d,10.1016/j.cities.2019.102405,"An environmental justice study on spatial access to parks for youth by using an improved 2SFCA method in Wuhan, China",2020.0,Cities,Li-Jun Xing; Yan-Fang Liu; Baoshun Wang; Yi-Heng Wang; Haijian Liu,"Abstract Recent environmental justice studies have focused on measuring access to parks for young people due to the decreasing contact with nature for outdoor activities in most developed countries. Results of these analyses reflect the disparities in accessibility better but with digress among different access models. The present study aims to explore an appropriate accessibility measurement for youth and proposes a supply-demand improved two step floating catchment area (2FSCA) method to estimate environmental justice in access to parks in developing countries. Results indicated that the proposed method could identify more underserved communities and youth population with lower mean values of accessibility compared with the traditional 2SFCA method. Spatial accessibility exhibited clustering characteristics in three scenarios wherein high-accessibility areas were clustered nearby the center along the Yangtze River with larger parks, whereas those with low-accessibility were distributed in the eastern and southern regions. Among three age groups, the 0–6 years age group had slightly higher disparity of accessibility than the 7–12 years age group and the majority of teenagers could",188.0,670f401a73c829e59705aa4f541c4391d51382f8036,10.1080/24694452.2024.2350982,GeoShapley: A Game Theory Approach to Measuring Spatial Effects in Machine Learning Models,2023.0,Annals of the American Association of Geographers,Ziqi Li,"This article introduces GeoShapley, a game theory approach to measuring spatial effects in machine learning models. GeoShapley extends the Nobel Prize–winning Shapley value framework in game theory by conceptualizing location as a player in a model prediction game, which enables the quantification of the importance of location and the synergies between location and other features in a model. GeoShapley is a model-agnostic approach and can be applied to statistical or black-box machine learning models in various structures. The interpretation of GeoShapley is directly linked with spatially varying coefficient models for explaining spatial effects and additive models for explaining non-spatial effects. Using simulated data, GeoShapley values are validated against known data-generating processes and are used for cross-comparison of seven statistical and machine learning models. An empirical example of house price modeling is used to illustrate GeoShapley’s utility and interpretation with real-world data. The method is available as an open source Python package named geoshapley.",188.0,https://www.tandfonline.com/doi/pdf/10.1080/24694452.2024.2350982?needAccess=true671ca513f08cb6330e43b54983e2bd63a91e9e7ba4f,10.1371/journal.pone.0250080,A city of cities: Measuring how 15-minutes urban accessibility shapes human mobility in Barcelona,2021.0,PLoS ONE,Eduardo Graells-Garrido; Feliu Serra-Burriel; Francisco Rowe; F. Cucchietti; Patricio Reyes,"As cities expand, human mobility has become a central focus of urban planning and policy making to make cities more inclusive and sustainable. Initiatives such as the “15-minutes city” have been put in place to shift the attention from monocentric city configurations to polycentric structures, increasing the availability and diversity of local urban amenities. Ultimately they expect to increase local walkability and increase mobility within residential areas. While we know how urban amenities influence human mobility at the city level, little is known about spatial variations in this relationship. Here, we use mobile phone, census, and volunteered geographical data to measure geographic variations in the relationship between origin-destination flows and local urban accessibility in Barcelona. Using a Negative Binomial Geographically Weighted Regression model, we show that, globally, people tend to visit neighborhoods with better access to education and retail. Locally, these and other features change in sign and magnitude through the different neighborhoods of the city in ways that are not explained by administrative boundaries, and that provide deeper insights regarding urban char",187.0,https://doi.org/10.1371/journal.pone.02500806723b242d6890d90a3efdca2dcacfb5e0c709c67cee,10.3386/w26142,Income Growth and the Distributional Effects of Urban Spatial Sorting,2019.0,Social Science Research Network,Victor Couture; C. Gaubert; Jessie Handbury; Erik Hurst,"673 We explore the impact of rising incomes at the top of the distribution on spatial sorting patterns within large U.S. cities. We develop and quantify a spatial model of a city with heterogeneous agents and non-homothetic preferences for neighborhoods with endogenous amenity quality. As the rich get richer, demand increases for the high-quality amenities available in downtown neighborhoods. Rising demand drives up house prices and spurs the development of higher quality neighborhoods downtown. This gentrification of downtowns makes poor incumbents worse off, as they are either displaced to the suburbs or pay higher rents for amenities that they do not value as much. We quantify the corresponding impact on well-being inequality. Through the lens of the quantified model, the change in the income distribution between 1990 and 2014 led to neighborhood change and spatial resorting within urban areas that increased the welfare of richer households relative to that of poorer households, above and beyond rising nominal income inequality.",184.0,http://www.nber.org/papers/w26142.pdf6749f8dd6d7d285b9c85074afd18cda4ad19c0a9688,10.1016/j.cities.2019.05.028,Discovering the spatio-temporal impacts of built environment on metro ridership using smart card data,2019.0,,En-Hui Chen; Zhirui Ye; Chao Wang; Wenbo Zhang,"Abstract The primary objective of this study is to identify the spatio-temporal relationship between metro ridership and built environment by integrating smart card data with online point of interest (POI) data. This study proposes the geographically weighted regression (GWR) model to address the spatial autocorrelation and nonstationarity of metro ridership at the station level. Different from the Euclidean distance (ED) commonly used in the traditional GWR, the Minkowski distance (MD) metric is introduced into the study to measure geographical distance and improve weighting matrix calibrations. This study provides useful insights in adaptive model settings based on selections of spatial range and distance metric parameters. A case study is conducted in Nanjing, China, by utilizing large-scale metro smart card data and POI data obtained from the Gaode map by a web crawler written in Python. The comparative analysis indicates that MD-GWR achieves better goodness-of-fit than the global ordinary least squares (OLS) and traditional GWR in the case of modeling metro ridership. Finally, this study quantifies the impacts of built environment at both spatial and temporal scales, under the",182.0,67578dccbcc7eeb5e8c3e11cfe3959dc5e13733eb81,10.1111/j.1468-5957.2006.00638.x,"House prices, fundamentals and bubbles",2006.0,,Angela J. Black; P. Fraser; Martin Hoesli,"This paper studies actual (real) house prices relative to fundamental (real) house values. Such a focus is warranted since housing constitutes a large fraction of most household portfolios, and its characteristics are such that, in contrast to what prevails in financial markets, arbitrage will be limited and hence correction toward 'true' value is likely to be a prolonged process. Using UK data and a time-varying present value approach, our results preclude the existence of an explosive rational bubble due to non-fundamental factors. We further find that intrinsic bubbles have an important role to play in determining actual house prices although price dynamics appear to impact, particularly in periods of strong deviation from fundamental value. Price dynamics are found to be driven by momentum behaviour. Copyright 2006 The Authors Journal compilation (c) 2006 Blackwell Publishing Ltd.",179.0,https://archive-ouverte.unige.ch/unige:3656267654193afb4da3db05fdfee04faff9c521675f7e62,10.1145/3342240,Take a Look Around,2018.0,ACM Transactions on Intelligent Systems and Technology,S. Law; Brooks Paige; C. Russell,"When an individual purchases a home, they simultaneously purchase its structural features, its accessibility to work, and the neighborhood amenities. Some amenities, such as air quality, are measurable while others, such as the prestige or the visual impression of a neighborhood, are difficult to quantify. Despite the well-known impacts intangible housing features have on house prices, limited attention has been given to systematically quantifying these difficult to measure amenities. Two issues have led to this neglect. Not only do few quantitative methods exist that can measure the urban environment, but that the collection of such data is both costly and subjective. We show that street image and satellite image data can capture these urban qualities and improve the estimation of house prices. We propose a pipeline that uses a deep neural network model to automatically extract visual features from images to estimate house prices in London, UK. We make use of traditional housing features such as age, size, and accessibility as well as visual features from Google Street View images and Bing aerial images in estimating the house price model. We find encouraging results where learnin",174.0,http://arxiv.org/abs/1807.071556771196e55c7401009f4e60d7c8db96469c1e13b00e,10.1017/s1068280500002483,Capitalization of Open Spaces into Housing Values and the Residential Property Tax Revenue Impacts of Agricultural Easement Programs,2003.0,Agricultural and Resource Economics Review,J. Geoghegan; L. Lynch; S. Bucholtz,,169.0,https://www.cambridge.org/core/services/aop-cambridge-core/content/view/076D57A450320D5F9147EF29B57F5650/S1068280500002483a.pdf/div-class-title-capitalization-of-open-spaces-into-housing-values-and-the-residential-property-tax-revenue-impacts-of-agricultural-easement-programs-div.pdf678c48b0e1b9df9d2ca997b90fd77c5ee7fc68af2a9,10.1016/j.jue.2008.06.002,"Changes in the distribution of house prices over time: Structural characteristics, neighborhood, or coefficients?",2008.0,,Daniel P. McMillen,,168.0,679ff67e0f67e71d0324ad2684ee7aba4eae2cba2e0,10.1111/j.1475-5890.2008.00074.x,The Anticipated Capitalisation Effect of a New Metro Line on Housing Prices,2008.0,,Claudio A. Agostini; G. Palmucci,,168.0,68077bd2c12a79311a7a3efb580b21cf763dde662ac,10.5751/es-01504-110103,Urban Containment Policies and the Protection of Natural Areas: The Case of Seoul's Greenbelt,2006.0,,D. Bengston; Y. Youn,"Countries around the world have responded to the problems associated with rapid urban growth and increasingly land-consumptive development patterns by creating a wide range of policy instruments designed to manage urban growth. Of the array of growth management techniques, urban containment policies are considered by some to be a promising approach. This paper focuses on greenbelts, the most restrictive form of urban containment policy. The long-standing greenbelt of Seoul, Republic of Korea is examined as a case study. Seoul's greenbelt has generated both significant social costs and benefits. Costs include higher land and housing prices in the urban area surrounded by the greenbelt, additional costs incurred by commuters who live beyond the greenbelt and work in Seoul, and increased congestion and related quality of life impacts. Benefits include the amenity value of living near the greenbelt, recreational resources, bequest and heritage values, fiscal savings due to increased efficiency in the provision of public services and infrastructure, and a wide range of life-supporting ecosystem services. After standing virtually unchanged for almost three decades, Korea's greenbelt poli",166.0,https://www.ecologyandsociety.org/vol11/iss1/art3/ES-2005-1504.pdf681a03a47a7745d227abfc80b28bb977544f2c1afd1,10.1016/j.procs.2022.01.100,House Price Prediction using Random Forest Machine Learning Technique,2021.0,International Conference on Information Technology and Quantitative Management,A. B. Adetunji; N. Akande; F. Ajala; O. Oyewo; Y. Akande; Gbenle Oluwadara,,166.0,https://www.sciencedirect.com/science/article/pii/S1877050922001016/pdf682d66a05fcbc4b4524cdd12fc86641d53ea2ed7dec,10.1371/journal.pone.0148952,Lower Neighborhood Socioeconomic Status Associated with Reduced Diversity of the Colonic Microbiota in Healthy Adults,2016.0,PLoS ONE,G. Miller; P. Engen; P. Gillevet; M. Shaikh; M. Sikaroodi; C. Forsyth; Ece A. Mutlu; A. Keshavarzian,"In the United States, there are persistent and widening socioeconomic gaps in morbidity and mortality from chronic diseases. Although most disparities research focuses on person-level socioeconomic-status, mounting evidence suggest that chronic diseases also pattern by the demographic characteristics of neighborhoods. Yet the biological mechanisms underlying these associations are poorly understood. There is increasing recognition that chronic diseases share common pathogenic features, some of which involve alterations in the composition, diversity, and functioning of the gut microbiota. This study examined whether socioeconomic-status was associated with alpha-diversity of the colonic microbiota. Forty-four healthy adults underwent un-prepped sigmoidoscopy, during which mucosal biopsies and fecal samples were collected. Subjects’ zip codes were geocoded, and census data was used to form a composite indicator of neighborhood socioeconomic-status, reflecting household income, educational attainment, employment status, and home value. In unadjusted analyses, neighborhood socioeconomic-status explained 12–18 percent of the variability in alpha-diversity of colonic microbiota. The dire",162.0,https://doi.org/10.1371/journal.pone.01489526833b4f9afbb72a914409944041ae8918e3e066d8d9,10.1016/s0198-9715(03)00018-8,Interpolation methods for spatio-temporal geographic data,2004.0,"Computers, Environment and Urban Systems",Lixin Li; P. Revesz,"We consider spatio-temporal interpolation of geographic data using both the reduction method, which treats time as an independent dimension, and the extension method, which treats time as equivalent to a spatial dimension. We adopt both 2-D and 3-D shape functions from finite element methods for the spatio-temporal interpolation of 2-D spatial and 1-D temporal data sets. We also develop new 4-D shape functions and use them for the spatio-temporal interpolation of 3-D spatial and 1-D temporal data sets. Using an actual real estate data set with house prices, we compare these methods with other spatio-temporal interpolation methods based on inverse distance weighting and kriging. The comparison criteria include interpolation accuracy, error-proneness to time aggregation, invariance to scaling on the coordinate axes, and the type of constraints used in the representation of the interpolated data. Our experimental results show that the extension method based on shape functions is the most accurate and the overall best spatio-temporal interpolation method. New color rendering algorithms are also developed for the visualization of time slices of the interpolated spatio-temporal data. We ",159.0,68430a9ec3fc7f89e83e46a8d5d8577fec08aeb4a62,10.1016/j.landusepol.2020.105023,Land finance dependence and urban land marketization in China: The perspective of strategic choice of local governments on land transfer,2020.0,,Xin-Gang Fan; Sai-Nan Qiu; Yu-Kun Sun,"Abstract In the context of tax-sharing system, the issue of using profits from land transfers to cover local government deficits has attracted widespread attention. However, research on how local governments contingently choose different types of urban land transfer methods and the transfer volumes remains limited. This paper utilizes China’s transfer of land parcels data from 2007 to 2016 to calculate the marketization level of different types of urban land, and investigates the driving forces of urban land marketization in China, paying special attention to land finance dependence and urban land marketization. We find that urban land marketization level is increasing. Among different urban land types, residential land has the highest marketization level, while industrial land has seen the largest increase in marketization. The results of a spatial lag model also show that when local governments increase the level of land marketization, governments in neighboring regions react correspondingly. Judging from the status quo of economic development in most cities, local governments usually tackle financial deficits by vigorously promoting urban land marketization, but they tend to pri",157.0,68599d884a6f8dbe34c9d19aaf0ea0da41c46efa9bc,10.1080/01621459.2021.1956937,Wasserstein Regression,2020.0,Journal of the American Statistical Association,Ya-Qing Chen; Zhenhua Lin; Hans-Georg Müller,"Abstract The analysis of samples of random objects that do not lie in a vector space is gaining increasing attention in statistics. An important class of such object data is univariate probability measures defined on the real line. Adopting the Wasserstein metric, we develop a class of regression models for such data, where random distributions serve as predictors and the responses are either also distributions or scalars. To define this regression model, we use the geometry of tangent bundles of the space of random measures endowed with the Wasserstein metric for mapping distributions to tangent spaces. The proposed distribution-to-distribution regression model provides an extension of multivariate linear regression for Euclidean data and function-to-function regression for Hilbert space-valued data in functional data analysis. In simulations, it performs better than an alternative transformation approach where one maps distributions to a Hilbert space through the log quantile density transformation and then applies traditional functional regression. We derive asymptotic rates of convergence for the estimator of the regression operator and for predicted distributions and also stud",156.0,686ec63c3fbb71c48fb41af79adb6e35a856b60e736,10.1080/00420980600990928,Determinants of House Price: A Decision Tree Approach,2006.0,,Gang-Zhi Fan; S. Ong; H. Koh,,156.0,6878dce8ee31abff6423a50e1ad0facb9c4304edda6,10.1016/j.jenvman.2018.11.110,Gully erosion zonation mapping using integrated geographically weighted regression with certainty factor and random forest models in GIS.,2019.0,Journal of Environmental Management,A. Arabameri; B. Pradhan; K. Rezaei,"Every year, gully erosion causes substantial damage to agricultural land, residential areas and infrastructure, such as roads. Gully erosion assessment and mapping can facilitate decision making in environmental management and soil conservation. Thus, this research aims to propose a new model by combining the geographically weighted regression (GWR) technique with the certainty factor (CF) and random forest (RF) models to produce gully erosion zonation mapping. The proposed model was implemented in the Mahabia watershed of Iran, which is highly sensitive to gully erosion. Firstly, dependent and independent variables, including a gully erosion inventory map (GEIM) and gully-related causal factors (GRCFs), were prepared using several data sources. Secondly, the GEIM was randomly divided into two groups: training (70%) and validation (30%) datasets. Thirdly, tolerance and variance inflation factor indicators were used for multicollinearity analysis. The results of the analysis corroborated that no collinearity exists amongst GRCFs. A total of 12 topographic, hydrologic, geologic, climatologic, environmental and soil-related GRCFs and 150 gully locations were used for modelling. The wa",155.0,https://opus.lib.uts.edu.au/bitstream/10453/130787/2/JEMA-D-18-04956R1.pdf688f300cd3fcc1d1c9e1e554d644c2e3b3b26cfb3b1,10.1016/j.apgeog.2016.12.003,Identifying the determinants of housing prices in China using spatial regression and the geographical detector technique,2017.0,,Yang Wang; Shaojian Wang; Guang-Dong Li; Hong'ou Zhang; Lixia Jin; Yong-Xian Su; Kang-Min Wu,,155.0,68950069676e51c48ef88d110de535147675b945e39,10.1080/09599916.2020.1858937,Metrics for evaluating the performance of machine learning based automated valuation models,2021.0,,Miriam Steurer; R. Hill; Norbert Pfeifer,"ABSTRACT Automated Valuation Models (AVMs) based on Machine Learning (ML) algorithms are widely used for predicting house prices. While there is consensus in the literature that cross-validation (CV) should be used for model selection in this context, the interdisciplinary nature of the subject has made it hard to reach consensus over which metrics to use at each stage of the CV exercise. We collect 48 metrics (from the AVM literature and elsewhere) and classify them into seven groups according to their structure. Each of these groups focuses on a particular aspect of the error distribution. Depending on the type of data and the purpose of the AVM, the needs of users may be met by some classes, but not by others. In addition, we show in an empirical application how the choice of metric can influence the choice of model, by applying each metric to evaluate five commonly used AVM models. Finally – since it is not always practicable to produce 48 different performance metrics – we provide a short list of 7 metrics that are well suited to evaluate AVMs. These metrics satisfy a symmetry condition that we find is important for AVM performance, and can provide a good overall model perform",154.0,https://www.tandfonline.com/doi/pdf/10.1080/09599916.2020.1858937?needAccess=true690ada940af79b65a3bf6d41eca4169f39d460c83e0,10.1257/pol.20150578,Trade Shocks and the Provision of Local Public Goods,2017.0,Social Science Research Network,Leo Feler; M. Z. Senses,"We analyze the impact of trade-induced income shocks on the size of local government, and the provision of public services. Areas in the US with declining labor demand and incomes due to increasing import competition from China experience relative declines in housing prices and business activity. Since local governments are disproportionately funded through property and sales taxation, declining property values and a decrease in economic activity translate into less revenue, which constrains the ability of local governments to provide public services. State and federal governments have limited ability to smooth local shocks, and the impact on the provision of public services is compounded when local income shocks are highly correlated with shocks in the rest of the state. The outcome is greater inequality not only in incomes but also in the quality of public services and amenities across US jurisdictions.",153.0,https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdocs.iza.org%2Fdp10231.pdf;h=repec:iza:izadps:dp10231691e74dce110afd377849f60841d3e42a1329bf5be7,10.1002/eng2.12599,A boosting ensemble learning based hybrid light gradient boosting machine and extreme gradient boosting model for predicting house prices,2022.0,Engineering Reports,Racheal Sibindi; R. Mwangi; A. Waititu,"The implementation of tree‐ensemble models has become increasingly essential in solving classification and prediction problems. Boosting ensemble techniques have been widely used as individual machine learning algorithms in predicting house prices. One of the techniques is LGBM algorithm that employs leaf wise growth strategy, reduces loss and improves accuracy during training which results in overfitting. However, XGBoost algorithm uses level wise growth strategy which takes time to compute resulting in higher computation time. Nevertheless, XGBoost has a regularization parameter, implements column sampling and weight reduction on new trees which combats overfitting. This study focuses on developing a hybrid LGBM and XGBoost model in order to prevent overfitting through minimizing variance whilst improving accuracy. Bayesian hyperparameter optimization technique is implemented on the base learners in order to find the best combination of hyperparameters. This resulted in reduced variance (overfitting) in the hybrid model since the regularization parameter values were optimized. The hybrid model is compared to LGBM, XGBoost, Adaboost and GBM algorithms to evaluate its performance i",152.0,https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/eng2.125996924e8c18bf0cf53a7a2c58d4c3e46187ca86b4aa4c,10.2139/ssrn.1280157,Beautiful city: Leisure amenities and urban growth,2019.0,Journal of Regional Science,Gerald A. Carlino; Albert Saiz,"Modern urban economic theory and policymakers are coming to see the provision of consumer leisure amenities as a way to attract population, especially the highly skilled and their employers. However, past studies have only provided indirect evidence of the importance of leisure amenities for urban development. In this paper we propose and validate the number of leisure trips to MSAs as a measure of consumer revealed preferences for local leisure-oriented amenities. Population and employment growth in the 1990s was about 2 percent higher in an MSA with twice as many leisure visits: the third most important predictor of recent population growth in standardized terms. Moreover, this variable does a good job at forecasting out-of-sample growth for the period 2000-2006. ""Beautiful cities"" disproportionally attracted highly-educated individuals, and experienced faster housing price appreciation, especially in supply-inelastic markets. Investment by local government in new public recreational areas within an MSA was positively associated with higher subsequent city attractiveness. In contrast to the generally declining trends in the American central city, neighborhoods that were close to ",151.0,https://doi.org/10.21799/frbp.wp.2019.16693efa13f8d7a76b071d2951b77b7da4a3cb2046039,10.5888/pcd21.230267,Chronic Disease Prevalence in the US: Sociodemographic and Geographic Variations by Zip Code Tabulation Area,2024.0,Preventing Chronic Disease,G. Benavidez; Whitney E. Zahnd; Pei-Yin Hung; Jan M. Eberth,"Introduction We examined the geographic distribution and sociodemographic and economic characteristics of chronic disease prevalence in the US. Understanding disease prevalence and its impact on communities is crucial for effective public health interventions. Methods Data came from the American Community Survey, the American Hospital Association Survey, and the Centers for Disease Control and Prevention’s PLACES. We used quartile thresholds for 10 chronic diseases to assess chronic disease prevalence by Zip Code Tabulation Areas (ZCTAs). ZCTAs were scored from 0 to 20 based on their chronic disease prevalence quartile. Three prevalence categories were established: least prevalent (score ≤6), moderately prevalent (score 7–13), and highest prevalence (score ≥14). Community characteristics were compared across categories and spatial analyses to identify clusters of ZCTAs with high disease prevalence. Results Our study showed a high prevalence of chronic disease in the southeastern region of the US. Populations in ZCTAs with the highest prevalence showed significantly greater socioeconomic disadvantages (ie, lower household income, lower home value, lower educational attainment, and h",148.0,https://www.cdc.gov/pcd/issues/2024/pdf/23_0267.pdf694e2b97b7933cf7d856c427ec68a2fa7b925e31264,10.3390/rs8030184,National-Scale Estimates of Ground-Level PM2.5 Concentration in China Using Geographically Weighted Regression Based on 3 km Resolution MODIS AOD,2016.0,Remote Sensing,W. You; Zeng-Liang Zang; Lifeng Zhang; Yi Li; Xiaobin Pan; Wen Wang,"High spatial resolution estimating of exposure to particulate matter 2.5 (PM2.5) is currently very limited in China. This study uses the newly released nationwide, hourly PM2.5 concentrations to create a nationwide, geographically weighted regression (GWR) model to estimate ground-level PM2.5 concentrations in China. A3 km resolution aerosol optical depth (AOD) product from MODIS is used as the primary predictor. Fire emissions detected by MODIS fire count were considered in the model development process. Additionally, meteorological features were used as covariates in the model to improve the estimation of ground-level PM2.5 concentrations. The model performed well and explained 81% of the daily PM2.5 concentration variations in model predictions, and the cross validations R2 is 0.79. The cross-validated root mean squared error (RMSE) of the model was 18.6 μg/m3.Annual PM2.5 concentrations retrieved by the MODIS 3 km AOD product indicated that most of the residential community areas exceeded the new annual Chinese PM2.5 National Standard level 2. Estimated high-resolution national-scale daily PM2.5 maps are useful to identify severe air pollution episodes and determine health risk",148.0,https://www.mdpi.com/2072-4292/8/3/184/pdf?version=1456476295695dbac8359122a307e19074dd2bad175b07c85f399,10.17016/bulletin.2002.88-12,Mortgage refinancing in 2001 and early 2002,2002.0,,Glenn B. Canner; Karen E. Dynan; Wayne Passmore,"Over the past ten years, millions of homeowners have taken advantage of lower mortgage interest rates and higher home values and have refinanced their mortgage loans. For many, the decision to refinance was motivated by a desire to reduce their monthly mortgage payments, either by obtaining a lower interest rate or by extending the maturity of their mortgage. When they have refinanced, many homeowners have liquefied some of the equity they accumulated in their homes by borrowing more than they needed to pay off their former mortgage and cover the transaction costs of the refinancing. They have used the funds raised in so-called cash-out refinancings to make home improvements, to repay other debts, or to purchase goods and services or other assets. This article presents estimates, based on recent survey findings, of the incidence of refinancing, the changes in terms and conditions of mortgages after refinancing, the amount of funds homeowners raised in the process, and the ways in which homeowners used the funds. It also provides comparisons with previous surveys of refinancing activity and a statistical analysis of the relative importance of different determinants of refinancing an",147.0,https://doi.org/10.17016/bulletin.2002.88-12696d6025da4a726b48db065907e98b493e291705616,10.48044/jauf.1980.074,The Contribution of Trees to Residential Property Value,1980.0,Arboriculture & Urban Forestry,D. J. Morales,"This study was conducted to determine whether or not trees contribute to residential property value and the extent of that contribution in the areas observed. To accomplish this, homes were observed with a substantial amount of mature tree cover and homes were observed without tree cover. It is realized that there are other variables that contribute to residential property value and this information was obtained from tax cards on file in the town tax assessor's office. All possible variables were noted for each house observed including the sale price. Factor and multiple regression analysis was used to determine the effect of the independent variables on the dependent variable which is sales price of the house. The results showed that trees do contribute to property value in the areas observed. By using the equation formulated by the regression analysis, we can predict the value of homes. From the values derived by the regression analysis, it was found that good tree cover added $2,686 (or six percent of the total) to the property value of the homes observed.",147.0,https://joa.isa-arbor.com/request.asp?JournalID=1&ArticleID=1694&Type=2697b0a19c5384d927e6e187c637cf7cc9877f1c7950,10.1016/j.iswa.2021.200052,House price forecasting with neural networks,2021.0,Intelligent Systems with Applications,Xiaojie Xu; Yun Zhang,"Abstract The house market has been rapidly growing for the past decade in China, making price forecasting an important issue to the people and policy makers. We approach this problem by exploring neural networks for forecasting of house prices from one hundred major cities for the period of June 2010–May 2019, serving as the first study with such wide coverage for the emerging Chinese market through a machine learning technique. We aim at constructing simple and accurate neural networks as a contribution to pure technical forecasting of house prices. To facilitate the analysis, we investigate different model settings over the algorithm (the Levenberg-Marquardt, scaled conjugate gradient, and Bayesian regularization), delay (from two to six), hidden neuron (two, three, five, and eight), and data spitting ratio (70%–15%–15%, 60%–20%–20%, and 80%–10%–10% for trainingvalidationtesting), and arrive at a rather simple neural network with only four delays and three hidden neurons that leads to stable performance of 1% average relative root mean square error across the one hundred cities for the training, validation, and testing phases. We demonstrate the usefulness of the machine learning",145.0,https://www.sciencedirect.com/science/article/pii/S2667305321000417/pdf69896290c82cb032dd45b9730fde670e10374377ea0,10.1016/j.jtrangeo.2018.06.025,Causal identification of transit-induced gentrification and spatial spillover effects: The case of the Denver light rail,2018.0,Journal of Transport Geography,Eleni Bardaka; Michael S. Delgado; R. Florax,"Abstract We test the hypothesis of transit-induced gentrification for the Regional Transportation District light rail system in Denver, CO. We use a quasi-experimental spatial econometric approach, the spatial difference-in-differences model, to measure the causal relationship between urban rail investments and gentrification, which allows us to capture the average direct and indirect (spatial spillover) effects of urban rail on several socioeconomic measures of gentrification. We further account for unobserved heterogeneity and spatial dependence via the use of a panel data estimator with spatial error components. Our analysis shows that the installation of a light rail station significantly increases household income and housing values in neighborhoods up to one mile from the station.",145.0,69984969b886dacd6fc7536328bbd0b0f427fa42e4a,10.1016/j.econmod.2012.06.025,Exploring determinants of housing prices: A case study of Chinese experience in 1999–2010,2012.0,,Yan-Bing Zhang; X. Hua; Liang Zhao,,143.0,70094b1f2830d00dabc5e72e47b87211acaffa9afad,10.1016/j.cities.2016.07.001,"Amenity, accessibility and housing values in metropolitan USA: A study of Salt Lake County, Utah",2016.0,,Han-Duo Li; Y. Wei; Zhou Yu; Guang Tian,,139.0,7014e661a9ca0c555a66e89f669550971d912baa829,10.1007/s11135-025-02080-3,Predictions of residential property price indices for China via machine learning models,2025.0,Quality & Quantity: International Journal of Methodology,Bing-Zi Jin; Xiao-Jie Xu,,138.0,702ea29b0b6d4e241af1817808d2727f2938d429a9e,10.1016/j.econmod.2014.10.050,Forecasting the U.S. Real House Price Index,2015.0,,V. Plakandaras; Rangan Gupta; Periklis Gogas; Theophilos Papadimitriou,"The 2006 sudden and immense downturn in U.S. House Prices sparked the 2007 global financial crisis and revived the interest about forecasting such imminent threats for economic stability. In this paper we propose a novel hybrid forecasting methodology that combines the Ensemble Empirical Mode Decomposition (EEMD) from the field of signal processing with the Support Vector Regression (SVR) methodology that originates from machine learning. We test the forecasting ability of the proposed model against a Random Walk (RW) model, a Bayesian Autoregressive and a Bayesian Vector Autoregressive model. The proposed methodology outperforms all the competing models with half the error of the RW model with and without drift in out-of-sample forecasting. Finally, we argue that this new methodology can be used as an early warning system for forecasting sudden house prices drops with direct policy implications.",137.0,http://arxiv.org/pdf/1707.04868703b11422e15014cb4b89c0bc53b8999740701dfe89,10.1016/j.jhe.2004.01.001,A prediction comparison of housing sales prices by parametric versus semi-parametric regressions,2004.0,,Okmyung Bin,,132.0,704a920383589b970b88f4b7e916c80e04380989d02,10.1016/j.ecolind.2018.05.024,Spatial variation of green space equity and its relation with urban dynamics: A case study in the region of Munich,2018.0,Ecological Indicators,Chao Xu; D. Haase; D. O. Pribadi; S. Pauleit,"Abstract Green spaces provide urban residents with numerous environmental and social benefits and are regarded as a fundamental part of sustainable urban development. However, the spatial distribution of green spaces is uneven in most cities and urban regions, which has been considered as an issue of environmental injustice. We present a study in which the spatial variation of green space equity and its relationship with socioeconomic variables were analyzed across different municipalities in the region of Munich, southern Germany. The Gini coefficient was applied as an indicator of green space equity and its relationship with socioeconomic variables was explored by using a geographically weighted regression (GWR) model. Moreover, the impacts of different urban dynamic scenarios on green space equity were comparatively assessed at both the regional and sub-regional zone levels by incorporating a multiple urban dynamic scenario modeling approach. The results indicate that the relationships between green space equity and socioeconomic variables are not always consistently significant over space and the coefficients of GWR reflect great spatial heterogeneity indicating the relationshi",129.0,70551b5b1c1588ea45c2faf233faa9c41575e282e78,10.1016/j.regsciurbeco.2016.06.005,Flood hazards impact on neighborhood house prices: A spatial quantile regression analysis,2016.0,,Lei Zhang,,129.0,7067f8c1ab2fb8013a9343cd579ddc94c4e22384a22,10.1016/j.regsciurbeco.2017.04.001,A new method for dealing simultaneously with spatial autocorrelation and spatial heterogeneity in regression models,2017.0,Regional Science and Urban Economics,G. Geniaux; Davide Martinetti,"Although spatial heterogeneity and spatial dependence are two cornerstones of spatial econometrics, models and methods for dealing at the same time with both issues are still rare in the literature, with few notable exceptions. The same can be said for studies on the performance of spatial econometric models under misspecification of explanatory variables and unknown structure of the spatial weight matrix. In this article, we introduce a new class of data generating processes (DGP), called MGWR-SAR, in which the regression parameters and the spatial autocorrelation coefficient can vary over the space. For the estimation of these new models, we resort to the Spatial Two-Stage Least Squares (S2SLS) technique. We rely on a Monte Carlo experiment for testing the performance of classical models, such as OLS, GWR (Geographically Weighted Regression), mixed GWR and SAR (Spatial AutoRegressive model), as well as our proposals, paying special attention to simulated data under the realistic assumption that they suffer from multicollinearity/concurvity problems and/or misspecification of the covariates. The results suggest that certain model specifications amongst the newly proposed family MG",128.0,707bd9c148008deb187657346c648b4359db5f7a681,10.1016/j.cities.2018.02.008,Labour mobility between cities and metropolitan integration: The role of high speed rail commuting in Spain,2018.0,Cities,B. Guirao; Juan Luis Campa; Natalia Casado-Sanz,"Abstract Although the link between transport accessibility and the regional and local scope of labour markets has been widely studied in the literature, high speed rail (HSR) commuting is a relatively new user behaviour and little research has been done to date on labour migration derived from inter-regional HSR commuting. This paper contributes to the limited existing literature by analysing the evolution of the impact of HSR on labour markets in commuting relations. The added value of this research is that it is the first assessment of a panel data regression analysis taking account of HSR as a variable and using labour inter-regional mobility data (2002–2014). The model has been validated using the HSR commuting areas that converge in the metropolitan areas of Madrid, Barcelona, Seville and Malaga. Results have highlighted the complexity of the variables involved in the decision to commute by HSR. This complexity is linked to the causal relations between the most representative variables, namely unemployment rates and housing prices, which are more difficult to study during periods of economic crisis. The location of the HSR station has been revealed as a key indicator, and is e",127.0,708e8a3d204da39c6ba6ff566893f41dda864696115,10.1068/b32119,"Modeling Spatial Dimensions of Housing Prices in Milwaukee, WI",2007.0,,Danlin Yu; Y. Wei; Chang-Shan Wu,,125.0,709b77f201abed90b1366c7c88bf8f9644608ab2913,10.1080/00343400903497897,Regional Housing Price Cycles: A Spatio-temporal Analysis Using US State-level Data,2011.0,,Todd H. Kuethe; V. Pede,"Kuethe T. H. and Pede V. O. Regional housing price cycles: a spatio-temporal analysis using US state-level data, Regional Studies. A study is presented of the effects of macroeconomic shocks on housing prices in the Western United States using quarterly state-level data from 1988:1 to 2007:4. The study contributes to the existing literature by explicitly incorporating locational spillovers through a spatial econometric adaptation of vector autoregression (SpVAR). The results suggest these spillovers may Granger cause housing price movements in a large number of cases. SpVAR provides additional insights through impulse response functions that demonstrate the effects of macroeconomic events in different neighbouring locations. In addition, it is demonstrated that including spatial information leads to significantly lower mean-square forecast errors. Kuethe T. H. et Pede V. O. La variation cyclique régionale du prix du logement: une analyse géographico-temporelle des données sur les états aux E-U, Regional Studies. A partir des données trimestrielles au premier trimestre de 1988 jusqu'au quatrième trimestre de 2007, on présente ici une étude des effets des chocs macroéconomiques sur l",124.0,https://ageconsearch.umn.edu/record/47596/files/09-04.pdf710d015f0b776c392781354396e005d138d2c4fdfd4,10.1016/j.ufug.2015.09.013,"Assessing amenity effects of urban landscapes on housing price in Hangzhou, China.",2015.0,,Hai-Zhen Wen; Yan Zhang; Ling Zhang,,124.0,711750fe05ace45d8d7fea566bc10722441b463b2c7,10.1016/j.aap.2024.107535,A spatial autocorrelation analysis of road traffic crash by severity using Moran's I spatial statistics: A comparative study of Addis Ababa and Berlin cities.,2024.0,Accident Analysis and Prevention,Wondwossen Taddesse Gedamu; Uwe Plank-Wiedenbeck; B. Wodajo,"Methodological advancements in road safety research reveal an increasing inclination toward integrating spatial approaches in hot spot identification, spatial pattern analysis, and developing spatially lagged models. Previous studies on hot spot identification and spatial pattern analysis have overlooked crash severities and the spatial autocorrelation of crashes by severity, missing valuable insights into crash patterns and underlying factors. This study investigates the spatial autocorrelation of crash severity by taking two capital cities, Addis Ababa and Berlin, as a case study and compares patterns in low and high-income countries. The study used three-year crash data from each city. It employed the average nearest neighbor distance (ANND) method to determine the significance of spatial clustering of crash data by severity, Global Moran's I to examine the statistical significance of spatial autocorrelation, and Local Moran's I to identify significant cluster locations with High-High (HH) and Low-Low (LL) crash severity values. The ANND analysis reveals a significant clustering of crashes by severity in both cities, except in Berlin's fatal crashes. However, different Global Mo",123.0,https://doi.org/10.1016/j.aap.2024.107535712d24166f00700f9016f06cfeea4b5a863ed0cc8a0,10.1007/bf00219506,Housing prices and flood risk: An examination using spline regression,1991.0,,J. Speyrer; Wade R. Ragas,,123.0,713fdefd221716d08da85ac54cd18b1ddde694f16e5,10.1289/ehp.113-a290,"Guest Editorial: Health, Equity, and the Built Environment",2005.0,Environmental Health Perspectives,H. Frumkin,"The modern era of environmental health dates from the publication of Silent Spring in 1962. In her classic book, Rachel Carson warned of the effects of pesticides on wildlife ecology, invoking a nightmarish die-off of songbirds in the book’s title. However, she also warned of human health effects, both acute and chronic, from liver damage to neurotoxicity to cancer (Carson 1962). In the ensuing decades, environmental health essentially became synonymous with the recognition and control of chemical exposures. Environmental health scientists were toxicologists and epidemiologists, specializing in pesticides, metals, solvents, asbestos, or persistent organic pollutants. 714 715At least two paradigm shifts have revolutionized the field since Rachel Carson’s day. One occurred when environmental health encountered civil rights, forming the environmental justice movement. We are in the midst of the second, as environmental health reunites with architecture and urban planning. 716 717The environmental justice movement coalesced around 1982, when a predominantly African-American community in Warren County, North Carolina, challenged a proposed polychlorinated biphenyl landfill as an act of “environ",122.0,https://doi.org/10.1289/ehp.113-a290718e60fb2a2f6128aea75edf521d17b5f378d1464fe,10.1017/s0033291718000612,"Not urbanization level but socioeconomic, physical and social neighbourhood characteristics are associated with presence and severity of depressive and anxiety disorders",2018.0,Psychological Medicine,E. Generaal; E. Timmermans; Jasper E. C. Dekkers; J. Smit; B. Penninx,"Abstract Background Which neighbourhood factors most consistently impact on depression and anxiety remains unclear. This study examines whether objectively obtained socioeconomic, physical and social aspects of the neighbourhood in which persons live are associated with the presence and severity of depressive and anxiety disorders. Methods Cross-sectional data are from the Netherlands Study of Depression and Anxiety including participants (n = 2980) with and without depressive and anxiety disorders in the past year (based on DSM-based psychiatric interviews). We also determined symptom severity of depression (Inventory of Depression Symptomatology), anxiety (Beck Anxiety Inventory) and fear (Fear Questionnaire). Neighbourhood characteristics comprised socioeconomic factors (socioeconomic status, home value, number of social security beneficiaries and percentage of immigrants), physical factors (air pollution, traffic noise and availability of green space and water) and social factors (social cohesion and safety). Multilevel regression analyses were performed with the municipality as the second level while adjusting for individual sociodemographic variables and household income. Res",122.0,https://www.cambridge.org/core/services/aop-cambridge-core/content/view/288B46C4BD46028B43CC4DC868CDA84B/S0033291718000612a.pdf/div-class-title-not-urbanization-level-but-socioeconomic-physical-and-social-neighbourhood-characteristics-are-associated-with-presence-and-severity-of-depressive-and-anxiety-disorders-div.pdf719cfffeddb3db807becd9daf436533b7a4cb9f6358,10.1016/j.jhe.2017.08.001,The Visible Host: Does race guide Airbnb rental rates in San Francisco?,2017.0,Journal of Housing Economics,Venoo Kakar; J. Voelz; J. Wu; J. Franco,"Peer to Peer e-commerce is increasingly characterized by trends towards the personalization of buyers and sellers in the on-line marketplace. This personalization includes buyer reviews, personal pictures and profiles, and other biographical information intended to reduce buyers’ perceived “purchase risk” or to facilitate trust in the sellers. However, this phenomenon is transforming what started as an essentially “anonymous” market to one susceptible to traditional market failures, including potential racial discrimination, in a manner similar to its brick and mortar counterparts. In this paper, we examine the effect of on-line host information (race, gender, sexual orientation, etc.) on the price of available rental listings in San Francisco on Airbnb.com. We find that on average, Asian and Hispanic hosts charge 8%-10% lower prices relative to their White counterparts on equivalent rental properties, after controlling for all renter-available information on rental unit characteristics, as well as additional information on neighborhood property values, area demographics, and occupancy rates. We do not find any differences in occupancy rates between minority and White hosts. This m",122.0,https://doi.org/10.2139/ssrn.29679027207241a2231753bc271686fa266cdefa5bc92ebcde,10.1080/01402382.2018.1561054,Housing prices and wealth inequality in Western Europe,2019.0,West European Politics,Gregory W. Fuller; A. Johnston; Aidan Regan,"Abstract Comparative political economy (CPE) has robustly examined the political and institutional determinants of income inequality. However, the study of wealth, which is more unequally distributed than income, has been largely understudied within CPE. Using new data from the World Income Database (WID), this article examines how economic, political and institutional dynamics shape wealth-to-income ratios within Western European and OECD countries. It is found that the political and institutional determinants that affect income inequality have no short- or long-run effects on the wealth-to-income ratio. Rather, the rise in wealth-to-income ratios is driven by rising housing prices, as well as price changes in other financial assets, not home ownership or national saving rates. The article concludes by examining how the changing dynamics of housing prices and wealth inequality will increasingly shape intergenerational – and associated class-based – political conflict in Western Europe.",121.0,https://www.tandfonline.com/doi/pdf/10.1080/01402382.2018.1561054?needAccess=true7212d3aac58348167204ad7a0e8c2b780d0c4717d42,10.1111/1540-6229.00557,The measurement and determinants of single-family house prices,1991.0,,J. Peek; J. A. Wilcox,,120.0,http://www.bostonfed.org/economic/wp/wp1991/wp91_7.pdf722aa5cb7eeed59163ccb9d39b9b5f9cb90a35a63e4,10.2139/ssrn.1670820,The Effect of Foreclosures on Nearby Housing Prices: Supply or Disamenity?,2014.0,,Daniel A. Hartley,,120.0,https://www.clevelandfed.org/-/media/project/clevelandfedtenant/clevelandfedsite/publications/working-papers/2014/wp-1011r-the-effect-of-foreclosures-on-nearby-housing-prices-supply-or-disamenity-pdf.pdf723d23f164194d63279863ed0d88eb4eafba8f3202f,10.1016/j.jtrangeo.2016.05.010,"Residential property value impacts of proximity to transport infrastructure: An investigation of bus rapid transit and heavy rail networks in Brisbane, Australia",2016.0,,C. Mulley; Liang Ma; G. Clifton; Barbara T. H. Yen; M. Burke,"Public transport investment is normally targeted at increasing accessibility which land rent theory identifies and will in turn increase land values. There is a clear policy interest in how much land values increase following a new transport investment so as to establish if there is sufficient land value uplift to capture and to help pay or contribute to investment plans. Identifying an uplift for residential land has been well studied in the context of new light rail systems and bus rapid transit (BRT) systems in developing countries but there is little evidence for BRT in developed countries. 724 725This paper has two objectives. First, to examine long term impact of BRT in a developed world context in Brisbane, Australia. Brisbane's BRT uses an open system design which contrasts with the closed system design of the successful BRT systems in South America and elsewhere, including the BRT in the suburbs of Sydney, Australia. Second, BRT in Brisbane was introduced to a network already dominated by a radial heavy rail network and this investigation recognises that the uplift from BRT introduction may therefore be different to a BRT in a single mode city. A third motivation is to conside",118.0,http://hdl.handle.net/10072/142793726eed33da221f4169656953ec8e7c935c9d27ce8ed,10.1016/s0950-7051(01)00169-1,Residential property price time series forecasting with neural networks,2002.0,Knowledge-Based Systems,I. D. Wilson; Stuart D. Paris; J. Ware; D. Jenkins,,118.0,7275b5c65900fc3c7e539bc1408b8b5baff3633db65,10.1016/j.habitatint.2015.07.004,"Retail accessibility and proximity effects on housing prices in Seoul, Korea: A retail type and housing submarket approach",2015.0,,Myungjun Jang; Chang-Deok Kang,,116.0,728e542319befda01bf0a0d47b9ae0a71fb740a4cfb,10.1016/j.jue.2019.103228,"Accounting for central neighborhood change, 1980–2010",2020.0,Journal of Urban Economics,Nathaniel Baum-snow; Daniel A. Hartley,"Neighborhoods within 2 km of most central business districts of U.S. metropolitan areas experienced population declines from 1980 to 2000 but have rebounded markedly since 2000 at greater pace than would be expected from simple mean reversion. Statistical decompositions reveal that 1980-2000 departures of residents without a college degree (of all races) generated most of the declines while the return of college educated whites and the stabilization of neighborhood choices by less educated whites promoted most of the post-2000 rebound. The rise of childless households and the increase in the share of the population with a college degree, conditional on race, also promoted 1980-2010 increases in central area population and educational composition of residents, respectively. Estimation of a neighborhood choice model shows that changes in choices to live in central neighborhoods primarily reflect a shifting balance between rising home prices and valuations of local amenities, though 1980-2000 central area population declines also reflect deteriorating nearby labor market opportunities for low skilled whites. Rising 1980-2000 central neighborhood home prices were about equally offset b",115.0,https://www.chicagofed.org/~/media/publications/working-papers/2016/wp2016-09-pdf.pdf729f072fcf2f0c18e54551ff1b0d5853a05a7ae05c2,10.1016/j.habitatint.2015.04.002,Multi-scale analysis of rural housing land transition under China's rapid urbanization: The case of Bohai Rim,2015.0,,Ting-Ting Li; Hua-Lou Long; Yong-Qiang Liu; Shuang-Shuang Tu,"Abstract With the rural-to-urban migration under China's rapid urbanization, the Bohai Rim of China experienced dramatic rural housing land transition (RHLT) in the last decade, especially in terms of per capita rural housing land (PRHL). The objectives of this study are to (i) analyze the spatio-temporal patterns of RHLT, and (ii) detect the underlying driving forces and mechanism of RHLT in Bohai Rim during 2000–2010. To achieve these goals, we collected and rasterized high resolution Landsat TM data, socio-economic and physical environmental data for the Bohai Rim. Spatial econometric regression models at both grid scale and county scale were developed to examine the driving forces of RHLT in Bohai Rim. The results indicated that the distribution of rural housing land was characterized by vertical zonality, i.e., the proportion of rural housing land decreased gradually with the increase of elevation, and was more sensitive to slope than to elevation. The results of hot spots analysis showed that the spatial mismatch of rural housing land change and rural population migration made the regional differences of RHLT more remarkable, based on which four rural housing land consolidati",114.0,http://ir.igsnrr.ac.cn/handle/311030/38712730cdc81ce8be295ca18d0559f0457938f3e6153618,10.3390/app8112321,Identifying Real Estate Opportunities using Machine Learning,2018.0,Applied Sciences,A. Baldominos; I. Blanco; Antonio José Moreno; Rubén Iturrarte; Óscar Bernárdez; C. Afonso,"The real estate market is exposed to many fluctuations in prices because of existing correlations with many variables, some of which cannot be controlled or might even be unknown. Housing prices can increase rapidly (or in some cases, also drop very fast), yet the numerous listings available online where houses are sold or rented are not likely to be updated that often. In some cases, individuals interested in selling a house (or apartment) might include it in some online listing, and forget about updating the price. In other cases, some individuals might be interested in deliberately setting a price below the market price in order to sell the home faster, for various reasons. In this paper, we aim at developing a machine learning application that identifies opportunities in the real estate market in real time, i.e., houses that are listed with a price substantially below the market price. This program can be useful for investors interested in the housing market. We have focused in a use case considering real estate assets located in the Salamanca district in Madrid (Spain) and listed in the most relevant Spanish online site for home sales and rentals. The application is formally i",114.0,https://www.mdpi.com/2076-3417/8/11/2321/pdf?version=1542794649731f94f19e4ae3c623a6181ee4868a28358b1a0879b,10.1016/j.landurbplan.2020.103900,Eco-gentrification and who benefits from urban green amenities: NYC’s high Line,2020.0,,Katie Jo Black; M. Richards,"Abstract This study estimates the impact of the introduction of New York’s High Line, an elevated walkway in Manhattan by relating the increase in housing values to the issue of eco-gentrification in urban areas. Studies have shown that increasing the amount of green space can lead to gentrification: rising property values, displacement of existing residents, and a large in-migration of wealthy populations. We utilize Geographic Information Systems (GIS) to spatially model the effects of the High Line on residential property values. We exploit spatial and temporal differences of the High Line’s opening to estimate its impact on residential home values. We find that homes closest to the High Line experienced a 35.3% increase in housing values. We estimate the driving force behind this premium by using a triple difference approach by analyzing elevation levels and find that homes with relatively the same height as the High Line receive the largest premium. This study serves to inform policy makers regarding potential inequality of green space provisions. We provide policy recommendations for minimizing the housing price impact of green space creation.",114.0,732cc667ff1c6266ef85aa48678b7c69b3d4f0aa9c9,10.1109/icmlde.2018.00017,"Housing Price Prediction Using Machine Learning Algorithms: The Case of Melbourne City, Australia",2018.0,2018 International Conference on Machine Learning and Data Engineering (iCMLDE),The Danh Phan,"House price forecasting is an important topic of real estate. The literature attempts to derive useful knowledge from historical data of property markets. Machine learning techniques are applied to analyze historical property transactions in Australia to discover useful models for house buyers and sellers. Revealed is the high discrepancy between house prices in the most expensive and most affordable suburbs in the city of Melbourne. Moreover, experiments demonstrate that the combination of Stepwise and Support Vector Machine that is based on mean squared error measurement is a competitive approach.",113.0,7338e4b54510320bf32a60ad97292a79fb39b9dd211,10.1108/jm2-12-2023-0315,Pre-owned housing price index forecasts using Gaussian process regressions,2024.0,Journal of Modelling in Management,Bing-Zi Jin; Xiao-Jie Xu,"734Purpose735The purpose of this study is to make property price forecasts for the Chinese housing market that has grown rapidly in the last 10 years, which is an important concern for both government and investors.736737738Design/methodology/approach739This study examines Gaussian process regressions with different kernels and basis functions for monthly pre-owned housing price index estimates for ten major Chinese cities from March 2012 to May 2020. The authors do this by using Bayesian optimizations and cross-validation.740741742Findings743The ten price indices from June 2019 to May 2020 are accurately predicted out-of-sample by the established models, which have relative root mean square errors ranging from 0.0458% to 0.3035% and correlation coefficients ranging from 93.9160% to 99.9653%.744745746Originality/value747The results might be applied separately or in conjunction with other forecasts to develop hypotheses regarding the patterns in the pre-owned residential real estate price index and conduct further policy research.748",112.0,749d7da46c7cf311d72cf9bf91cd870dfe73509d542,10.1016/j.cities.2022.103941,Housing price prediction incorporating spatio-temporal dependency into machine learning algorithms,2022.0,Cities,A. Soltani; M. Heydari; F. Aghaei; C. Pettit,,110.0,750dd89d2df427b5c576136b505c1822f55e64666af,10.1080/01621459.2013.772897,Nonparametric Mixture of Regression Models,2013.0,Journal of the American Statistical Association,Mian Huang; Run-Ze Li; Shao-Li Wang,"Motivated by an analysis of U.S. house price index (HPI) data, we propose nonparametric finite mixture of regression models. We study the identifiability issue of the proposed models, and develop an estimation procedure by employing kernel regression. We further systematically study the sampling properties of the proposed estimators, and establish their asymptotic normality. A modified EM algorithm is proposed to carry out the estimation procedure. We show that our algorithm preserves the ascent property of the EM algorithm in an asymptotic sense. Monte Carlo simulations are conducted to examine the finite sample performance of the proposed estimation procedure. An empirical analysis of the U.S. HPI data is illustrated for the proposed methodology.",108.0,https://europepmc.org/articles/pmc3865811?pdf=render7515bf0adcaf64d072ab8a9ceeedbba3cd330be5411,10.1007/s00521-024-10726-w,"Machine learning-based forecasts of residential property prices in Hangzhou City, Zhejiang Province, China",2024.0,Neural computing & applications (Print),Bing-Zi Jin; Xiao-Jie Xu,,107.0,752252045b616ef9311fe7438d6ff02978aa1888f62,10.1109/icsss.2019.8882834,House Price Prediction Using Regression Techniques: A Comparative Study,2019.0,2019 International Conference on Smart Structures and Systems (ICSSS),C. Madhuri; G. Anuradha; M. Pujitha,"People are careful when they are trying to buy a new house with their budgets and market strategies. The objective of the paper is to forecast the coherent house prices for non-house holders based on their financial provisions and their aspirations. By analyzing the foregoing merchandise, fare ranges and also forewarns developments, speculated prices will be estimated. The paper involves predictions using different Regression techniques like Multiple linear, Ridge, LASSO, Elastic Net, Gradient boosting and Ada Boost Regression. House price prediction on a data set has been done by using all the above mentioned techniques to find out the best among them. The motive of this paper is to help the seller to estimate the selling cost of a house perfectly and to help people to predict the exact time slap to accumulate a house. Some of the related factors that impact the cost were also taken into considerations such as physical conditions, concept and location etc.",106.0,753e4e8aa7932f5c7c657867d90a869692406fed8a0,10.1016/j.tra.2018.07.007,Is transport poverty socially or environmentally driven? Comparing the travel behaviours of two low-income populations living in central and peripheral locations in the same city,2018.0,Transportation Research Part A: Policy and Practice,K. Lucas; I. Philips; C. Mulley; Liang Ma,"Abstract The paper presents a study to explore the relationship between travel poverty and social disadvantage at the local geographical level. The main aim of the research was to identify the extent to which the revealed travel behavioural outcomes of the study participants are due to personal social constraints or environmental conditions in their residential locations. Specifically, we sought to identify if the greater access to local amenities and public transport services of inner city residents led to an increase in their daily travel activities when compared with their urban peripheral counterparts. The research analysed data from a personal travel survey and one-day travel diary with 502 adults aged between 16 and 65 years in two different deprived areas in Merseyside, North West England. Our analysis is somewhat hampered by the small sample size, but the modelled results suggest that more trips, and longer journey distances do not necessarily imply greater social inclusion. The geographically weighted regression models (GWR) highlighted that the physical location of where people live within the city is more influential on their trip-making patterns than social determinants",105.0,https://www.sciencedirect.com/science/article/pii/S0965856416310114/pdf75441908e2de580232dcc663236c801b8f66e139d18,10.1111/j.1467-9787.1996.tb01107.x,STRUCTURAL ESTIMATION OF RESIDENTIAL MOBILITY AND HOUSING TENURE CHOICE*,2006.0,,Yannis M. Ioannides; Kam-Hon Kan,"This study is devoted to studying households' decisions about moving and about whether to rent or own after moving. It employs dynamic discrete choice models which condition households' decisions on their circumstances at every point in time during the length of the observation while accounting for individual heterogeneity. The results show that key dynamic elements, captured by means of lagged dependent variables, as well as household heterogeneity, are very significant determinants of the tenure choice and mobility decisions. Moreover, homeowners are found to be responsive to housing market conditions in adjusting their housing stock. Housing price appreciation is found to be discouraging renters from moving and owning. Finally, our results reject the proportional monetary transaction costs specification suggesting that monetary transaction cost might be fixed",105.0,7558470867d39b5ad5fdb8d21ce2dafac261efe5a5b,10.1080/13658816.2018.1555832,Street-Frontage-Net: urban image classification using deep convolutional neural networks,2018.0,International Journal of Geographical Information Science,S. Law; C. Seresinhe; Yao Shen; M. Gutiérrez-Roig,"ABSTRACT Quantifying aspects of urban design on a massive scale is crucial to help develop a deeper understanding of urban designs elements that contribute to the success of a public space. In this study, we further develop the Street-Frontage-Net (SFN), a convolutional neural network (CNN) that can successfully evaluate the quality of street frontage as either being active (frontage containing windows and doors) or blank (frontage containing walls, fences and garages). Small-scale studies have indicated that the more active the frontage, the livelier and safer a street feels. However, collecting the city-level data necessary to evaluate street frontage quality is costly. The SFN model uses a deep CNN to classify the frontage of a street. This study expands on the previous research via five experiments. We find robust results in classifying frontage quality for an out-of-sample test set that achieves an accuracy of up to 92.0%. We also find active frontages in a neighbourhood has a significant link with increased house prices. Lastly, we find that active frontage is associated with more scenicness compared to blank frontage. While further research is needed, the results indicate th",104.0,https://figshare.com/articles/journal_contribution/Street-Frontage-Net_urban_image_classification_using_deep_convolutional_neural_networks/75196647565cb9301fef5dee27901474ebc9e6c150ed0bcd6b,10.5089/9781475505672.001.a001,Global Housing Cycles,2012.0,Social Science Research Network,Deniz Igan; P. Loungani,"Housing cycles and their impact on the financial system and the macroeconomy have become the center of attention following the global financial crisis. This paper documents the characteristics of housing cycles in a large set of countries, and examines the determinants of house price movements. Empirical analysis shows that house price dynamics are mostly driven by income and demographics but fluctuations in these fundamentals and credit conditions can create deviations from the implied equilibrium path. We conclude with a discussion of the macroeconomic implications of house price corrections.",104.0,https://www.elibrary.imf.org/downloadpdf/journals/001/2012/217/001.2012.issue-217-en.xml75753ab5a1e05b59357a76ba94951aa2b5bfa619ab0,10.1016/j.jtrangeo.2020.102769,"How does ridesourcing substitute for public transit? A geospatial perspective in Chengdu, China",2020.0,,Hui Kong; Xiaohu Zhang; Jin-Huan Zhao,"Abstract The explosive growth of ridesourcing services has stimulated a debate on whether they represent a net substitute for or a complement to public transit. Among the empirical evidence that supports discussion of the net effect at the city level, analysis at the disaggregated level from a geospatial perspective is lacking. Besides, it remains unexplored the spatiotemporal pattern of ridesourcing's effect on public transit, and the factors that impact the effect. Using DiDi Chuxing data in Chengdu, China, this paper develops a three-level structure to recognize the potential substitution or complementary effects of ridesourcing on public transit. Furthermore, this paper investigates the effects through exploratory spatiotemporal data analysis, and examines the factors influencing the degree of substitution via linear, spatial autoregressive, and zero-inflated beta regression models. The results show that 33.1% of DiDi trips have the potential to substitute for public transit. The substitution rate is higher during the day (8:00–18:00), and the trend follows changes in public transit coverage. The substitution effect is more exhibited in the city center and the areas covered by ",103.0,https://hdl.handle.net/1721.1/127238758a05f46f80241aefc123b8f16ff33a12dc9d62184,10.1016/j.landusepol.2020.104889,A mass appraisal assessment study using machine learning based on multiple regression and random forest,2020.0,,Seckin Yilmazer; S. Kocaman,"Abstract Mass appraisal is a complex matter because it depends on several categorical and continuously changing or constant parameters. In addition, development of new assessment approaches for mass appraisal of real estate properties in highly complex urban environments is desirable. The advancements in geospatial technologies and machine learning algorithms open up new horizons. For this reason, the purpose of the present study is to compare one conventional stepwise linear multiple regression (MRA) and one more automated machine learning approach, random forest (RF), for mass appraisal in an urban residential area where commercial properties are also available. A part of Mamak District, Ankara, Turkey is selected as the study area since the property values are diverse and representative. Additionally, the district has a complex and developing urban structure. The data employed in the study were compiled under a cadastral modernization project of General Directorate of the Land Registry and Cadastre of Turkey (GDLRC) and were based on the reports of licensed experts (∼50 %), court reports (∼20 %), field surveys, or a combined analysis of all. Consequently, the data used in the st",103.0,759b98e8c330b19cc91bf7288a0496eef94329ee35d,10.1287/mnsc.2019.3550,The Last Mile Matters: Impact of Dockless Bike Sharing on Subway Housing Price Premium,2021.0,Management Sciences,Jun-Hong Chu; Yi-Ge Duan; Xianling Yang; Li Wang,"Dockless bike sharing provides a convenient and affordable means of transport for urban residents. It solves the “last-mile problem” in public transport by reducing the travel cost between home and subway stations and thus increasing the attractiveness of distant apartments. This may affect the relationship between housing price and distance to subway and reduce the price premium enjoyed by proximate apartments. Using resale apartment data in 10 major cities in China, a difference-in-differences approach at the apartment level, and a two-step estimator at the city-month level, we find that the entry of bike sharing reduces the housing price premium by 29% per km away from a subway station. The effect is equivalent to a reduction of 1,893–2,127 CNY (282–317 USD) in commuting costs per household per annum over 30 years. The effect is driven by a relative increase in the listing price of, and in the demand for, apartments distant from vis-à-vis proximate to subway stations. This paper was accepted by Juanjuan Zhang, marketing.",103.0,https://doi.org/10.2139/ssrn.3195004760c1d9d50faf0276a3d26ba46e3d70fcbc88d3f5d4,10.1109/icicct.2018.8473231,House Price Prediction Using Machine Learning and Neural Networks,2018.0,International Conference Inventive Communication and Computational Technologies,Ayush Varma; Abhijit Sarma; Sagar Doshi; Rohini Nair,,103.0,76146fdcf9794cd8ad3ce5a38e5501a1680aeb34c03,10.1016/j.habitatint.2018.09.004,"The effects of locational factors on the housing prices of residential communities: The case of Ningbo, China",2018.0,Habitat International,Xiaojin Liang; Yao-Lin Liu; Tianqi Qiu; Ying Jing; F. Fang,"Abstract Residential communities are the basic living units in Chinese cities. Housing prices are closely associated with the community location and surrounding support facilities. When selecting satisfactory residential accommodation, potential real estate purchasers prioritize the community location in a city at the macro-level and then consider other micro-factors (i.e., the floor, orientation, structure, etc.). This paper attempts to explore the relationship between housing prices and locational factors at the community level. We collect the current market prices of 545 residential communities built in the last decade in Ningbo, the second largest city in Zhejiang Province. Then, thirteen locational factors of five dimensions are identified to research their influences on housing prices. In the process of selecting certain locational variables, both extant features and additional features (i.e., planned ones) are considered. The geographic field model is introduced to quantify the external effects of locational factors, due to its advantages of producing more accurate results than that of traditional distance-based measure methods. Then, regression analysis is performed based o",101.0,762906a905363dd9e9e56d4e410ddf26aead94abcc9,10.1016/j.trd.2018.08.015,Promoting carsharing attractiveness and efficiency: An exploratory analysis,2018.0,Transportation Research Part D: Transport and Environment,Song-Hua Hu; Peng Chen; Hang-Fei Lin; Chi Xie; Xiao-Hong Chen,"Abstract Carsharing has grown significantly over recent years. Understanding factors related to the usage and turnover rate of shared cars will help promote the growth of carsharing programs. This study sets station-based shared car booking requests and turnover rates as learning objectives, by which generalized additive mixed models are employed to examine various effects. The results are: (1) stations with more parking spaces, longer business hours and fewer nearby stations are likely to receive more booking requests and have a higher turnover rate; (2) an area with a higher population density, a higher percentage of adults, a higher percentage of males, a greater road density, or more mixed land use is associated with more car usage and a higher turnover rate; (3) stations nearby transit hubs, colleges, and shopping centers attract more shared car users; (4) shared cars are often oversupplied at transit hubs; (5) both transit proximity and housing price present high degrees of nonlinearity in relation to shared car usage and turnover rates. Findings provide evidence for optimizing the usage and efficiency of carsharing programs: carsharing companies should identify underserved a",101.0,763386700fa205d3f393af4de56fb9f3e5ca497fd16,10.1016/j.jclepro.2015.09.012,"The impact of socio-demographic, environmental, and individual factors on urban park visitation in Beijing, China",2017.0,,Hong-Xiao Liu; Feng Li; Lianfang Xu; Bao-Long Han,"Abstract Urban parks improve quality of life by providing an array of cultural and natural ecosystem services, such as maintaining biodiversity, reducing air pollution, and benefiting residents' physical and mental states. Although government invests a large amount of capital into park management, parks are still underused in many cases. In this study, the association and relative importance of socio-demographic, environmental, and individual factors were investigated with regards to their impact on citizens' park visitation. Data was collected through cross-sectional door-to-door questionnaires and online databases, and was analyzed using a hierarchical regression model. Results showed that physical exercise (27.4% of collected reports) and rest and relaxation (26.7%) were the two most widespread reasons for park use. When asked about constraints of park visitation, time limitations were reported as being the most constraining factor. However, our quantitative analysis found no significant correlation. Socio-demographic, environmental, and individual variables explained 1%, 20% and 26% (adjusted R 2 ) of the total variance in frequency of park visitation between participants, resp",100.0,https://ir.rcees.ac.cn/bitstream/311016/39128/1/The%20impact%20of%20socio-demographic%2c%20environmental%2c%20and%20individual%20factors%20on%20urban%20park%20visitation%20in%20Beijing%2c%20China.pdf764e603682785384bae33091e333597a6e6b0e23c9e,10.1080/07350015.2023.2277172,Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure,2023.0,Journal of business & economic statistics,Xiao-Rong Yang; Jia Chen; De-Gui Li; Run-Ze Li,"Abstract This article considers estimating functional-coefficient models in panel quantile regression with individual effects, allowing the cross-sectional and temporal dependence for large panel observations. A latent group structure is imposed on the heterogeneous quantile regression models so that the number of nonparametric functional coefficients to be estimated can be reduced considerably. With the preliminary local linear quantile estimates of the subject-specific functional coefficients, a classic agglomerative clustering algorithm is used to estimate the unknown group structure and an easy-to-implement ratio criterion is proposed to determine the group number. The estimated group number and structure are shown to be consistent. Furthermore, a post-grouping local linear smoothing method is introduced to estimate the group-specific functional coefficients, and the relevant asymptotic normal distribution theory is derived with a normalization rate comparable to that in the literature. The developed methodologies and theory are verified through a simulation study and showcased with an application to house price data from U.K. local authority districts, which reveals different ",100.0,https://scholarsphere.psu.edu/resources/cb29b90f-7953-4bf0-972b-8740b699a920/downloads/41583765ba41455a119c70bc59c31ff0f9f9f0147f28e2bd,10.2139/ssrn.2490969,How Do Households Allocate Their Assets? Stylised Facts from the Eurosystem Household Finance and Consumption Survey,2014.0,Social Science Research Network,Luc Arrondel; L. Bartiloro; Pirmin Fessler; Peter Lindner; Thomas Y. Mathä; C. Rampazzi; F. Savignac; T. Schmidt; Martin Schuerz; P. Vermeulen,"Using the Household Finance and Consumption Survey (HFCS), a large micro-level dataset on households' wealth in fifteen euro area countries, this paper explores how households allocate their assets. We derive stylized facts on asset participation as well as levels of asset holdings and investigate the systematic relationships between household characteristics and asset holding patterns. Real assets make up the bulk of total assets. Whereas ownership of the main residence varies strongly between countries, the value of the main residence tends to be the major asset for home-owners and is a significant part of total assets in all countries. While almost all households hold safe financial assets, a low share of households holds risky assets. The ownership rates of all asset categories generally increase with wealth (and income). The significance of inheritances for wealth accumulation is remarkable and underlines its key role in the process of persistent wealth inequality. We tentatively link differences in asset holding patterns across countries to differences in institutions, such as mortgage market institutions and house price-to-rent ratios.",100.0,https://doi.org/10.2139/ssrn.2490969766a33a6440d3a43c11be719a4f8a6b9a85a320afa4,10.1016/j.proenv.2011.07.017,Geographically Weighted Regression Using a Non-Euclidean Distance Metric with a Study on London House Price Data,2011.0,,Binbin Lu; M. Charlton; A. Stewart Fotheringhama,"Geographically Weighted Regression (GWR) is a local modelling technique to estimate regression models with spatially varying relationships. Generally, the Euclidean distance is the default metric for calibrating a GWR model in previous research and applications; however, it may not always be the most reasonable choice due to a partition by some natural or man-made features. Thus, we attempt to use a non-Euclidean distance metric in GWR. In this study, a GWR model is established to explore spatially varying relationships between house price and floor area with sampled house prices in London. To calibrate this GWR model, network distance is adopted. Compared with the other results from calibrations with Euclidean distance or adaptive kernels, the output using network distance with a fixed kernel makes a significant improvement, and the river Thames has a clear cut-off effect on the parameter estimations.",99.0,https://doi.org/10.1016/j.proenv.2011.07.017767f994559f690250ac6eb77d1e14251291e09c21c0,10.1016/j.landusepol.2018.03.045,"Policy change, amenity, and spatiotemporal dynamics of housing prices in Nanjing, China",2018.0,Land Use Policy,Feng-Lin Yuan; Jia-Wei Wu; Y. Wei; Lei Wang,"Understanding the spatiotemporal heterogeneity of the housing market is critical for formulating land/housing policies and achieving sustainable urbanization. This study analyzes the housing transactions at the city, community, and apartment levels in Nanjing, focusing on the effects of government policy and amenity. We find that housing prices have appreciated significantly in Chinese cities, and prices also vary within cities. We also find that changes in government policies, especially policies for the development of new urban districts and public facilities, significantly influence the spatiotemporal heterogeneity and dynamics of housing prices. Moreover, high-quality schools provided by governments are evidently exerting an increasing influence on housing values, while proximities to parks, (sub-)CBDs and government service centers also emerge as important factors. We can therefore summarize that housing price variation within Chinese cities is largely institutionally driven, and the Chinese government is the dominant agent of creating uneven urban development in China. We suggest that development policies should consider the need and location of residential areas and improve ",99.0,76871d275a0df756d330dfaa1a827205ce0bb9b9b41,10.1101/2020.06.09.20126805,What does and does not correlate with COVID-19 death rates,2020.0,medRxiv,Christopher R. Knittel; Bora Ozaltun,"We correlate county-level COVID-19 death rates with key variables using both linear regression and negative binomial mixed models, although we focus on linear regression models. We include four sets of variables: socio-economic variables, county-level health variables, modes of commuting, and climate and pollution patterns. Our analysis studies daily death rates from April 4, 2020 to May 27, 2020. We estimate correlation patterns both across states, as well as within states. For both models, we find higher shares of African American residents in the county are correlated with higher death rates. However, when we restrict ourselves to correlation patterns within a given state, the statistical significance of the correlation of death rates with the share of African Americans, while remaining positive, wanes. We find similar results for the share of elderly in the county. We find that higher amounts of commuting via public transportation, relative to telecommuting, is correlated with higher death rates. The correlation between driving into work, relative to telecommuting, and death rates is also positive across both models, but statistically significant only when we look across states",98.0,https://www.medrxiv.org/content/medrxiv/early/2020/06/11/2020.06.09.20126805.full.pdf769db8a3faa3780e81eade4d76093121ed88d023484,10.1111/j.1540-6229.2009.00242.x,House Price Changes and Idiosyncratic Risk: The Impact of Property Characteristics,2009.0,,Steven C. Bourassa; Donald R. Haurin; Jessica L. Haurin; M. Hoesli; Jian Sun,,98.0,https://doi.org/10.2139/ssrn.87345177065d48061efcc2ee43e9951cf6ba9e7781bef4946,10.3828/jtep.1990.24.1.49,Aircraft Noise and Residential Property Values Adjacent to Manchester International Airport,1990.0,Journal of Transport Economics and Policy,G. Pennington; N. Topham; R. Ward,Lower market values of properties affected by aircraft noise are found to be wholly attributable to the neighbourhood and other characteristics of the properties - the effects of noise are insignificant. The authors question the need for the proposed ban on aircraft with acoustical certificates issued before 1977.,98.0,771cf2ceb976c9b804633f11d3a52d477f348c07eeb,10.1109/ieem.2017.8289904,A hybrid regression technique for house prices prediction,2017.0,IEEE International Conference on Industrial Engineering and Engineering Management,Sifei Lu; Zeng-Xiang Li; Zheng Qin; Xulei Yang; R. Goh,,98.0,7724bc8bd1fab3d1dc24e8c3d6cd2b071c091183974,10.1016/j.envint.2019.01.061,"Wastewater-based epidemiology in Beijing, China: Prevalence of antibiotic use in flu season and association of pharmaceuticals and personal care products with socioeconomic characteristics.",2019.0,Environment International,Yi-Zhe Zhang; L. Duan; Bin Wang; Yulin Du; G. Cagnetta; Jun Huang; Lee Blaney; Gang Yu,"Wastewater-based epidemiology is an emerging field that has mostly been applied to investigate consumption of illicit drugs. In this study, the wastewater-based epidemiology approach was employed to study consumption of pharmaceuticals and personal care products (PPCPs) and measure their prevalence of use in eight densely populated, urban areas of Beijing, China. Ammonium loads were used to estimate the population equivalents of each sewershed. These estimates were applied to calculate population-normalized antibiotic consumption and prevalence of use during flu season, when antibiotics are frequently misused as a medical treatment. Results indicated that 21.9 g d-1 (104 people)-1 of ten popular antibiotics were consumed across the eight sewersheds, indicating that 1.98‰ of the 12.5 million population equivalents used these antibiotics during the sampling period. A comparison of these results to calculations made using previously reported data from 2013 suggest that recent Chinese antibiotic control policies have been effective. Uncertainty analyses were conducted to identify the 95% confidence range for antibiotic prevalence of use as 1.44-3.61‰. Human excretion factors were ident",97.0,https://www.sciencedirect.com/science/article/pii/S0160412018320877/pdf7737a7e0d7a532134e064d43b123f5b76b8428af733,10.1016/j.jeem.2019.02.006,The impact of flooding on property prices: A repeat-sales approach,2019.0,Journal of Environmental Economics and Management,Allan Beltrán; D. Maddison; R. Elliott,"Abstract In this paper we use a repeat-sales model to analyse the price path of properties affected by flooding in England between 1995 and 2014. Our dataset contains information on 4.8 million houses with at least one repeat-sale. This database is merged with high-definition GIS data delineating the spatial extent of all recorded flood incidents in England covering a total area of 2,654 km2. Our results show that immediately after a flood event the price of property in a postcode entirely inundated by inland flooding is on average 24.9% lower than non-flooded property, whereas for property in a postcode entirely inundated by coastal flooding the price reduction is 21.1%. Nonetheless, we find that this discount is short-lived and the discount is no longer statistically significant for properties affected by inland flooding after 5 years, which falls to just 4 years for properties affected by coastal flooding. For lower-priced properties however, the post-flood price discount can be observed up to 6–7 years for both inland and coastal flooding. The magnitude of the impact also depends on the characteristics of the properties, the characteristics of the flood and the existence of flo",97.0,https://research.birmingham.ac.uk/portal/en/publications/the-impact-of-flooding-on-property-prices(df4b207c-6f77-4c62-b16b-0259b3c2c5a7).html77475733ce74a1ba8ee58025e83c7c20dc90d75c6cd,10.1016/j.trd.2020.102596,"Variation in ride-hailing trips in Chengdu, China",2021.0,,Si-Cheng Wang; R. Noland,"Abstract We investigate various spatial, economic, and land-use factors associated with the generation of trips for ride-hailing services in Chengdu, China. Using one month of data for DiDi Chuxing trips in Chengdu, we characterize the unique pattern of TNC ride-hailing trips over space and for different time periods. We examine the association between the generation of ride-hailing trips and spatial characteristics, including population density, floor-area ratio, housing prices, road networks, the proximity of public transit, land use mix, and points of interests. We estimate “global” regression models and “local” Geographically Weighted Regression models that account for the spatial variation of each factor on trip generation. Results suggest that population density, local road density, floor-area ratio, housing price, and the proximity to subways have positive associations with DiDi trip generation. We also examine the spatial variation associated with the local population density coefficients which vary throughout the city.",97.0,https://scholarship.libraries.rutgers.edu/esploro/fulltext/journalArticle/Variation-in-ride-hailing-trips-in-Chengdu/991031578749004646?repId=12648349680004646&mId=13648349670004646&institution=01RUT_INST7752f2f4935810c94b36fefa44c90d1841663e0b2f3,10.2307/252950,Flood Hazard Pricing and Insurance Premium Differentials: Evidence From the Housing Market,1990.0,,Don N. Macdonald; Harry L. White; P. M. Taube; W. Huth,,97.0,77698cc940874e216441427b1c5c025206d6bf94dc1,10.1108/ijhma-04-2014-0008,Factors influencing the price of housing in Indonesia,2015.0,,R. A. Rahadi; S. K. Wiryono; Deddy P. Koesrindartoto; I. B. Syamwil,"Purpose - – This study aims to address the factors or attributes that would influence the price of residential products in Jakarta Metropolitan Region. Design/methodology/approach - – In total, 202 respondents from all across Jakarta Metropolitan Region participated in the questionnaire for this study. Demographic questions are categorized into age, gender and preferences for real estate locations. The questionnaire was made based on the author’s previous studies. Of the total respondents, 127 were males and 75 were females with age ranging from 18 to 56 years old. For data analysis, the authors utilized factor analysis, Cronbach’ a test and analysis of correlation to reach the conclusion of this study. Findings - – The findings suggested that from the initial three factors groups, there are five new groups that emerge as influencing factors for housing prices. Cronbach’ a score were verified (a = 0.906). Correlation study result suggested that the initial three factors groups produce a significant correlation between each of them, except for the factor of “overall location” and “located near family.” After factor analysis, the research results show that there are two new additiona",96.0,777d458e3973f160efbbd5c7fd28ec076d63dc933e1,10.1007/s11146-009-9195-x,An Estimation of the Coastal Premium for Residential Housing Prices in San Diego County,2011.0,,Stephen J Conroy; Jennifer Milosch,"The authors attempt to estimate the “coastal premium”—additional value conferred on a residence from being located near the coast—of single family homes in San Diego County, while controlling for other locational and structural characteristics. A previous investigation published in 2001 for south Orange County found that moving away from the coast by one mile was associated with a $42,000 lower housing price. Intrigued by this finding, we investigate whether (a) a similar coastal premium exists for all of San Diego County and (b) the premium varies by incremental distance from the coast (e.g., for 500-feet increments). Using data from 9,755 San Diego County home sales in 2006, results presented here suggest that for a median-priced home ($540,000) at the mean distance from the coast (approximately 9 miles—and considerably farther than the Orange County estimate) a one-mile increase in distance from the coast would reduce the sale price by approximately $8,680. Specifying by specific distance increments, we find that the coastal premium is approximately 101.9% for houses within 500 feet of the coast (i.e., their value is 101.9% higher than similar homes located beyond six miles of t",95.0,https://link.springer.com/content/pdf/10.1007/s11146-009-9195-x.pdf7786b87d18d546137967ad2389b93e258d14eca09c6,10.1016/j.enbuild.2019.05.018,The effect of neighbourhood-level urban form on residential building energy use: A GIS-based model using building energy benchmarking data in Seattle,2019.0,Energy and Buildings,Yongjin Ahn; Dong-Wook Sohn,"Abstract Despite numerous studies on computerised simulations for analysing the relationship between the physical characteristics of an urban environment and energy consumption in buildings, the correlation between the actual energy use and physical parameters influencing a building's energy performance has rarely been explored. Previous research has identified several physical characteristics of the urban environment as potential drivers of a building's energy demand. Using the building energy consumption data from the Seattle city government, and geographic information system (GIS) data obtained from the Washington Geospatial Data Archive, this study presents an investigation of the effect of three urban form variables—horizontal compactness, vertical density, and variation of building heights—on the residential energy consumption of multi-family housings in Seattle. The results of the spatial lag models of building energy use and its neighbourhood-level correlates confirm that the building's energy consumption is spatially dependent. In Seattle, the annual energy use of a multi-family building was reduced with an increased horizontal density and smaller variations in building he",95.0,779ba5ed03c8923ba8be83e8e6cc5c7d830cea3ae82,10.1093/rof/rfac022,Data vs Collateral,2020.0,Review of Finance,L. Gambacorta; Yi-Ping Huang; Zhenhua Li; Hannuo Qiu; Shu Chen,"780 Using a unique dataset of more than 2 million Chinese firms that received credit from both an important big tech firm (Ant Group) and traditional commercial banks, this paper investigates how different forms of credit correlate with local economic activity, house prices and firm characteristics. We find that big tech credit does not correlate with local business conditions and house prices when controlling for demand factors, but reacts strongly to changes in firm characteristics, such as transaction volumes and network scores used to calculate firm credit ratings. By contrast, both secured and unsecured bank credit react significantly to local house prices, which incorporate useful information on the environment in which clients operate and on their creditworthiness. This evidence implies that the wider use of big tech credit could reduce the importance of the collateral channel but, at the same time, make lending more reactive to changes in firms’ business activity.",94.0,781cb0a26e016a856d0b443b7d536c811f5bec53484,10.1080/09599916.2021.1996446,Second-hand house price index forecasting with neural networks,2021.0,Journal of Property Research,Xiaojie Xu; Yun Zhang,"ABSTRACT The house market in China has been growing rapidly for the past decade and price forecasting has become a significant issue to the people and policymakers. We approach this problem by examining neural networks for second-hand house price index forecasting from 10 major cities for March 2012–May 2020. Our purpose is to build simple and accurate neural networks to contribute to pure technical house price forecasting of the Chinese market. We explore various model settings across the algorithm, delay, hidden neuron, and data spitting ratio, and arrive at a rather simple neural network with three delays and eight hidden neurons, which leads to stable performance of 0.8% average relative root-mean-square error across the 10 cities for the training, validation, and testing phases. Results here can be used on a standalone basis or combined with fundamental forecasting in forming perspectives of house price trends and conducting policy analysis.",94.0,7828c47d5caab58baa3f592023102bbfa6419c66471,10.1016/j.landusepol.2020.104528,"Effect of the housing purchase restriction policy on the Real Estate Market: Evidence from a typical suburb of Beijing, China",2020.0,,Yao-Yao Li; Dao-Lin Zhu; Jiangmeng Zhao; Xiaodong Zheng; Lan-Yue Zhang,"Abstract To curb excessive rises in housing prices, the government has instituted a series of macro-control measures in the real estate market. The housing purchase restriction (HPR) policy, one of the most severe policies, aims to curb a rapid rise in housing prices by excluding investment demand for housing. The real estate market of Langfang City was a particularly pertinent case because it is adjacent to Beijing, the capital of China. This study collected 11,597 sets of second-hand housing transaction data from five counties around Beijing in Langfang. A regression discontinuity design was then used to indicate that the HPR policy of Langfang did not significantly reduce the price of second-hand houses in the study area. In addition, the effect of the HPR policy on housing prices had an obvious spatial heterogeneity. Within 500 m of the buffer zone around Beijing, the implementation of the HPR policy significantly increased the price by 8.07 %. Within 1000 m of the buffer zone, the implementation of the policy increased the price by an average of 6.70 %. Although the HPR policy played a role in reducing the price further than 1000 m, it was not robust. Finally, the paper highli",92.0,783ae4861428c7c7e583c05d5495f1efc10648aff7f,10.2139/ssrn.910667,Regional Business Cycles in New Zealand: Do they exist? What might drive them?,2004.0,,V. Hall; C. McDermott,"We use National Bank of New Zealand Regional Economic Activity data, to identify and characterise classical business cycle turning points, for New Zealand's 14 regions and aggregate New Zealand activity. Using Concordance statistic measures, logistic model and GMM estimation methods, meaningful regional business cycles have been identified and a number of significant associations established. All regions exhibit cyclical asymmetry for both durations and amplitudes, and synchronisations between aggregate NZ activity and each region are contemporaneous. The regional cycles rarely die of old age but are terminated by particular events. The regions most highly synchronised with the NZ activity cycle are Auckland, Canterbury, and Nelson-Marlborough; those least so are Gisborne and Southland. Noticeably strong co-movements are evident for certain regions. Geographical proximity matters, and unusually dry conditions can be associated with cyclical downturns in certain regions. There is no discernable evidence of association with net immigration movements, and no significant evidence of regional cycle movements being associated with real national house price cycles. The agriculture-based n",91.0,https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/j.1435-5957.2007.00119.x784783542bde70478f53dea2d9af920eb66c5e15483,10.1108/17538270910977572,Housing price volatility and its determinants,2009.0,,C. Lee,,90.0,785b1845502319aed3660f94a9f1528c3f2ac2f8e9f,10.1007/s10666-018-9597-3,Assessment of Flood Losses with Household Responses: Agent-Based Simulation in an Urban Catchment Area,2018.0,Environmental Modelling and Assessment,L. Yang; J. Scheffran; D. Süsser; R. Dawson; Y. Chen,"Densely populated coastal urban areas are often exposed to multiple hazards, in particular floods and storms. Flood defenses and other engineering measures contribute to the mitigation of flood hazards, but a holistic approach to flood risk management should consider other interventions from the human side, including warning information, adaptive behavior, people/property evacuation, and the multilateral relief in local communities. There are few simulation approaches to consider these factors, and these typically focus on collective human actions. This paper presents an agent-based model that simulates flood response preferences and actions taken within individual households to reduce flood losses. The model implements a human response framework in which agents assess different flood scenarios according to warning information and decide whether and how much they invest in response measures to reduce potential inundation damages. A case study has been carried out in the Ng Tung River basin, an urbanized watershed in northern Hong Kong. Adopting a digital elevation model (DEM) as the modeling environment and a building map of household locations in the case area, the model considers",89.0,https://link.springer.com/content/pdf/10.1007%2Fs10666-018-9597-3.pdf786670de17a2cea9033a002b2058faeb759a64133f0,10.1016/j.habitatint.2017.03.007,"Spatial effect of river landscape on housing price: An empirical study on the Grand Canal in Hangzhou, China",2017.0,,Hai-Zhen Wen; Yue Xiao; Ling Zhang,,89.0,7878f9d34d9cf70640fce27072a23f4670e02d1dc54,10.1002/jae.2792,Estimation and inference for spatial models with heterogeneous coefficients: An application to US house prices,2020.0,Journal of applied econometrics,M. Aquaro; N. Bailey; M. Pesaran,"This paper considers the problem of identification, estimation and inference in the case of spatial panel data models with heterogeneous spatial lag coefficients, with and without (weakly) exogenous regressors, and subject to heteroskedastic errors. A quasi maximum likelihood (QML) estimation procedure is developed and the conditions for identification of spatial coefficients are derived. Regularity conditions are established for the QML estimators of individual spatial coefficients, as well as their means (the mean group estimators), to be consistent and asymptotically normal. Small sample properties of the proposed estimators are investigated by Monte Carlo simulations for Gaussian and non-Gaussian errors, and with spatial weight matrices of differing degrees of sparsity. The simulation results are in line with the paper's key theoretical findings even for panels with moderate time dimensions, irrespective of the number of cross section units. An empirical application to U.S. house price changes during the 1975-2014 period shows a significant degree of heterogeneity in spill-over effects over the 338 Metropolitan Statistical Areas considered.",88.0,https://www.cesifo.org/DocDL/cesifo1_wp7542.pdf7889fa7e0e1746e7692081411abf3815c07c8165468,10.1016/j.cities.2021.103185,Roles of locational factors in the rise and fall of restaurants: A case study of Beijing with POI data,2021.0,,Mingbo Wu; T. Pei; Wenlai Wang; Si-Hui Guo; Ci Song; Jie Chen; Cheng-Hu Zhou,"Abstract Restaurants are basic urban amenities. With the dynamic evolution of cities, restaurants rise and fall: new restaurants may open (birth), and existing restaurants may close (death). Analyzing the rise and fall of restaurants may assist urban dynamics exploration and urban policy assessment. Location is crucial for restaurant success. Roles of locational factors in restaurants' rise and fall were empirically explored in this case study of Beijing based on point of interest (POI) data, a more available and universal data source than conventional statistics used by previous studies. We characterized restaurant birth and death through matching POI data across years, examined their spatial patterns, and regressed restaurant distribution, birth, and death against various locational factors with count regression models. The rise and fall of restaurants revealed the impact of policies relieving Beijing of functions non-essential to its role as China's capital. Regressions suggested four roles of locational factors: 1) Promoting factors, including accessibility, commercial land use, and building capacity; 2) Hindering factors, namely, existing restaurant density; 3) Stabilizing fac",88.0,78951bd71d118c348c6fea8c03557e3a4d2712b7442,10.1192/bjp.2019.100,Neighbourhood characteristics and prevalence and severity of depression: pooled analysis of eight Dutch cohort studies,2019.0,British Journal of Psychiatry,E. Generaal; E. Hoogendijk; M. Stam; Celina E. Henke; F. Rutters; M. Oosterman; M. Huisman; S. Kramer; P. Elders; E. Timmermans; J. Lakerveld; E. Koomen; M. ten Have; R. de Graaf; M. Snijder; K. Stronks; G. Willemsen; D. Boomsma; J. Smit; B. Penninx,"Background Studies on neighbourhood characteristics and depression show equivocal results. Aims This large-scale pooled analysis examines whether urbanisation, socioeconomic, physical and social neighbourhood characteristics are associated with the prevalence and severity of depression. Method Cross-sectional design including data are from eight Dutch cohort studies (n = 32 487). Prevalence of depression, either DSM-IV diagnosis of depressive disorder or scoring for moderately severe depression on symptom scales, and continuous depression severity scores were analysed. Neighbourhood characteristics were linked using postal codes and included (a) urbanisation grade, (b) socioeconomic characteristics: socioeconomic status, home value, social security beneficiaries and non-Dutch ancestry, (c) physical characteristics: air pollution, traffic noise and availability of green space and water, and (d) social characteristics: social cohesion and safety. Multilevel regression analyses were adjusted for the individual's age, gender, educational level and income. Cohort-specific estimates were pooled using random-effects analysis. Results The pooled analysis showed that higher urbanisation gra",87.0,https://www.cambridge.org/core/services/aop-cambridge-core/content/view/ABB0DB9FE78B28BFE4E2ED7EAE69FE03/S0007125019001004a.pdf/div-class-title-neighbourhood-characteristics-and-prevalence-and-severity-of-depression-pooled-analysis-of-eight-dutch-cohort-studies-div.pdf790fee2ebeee4eafa6b7e9e3cafd5aa3c8daa232aff,10.1093/restud/rdaa029,"The Impact of Immigration on Wages, Internal Migration, and Welfare",2020.0,The Review of Economic Studies,Suphanit Piyapromdee,"791 This article studies the impact of immigration on wages, internal migration, and welfare. Using U.S. Census data, I estimate a spatial equilibrium model where labour differs by skill level, gender, and nativity. Workers are heterogeneous in city preferences. Cities vary in productivity levels, housing prices, and amenities. I use the estimated model to assess the distributional consequences of several immigration policies. The results show that a skill selective immigration policy leads to welfare gains for low skill workers, but welfare losses for high skill workers. The negative impacts are more substantial among the incumbent high skill immigrants. Internal migration mitigates the initial negative impacts, particularity in cities where housing supplies are inelastic. However, the negative wage impacts on some workers intensify. This is because an out-migration of workers of a given type may raise the local wages for workers of that type, while reducing the local wages of workers with complementary characteristics. Overall, there are substantial variations in the welfare effects of immigration across and within cities. Further, I use the model to assess the welfare effects of t",87.0,https://discovery.ucl.ac.uk/10094994/1/Immigration_v43_Restud_R3.pdf792a3b80386bfb59c8617620d3b748a2f6be7a231d9,10.1016/j.jue.2013.07.003,Do Political Parties Matter for Local Land Use Policies?,2013.0,Social Science Research Network,alberT Solé-Ollé; Elisabet Viladecans-Marsal,"Despite interest in the impact of land use regulations on housing793construction and housing prices, little is known about the drivers of these policies. The794conventional wisdom holds that homeowners have an influence on restrictive local795zoning. In this paper, we contend that the party controlling local government might796make a major difference. We draw on data from a large sample of Spanish cities for the7972003-2007 political term and employ a regression discontinuity design to document798that cities controlled by left-wing parties convert much less land from rural to urban799uses than is the case in similar cities controlled by the right. The differences between800governments on the two sides of the political spectrum are more pronounced in places801with greater population heterogeneity and in those facing higher housing demand.",87.0,https://doi.org/10.2139/ssrn.228477380209578f6de2b11892678adc47aa9ac46d0467b122,10.1016/j.apgeog.2019.102136,Understanding Airbnb spatial distribution in a southern European city: The case of Barcelona,2020.0,,R. Lagonigro; J. Martori; P. Apparicio,"Abstract The recent proliferation of private tourist accommodations on what has been known as sharing economy has induced new models on urban tourism and on the use of traditional housing. Urban tourism pressure has caused many transformation processes with important impacts in neighborhoods with high tourist interest. In our work, we analyze the spatial distribution of Airbnb accommodations in the city of Barcelona and we explore the factors associated with the situation of Airbnb rentals in relation to the socioeconomic characteristics of the population and tourism indicators. In order to model spatial non-stationarity, a Geographically Weighted Regression (GWR) model has been used. The GWR model proposed in our study provides local insight to gain understanding of how socioeconomic factors explain the variation of the ratio of Airbnb short-term rentals in the different neighborhoods of the city and reveals dissimilar correlations in several areas. The main factors explaining the variation on the ratio of Airbnb rentals over the total number of households are family income, education level, and dwelling size, with opposed spatial patterns of positive and negative significant coef",87.0,8036032003c248d3b31ed659fc5d5b2680feeb3490d,10.1007/s00521-022-07309-y,Residential housing price index forecasting via neural networks,2022.0,Neural computing & applications (Print),Xiaojie Xu; Yun Zhang,,87.0,8043f833b220ee504e341720a456f2e8e006e869c0a,10.5815/ijmecs.2020.06.04,House Price Prediction using a Machine Learning Model: A Survey of Literature,2020.0,International Journal of Modern Education and Computer Science,Nor Hamizah Zulkifley; Shuzlina Abdul-Rahman; N. Ubaidullah; I. Ibrahim,": Data mining is now commonly applied in the real estate market. Data mining's ability to extract relevant knowledge from raw data makes it very useful to predict house prices, key housing attributes, and many more. Research has stated that the fluctuations in house prices are often a concern for house owners and the real estate market. A survey of literature is carried out to analyze the relevant attributes and the most efficient models to forecast the house prices. The findings of this analysis verified the use of the Artificial Neural Network, Support Vector Regression and XGBoost as the most efficient models compared to others. Moreover, our findings also suggest that locational attributes and structural attributes are prominent factors in predicting house prices. This study will be of tremendous benefit, especially to housing developers and researchers, to ascertain the most significant attributes to determine house prices and to acknowledge the best machine learning model to be used to conduct a study in this field",86.0,https://doi.org/10.5815/ijmecs.2020.06.04805572bdb7f10c65849aca8448a6c9a09168fdcdf68,10.1007/s11146-009-9203-1,Repeat Sales Index for Thin Markets,2010.0,,Marc K. Francke,"The repeat sales model is commonly used to construct reliable house price indices in absence of individual characteristics of the real estate. Several adaptations of the original model by Bailey et al. (J Am Stat Assoc 58:933–942, 1963) are proposed in literature. They all have in common using a dummy variable approach for measuring price indices. In order to reduce the impact of transaction price noise on the estimates of price indices, Goetzmann (J Real Estate Finance Econ 5:5–53, 1992) used a random walk with drift process for the log price levels instead of the dummy variable approach. The model that is proposed in this article can be interpreted as a generalization of the Goetzmann methodology. We replace the random walk with drift model by a structural time series model, in particular by a local linear trend model in which both the level and the drift parameter can vary over time. An additional variable—the reciprocal of the time between sales—is included in the repeat sales model to deal with the effect of the time between sales on the estimated returns. This approach is robust can be applied in thin markets where relatively few selling prices are available. Contrary to the ",85.0,https://link.springer.com/content/pdf/10.1007/s11146-009-9203-1.pdf806254126ab0eeb5d42d9310c9dacc928cc10ca057d,10.3390/land12040831,Monitoring House Vacancy Dynamics in The Pearl River Delta Region: A Method Based on NPP-VIIRS Night-Time Light Remote Sensing Images,2023.0,Land,Xuan Liu; Ze-Hao Li; Xinyi Fu; Zheng-Tong Yin; Ming-Zhe Liu; L. Yin; Wen-Feng Zheng,"Urban spatial interaction integrates cities into closely related urban network systems in continuous urban regions. However, it also brings differentiation and has mutual negative impacts between each location. Unbalanced development is one such impacts and needs closely monitoring. The housing vacancy rate (HVR) in a continuous urban region is an important index in the unbalanced development of a continuous urban region since it indicates the uneven distribution of population and investment across cities. This study uses NPP-VIIRS NTL data and Landsat 8 OLT images to estimate HVRs at the district level. Additionally, this study tracks the spatial–temporal dynamics of HVR distributions in the Pearl River Delta (PRD) region. The comparison between the sampled HVRs and estimated HVRs verifies the effectiveness of the estimated HVRs in identifying dynamic changes in HVRs. This study has found that although overall decreasing HVRs are observed in the PRD, speculations and irrational real estate investment exist in cities on the west bank of the Pearl River Estuary and in some isolated districts in other cities. Furthermore, increasing proportions of vacant pixels in most cities indicat",85.0,https://doi.org/10.3390/land120408318073730a54ec2a8a9214678176bb99b6a20ed2c6e61,10.2139/ssrn.2492234,Speed 2.0: Evaluating Access to Universal Digital Highways,2017.0,,Gabriel M. Ahlfeldt; Pantelis Koutroumpis; T. Valletti,"This paper shows that having access to a fast Internet connection is an important determinant of capitalization effects in property markets. Our empirical strategy combines a boundary discontinuity design with controls for time-invariant effects and arbitrary macro-economic shocks at a very local level to identify the causal effect of broadband speed on property prices from variation that is plausibly exogenous. Applying this strategy to a micro data set from England between 1995 and 2010 we find a significantly positive effect, but diminishing returns to speed. Our results imply that disconnecting an average property from a high-speed first-generation broadband connection (offering Internet speed up to 8 Mbit/s) would depreciate its value by 2.8%. In contrast, upgrading such a property to a faster connection (offering speeds up to 24 Mbit/s) would increase its value by no more than 1%. We decompose this effect by income and urbanization, finding considerable heterogeneity. These estimates are used to evaluate proposed plans to deliver fast broadband universally. We find that increasing speed and connecting unserved households passes a cost-benefit test in urban and some suburban a",85.0,https://doi.org/10.2139/ssrn.24922348084412aee0e7a8f6e06b29fcf503a47f1ab09ffd8c,10.3390/ijgi11040242,Incorporating Spatial Autocorrelation in Machine Learning Models Using Spatial Lag and Eigenvector Spatial Filtering Features,2022.0,ISPRS Int. J. Geo Inf.,Xiaojian Liu; O. Kounadi; R. Zurita-Milla,"Applications of machine-learning-based approaches in the geosciences have witnessed a substantial increase over the past few years. Here we present an approach that accounts for spatial autocorrelation by introducing spatial features to the models. In particular, we explore two types of spatial features, namely spatial lag and eigenvector spatial filtering (ESF). These features are used within the widely used random forest (RF) method, and their effect is illustrated on two public datasets of varying sizes (Meuse and California housing datasets). The least absolute shrinkage and selection operator (LASSO) is used to determine the best subset of spatial features, and nested cross-validation is used for hyper-parameter tuning and performance evaluation. We utilize Moran’s I and local indicators of spatial association (LISA) to assess how spatial autocorrelation is captured at both global and local scales. Our results show that RF models combined with either spatial lag or ESF features yield lower errors (up to 33% different) and reduce the global spatial autocorrelation of the residuals (up to 95% decrease in Moran’s I) compared to the RF model with no spatial features. The local aut",84.0,https://www.mdpi.com/2220-9964/11/4/242/pdf?version=1649398052809bd50a67fe743f42f6f0fb4702231f0844b79f000,10.5220/0006040700620068,House Price Estimation from Visual and Textual Features,2016.0,International Joint Conference on Computational Intelligence,Eman Ahmed; Mohamed N. Moustafa,"Most existing automatic house price estimation systems rely only on some textual data like its neighborhood area and the number of rooms. The final price is estimated by a human agent who visits the house and assesses it visually. In this paper, we propose extracting visual features from house photographs and combining them with the house's textual information. The combined features are fed to a fully connected multilayer Neural Network (NN) that estimates the house price as its single output. To train and evaluate our network, we have collected the first houses dataset (to our knowledge) that combines both images and textual attributes. The dataset is composed of 535 sample houses from the state of California, USA. Our experiments showed that adding the visual features increased the R-value by a factor of 3 and decreased the Mean Square Error (MSE) by one order of magnitude compared with textual-only features. Additionally, when trained on the benchmark textual-only features housing dataset, our proposed NN still outperformed the existing model published results.",84.0,https://doi.org/10.5220/0006040700620068810ba886a27ec4cc47f7e244817b93ecb87915bf430,10.2139/ssrn.3293399,Expectations Uncertainty and Household Economic Behavior,2018.0,,Itzhak Ben-David; Elyas Fermand; C. Kuhnen; Lin-Tian Geng,"We show that there exists significant heterogeneity across US households in how uncertain they are in their expectations regarding personal and macroeconomic outcomes, and that uncertainty in expectations predicts households' choices. Individuals with lower income or education, more precarious finances, and living in counties with higher unemployment are more uncertain in their expectations regarding own-income growth, inflation, and national home price changes. People with more uncertain expectations, even accounting for their socioeconomic characteristics, exhibit more precaution in their consumption, credit, and investment behaviors.",84.0,https://doi.org/10.2139/ssrn.3293399811063a45d2d00b5795df901fd9bbb8c8879ace21ee,10.1016/j.envres.2022.113397,"Identifying the spatial heterogeneity in the effects of the construction land scale on carbon emissions: Case study of the Yangtze River Economic Belt, China.",2022.0,Environmental Research,Min Wang; Yang Wang; Ying-Mei Wu; Xiao-Li Yue; Meng-Jiao Wang; Pingping Hu,"Low-carbon emissions are a major research focus to solve the problem of global warming and an important area that China needs to focus on to achieve high-quality development. Construction land scale is a non-negligible factor affecting carbon emissions. However, carbon emission impacts of county-scale spatial heterogeneity in construction land scale are under addressed in contemporary research. To address this gap, this paper took 1042 counties in China's Yangtze River Economic Belt (YREB) and developed datasets of the influencing factors including the construction land scale, GDP, secondary industry output proportion in GDP, residential population, and fixed asset investment. After comparing the ordinary least squares and geographically weighted regression (GWR) models, we applied GWR for more in-depth analyses. The global regression model results showed that the effect of the scale of construction land on carbon emissions was exceedingly significant and that the directions of the impacts coincided with the predictions. Further, local regression model results showed that construction land scale had significant spatial heterogeneity in the impact on carbon emissions and most counti",83.0,8128680fb5772ac5f1f54de39bc55efe52a7ca42812,10.2139/ssrn.2192658,Do Housing Prices Reflect Environmental Health Risks? Evidence from More than 1600 Toxic Plant Openings and Closings,2012.0,,Janet Currie; Lucas W. Davis; Michael Greenstone; Reed Walker,"A ubiquitous and largely unquestioned assumption in studies of housing markets is that there is perfect information about local amenities. This paper measures the housing market and health impacts of 1,600 openings and closings of industrial plants that emit toxic pollutants. We find that housing values within one mile decrease by 1.5 percent when plants open, and increase by 1.5 percent when plants close. This implies an aggregate loss in housing values per plant of about $1.5 million. While the housing value impacts are concentrated within 1/2 mile, we find statistically significant infant health impacts up to one mile away.",83.0,https://doi.org/10.2139/ssrn.2192658813c9931b4640cad4fa14b30afa7c444830a75a7eae,10.1177/0042098011404936,Historic Preservation and Residential Property Values: Evidence from Quantile Regression,2012.0,,Velma Zahirovic-Herbert; Swarn Chatterjee,,83.0,8146ec56d25384649ba0577a988ce53ae65f7ae63b8,10.1101/839969,Patterns of sociocognitive stratification and perinatal risk in the child brain,2019.0,Proceedings of the National Academy of Sciences of the United States of America,D. Alnæs; T. Kaufmann; A. Marquand; Stephen M. Smith; L. Westlye,"Significance Adolescence is a transition period between childhood to adulthood, associated with heightened sensitivity to the social and cultural environment, and offers opportunities for adaptation and growth but also increased susceptibility to detrimental perturbations. We reveal three population-level patterns in children aged 9 to 11, linking measures of brain morphology and white matter fiber properties to cognitive, behavioral, psychosocial, and socioeconomic measures. They reveal associations with early life factors, such as preterm birth, birth complications, and duration of breastfeeding; socioeconomic and cognitive stratification; and urbanicity, home value, and air pollution. The results support that political priorities and decisions aiming to improve health outcomes and adaptation during transformative life phases should be based on interdisciplinary perspectives integrating social, psychological, and biological sciences. The expanding behavioral repertoire of the developing brain during childhood and adolescence is shaped by complex brain–environment interactions and flavored by unique life experiences. The transition into young adulthood offers opportunities for ada",81.0,https://www.biorxiv.org/content/biorxiv/early/2020/01/26/839969.full.pdf81582df4d44d5c125054ba33df1ea1b45835d4baa3e,10.1136/jech-2016-208475,"Inequalities in tobacco outlet density by race, ethnicity, and socioeconomic status, 2012, USA: Results from the ASPiRE Study",2017.0,Journal of Epidemiology and Community Health,Joseph G. L. Lee; Dennis L. Sun; Nina Schleicher; K. Ribisl; D. Luke; Lisa Henriksen,"Background Evidence of racial/ethnic inequalities in tobacco outlet density is limited by: (1) reliance on studies from single counties or states, (2) limited attention to spatial dependence, and (3) an unclear theory-based relationship between neighbourhood composition and tobacco outlet density. Methods In 97 counties from the contiguous USA, we calculated the 2012 density of likely tobacco outlets (N=90 407), defined as tobacco outlets per 1000 population in census tracts (n=17 667). We used 2 spatial regression techniques, (1) a spatial errors approach in GeoDa software and (2) fitting a covariance function to the errors using a distance matrix of all tract centroids. We examined density as a function of race, ethnicity, income and 2 indicators identified from city planning literature to indicate neighbourhood stability (vacant housing, renter-occupied housing). Results The average density was 1.3 tobacco outlets per 1000 persons. Both spatial regression approaches yielded similar results. In unadjusted models, tobacco outlet density was positively associated with the proportion of black residents and negatively associated with the proportion of Asian residents, white residents",81.0,https://www.ncbi.nlm.nih.gov/pmc/articles/5458784816c2657bda314854e8acbac8a20937218a6661a7cf,10.1016/j.jue.2017.02.002,Nuclear power plant closures and local housing values: Evidence from Fukushima and the German housing market,2017.0,,T. Bauer; S. Braun; M. Kvasnička,"The Fukushima Daiichi accident in Japan in March 2011 caused a fundamental change in Germany’s energy policy which led to the immediate shut down of nearly half of its nuclear power plants. Using data from Germany’s largest internet platform for real estate and employing a difference-in-differences approach, we find that Fukushima reduced housing prices near nuclear power plants that were in operation before Fukushima by 4.9%. Housing prices near sites that were shut down right after the accident even fell by 9.8%. Our results suggest that on the German housing market, the negative economic effects of the closure of nuclear power plants dominate potential positive changes in local amenities.",80.0,https://hdl.handle.net/10419/306480817deb934e30e2e3416eb127b6f11aaf6f3305e2351,10.3828/jtep.1994.28.2.199,Modelling the Effects of Airport Noise on Residential Housing Markets: A Case Study of Winnipeg International Airport,1994.0,Journal of Transport Economics and Policy,T. Levesque,"This hedonic price study uncovers relationships with the number of events and the mean and variance of the loudness of the events. The results suggest models that include cumulative energy noise measures, such as the Noise Exposure Forecast, do not perform as well as models that use the number and loudness of aircraft noise incidents.",80.0,8187cd7a550548ca309f4dd293cd8e7e258fb8b10e4,10.1186/1471-2431-14-45,"Feeding and smoking habits as cumulative risk factors for early childhood caries in toddlers, after adjustment for several behavioral determinants: a retrospective study",2014.0,BMC Pediatrics,A. Majorana; M. Cagetti; E. Bardellini; F. Amadori; G. Conti; L. Strohmenger; G. Campus,"BackgroundSeveral maternal health determinants during the first period of life of the child, as feeding practice, smoking habit and socio-economic level, are involved in early childhood health problems, as caries development. The potential associations among early childhood caries, feeding practices, maternal and environmental smoking exposure, Socio-Economic Status (SES) and several behavioral determinants were investigated.MethodsItalian toddlers (n = 2395) aged 24–30 months were recruited and information on feeding practices, sweet dietary habit, maternal smoking habit, SES, and fluoride supplementation in the first year of life was obtained throughout a questionnaire administered to mothers. Caries lesions in toddlers were identified in visual/tactile examinations and classified using the International Caries Detection and Assessment System (ICDAS). Associations between toddlers’ caries data and mothers’ questionnaire data were assessed using chi-squared test. Ordinal logistic regression was used to analyze associations among caries severity level (ICDAS score), behavioral factors and SES (using mean housing price per square meter as a proxy).ResultsCaries prevalence and severi",79.0,https://bmcpediatr.biomedcentral.com/counter/pdf/10.1186/1471-2431-14-45819a4908625ccfda5cd40bfeb9400b0e333108faa0e,10.3386/w21729,"Bright Minds, Big Rent: Gentrification and the Rising Returns to Skill",2015.0,Social Science Research Network,L. Edlund; Cecilia Machado; M. Sviatschi,"In 1980, housing prices in large US cities rose with distance from the city center. By 2010, that relationship had reversed. We propose that the inversion can be traced to more hours worked by the skilled. Scarce non-market time downgrades the importance of residential space and upgrades that of proximity to work, factors favoring the central-city location. Geo- coded census micro data covering the 27 largest US cities and the period 1980-2010 support our hypothesis: full-time skilled workers are more likely to locate in the city center and their growth can account for the observed price changes.",79.0,https://doi.org/10.2139/ssrn.282367282047c3f3440ec06190a2d4f88a4e151abc21ccdaf4,10.1111/1540-6229.00048,Predicting Spatial Patterns of House Prices Using LPR and Bayesian Smoothing,2002.0,,J. Clapp; Hyon‐Jung Kim; A. Gelfand,,79.0,8218670ef9e494cf9b9485eda0917b30ea0efd367ee,10.1016/j.ejrs.2018.04.006,Carbon stock assessment of mangroves using remote sensing and geographic information system,2020.0,,G. Bindu; P. Rajan; E. S. Jishnu; K. A. Joseph,"Abstract Mangrove forests are among the most carbon-rich habitats on the planet. The protection of mangroves for mitigation of greenhouse gases in the atmosphere as well as for multifaceted sustainable growth of ecosystem is of great scientific concern. Mangrove vegetation in Kerala is now restricted largely to river mouths and tidal creeks with about 15 species of mangroves and 8 associated species. Kannur holds the largest mangrove area in Kerala with an area of about 32 Km2. Located at 12°15′ North and 75°13′ East, Kunhimangalam, in Kannur district, has luxuriant mangroves. A considerable part of mangroves are undergoing destruction and over exploitation. There are organised attempts to acquire all the mangrove areas under private ownership by the real estate groups. Although a large scale conversion of the mangroves was prevented by the timely intervention of local people and NGOs, long term preservation of this system is under question. The urge to establish this mangrove as a protected area is very relevant in this context. The aim of the study is to promote restoration of these mangroves through community and government participation. The study integrates field inventory dat",78.0,https://www.sciencedirect.com/science/article/pii/S1110982317303861/pdf82255d2755a7f64623fb6df72b9e674161910ff16db,10.22004/ag.econ.269086,The impact of public employment: Evidence from Bonn,2020.0,Journal of Urban Economics,Sascha O. Becker; Stephan Heblich; D. Sturm,"This paper evaluates the impact of public employment on private sector activity using the relocation of the German federal government from Berlin to Bonn in the wake of the Second World War as a source of exogenous variation. To guide our empirical analysis, we develop a simple economic geography model in which public sector employment in a city can crowd out private employment through higher wages and house prices, but also generates potential productivity and amenity spillovers. We find that relative to a control group of cities, Bonn experiences a substantial increase in public employment. However, this results in only modest increases in private sector employment with each additional public sector job destroying around 0.2 jobs in industries and creating just over one additional job in other parts of the private sector. We show how this finding can be explained by our model and provide several pieces of evidence for the mechanisms emphasised by the model.",78.0,https://www.sciencedirect.com/science/article/pii/S0094119020300620?via%3Dihub8237f392b79b30b2c429f84e9c6b721b67b0459551a,10.5089/9781513551449.001.a001,LTV and DTI Limits - Going Granular,2015.0,Social Science Research Network,L. I. Jácome; Srobona Mitra,"There is increasing interest in loan-to-value (LTV) and debt-service-to-income (DTI) limits as many countries face a new round of rising house prices. Yet, very little is known on how these regulatory instruments work in practice. This paper contributes to fill this gap by looking closely at their use and effectiveness in six economies — Brazil, Hong Kong SAR, Korea, Malaysia, Poland, and Romania. Insights include: rapid growth in high-LTV loans with long maturities or in the number of borrowers with multiple mortgages can be signs of build up in systemic risk; monitoring nonperforming loans by loan characteristics can help in calibrating changes in the LTV and DTI limits; as leakages are almost inevitable, countries strive to address them at an early stage; and, in most cases, LTVs and DTIs were effective in reducing loan-growth and improving debt-servicing performances of borrowers, but not always in curbing house price growth.",78.0,https://www.elibrary.imf.org/downloadpdf/journals/001/2015/154/001.2015.issue-154-en.xml824c0c761275295ad1801b144a79ec5e98ef8d1c41e,10.1016/j.habitatint.2014.05.001,"Spatial effect of lake landscape on housing price: A case study of the West Lake in Hangzhou, China",2014.0,,Hai-Zhen Wen; Xiao-Qing Bu; Zhong-Fu Qin,,78.0,825baea1cf058d477060835a22631404dabb3dcc9ac,10.1016/j.jclepro.2018.08.220,Pricing for the clean air: Evidence from Chinese housing market,2019.0,Journal of Cleaner Production,Shi-Yi Chen; Hao Jin,"Abstract Air pollution is widely believed to cause healthy risks and influence nations' economic dimensions. This paper investigates the impact of air pollution on housing prices in China's 286 prefectural-level cities during 2005–2013. To address the endogeneity problem of PM2.5 concentrations in our regression, we propose an instrument variable strategy based on ventilation coefficient. The estimation results suggest that a 10% increase in PM2.5 concentrations causes a 2.4% reduction in local housing prices. Air pollution also hinders the progress of urbanization, limits cities' human capital formation and changes people's expectations of housing prices that we interpret as three potential mechanisms behind our main findings.",77.0,https://doi.org/10.1016/j.jclepro.2018.08.2208263191166da780982413170e2c9b4ef27bce8249b4,10.1016/j.scs.2021.103485,"Spatial disparities of self-reported COVID-19 cases and influencing factors in Wuhan, China",2021.0,Sustainable cities and society,Gang Xu; Yuhan Jiang; Shuai Wang; K. Qin; Jing Ding; Yang Liu; Bin-Bin Lu,"The lack of detailed COVID-19 cases at a fine spatial resolution restricts the investigation of spatial disparities of its attack rate. Here, we collected nearly one thousand self-reported cases from a social media platform during the early stage of COVID-19 epidemic in Wuhan, China. We used kernel density estimation (KDE) to explore spatial disparities of epidemic intensity and adopted geographically weighted regression (GWR) model to quantify influences of population dynamics, transportation, and social interactions on COVID-19 epidemic. Results show that self-reported COVID-19 cases concentrated in commercial centers and populous residential areas. Blocks with higher population density, higher aging rate, more metro stations, more main roads, and more commercial point-of-interests (POIs) have a higher density of COVID-19 cases. These five explanatory variables explain 76% variance of self-reported cases using an OLS model. Commercial POIs have the strongest influence, which increase COVID-19 cases by 28% with one standard deviation increase. The GWR model performs better than OLS model with the adjusted R2 of 0.96. Spatial heterogeneities of coefficients in the GWR model show th",76.0,https://europepmc.org/articles/pmc8545724?pdf=render827aa1dfa2d3bc797fae69fed236764602c0e9c4f41,10.1080/00420987420080341,Determinants of Urban House Prices,1974.0,,H. Richardson; J. Vipond; Robert Furbey,,76.0,82865162dbf8b1e621c4eebd94841d05e522a512aa7,10.1038/ijo.2013.97,FOOD SHOPPING BEHAVIORS AND SOCIOECONOMIC STATUS INFLUENCE OBESITY RATES IN SEATTLE AND IN PARIS,2013.0,International Journal of Obesity,A. Drewnowski; A. Moudon; J. Jiao; A. Aggarwal; H. Charreire; B. Chaix,"Objective:To compare the associations between food environment at the individual level, socioeconomic status (SES) and obesity rates in two cities: Seattle and Paris.Methods:Analyses of the SOS (Seattle Obesity Study) were based on a representative sample of 1340 adults in metropolitan Seattle and King County. The RECORD (Residential Environment and Coronary Heart Disease) cohort analyses were based on 7131 adults in central Paris and suburbs. Data on sociodemographics, health and weight were obtained from a telephone survey (SOS) and from in-person interviews (RECORD). Both studies collected data on and geocoded home addresses and food shopping locations. Both studies calculated GIS (Geographic Information System) network distances between home and the supermarket that study respondents listed as their primary food source. Supermarkets were further stratified into three categories by price. Modified Poisson regression models were used to test the associations among food environment variables, SES and obesity.Results:Physical distance to supermarkets was unrelated to obesity risk. By contrast, lower education and incomes, lower surrounding property values and shopping at lower-cost",75.0,https://www.nature.com/articles/ijo201397.pdf829ce1985524abc39f928ca1e16c551c56b84c81bec,10.1016/j.jhe.2017.12.002,Institutional settings and urban sprawl: Evidence from Europe,2017.0,Journal of Housing Economics,Maximilian V. Ehrlich; Christian A. L. Hilber; Olivier Schöni,"This article explores the role of institutional settings in determining spatial variation in urban sprawl across Europe. We first synthesize the emerging literature that links land use policies and local fiscal incentives to urban sprawl. Next, we compile a panel dataset on various measures of urban sprawl for European countries using high-resolution satellite images. We document substantial variation in urban sprawl across countries. This variation remains roughly stable over the period of our analysis (1990–2012). Urban sprawl is particularly pronounced in emerging Central and Eastern Europe but is comparatively low in Northern European countries. Urban sprawl – especially outside functional urban areas – is strongly negatively associated with real house price growth, suggesting a trade-off between urban containment and housing affordability. Our main novel empirical findings are that decentralization and local political fragmentation are significantly positively associated with urban sprawl. Decentralized countries have a 25–30% higher sprawl index than centralized ones. This finding is consistent with the proposition that in decentralized countries fiscal incentives at local le",75.0,http://eprints.lse.ac.uk/86364/1/Ehrlich_%20Hilber_Schoni_author-2017_.pdf830323821f9a8d6adab4ca67c6e53a0feb6ffae3ca2,10.2139/ssrn.2511411,Returning to the nest: Debt and parental co-residence among young adults,2017.0,Labour Economics,Lisa J. Dettling; Joanne W. Hsu,"This paper examines the relationship between a young adults' debt burden and the decision to co-reside with a parent. Using a quarterly panel of young adults' credit histories, and controlling for age, country, and quarter fixed effects, and local demographic characteristics, unemployment rates, and house prices, we estimate the relationship between current period debt and subsequent decisions to co-reside with a parent. Our results indicate that indebtedness -- increases flows into parental co-residence. Moreover, after moving in, delinquency and low credit scores increase time spent in co-residence. We find that the changing debt portfolios of young adults over this period -- characterized by rising student loan debt and small declines in credit card, auto and mortgage debt -- can predict 30 percent of the observed increase in flows into co-residence, and 26 percent of the observed increase in time spent in co-residence.",75.0,http://www.federalreserve.gov/econresdata/feds/2014/files/201480pap.pdf831446bce2fb8227690a8724d291271f6dc6d4d5ad6,10.1016/j.ijdrr.2020.101707,Quantitative assessment of flood risk with evaluation of the effectiveness of dam operation for flood control: A case of the Bago River Basin of Myanmar,2020.0,,B. Shrestha; A. Kawasaki,"Abstract Because property damage and loss of life owing to floods have increased in many countries in recent years, accurate assessment of flood risk is urgently needed for effective flood management. Improving the assessment of flood risk requires considering the impact of dam operation for flood control because dams and reservoirs play important roles in the assessment of flood hazards and associated damage. However, the impact of dam operation on flood hazards and associated damage was not considered well in previous assessments of flood risk. This paper focused on the quantitative assessment of flood hazard and risk, including the effectiveness of dam operation for flood prevention. The grid-based approach integrating the following was applied for analysis: (i) a hydrological–hydraulic model, (ii) a method considering the dam operation for flood control, and (iii) an assessment of flood damage. To assess the risk, flood characteristics were computed using the rainfall–runoff–inundation hydrological–hydraulic model, and flood damage was estimated by integrating the flood characteristics, flood damage curves, exposure characteristics, and property values. The risk was assessed by",74.0,https://doi.org/10.1016/j.ijdrr.2020.101707832a57e706a2d8ce09bcfcb0edec9fc401a52f96b9e,10.3390/ijgi9060380,Spatial Analysis of Housing Prices and Market Activity with the Geographically Weighted Regression,2020.0,ISPRS Int. J. Geo Inf.,R. Cellmer; Aneta Cichulska; M. Bełej,"The main part of the study will be to demonstrate that models taking into account spatial heterogeneity (Geographically Weighted Regression and Mixed Geographically Weighted Regression) which reproduce housing market determinants better reflect market relationships than conventional regression models. The spatial heterogeneity of the housing market determinants results in the spatial diversity of the market activity, as well as of real estate prices and values. The main aim of the study was to analyse an effect of these socio-demographic and environmental factors on average housing property prices and on the number of transactions in a spatial approach. In previous research conducted on a national scale, usually all variables were treated in a similar way, i.e., as global or local variables. During the research, an attempt was also made to answer the question of which of the variables adopted for analysis have a local impact on prices and market activity, and which are global. The study was conducted in Poland and used data from the year 2018 on 380 counties (Local Administrative Units). The study showed that determinants both for average prices and for the housing market activity ",74.0,https://www.mdpi.com/2220-9964/9/6/380/pdf?version=1593514058833758c30bf0d1effcd2d70009820ffb87b918fbb81,10.1016/j.tranpol.2016.03.008,Subways near the subway: Rail transit and neighborhood catering businesses in Beijing,2016.0,,Si-Qi Zheng; Xiaoke Hu; Jiang-Hao Wang; Rui Wang,"Beijing has made enormous investment in rail transit since the late 2000s. The rapidly growing subway system greatly improves the accessibility of neighborhoods nearby subway stations and often increases neighborhood population and employment densities, both resulting in a larger market for local retail businesses. While numerous studies have shown that rail transit investment tends to raise property value close to stations, few have provided direct evidence on rail transit's effects on local consumer amenities. Using citywide catering establishment data since 2004 from dianping.com (China's yelp.com), we study the effects of new subway stations on catering openings, diversity and consumer demand in neighborhoods near a subway station opened during 2004–2013. We find that a new subway station positively contributes to the quantity, diversity and consumer demand of nearby food and beverage services. These effects are heterogeneous spatially and in terms of catering types. This study enriches the limited extant empirical evidence on urban rail transit's impact on local economic activities and consumer amenities. In China, where unprecedented rail transit expansion has transformed lar",74.0,http://www.sciencedirect.com/science/article/pii/S0967070X1630114783405c8786326460cf090915b2c8078a1edbb549768,10.1016/j.scs.2021.102810,"Environmental justice and surface temperature: Income, ethnic, gender, and age inequalities",2021.0,,B. Mashhoodi,"Abstract Severe land surface temperature (LST) significantly impacts residents' thermal discomfort and can be life-threatening during warm seasons. Therefore, it is essential to identify the inequalities in LST exposure, i.e. the socioeconomic groups who are over- or underexposed to LST. There is a knowledge gap in the literature: there is no previous study which differentiates between national-scale inequalities -i.e. inequalities apparent in all location of a country, and the local-scale inequalities -i.e. inequalities existing in some areas of a country. Employing a semi-parametric geographically weighted regression model to study LST in Dutch residential zones in the summer of 2014, the results of this study show that two national-scale inequalities are significant: overexposure of high-income groups and underexposure of the owners of high-value properties. Additionally, eight local-scale inequalities are identified. Among the latter, ethnic inequalities, overexposure of Non-western and Western immigrants, found to be the most severe and frequent at the local scale. Additionally, females are often the second most overexposed to LST at the local-scale. To a lesser degree Rental ",74.0,https://www.sciencedirect.com/science/article/pii/S2210670721001013/pdf835bae4037bb5d801e5767ae9ba85312b4e96fe78e4,10.5089/9781463925949.001.a001,Determinants of Property Prices in Hong Kong Sar: Implications for Policy,2011.0,Social Science Research Network,R. Craig; Chang-I Hua,"This paper uses an econometric model of residential property prices in Hong Kong SAR to assess the effectiveness of alternative policies in slowing the increase in property prices. The rapid rise in property prices is well explained by macroconomic fundamentals; real GDP per capital, real domestic credit, construction costs, land supply, and the real interest rate. Policy can influence the property market though land supply and prudential and tax policy, with the latter policies taking the form of a stamp duty on property transactions and a tighter loan-to-value ratio (LTV) on lending. Land supply is the most effective policy insturment for restraining property price increases but it operates with a significant lag. The LTV and stamp duty dampen speculative activity that drives up property prices. While these policies can slow the increase in the short run, they should be guided by their long run objectives of financial stability and counteracting speculation.",74.0,https://www.elibrary.imf.org/downloadpdf/journals/001/2011/277/001.2011.issue-277-en.xml83650ac40f65d7a95a32e6f4b3e077ff1ef1c26d015,10.14569/ijacsa.2017.081042,"Modeling House Price Prediction using Regression Analysis and Particle Swarm Optimization Case Study : Malang, East Java, Indonesia",2017.0,,Adyan Nur Alfiyatin; Ruth Ema Febrita; Hilman Taufiq; W. Mahmudy,"House prices increase every year, so there is a need for a system to predict house prices in the future. House price prediction can help the developer determine the selling price of a house and can help the customer to arrange the right time to purchase a house. There are three factors that influence the price of a house which include physical conditions, concept and location. This research aims to predict house prices based on NJOP houses in Malang city with regression analysis and particle swarm optimization (PSO). PSO is used for selection of affect variables and regression analysis is used to determine the optimal coefficient in prediction. The result from this research proved combination regression and PSO is suitable and get the minimum prediction error obtained which is IDR 14.186.",74.0,http://thesai.org/Downloads/Volume8No10/Paper_42-Modeling_House_Price_Prediction_using_Linear_Regression.pdf837c1a558e21cbe61c4208f820c297a1ce936f81ad2,10.5194/nhess-14-2531-2014,Decision-tree analysis of factors influencing rainfall-related building structure and content damage,2014.0,,M. Spekkers; M. Kok; F. Clemens; J. A. E. ten Veldhuis,"Abstract. Flood-damage prediction models are essential building blocks in flood risk assessments. So far, little research has been dedicated to damage from small-scale urban floods caused by heavy rainfall, while there is a need for reliable damage models for this flood type among insurers and water authorities. The aim of this paper is to investigate a wide range of damage-influencing factors and their relationships with rainfall-related damage, using decision-tree analysis. For this, district-aggregated claim data from private property insurance companies in the Netherlands were analysed, for the period 1998–2011. The databases include claims of water-related damage (for example, damages related to rainwater intrusion through roofs and pluvial flood water entering buildings at ground floor). Response variables being modelled are average claim size and claim frequency, per district, per day. The set of predictors include rainfall-related variables derived from weather radar images, topographic variables from a digital terrain model, building-related variables and socioeconomic indicators of households. Analyses were made separately for property and content damage claim data. Resul",73.0,https://nhess.copernicus.org/articles/14/2531/2014/nhess-14-2531-2014.pdf83845efb25c539abcec425466dd3f205a8d35bce89c,10.3390/land11112100,Housing Price Prediction Using Machine Learning Algorithms in COVID-19 Times,2022.0,Land,R. Mora-García; M. Cespedes-Lopez; V. Pérez-Sánchez,"Machine learning algorithms are being used for multiple real-life applications and in research. As a consequence of digital technology, large structured and georeferenced datasets are now more widely available, facilitating the use of these algorithms to analyze and identify patterns, as well as to make predictions that help users in decision making. This research aims to identify the best machine learning algorithms to predict house prices, and to quantify the impact of the COVID-19 pandemic on house prices in a Spanish city. The methodology addresses the phases of data preparation, feature engineering, hyperparameter training and optimization, model evaluation and selection, and finally model interpretation. Ensemble learning algorithms based on boosting (Gradient Boosting Regressor, Extreme Gradient Boosting, and Light Gradient Boosting Machine) and bagging (random forest and extra-trees regressor) are used and compared with a linear regression model. A case study is developed with georeferenced microdata of the real estate market in Alicante (Spain), before and after the pandemic declaration derived from COVID-19, together with information from other complementary sources such ",73.0,https://www.mdpi.com/2073-445X/11/11/2100/pdf?version=1669037631839c5f637238fa8d25f3ccc30efb3387aa075277c7e,10.1016/j.jhe.2022.101908,Stuck at home: Housing demand during the COVID-19 pandemic,2022.0,Journal of Housing Economics,William Gamber; James Graham; Anirudh Yadav,"The COVID-19 pandemic induced an increase in both the amount of time that households spend at home and the share of expenditures allocated to at-home consumption. These changes coincided with a period of rapidly rising house prices. We interpret these facts as the result of stay-at-home shocks that increase demand for goods consumed at home as well as the homes that those goods are consumed in. We first test the hypothesis empirically using US cross-county panel data and instrumental variables regressions. We find that counties where households spent more time at home experienced faster increases in house prices. We then study various pandemic shocks using a heterogeneous agent model with general equilibrium in housing markets. Stay-at-home shocks explain around half of the increase in model house prices in 2020. Lower mortgage rates explain around one third of the price rise, while unemployment shocks and fiscal stimulus have relatively small effects on house prices. We find that young households and first-time home buyers account for much of the increase in housing demand during the pandemic, but they are largely crowded out of the housing market by the equilibrium rise in house ",73.0,https://doi.org/10.1016/j.jhe.2022.101908840455d466245200cb7ffd51dcfdda2cf37a2ed85c3,10.2139/ssrn.3335592,Towards Explainable AI: Significance Tests for Neural Networks,2019.0,arXiv.org,Enguerrand Horel; K. Giesecke,"Neural networks underpin many of the best-performing AI systems. Their success is largely due to their strong approximation properties, superior predictive performance, and scalability. However, a major caveat is explainability: neural networks are often perceived as black boxes that permit little insight into how predictions are being made. We tackle this issue by developing a pivotal test to assess the statistical significance of the feature variables of a neural network. We propose a gradient-based test statistic and study its asymptotics using nonparametric techniques. The limiting distribution is given by a mixture of chi-square distributions. The tests enable one to discern the impact of individual variables on the prediction of a neural network. The test statistic can be used to rank variables according to their influence. Simulation results illustrate the computational efficiency and the performance of the test. An empirical application to house price valuation highlights the behavior of the test using actual data.",73.0,841241c5fc0abd9a26a49cc878aa75f6ba189c9f7a6,10.1371/journal.pone.0212606,Using OpenStreetMap point-of-interest data to model urban change—A feasibility study,2019.0,PLoS ONE,Liming Zhang; D. Pfoser,"User-generated content is a valuable resource for capturing all aspects of our environment and lives, and dedicated Volunteered Geographic Information (VGI) efforts such as OpenStreetMap (OSM) have revolutionized spatial data collection. While OSM data is widely used, considerably little attention has been paid to the quality of its Point-of-interest (POI) component. This work studies the accuracy, coverage, and trend worthiness of POI data. We assess the accuracy and coverage using another VGI source that utilizes editorial control. OSM data is compared to Foursquare data by using a combination of label similarity and positional proximity. Using the example of coffee shop POIs in Manhattan we also assess the trend worthiness of OSM data. A series of spatio-temporal statistical models are tested to compare change in the number of coffee shops to home prices in certain areas. This work overall shows that, although not perfect, OSM POI data and specifically its temporal aspect (changeset) can be used to drive urban science research and to study urban change.",72.0,https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0212606&type=printable8425cb748b0cd8331444555f8951964d07bbb62d479,10.3390/su12114382,Key Factors Influencing Purchase or Rent Decisions in Smart Real Estate Investments: A System Dynamics Approach Using Online Forum Thread Data,2020.0,Sustainability,Fahim Ullah; S. Sepasgozar,"The real estate sector is receiving mix responses throughout the world, with some countries like USA receiving lesser and European and Asia Pacific markets receiving more transactions in recent years. Among the concerning factors, post-purchase regrets by the real estate owners or renters are on the rise, which have never been assessed to date through scholarly research. These regrets can further increase in the time of lockdowns and bans on inspections due to Corona Virus Disease 2019 (COVID-19) and social distancing rules enforced by various countries such as Australia. The current study aims at investigating the key post-purchase regret factors of real estate and property owners and renters over the last decade using published literature and online threads. Based on pertinent literature, 118 systematically identified and text-mined articles, and four online threads with 135 responses, the current study develops system dynamics models to assess and predict the increase in consumers’ regrets over the last decade. Further, a user-generated thread with 23 responses involving seven real estate managers and five agents with more than 20 years of experience, 10 buyers with at least thr",71.0,https://www.mdpi.com/2071-1050/12/11/4382/pdf?version=15908223798439a5548e1aed319aaa8d9b562ae7da4447fc3117c,10.3390/ijerph17186712,Associating COVID-19 Severity with Urban Factors: A Case Study of Wuhan,2020.0,International Journal of Environmental Research and Public Health,Xin Li; Lin Zhou; T. Jia; Ran Peng; Xiong-Wu Fu; Yuliang Zou,"Wuhan encountered a serious attack in the first round of the coronavirus disease 2019 (COVID-19) pandemic, which has resulted in a public health social impact, including public mental health. Based on the Weibo help data, we inferred the spatial distribution pattern of the epidemic situation and its impacts. Seven urban factors, i.e., urban growth, general hospital, commercial facilities, subway station, land-use mixture, aging ratio, and road density, were selected for validation with the ordinary linear model, in which the former six factors presented a globally significant association with epidemic severity. Then, the geographically weighted regression model (GWR) was adopted to identify their unevenly distributed effects in the urban space. Among the six factors, the distribution and density of major hospitals exerted significant effects on epidemic situation. Commercial facilities appear to be the most prevalently distributed significant factor on epidemic situation over the city. Urban growth, in particular the newly developed residential quarters with high-rise buildings around the waterfront area of Hanyang and Wuchang, face greater risk of the distribution. The influence o",71.0,https://www.mdpi.com/1660-4601/17/18/6712/pdf?version=1600163864844d7fa75b3aa937ed9f56e61e7e373fdfd92935f56,10.1016/j.cities.2018.11.008,"Quality of urban area, distance from city centre, and housing value. Case study on real estate values in Turin",2019.0,Cities,L. D'Acci,"Abstract A tremendous number of studies have investigated the relation between real estate value and characteristics of the area. This paper briefly shows more than one hundred empirical results from the literature, quantifying how much positional factors such as green, social context, pedestrian areas, pollution, aesthetics, views and accessibility influence the property value. We call Positional Value that part of the real estate value given from the characteristics of the area. As an empirical example, an analysis of the city of Turin shows how, changing the area of the city, the value of a house increases/decreases as much as 142% of its own value, ceteris paribus, even among areas quite close to each other. More specifically, the output of this study indicates that the real estate value decreases by 0.23% for each 1% increase of the distance from the city centre, but increases by 0.58% for each 1% increase of the quality of the site. The monetary costs of housing, time and transport, and the qualitative benefits received from the site's characteristics, play a main role within the households' decision processes when choosing among alternative dwellings. On the other way round,",71.0,https://www.sciencedirect.com/science/article/pii/S026427511830855284551b17ddb368923119b9252a67f233235b9445bd1,10.1186/s12889-018-6213-z,"Prevalence, patterns, and predictors of diarrhea: a spatial-temporal comprehensive evaluation in India",2018.0,BMC Public Health,Nilima; A. Kamath; K. Shetty; B. Unnikrishnan; Siddharth Kaushik; S. Rai,BackgroundSpatial analysis has been vital in mapping the spread of diseases and assisting in policy making. Targeting diarrhea transmission hotspots is one of the potential strategies for reducing diarrhea cases. This study aimed to examine the spatial-temporal variations and to identify the modifiable determinants of diarrhea while controlling for the spatial dependence in the data.MethodsAn ecological study on diarrhea data from DLHS-3 and NFHS- 4 in India. Moran’s I and LISA were used to detect the spatial clustering of diarrhea cases and to test for clustering in the data. Spatial regression was used to identify the modifiable factors associated with the prevalence of diarrhea. The study comprised of the prevalence of diarrhea among the children below the age of five years (U-5 s) across different states in India. The determinants of diarrhea were obtained using spatial lag models. The software used were GeoDa 1.6.6 and QGIS 2.0.ResultsThe presence of spatial autocorrelation in DLHS-3 and NFHS-4 (Moron’s I = 0.577 and 0.369 respectively) enforces the usage of geographical properties while modeling the diarrhea data. The geographic clustering of high-prevalence districts was obs,70.0,https://bmcpublichealth.biomedcentral.com/track/pdf/10.1186/s12889-018-6213-z846e2459715fae0e20316482cb1778f7b7fac58b6af,10.5198/jtlu.v5i2.225,Understanding Spatial Variations in the Impact of Accessibility on Land Value Using Geographically Weighted Regression,2012.0,,H. Du; Corinne Mulley,"This paper aims to understand the spatial variability in house prices and accessibility. The motivation for understanding the connection between accessibility and house prices stems from the increasing attention given in recent years to the potential for funding transport infrastructure by land value capture policies. Establishing whether there is identifiable land value uplift, and further quantifying this uplift, is a prerequisite to sensible discussions on the potential for land value capture. Although there has been substantial related research in the United States, not only have there been fewer studies in the United Kingdom, but these have concentrated on London. London, as a capital city, differs in many respects from other cities. Large conurbations such as Manchester, Sheffield, and Tyne and Wear are more typical of British cities. This study focuses on the Tyne and Wear area, which has an extensive public transport system, with a light rail system—the Tyne and Wear Metro—forming the backbone of the public transport system. The investigation reported in this paper is underpinned by the use of Geographically Weighted Regression (GWR) methodology with property prices as the ",70.0,https://www.jtlu.org/index.php/jtlu/article/download/225/241847e14a6701db5952f10f8bea88b1928609be3e9da7,10.3390/su12052034,Exploring the Effects of the Built Environment on Two Transfer Modes for Metros: Dockless Bike Sharing and Taxis,2020.0,Sustainability,Ying Ni; Jiaqi Chen,"The success of metro systems depends on effective multimodal solutions that bridge the first-and-last-mile gaps. Both dockless bike sharing (DBS) and taxis are important feeder modes for metros, which provide on-demand travel options with high flexibility and accessibility. Based on one-week trip data of DBS and taxis during a concurrent period in Beijing, China, the paper aims to compare the temporal-spatial distribution of two modes as first-and-last-mile connectors and find out the socio-demographic and built-environment factors that impact their usage. K-means clustering is implemented to visualize the spatial distribution of DBS and taxis around metro stations, and the spatial lag model incorporating spatial autocorrelations of variables is developed. The results show that people prefer to use DBS as a substitutable mode for bus services to serve first-mile interchange in the morning. Also, less economically developed areas with a high density of branches and fewer signalized intersections are more favored by DBS users, whereas people in the central areas with high housing price and developed arterial road network tend to take a taxi, especially during evening peak period. The",70.0,https://www.mdpi.com/2071-1050/12/5/2034/pdf848c08f74bc6454b440f390e025ce0416d1e5513b77,10.2139/ssrn.3428675,Infrastructure Costs,2023.0,Social Science Research Network,L. Brooks; Zachary D. Liscow,"Despite infrastructure's importance to the US economy, evidence on its cost trajectory over time is sparse. We document real spending per new mile over the history of the Interstate Highway System. We find that spending per mile increased more than threefold from the 1960s to the 1980s. This increase persists even conditional on pre-existing observable geographic cost determinants. We then provide suggestive evidence on why. Input prices explain little of the increase. Statistically, changes in income and housing prices explain about half of the increase. We find suggestive evidence that the rise of “citizen voice” in government decision-making increased spending per mile. (JEL D72, H54, N42, N72, R31, R42)",70.0,https://doi.org/10.2139/ssrn.3428675849fe09b86662873af89f2b429bb31665d8c4d92912,10.1007/s11769-018-0954-6,Impact of Accessibility on Housing Prices in Dalian City of China Based on a Geographically Weighted Regression Model,2018.0,Chinese Geographical Science,J. Yang; Yajun Bao; Yu-Qing Zhang; Xueming Li; Q. Ge,,70.0,https://doi.org/10.60692/h2jf0-z0903850deba2679679f7a07e4e121cf707c68f3d82b6791,10.1016/j.tra.2015.07.015,The capitalization of subway access in home value: A repeat-rentals model with supply constraints in Beijing,2015.0,,Wei-Zeng Sun; Si-Qi Zheng; Rui Wang,,70.0,851941b3fedab29a49ec925268cafc82ba1c73409d8,10.1080/01944363.2021.1880961,Jobs–Housing Balance Re-Re-Visited,2021.0,Journal of the American Planning Association,Evelyn Blumenberg; Hannah R. King,"Abstract Problem, research strategy, and findings In many U.S. metropolitan areas housing costs have skyrocketed in recent years relative to average incomes. A worsening shortage of affordable housing in these metros may push households away from job-rich cities and expensive neighborhoods into outlying areas, where housing is cheaper but jobs are more distant. To examine this issue, we revisit the jobs–housing balance, a popular topic of research in the 1990s, with a focus on the relationship between housing and the spatial location of workers relative to jobs. Our analysis draws on data from the Longitudinal Employer–Household Dynamics Origin–Destination Employment Statistics (LODES) for cities in California in 2002 and 2015. In contrast to earlier jobs–housing balance research, we find that California cities are becoming less self-contained over time, defined as a decline in the number of workers who both live and work within a jurisdiction relative to the number of commuters who travel either into or out of a city for work. Statistical models show that self-containment was higher in cities with lower housing costs and, in 2015, in cities with a greater balance between jobs and ",69.0,https://figshare.com/articles/journal_contribution/Jobs_Housing_Balance_Re-Re-Visited/1462384985298fb58b3412086bde34cedc38016818405eff5e2,10.1016/j.cities.2018.05.013,The unaffordable city: Housing and transit in North American cities,2018.0,Cities,A. Kramer,"Abstract This paper presents an empirical analysis of seventeen large American and Canadian metropolitan regions to look at geographies of affordability in transportation and housing. A pre-recession snapshot of frequent transit networks are mapped against housing cost, urban form and socioeconomic variables from census data, and the relationship of housing cost to transit access is tested visually, by descriptive statistics, and with logistic regression. The results show apparent contradictions: while there is great variance in transit access and housing cost between and across cities, transitscapes are consistently more racially diverse, higher density, and poorer than surrounding autoscapes; but, once income and racialization are held constant, there is a decreasing chance of access to transit as housing prices become more affordable. In other words, for many people, there is no affordable access. These paradoxes are interpreted with relevance to patterns of racial and economic geographies of land use and mobility, the dominance of postwar automobility, the suburbanization of poverty, and wealth inequality in North American cities. This research fills gaps in the transit-oriente",69.0,853773dd00cb6a6c108f28faf090ceeab30c534ca0e,10.1080/19475683.2018.1557253,Spatial homogeneity and heterogeneity of energy poverty: a neglected dimension,2018.0,Ann. GIS,B. Mashhoodi; D. Stead; A. van Timmeren,"ABSTRACT Since the 1970s, a variety of studies has searched for the sociodemographic, housing and economic determinants of energy poverty. A central question, however, has not been answered by any of the previous studies: what are the national-level determinants, i.e. the determinants that homogeneously provoke a high level of energy poverty in all areas of a country? What are the neighbourhood-specific determinants, i.e. the characteristics that have a heterogeneous impact across the neighbourhoods of a country? This study seeks to answer these questions by analysing the level of energy poverty, the percentage of households’ disposable income spent on energy expenditure, in 2473 neighbourhoods of the Netherlands in 2014. By employing a semi-parametric geographically weighted regression analysis, the effects of two of the determinants of energy poverty are found to be spatially homogeneous: (i) percentage of low-income households and (ii) percentage of pensioners. The results indicate that the impacts of six of the determinants are spatially heterogeneous: (i) household size, (ii) percentage of unemployment, (iii) building age, (iv) percentage of privately rented dwellings, (v) num",69.0,https://www.tandfonline.com/doi/pdf/10.1080/19475683.2018.1557253?needAccess=true8544b4af0641d759f9ae9cad96c30743bfc3323988c,10.1002/9781118266588.ch20,"The Past, Present, and Future of Subprime Mortgages",2008.0,,S. Sherlund,"This paper models the historical default and prepayment behavior for subprime mortgages using data on securitized mortgages originated from 2000 to 2007. I find that more recently originated subprime loans are more likely to default, well ahead of their first mortgage rate resets, and less likely to prepay (i.e., refinance). This rise in mortgage defaults stems largely from unprecedented declines in house prices, along with slack underwriting and tight credit market conditions. I estimate a competing hazards model to quantify the effects of (1) house price appreciation, (2) underwriting standards, (3) mortgage rate resets, and (4) household cash flow shocks, such as job loss and oil price increases, on the likelihood of borrowers with subprime mortgages to default or prepay. Ultimately, I find that borrower leverage is one of the most important factors explaining both default and prepayment for borrowers with subprime mortgages. Then, using several different assumptions about the future path of house prices, I simulate potential trajectories for subprime mortgage defaults between 2008 and 2010. Further, I explore the short-term sensitivities of default and prepayment to house price",69.0,https://doi.org/10.17016/feds.2008.63855cb6f558ba0314bc2f50ee100ea6578a7f35ade10,10.1016/j.landusepol.2021.105452,Impact of land quota and land supply structure on China’s housing prices: Quasi-natural experiment based on land quota policy adjustment,2021.0,Land Use Policy,Jian-Shuang Fan; Lin Zhou; Xiao-Feng Yu; Yanjiang Zhang,"Abstract From 2003 to 2019, housing prices in China jumped by 295%. Much of this growth can be attributed to the spatial and structural misallocation of land supply. Specifically, China’s government determines the urban land supply, using land quotas to allow for greater land supply in the country’s central and western regions, but less so in the eastern region. In addition, the government controls the land supply structure, whereby industrial lands take up a larger proportion than commercial and residential lands. This paper attempts to investigate how China’s land quota system and land supply structure impact the country’s housing prices. After setting up a theoretical framework, we construct a panel data set including land quota, land supply structure and housing prices for 282 prefecture-level cities from 2001 to 2016. We demonstrate that housing price growth in cities whose land quotas were lowered during the study period is about 10% higher than that in cities whose land quotas were raised, with the former being mostly big cities and coastal cities. We further find that land supply structure affects housing prices, whereby the lower the proportion of commercial and residentia",69.0,856fc001582958393c0b372fe861e56f41f03c80ae8,10.1007/s11146-011-9359-3,Spatial and Temporal Dependence in House Price Prediction,2013.0,,Xiaolong Liu,,69.0,https://papers.ssrn.com/sol3/papers.cfm?abstract_id=231383485796b1e18ca8b254ad8f9325b4e5fac3e5118b3a37,10.3390/su10124503,"Spatial Effects of Public Service Facilities Accessibility on Housing Prices: A Case Study of Xi’an, China",2018.0,Sustainability,F. Lan; Qi Wu; Tao Zhou; Huili Da,"The premium effect of public service facilities on the housing market is a critical determinant of housing prices, leading to the competition of different social groups in the housing market and fueling spatial inequality. Taking Xi’an, China as a case in point, this study uses Geographic Information System (GIS) to describe the spatial distribution pattern of housing prices and urban public service facilities. Using the mixed geographically weighted regression model (MGWR) and the geographical detector model (GD), this study reveals the spatial effects of these facilities’ accessibility on housing prices. The results show that commercial and leisure facilities are spatially stationary, whereas a non-stationary effect is observed among those providing educational, medical, cultural, sport, and financial services. From the urban spatial resource allocation perspective, facilities meeting people’s basic needs, such as medical care and education, constitute the basic elements of housing price differentiation. When any two of these interact, a bivariate-enhanced effect emerges. The decisive interactive elements of housing price differentiation involve the facilities meeting people’s hi",68.0,https://www.mdpi.com/2071-1050/10/12/4503/pdf?version=15435007648588cb454e0620af8b68abcc6ce0180a35f364cfc2f,10.2139/ssrn.3714858,The Financial Impact of Street-Level Greenery on New York Commercial Buildings,2020.0,Social Science Research Network,Jun-Cheng Yang; H. Rong; Yu-Hao Kang; Fan Zhang; Andrea M. Chegut,"Urban street-level greenery is empirically documented to improve mental and physical health, increase productivity, increase urban environmental equality and reduce carbon footprints. In addition, these benefits raise residents' welfare, which has been correlated with increases in residential house prices. We measure street-level greenness in New York City through a novel Green View Index (GVI) using Google Street View images and assess the impacts of greenness on commercial real estate prices. Using a sample of office transactions, we spatially correlate Google Street View Images for New York City over the 2010 to 2017 period. We find a 8.9% to 10.5% statistically, economically and positive transaction premium and a 5.6% to 7.8% rent premium for offices with low to high street-level greenness relative to those building transactions spatially correlated with very low greenness. Estimations are robust to proximity to parks, subway stations, sidewalk widths, household income levels and investments by Building Improvement Districts, as well as other vital and standard office valuation features. By documenting the role of greenery in commercial building valuations, our results give a m",68.0,8594a34e9ecd024b2e2aca73c4c99a6327daddcc341,10.1016/j.landusepol.2018.02.011,"Spatial and temporal effects of urban wetlands on housing prices: Evidence from Hangzhou, China",2018.0,,Xue-Jun Du; Zhong-Hua Huang,,68.0,860c337613cc6a8d34f28ef87ca2ddd6928f2ed7829,10.1002/for.2678,Forecasting Australia's real house price index: A comparison of time series and machine learning methods,2020.0,,George Milunovich,"We employ 47 different algorithms to forecast Australian log real house prices and growth rates, and compare their ability to produce accurate out‐of‐sample predictions. The algorithms, which are specified in both single‐ and multi‐equation frameworks, consist of traditional time series models, machine learning (ML) procedures, and deep learning neural networks. A method is adopted to compute iterated multistep forecasts from nonlinear ML specifications. While the rankings of forecast accuracy depend on the length of the forecast horizon, as well as on the choice of the dependent variable (log price or growth rate), a few generalizations can be made. For one‐ and two‐quarter‐ahead forecasts we find a large number of algorithms that outperform the random walk with drift benchmark. We also report several such outperformances at longer horizons of four and eight quarters, although these are not statistically significant at any conventional level. Six of the eight top forecasts (4 horizons × 2 dependent variables) are generated by the same algorithm, namely a linear support vector regressor (SVR). The other two highest ranked forecasts are produced as simple mean forecast combinations.",67.0,861592df8d3047587abb29dd4493da075e6413de193,10.1111/j.1467-9663.2008.00472.x,RESIDENTIAL ENVIRONMENT AND SPATIAL VARIATION IN HOUSE PRICES IN THE NETHERLANDS,2008.0,,P. Visser; F. Van Dam; P. Hooimeijer,,67.0,862709530034d67e0cb839d2860ada564e5ce909e9c,10.1016/j.ypmed.2015.11.021,Geographic disparities in Healthy Eating Index scores (HEI-2005 and 2010) by residential property values: Findings from Seattle Obesity Study (SOS),2015.0,Preventive Medicine,A. Drewnowski; A. Aggarwal; A. Cook; O. Stewart; A. V. Moudon,"Background Higher socioeconomic status (SES) has been linked with higher-quality diets. New GIS methods allow for geographic mapping of diet quality at a very granular level. Objective To examine the geographic distribution of two measures of diet quality: Healthy Eating Index (HEI 2005 and HEI 2010) in relation to residential property values in Seattle-King County. Methods The Seattle Obesity Study (SOS) collected data from a population-based sample of King County adults in 2008–09. Socio-demographic data were obtained by 20-min telephone survey. Dietary data were obtained from food frequency questionnaires (FFQs). Home addresses were geocoded to the tax parcel and residential property values were obtained from the King County tax assessor. Multivariable regression analyses using 1,116 adults tested associations between SES variables and diet quality measured (HEI scores). Results Residential property values, education, and incomes were associated with higher HEI scores in bivariate analyses. Property values were not collinear with either education or income. In adjusted multivariable models, education and residential property were better associated with HEI, compared to than inco",66.0,https://www.ncbi.nlm.nih.gov/pmc/articles/4724229863871c7b28de32691cb2c17f2d5cd75dcb521a7892,10.1016/j.tranpol.2020.03.006,Commuting inequity and its determinants in Shanghai: New findings from big-data analytics,2020.0,,Peng-Jun Zhao; Yushu Cao,"Abstract The heavy commuting burden borne by disadvantaged individuals and neighbourhoods is a key concern with regard to transport equity. Agreement on the best approach for addressing this problem has been elusive, however, and the existing literature is dominated by traditional survey approaches, which are liable to criticism for small sample sizes, especially when used in studies of megacities (those with populations exceeding 10 million). The aim of the present study was to help fill this gap in the literature by exploring commuting inequity and its determinants using big-data analytics, with Shanghai serving as a case study. A number of 81 million trips from 28 million transit smart cards in 2015 are analzyed. We found the top 20% of commuters in Shanghai, who accounted for about 78,000 of the cardholders, spent more than 60 min commuting each way daily. The results of a geographically weighted regression show that disadvantaged areas characterised by low rent or poor job accessibility tended to be inhabited by especially large numbers of workers with long commutes. Such commuters face a trade-off between housing and travel costs But interestingly, the areas with larger migra",66.0,864a2a7539a9c4a1cf05650ab56eedb83ae824bb636,10.20955/r.92.185-204,Nonlinear Effects of School Quality on House Prices,2003.0,,Abbigail J. Chiodo; Rubén Hernández-Murillo; Michael T. Owyang,"We reexamine the relationship between quality of public schools and house prices and find it to be nonlinear. Unlike most studies in the literature, we find that the price premium parents must pay to buy a house in an area associated with a better school increases as school quality increases. This is true even after controlling for neighborhood characteristics, such as the racial composition of neighborhoods, which is also capitalized into house prices. In contrast to previous studies that use the boundary discontinuity approach, we find that the price premium from school quality remains substantially large, particularly for neighborhoods associated with high-quality schools.",66.0,https://s3.amazonaws.com/real.stlouisfed.org/wp/2003/2003-039.pdf865ae18c32b2e12e9ee7787f5109c94267470804aad,10.1080/09599910902837051,An Artificial Neural Network and Entropy Model for Residential Property Price Forecasting in Hong Kong,2008.0,,K. Lam; C.-Y. Yu; K.-Y. A. Lam,,66.0,866c1df1ee05f68e8ba7cba186c2f808ca739f31296,10.1371/journal.pone.0135656,The Spatial Distribution of Hepatitis C Virus Infections and Associated Determinants—An Application of a Geographically Weighted Poisson Regression for Evidence-Based Screening Interventions in Hotspots,2015.0,PLoS ONE,B. Kauhl; J. Heil; C. Hoebe; Jürgen Schweikart; T. Krafft; N. Dukers-Muijrers,"Background Hepatitis C Virus (HCV) infections are a major cause for liver diseases. A large proportion of these infections remain hidden to care due to its mostly asymptomatic nature. Population-based screening and screening targeted on behavioural risk groups had not proven to be effective in revealing these hidden infections. Therefore, more practically applicable approaches to target screenings are necessary. Geographic Information Systems (GIS) and spatial epidemiological methods may provide a more feasible basis for screening interventions through the identification of hotspots as well as demographic and socio-economic determinants. Methods Analysed data included all HCV tests (n = 23,800) performed in the southern area of the Netherlands between 2002–2008. HCV positivity was defined as a positive immunoblot or polymerase chain reaction test. Population data were matched to the geocoded HCV test data. The spatial scan statistic was applied to detect areas with elevated HCV risk. We applied global regression models to determine associations between population-based determinants and HCV risk. Geographically weighted Poisson regression models were then constructed to determine lo",65.0,https://doi.org/10.1371/journal.pone.013565686792b3b40a7d627a20990f6a2bce357f2cf608d07f,10.1016/j.retrec.2019.01.003,Estimating land value uplift around light rail transit stations in Greater Kuala Lumpur: An empirical study based on geographically weighted regression (GWR),2019.0,Research on Transport Economics,M. Dziauddin,"Abstract Introducing a rail transit system into an urban region is expected to increase land values, and subsequently, residential property values. Despite this general belief, little is known about the spatial distributional effects of land value uplift. Thus, the goal of this paper is to provide new insights on how proximity to light rail transit stations may affect residential property values in Greater Kuala Lumpur, Malaysia using geographically weighted regression (GWR). The results provide information on spatial variations in the effects of a light rail transit system on residential property values. This study utilises GWR to account for spatial heterogeneity and spatial dependence. The results suggest that residential property values benefit from the provision of a light rail transit system but with considerable spatial variation over a geographical area. Evidently, proximity to the nearest light rail transit station gives positive premiums of up to 8% for a majority of properties located in lower-middle and upper-middle income neighbourhoods such as Wangsa Maju, Setapak, Keramat, Setiawangsa, Ampang and Sentul. In contrast, the impact of proximity to the nearest light rail ",65.0,8683ec1baf0d6d49f9dfa3daeaf93a8c7dcc4a5f63a,10.1080/13658816.2024.2342319,SGWR: similarity and geographically weighted regression,2024.0,International Journal of Geographical Information Science,M. Lessani; Zhen-Long Li,"Abstract Geographically weighted regression (GWR) offers a local approach to modeling spatial data, considering geographical location and spatial relationships between observations. A salient feature of GWR is the emphasis on geographical proximity, in accordance with Tobler’s First Law of Geography, which assumes that closer entities have a greater influence on the target location. Traditional GWR models have been augmented to consider various forms of physical distances aimed at enhancing model performance, and they often disregarded the potential influence of other data attributes, a shortcoming that extends to most GWR extensions. In this study, we introduce a novel weight matrix construction, which integrates data attribute similarity alongside the conventional geographically weighted matrix. The two weights are integrated in a manner that results in improved model performance. The proposed model, called Similarity and Geographically Weighted Regression or SGWR, was applied to five distinct datasets: housing prices, crime rates, and three health outcomes including mental health, depression, and HIV. Results show that SGWR significantly improved model performance based on sever",65.0,https://www.tandfonline.com/doi/pdf/10.1080/13658816.2024.2342319?needAccess=true869fc696d5787cdac3de5447a91fd0f6dc05ef7a067,10.5897/jgrp11.067,The effects of location and neighbourhood attributes on housing values in metropolitan Lagos,2011.0,,O. Aluko,"The aim of this paper is to analyse and determine the relative roles of location and neighbourhood characteristics in the determination of housing values/prices. In order to achieve this, attempts were made to evaluate the role of location and neighbourhood factors in the determination of house prices; study how house prices / values vary by area; show how spatial variation of the housing attributes leads to the determination of income sub-groups in cities; and determine the extent to which these findings help in the understanding of the structure of the housing market in Nigerian cities. This paper therefore examined the spatial variations of location and neighbourhood attributes on house prices in the valuation zones. The hypothesis tested is that house prices vary by neighbourhood and locational attributes in metropolitan Lagos. The analysis of variance and multiple regression models were used in the analysis. It is concluded that neighbourhood and locational attributes show more importance on house values when smaller geographical housing units are examined. 870 871 872 873 Key words: Locational attributes, neighbourhood characteristics, house values.",65.0,https://doi.org/10.5897/jgrp11.067874a55bee4aed44109dfff78fb4a94bc0d886aea1c9,10.1016/j.annals.2020.103108,What Airbnb does to the housing market,2020.0,,Beatriz Benítez-Aurioles; Iis P. Tussyadiah,"Based on a microeconometic model, this paper examines the effect of Airbnb in rents and house prices. Using borough-level data from the city of London between 2016 and 2019, we estimate System GMM regression models that indicate that Airbnb presence has an upward effect on the prices of both house purchases and of rentals, even disaggregating by categories; but the effect is stronger on house prices than rents, as theorized by the model. This evidence confirms that Airbnb affects the housing market by increasing the value of real estate properties.",65.0,https://openresearch.surrey.ac.uk/view/delivery/44SUR_INST/12139716940002346/13140593970002346875b0792843c775ae71af8a415310033a9291e111b8,10.1080/00036846.2011.636021,Explaining the spatial variation in housing prices: an economic geography approach,2013.0,,K. De Bruyne; J. Van Hove,,65.0,https://doi.org/10.2139/ssrn.947671876c7726836871fdc690e324c5879c3003504f42164,10.1108/ijhma-11-2016-0074,An exploration of determinants of affordable housing choice,2017.0,International Journal of Housing Markets and Analysis,A. Olanrewaju; Chai-Wo-On Tan,"877Purpose878Housing sufficiency is an indication of national development, and in recognition of this, a longstanding development objective of the Malaysian Government is the provision of affordable housing. The government has introduced various policies, schemes and regulations to increase housing supply. However, despite these measures, homeownership rates are dropping, and housing prices are outstripping inflation. For this reason, this paper aims to explain the determinants of housing choices. The issues in affordable housing supply in Malaysia are that of shortage and distributions. The problem of distribution is largely addressable through choice reconciliations.879880881Design/methodology/approach882The research is based on a cross-sectional survey questionnaire, comprising 20 determinants and 468 householders/users. The questionnaire was developed via a review of the literature and the authors’ experience. The survey forms are administered by hand.883884885Findings886Six determinants were found to be extremely important to households’ choice of housing. The Kaiser’s measure of sampling adequacy (MSA) indicated that the strength of the relationships among the determinants was strong (MSA = 0.76",64.0,887934e5d482e8f5b306cf3472138c95e04d5d6a13d,10.1186/s40537-021-00476-0,Predictive analytics using Big Data for the real estate market during the COVID-19 pandemic,2021.0,Journal of Big Data,Andrius Grybauskas; Vaida Pilinkienė; A. Stundžienė,"As the COVID-19 pandemic came unexpectedly, many real estate experts claimed that the property values would fall like the 2007 crash. However, this study raises the question of what attributes of an apartment are most likely to influence a price revision during the pandemic. The findings in prior studies have lacked consensus, especially regarding the time-on-the-market variable, which exhibits an omnidirectional effect. However, with the rise of Big Data, this study used a web-scraping algorithm and collected a total of 18,992 property listings in the city of Vilnius during the first wave of the COVID-19 pandemic. Afterwards, 15 different machine learning models were applied to forecast apartment revisions, and the SHAP values for interpretability were used. The findings in this study coincide with the previous literature results, affirming that real estate is quite resilient to pandemics, as the price drops were not as dramatic as first believed. Out of the 15 different models tested, extreme gradient boosting was the most accurate, although the difference was negligible. The retrieved SHAP values conclude that the time-on-the-market variable was by far the most dominant and cons",64.0,https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-021-00476-0888418754f83597ad46b54712e1cb8319e8a2bdfd3e,10.1080/02673037.2021.1879995,The determinants of homeownership affordability in Greater Sydney: evidence from a submarket analysis,2021.0,Housing Studies,Mustapha Bangura; C. Lee,"Abstract Recognising the existence of socio-economic and demographic disparities across metropolitan cities such as Greater Sydney, this study gauges the determinants of homeownership affordability in the different regions of Greater Sydney using local government area (LGA) data over 1991–2016 with a system generalised method of moments (GMM) and a panel error correction model (ECM). The results of the study showed that the determinants of homeownership affordability vary across the regions of Greater Sydney. Although house price and median personal income are the key drivers of homeownership affordability across all regions, the difference in the magnitude of these determinants between regions have also been documented. Specifically, Western Sydney is more sensitive to income and house price change than the other regions. In addition, Western Sydney is also sensitive to other determinants (i.e. housing supply, residential population, median rent, and housing investors), while no comparable evidence is found for the other regions. This clearly highlights the differences across regions and the importance of submarket considerations in the analysis of homeownership affordability. The",64.0,https://unsworks.unsw.edu.au/bitstreams/ae0b95b2-22a5-4c82-b5f7-738fbcd79d7b/download889110ee8b7cf810d9909c93038f69302fb01d327d5,10.1016/j.ufug.2021.127153,Spatial relationship between green view index and normalized differential vegetation index within the Sixth Ring Road of Beijing,2021.0,Urban Forestry & Urban Greening,Tao Li; Xiye Zheng; Jia-Hui Wu; Yonglin Zhang; Xiao Fu; H. Deng,"Abstract Urban green space (UGS) has been recognized as a critical urban landscape design element. The green view index (GVI), as an indicator to quantify the perception of green landscape from the pedestrians’ perspective, has been widely used to evaluate the quality and aesthetic ecosystem services of urban green spaces. Therefore, to quantify the quality and regional differences of urban road greening in the horizontal or vertical dimensions within the Beijing Sixth Ring Road, this study analyzed the spatial pattern of road GVI at different levels, including at sample points, roads, and counties, and evaluated the differences in road GVI in different urban functional zones in 2014. Based on the geographically weighted regression model, this study further analyzed the spatial heterogeneity between road GVI and the normalized difference vegetation index (NDVI). The results showed that the average road GVI at sample point level, road level, and county level within the study area were 17.2%, 15.3%, and 15.7%, respectively, which were overall relatively low. The road GVI between adjacent ring roads from inside to outside showed an obvious regional difference. The ranking of average r",64.0,890373ffe31ea2369d9255ffc8791b1a9e49de3065f,10.1111/j.1931-0846.2007.tb00280.x,Amenity Migration in the U.S. Sierra Nevada*,2007.0,,R. Loeffler; Ernst Steinicke,"Since 1960 California's Sierra Nevada counties have ranked among the regions with the strongest relative population growth in the state. Reassessment of peripheral areas has been the main force driving population and settlement growth in the central Sierra Nevada of California and Nevada, termed “amenity migration” or “counterurbanization.” This study analyzes the impacts of amenity migrants—“urban refugees”—on socioeconomic conditions in high‐mountain regions. We define these regions as the “High Sierra,” comprising zones at elevations more than 1,800 meters above sea level. People who migrate to the High Sierra tend to be white and well educated, with considerable household earnings. Unlike the population in the foothills, these migrants are not senior citizens. Their demand for periodic or permanent residences has caused housing prices to increase enormously. As a result, a majority of homes are now priced well beyond the reach of local salaries, which may lead to potential conflict between locals and newcomers. The massive settlement expansion in high‐mountain areas requires a new approach to land‐use planning, one that takes functional regions into account. Therefore, it is ex",64.0,891ee8f88889bceac1ddf9d74ba6dac9912e69ee211,10.1111/jmcb.12701,When to Lean against the Wind,2020.0,"Journal of Money, Credit and Banking",Björn Richter; M. Schularick; P. Wachtel,"This paper shows that policy-makers can distinguish between good and bad credit booms with high accuracy and they can do so in real time. Evidence from 17 countries over nearly 150 years of modern financial history shows that credit booms that are accompanied by house price booms and a rising loan-to-deposit-ratio are much more likely to end in a systemic banking crisis. We evaluate the predictive accuracy for different classification models and show that the characteristics of the credit boom contain valuable information for sorting the data into good and bad booms. Importantly, we demonstrate that policy-makers have the ability to spot dangerous credit booms on the basis of data available in real time. We also show that these results are robust across alternative specifications and time-periods.",64.0,892bdfad9362fdf37e46e3c5699909821e7c310bece,10.34117/bjdv11n2-010,"Gentrification, urban revitalization, and social equity: challenges and solutions",2025.0,Brazilian Journal of Development,C. E. D. de Oliveira,"Gentrification is an urban phenomenon that involves transforming disadvantaged neighborhoods into more desirable areas, often through the creation of public spaces like parks and infrastructure renewal. While these changes can improve the urban environment and enhance quality of life, they can also result in the displacement of long-term residents, particularly those from low-income or minority communities. This displacement exacerbates socio-economic and cultural inequalities, as new, wealthier residents move in, pushing up property values and living costs. The impact of gentrification is not only economic but also social and health-related. The effects on residents' health can vary depending on factors such as population characteristics, urban development type, and public policies in place. Studies by Kwon et al. (2017), Rigolon et al. (2019), Sun (2023), and Cole et al. (2021) stress the need for a more inclusive and balanced approach to urban planning. They emphasize that while parks and public spaces can bring positive changes, they must be accompanied by strategies to protect vulnerable communities. Rent control measures, affordable housing preservation, and community engagem",63.0,https://ojs.brazilianjournals.com.br/ojs/index.php/BRJD/article/download/77293/53701893ff707783436f01f844e3e1245716dbc6905f77ef,10.1016/j.energy.2020.119232,Performance evaluation and multi-objective optimization of a low-temperature CO2 heat pump water heater based on artificial neural network and new economic analysis,2020.0,Energy,Ying-Jie Xu; Cheng-Yuan Mao; Yuangong Huang; Xi Shen; Xiao-Xiao Xu; Guang-Ming Chen,"Abstract For the advantages of high efficiency and low impact to the environment, CO2 air source heat pump water heater (ASHPWH) is applied to produce domestic water, which also reveals good potential in cold regions. In order to boost the system performance and practicability under low ambient temperature, optimization for CO2 ASHPWH is conducted using non-dominated sorting genetic algorithm (NSGA-II). A validated artificial neural network (ANN) predicts energy parameters for the optimization. And an economic model provides economic and environmental parameters, which considers the influence of housing price, tank volume, and on/off-peak electricity price, rarely taken into account in published studies. Then the optimizing progress is conducted under −20 °C ambient temperature and 9–65 °C water temperature, in which four optimized variables are selected: gas cooler outlet temperature (Tgc), heat rejection pressure (Pgc), compressor displacement (qvh) and water tank volume (Vwt). The final solution of Tgc = 15 °C, Pgc = 8294.1 kPa, Vwt = 0.3647 m3, qvh = 401.33 mL/s results in two objectives (CO2 emission and total annual cost) of 8599.4 kg and 1626.9 $/year, revealing advantages b",63.0,894e9b4ccaad20af53fdc133a4cb4a3f7e599e36a3a,10.1016/j.retrec.2020.100813,"Effects of transit-oriented development (TOD) on housing prices: A case study in Wuhan, China",2020.0,,Jian-Yi Li; Hao-Cheng Huang,"Abstract Rail transit is becoming significant to urban growth and sustainability in China since China is investing more than 2 trillion yuan in urban rail transit during the 13th Five-Year Plan (2016–2020). Transit-oriented development (TOD) emphasizes using built-environment factors such as mixed-use, density, and walkability, to maximize the benefits of improving transit accessibility. Although studies illustrate how transit-oriented built-environments amplify the rail transit impact on housing prices within the American context, little attention has been paid to Chinese cities. Using a case study of Wuhan City in China, this study shows that a higher transit proximity premium of housing prices is more likely to occur in the place with more mixed land uses. Policy implications on TOD planning and land value capture near transit station areas are derived.",63.0,89587afc32f9481f17ef30967fc54e095d223bd8161,10.1007/s11146-009-9208-9,Nonlinear Spatial and Temporal Effects of Highway Construction on House Prices,2011.0,,Ekaterina Chernobai; M. Reibel; M. Carney,,63.0,https://papers.ssrn.com/sol3/papers.cfm?abstract_id=169875489630edc299760ebab59948344910cce423a497b2c6,10.1016/j.spasta.2014.01.002,Approximate Bayesian inference for spatial econometrics models,2014.0,,R. Bivand; V. Gómez-Rubio; H. Rue,"Abstract In this paper we explore the use of the Integrated Laplace Approximation (INLA) for Bayesian inference in some widely used models in Spatial Econometrics. Bayesian inference often relies on computationally intensive simulation methods, such as Markov Chain Monte Carlo. When only marginal inference is needed, INLA provides a fast and accurate estimate of the posterior marginals of the parameters in the model. Furthermore, we have compared the results provided by these models to those obtained with a more general class of Generalised Linear Models with random effects. In these models, spatial autocorrelation is modelled by means of correlated Gaussian random effects. We also discuss a procedure to extend the class of models that the R-INLA software can fit. This approach is based on conditioning on one or more parameters so that the resulting models can be fitted with R-INLA across sets of values of the fixed parameters. The posterior marginals of these parameters of interest are then obtained by combining the marginal likelihoods (which are conditioned on the values of the parameters fixed) of the fitted models and a prior on these parameters. This approach can also be used",62.0,http://hdl.handle.net/11250/2461377897e09114ab4348b867d2e4bca91148a9cd3f42aa7a,10.5089/9781513545400.001,Effects of Macroprudential Policy,2020.0,IMF Working Papers,J. Araujo; Manasa Patnam; A. Popescu; Fabián Valencia; Weijia Yao,"This paper builds a novel database on the effects of macroprudential policy drawing from 58 empirical studies, comprising over 6,000 results on a wide range of instruments and outcome variables. It encompasses information on statistical significance, standardized magnitudes, and other characteristics of the estimates. Using meta-analysis techniques, the paper estimates average effects to find i) statistically significant effects on credit, but with considerable heterogeneity across instruments; ii) weaker and more imprecise effects on house prices; iii) quantitatively stronger effects in emerging markets and among studies using micro-level data; and iii) statistically significant evidence of leakages and spillovers. Other findings include relatively stronger impacts for tightening than loosening actions and negative effects on economic activity in the near term.",62.0,https://www.elibrary.imf.org/downloadpdf/journals/001/2020/067/001.2020.issue-067-en.xml898c8b3879013243979b5846d4ef0d602ecd13f41e4,10.1016/j.jue.2013.10.006,Spatial Lag Models with Nested Random Effects: An Instrumental Variable Procedure with an Application to English House Prices,2014.0,,B. Baltagi; B. Fingleton; A. Pirotte,"This paper sets up a nested random effects spatial autoregressive panel data model to explain annual house price variation for 2000–2007 across 353 local authority districts in England. The estimation problem posed is how to allow for the endogeneity of the spatial lag variable producing the simultaneous spatial spillover of prices across districts together with the nested random effects in a panel data setting. To achieve this, the paper proposes new estimators based on the instrumental variable approaches of Kelejian and Prucha (1998) and Lee (2003) for the cross-sectional spatial autoregressive model. Monte Carlo results show that our estimators perform well relative to alternative approaches and produces estimates based on real data that are consistent with the theoretical house price model underpinning the reduced form.",62.0,https://surface.syr.edu/cpr/382899d3a12cd95deef40193d0765a759a0ca49a3ba0ef,10.1080/01621459.2020.1773831,Structure and Sensitivity in Differential Privacy: Comparing K-Norm Mechanisms,2018.0,Journal of the American Statistical Association,Jordan Awan; A. Slavkovic,"Abstract Differential privacy (DP) provides a framework for provable privacy protection against arbitrary adversaries, while allowing the release of summary statistics and synthetic data. We address the problem of releasing a noisy real-valued statistic vector T, a function of sensitive data under DP, via the class of K-norm mechanisms with the goal of minimizing the noise added to achieve privacy. First, we introduce the sensitivity space of T, which extends the concepts of sensitivity polytope and sensitivity hull to the setting of arbitrary statistics T. We then propose a framework consisting of three methods for comparing the K-norm mechanisms: (1) a multivariate extension of stochastic dominance, (2) the entropy of the mechanism, and (3) the conditional variance given a direction, to identify the optimal K-norm mechanism. In all of these criteria, the optimal K-norm mechanism is generated by the convex hull of the sensitivity space. Using our methodology, we extend the objective perturbation and functional mechanisms and apply these tools to logistic and linear regression, allowing for private releases of statistical results. Via simulations and an application to a housing pri",62.0,900ac5391a941230f1f880f136717f4e6ab1f4892a3,10.3386/w4196,"Patterns and Determinants of Metropolitan House Prices, 1977-91",1992.0,,Jesse M. Abraham; P. Hendershott,,62.0,https://doi.org/10.3386/w419690164e0e1c6b59d0309e540ea2150c2b7aab8cead09,10.1108/14635780310469102,Determinants of housing prices in Spanish cities,2003.0,,Paloma Taltavull de La Paz,,62.0,902d29e0bf47fcebffe19e76cbf3d312c1fbdb0274b,10.1177/088541229801200301,The Determinants of Residential Property Values: Implications for Metropolitan Planning,1998.0,,G. Knaap,,62.0,9037790746db023703b3c3e0f39d2ee019a502dad3f,10.1016/j.compenvurbsys.2018.12.006,Unraveling environmental justice in ambient PM2.5 exposure in Beijing: A big data approach,2019.0,"Computers, Environment and Urban Systems",Yanyan Xu; Shan Jiang; Ruiqi Li; Jiang Zhang; Jin-Huan Zhao; Sofiane Abbar; Marta C. González,"Abstract Air pollution imposes significant environmental and health risks worldwide and is expected to deteriorate in the coming decade as cities expand. Measuring population exposure to air pollution is crucial to quantifying risks to public health. In this work, we introduce a big data analytics framework to model residents' stay and commuters' travel exposure to outdoor PM2.5 and evaluate their environmental justice, with Beijing as an example. Using mobile phone and census data, we first infer travel demand of the population to derive residents' stay activities in each analysis zone, and then focus on commuters and estimate their travel routes with a traffic assignment model. Based on air quality observations from monitoring stations and a spatial interpolation model, we estimate the outdoor PM2.5 concentrations at a 500-m grid level and map them to road networks. We then estimate the travel exposure for each road segment by multiplying the PM2.5 concentration and travel time spent on the road. By combining the estimated PM2.5 exposure and housing price harnessed from online housing transaction platforms, we discover that in the winter, Beijing commuters with low wealth level a",61.0,https://dspace.mit.edu/bitstream/1721.1/126882/2/CEUS_Xu_2019.pdf904f2240999cc900df562cd1f39ec02f9dc977d1bfc,10.1016/j.habitatint.2020.102120,How does growing city size affect residents’ happiness in urban China? A case study of the Bohai rim area,2020.0,,Y. Dang; Li Chen; Wen-Zhong Zhang; D. Zheng; D. Zhan,"Abstract In China, rapid and extensive urbanization has brought not only benefits due to urban agglomeration but also various urban problems; both affect residents' happiness. Previous studies have emphasized the direct impacts of growing city size on happiness, and few have addressed the indirect effects of city size on happiness through subjective evaluations in developing countries. Based on an extensive questionnaire survey conducted in 44 cities in the Bohai rim area in 2014, this paper establishes a theoretical framework to explore both the direct and indirect effects of city size on residents' happiness by applying subjective measurements in urban China. City size is found to have a nonlinear correlation with happiness. Individual satisfaction with both urban life and income mediate the relationship between urban objective attributes and happiness. House price has a positive impact on urban satisfaction, while the influences of haze pollution and traffic congestion are negative. Income positively affects happiness at the individual level. However, the city-level average wage has little relationship with happiness. These findings provide insights for deeply improving citizens",61.0,905822b01aa6cb804500740396d0d07bfa8ab43beeb,10.1177/0042098019856822,City size and housing purchase intention: Evidence from rural–urban migrants in China,2020.0,Urban studies,Yanjiao Song; Chuan-Yong Zhang,"Despite the increased focus on housing choices among rural–urban migrants in China, there is a lack of studies on city size and housing purchase preferences. In this paper, we extend the conceptual framework of the Rosen–Roback model to analyse how city size affects rural–urban migrants’ housing purchase intention, and find that the impact of city size on the willingness to buy a house in the host city for migrants has an inverted U shape by using the China Migrants Dynamic Survey of 2014. To explain this phenomenon, we further adopt the Oaxaca–Blinder decomposition, which shows that rural–urban migrants have achieved a spatial equilibrium between housing costs and city amenities in large cities, compared with megacities and small cities. Specifically, the amenities in large cities can compensate for the negative impact of the high housing cost, making these large cities more attractive than small ones for rural–urban migrants, while rural migrants have to bear high housing prices and exclusive urban welfare because of the strict household registration system in megacities. This study thus sheds new light on the adoption of diversified housing policies to solve the housing problems",61.0,906d976321c4a7b382c028c950efb2ba2d9afd187a9,10.1080/09654313.2017.1376314,"Hedonic pricing analysis of the influence of urban green spaces onto residential prices: the case of Leipzig, Germany",2018.0,,V. Liebelt; Stephan Bartke; N. Schwarz,,61.0,https://research.utwente.nl/files/98722740/Hedonic_pricing_analysis_of_the_influence_of_urban_green_spaces_onto_residential_prices_the_case_of_Leipzig_Germany.pdf907ec6fdc763ceba51256f30c7d6a71f88e8490179d,10.17762/turcomat.v12i2.1870,Prediction of House Price Using XGBoost Regression Algorithm,2021.0,,Et. al. J. Avanijaa,"House price fluctuates each and every year due to changes in land value and change in infrastructure in and around the area. Centralised system should be available for prediction of house price in correlation with neighbourhood and infrastructure, will help customer to estimate the price of the house. Also, it assists the customer to come to a conclusion where to buy a house and when to purchase the house. Different factors are taken into consideration while predicting the worth of the house like location, neighbourhood and various amenities like garage space etc. Developing a model starts with Pre-processing data to remove all sort of discrepancies and fill null values or remove data outliers and make data ready to be processed. The categorical attribute can be converted into required attributes using one hot encoding methodology. Later the house price is predicted using XGBoost regression technique.",60.0,https://turcomat.org/index.php/turkbilmat/article/download/1870/1615908d2078d1de58b8a772e925359ccad3bbe096d77b4,10.1016/j.jpubeco.2019.05.004,The gradients of power: Evidence from the Chinese housing market,2019.0,Journal of Public Economics,Han-Ming Fang; Quan-Lin Gu; Li‐An Zhou,"Using a large, unique dataset on the Chinese housing market, we propose to measure corruption using the price differences paid by bureaucrat buyers and non-bureaucrat buyers in the housing market. We find that the housing price paid by bureaucrat buyers is on average 1.05 percentage points lower than non-bureaucrat buyers, after controlling for a full set of characteristics of buyers, houses and mortgage loans. More interestingly, we find that the bureaucrat price discounts exhibit interesting gradients with respect to their hierarchical ranks, the criticality of their government agencies to real estate developers, and geography. We argue that the bureaucrat price discounts and the gradients of these discounts are unlikely to be driven by alternative explanations, thus they are evidence of corruption and measures of the market value of government power.",60.0,https://doi.org/10.3386/w20317909a6804763764ab6078944483eb45c895fd76ebc15,10.2139/ssrn.2577211,Capturing the Financial Cycle in Europe,2015.0,Social Science Research Network,Hanno Stremmel,"In this study, we approximate the financial cycle in Europe by combining potential common and relevant financial indicators. We consider different credit aggregates and asset prices but also incorporate banking sector indicators for 11 European countries. We develop seven different synthetic financial cycle measures in order to best capture the characteristics of the financial cycle. We assess the various financial cycle measures using both graphical and statistical investigation techniques. The best fitted financial cycle measure includes the following financial ingredients: credit to GDP ratio, credit growth and house prices to income ratio. This study also highlights potential applications for the financial cycle measure in the macro-prudential policy context. JEL Classification: E30, E44, E61, G18, G28",60.0,https://www.econstor.eu/bitstream/10419/154244/1/ecbwp1811.pdf910ffe3872b1adf7659ae44c12e9ef28b1306745ebc,10.1007/bf01940131,Specification tests on the structure of interaction in spatial econometric models,1984.0,,L. Anselin,The structural assumptions embedded in a particular form of a spatial connectivity or dependence matrix are often not explicitly treated in the statistical analysis of mixed regressive-spatial autoregressive models. This paper sees the evaluation of different structures as an application of tests on non-nested hypotheses. Several recently developed statistics are outlined and their appropriateness for spatial analysis discussed. The tests are illustrated empirically in simple models that incorporate spatial spill-over effects in the explanation of urban housing value.,60.0,https://doi.org/10.1111/j.1435-5597.1984.tb00822.x911394f6db067aec4c732bf9902d02a7c12c9505a05,10.1016/j.dajour.2023.100166,A comparative assessment of machine learning methods for predicting housing prices using Bayesian optimization,2023.0,Decision Analytics Journal,S. Lahmiri; S. Bekiros; Christos Avdoulas,,60.0,https://doi.org/10.1016/j.dajour.2023.1001669124e7c0a01756517e11c20a003a274c49bafb74fb8,10.1186/s42854-020-00014-w,"Shifting landscapes of coastal flood risk: environmental (in)justice of urban change, sea level rise, and differential vulnerability in New York City",2020.0,Urban Transformations,P. Herreros-Cantis; Veronica Olivotto; Z. Grabowski; T. McPhearson,"Climate-driven changes in coastal flood risk have enormous consequences for coastal cities. These risks intersect with unequal patterns of environmental hazards exacerbating differential vulnerability of climate related flooding. Here we analyze differential vulnerability of coastal flooding in New York City, USA, as an environmental justice issue caused by shifts in flood risk due to increasing floodplain extents. These extents are represented by updates to the 100-year floodplain by the Federal Emergency Management Agency, and urban changes in land use, land value, and socio-economic characteristics of flood exposed populations. We focus on six local community districts containing disproportionately vulnerable communities. Across our study areas, we observed increases in the floodplain’s extent by 45.7%, total exposed population by 10.5%, and population living in vulnerable communities by 7.5%. Overall flood risk increases regardless of increases in the updated floodplain extent, as do floodplain property values. However, variability is high between community districts; in some cases, increases in exposure coincide with decreases in vulnerability due to shifts in racial demograph",59.0,https://doi.org/10.1186/s42854-020-00014-w91377144bed4c9e07722d1806029505c19b0626a4c8,10.1016/j.socscimed.2012.03.041,"Residential property values are associated with obesity among women in King County, WA, USA",2012.0,Social Science & Medicine (1967),C. Rehm; A. Moudon; P. Hurvitz; A. Drewnowski,"Studies of social determinants of weight and health in the US have typically relied on self-reported education and incomes as the two primary measures of socioeconomic status (SES). The assessed value of one’s home, an important component of wealth, may be a better measure of the underlying SES construct and a better predictor of obesity. The Seattle Obesity Study (SOS), conducted in 2008-9, was a cross-sectional random digit dial telephone survey of 2001 adults in King County, Washington State, US. Participants’ addresses were geo-coded and residential property values for each tax parcel were obtained from the county tax assessor’s database. Prevalence ratios of obesity by property values, education, and household income were estimated separately for women and men, after adjusting for age, race/ethnicity, household size, employment status and home ownership. Among women, the inverse association between property values and obesity was very strong and independent of other SES factors. Women in the bottom quartile of property values were 3.4 times more likely to be obese than women in the top quartile. No association between property values and obesity was observed for men. The prese",59.0,https://www.ncbi.nlm.nih.gov/pmc/articles/38896619148e2d3bf87dc36eb587637e693545e338f3ad866f,10.1016/j.landusepol.2019.04.004,Analyzing the private rental housing market in Shanghai with open data,2019.0,Land Use Policy,Han-Duo Li; Y. Wei; Yangyi Wu,"The failure of public housing policies and skyrocketing housing prices have made the private rental sector an increasingly important part of the housing system in Chinese metropolises. However, due to the lack of data, the private rental housing market remains poorly understood. By integrating open data, this paper comprehensively examines the spatial patterns and determinants of residential rents in Shanghai at the intra-urban level. We find that high rents are concentrated heavily in the inner-city area, which not only forces low-income families to live in the suburbs, where rents are still relatively affordable, but also makes housing costs a heavy burden to non-native young professionals. The results of spatial regressions suggest that the rental housing market in Shanghai is shaped by regional level factors such as job opportunities, salary levels, and the size of the “floating” population, and neighborhood level indicators like public transport facilities and service amenities. Such factors are differentiated across space. In the areas with better infrastructure, the roles of high salaries and attractive amenities are highly significant. In suburban districts, the presence of",59.0,915ca1aab9aed464a3beb419440e11b35373e30cdee,10.1016/j.ocecoaman.2019.105023,"Variables shaping coastal adaptation decisions to armor, nourish, and retreat in North Carolina",2020.0,,A. Siders; J. Keenan,"Abstract Understanding why and where decision-makers choose to use different climate change adaptation strategies remains an important theoretical and practical question for coastal adaptation. This article provides an exploratory statistical analysis of three adaptation measures (shoreline armoring, property acquisitions, and beach nourishment) and their deployment with respect to metrics of risk exposure, socioeconomic markers, and critical infrastructure in North Carolina (U.S.). This exploratory analysis evaluates two propositions. First, adaptation measures are deployed relative to specific metrics of risk. Second, adaptation choice disproportionately correlates with socioeconomic attributes. The findings support both propositions and reveal that shoreline armoring correlates with higher home values, household incomes, and population density and low racial diversity. Property acquisitions are found to correlate with low home values, household incomes, and population density and high racial diversity. Furthermore, adaptation measures are interconnected. Acquisitions are more likely to occur in areas with low levels of armoring. Beach nourishment occurs exclusively in areas with",59.0,9166f36ab3676e25dd58940f205906eacb7ddbd7361,10.1016/j.jtrangeo.2019.102489,Why do they live so far from work? Determinants of long-distance commuting in California,2019.0,Journal of Transport Geography,S. Mitra; J. Saphores,"Abstract The determinants of long-distance commuting (trips longer than 50 miles one-way) in the U.S. appear to be poorly understood even though long-distance commuting likely has substantial environmental, social, and economic impacts. A review of the literature shows that that few papers have considered how housing costs influence long-distance commuting. Moreover, residential self-selection has rarely been accounted for in commuting studies. To start addressing these gaps, we analyze the long-distance travel component of the 2012 California Household Travel Survey via a generalized structural equation model. In our model, land use and housing costs are explained by household and head of household characteristics; together with these characteristics, land use and housing costs influence long-distance commuting. We find that the probability of a household commuting long-distance decreases with an increase in the job-housing ratio (OR = 0.914***) and most importantly, with the median home value of the census tract where a household resides (OR = 0.488***). Conversely, this probability increases with the median census tract home values where household members work (OR = 1.765***). F",59.0,917ec2a78a168418b210995a867109655b651e14d47,10.1016/j.ufug.2018.11.011,Residential satisfaction about urban greenness: Heterogeneous effects across social and spatial gradients,2019.0,Urban Forestry & Urban Greening,Wen-Jie Wu; Mark Wang; N. Zhu; Wei-Yang Zhang; Hua Sun,"Abstract Rapid urbanisation in developing countries is putting pressure on urban greenness supplies and living environment. Access to parks plays an important role for people’s lived experiences about urban greenness. While existing studies have mostly focused on the capitalized value of access to parks on property values, few studies have been conducted on the relationship between access to parks and residential satisfaction towards the greenness domain in developing countries. This study fills this gap through the detailed investigation about individuals’ perceptions about residential satisfaction towards the greenness domain using a large-scale resident survey in metropolitan Beijing. We focus on the ways in which this relationship is moderated by complementary effects between access to parks and contextual amenities in order to explore how residents’ satisfaction perceptions are shaped by socio-spatial gradients. The results show that limited access to parks is associated with lower residential satisfaction towards the greenness domain. Importantly, the psychological implications of access to parks vary with household demographics, and contextual amenities such as schools, recr",59.0,918db234f08b8a5dc3cafcd6e86797480ebccf67de6,10.1016/j.jpubeco.2019.104110,Unlocking amenities: Estimating public good complementarity,2018.0,Journal of Public Economics,David Albouy; P. Christensen; Ignacio Sarmiento-Barbieri,"Abstract Public goods may exhibit complementarities that are essential for determining their individual value. Our results indicate that improving safety near parks can turn them from public bads to goods. Ignoring complementarities may lead to i) undervaluing the potential value of public goods; ii) overestimating heterogeneity in preferences; and iii) understating the value of public goods to minority households. Recent reductions in crime have “unlocked” almost $7 billion in property value in Chicago, New York and Philadelphia. Still, two-fifths of the potential value of park proximity, $10 billion, remains locked-in.",59.0,http://www.nber.org/papers/w25107.pdf919550566cc82be356cc72d32045e0ef786c0599602,10.2139/ssrn.2062536,Interjurisdictional Housing Prices and Spatial Amenities: Which Measures of Housing Prices Reflect Local Public Goods?,2013.0,,H. S. Banzhaf; Omar Al Farooque,,59.0,https://doi.org/10.3386/w17809920789a530073380f91a677d8db8f71821d573fc194,10.2747/1548-1603.44.3.267,Modeling Owner-Occupied Single-Family House Values in the City of Milwaukee: A Geographically Weighted Regression Approach,2007.0,,Danlin Yu,,59.0,https://www.tandfonline.com/doi/pdf/10.2747/1548-1603.44.3.267?needAccess=true&role=button921dd1db5adbc20b1f1cb9ebbdc8e79f7c4e4bd3725,10.1109/fskd.2016.7603227,Housing price prediction using neural networks,2016.0,"International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery",W. T. Lim; Lipo Wang; Yaoli Wang; Qing Chang,,59.0,9224edbfc479a576165ce41c9c84b49fc78f4a15f29,10.1016/j.apgeog.2015.06.020,Neighborhood diversity and the creative class in Chicago,2015.0,,Bradley Bereitschaft; Rex G. Cammack,"Abstract Richard Florida's creative class theory posits that highly skilled workers with creative- or knowledge-intensive occupations are particularly sensitive to ‘quality of place’, a key component of which is an open and tolerant attitude toward different peoples, cultures, and lifestyles. While diversity, as a proxy for tolerance, has proven to be a relatively weak pull-factor at the inter-metropolitan level, the potential role of neighborhood-level diversity in the residential location of creative class workers has yet to be explored empirically. In this study we use ordinary least squares (OLS) regression and geographically weighted regression (GWR) to test the hypothesis that there exists significant associations between particular types of neighborhood diversity (i.e., sexual orientation, language, race, and income) and the proportion of workers with specific creative class occupations. The results of our Chicago case study suggest a significant positive relationship between the creative class and the proportion of gay households and income diversity, but not racial or linguistic diversity. Overall, diversity appears to play a limited role in predicting where creative class",58.0,https://doi.org/10.1016/j.apgeog.2015.06.020923c8928b0530d86fdd74af692b76f7eca02da55618,10.1016/j.regsciurbeco.2019.103464,Mapping China’s time-varying house price landscape,2019.0,Regional Science and Urban Economics,M. Funke; Danilo Leiva-León; Andrew Tsang,"The recent increase in China’s house prices at the national level masks tremendous variation at the city level – a feature largely overlooked in the macroprudential literature. This paper measures the evolving heterogeneity in China’s house price dynamics across 70 major cities and assesses its relationship with housing market characteristics. We gauge the heterogeneity of house price dynamics using a novel regime-switching modelling approach to estimate the time-varying patterns of China’s city-level housing price synchronization. The estimates indicate an increasing synchronization leading up to 2015, and a decoupling pattern thereafter, which is associated to the heterogeneous strength of regional macroprudential policies. After sorting city-level housing prices into four clusters sharing similar cyclical features, we document high synchronization within clusters, but low synchronization among them. The empirical evidence suggests that differentials in the growth of population, income, and air quality are relevant explanatory factors of housing price synchronization among cities.",58.0,https://repositorio.bde.es/bitstream/123456789/9809/1/dt1930e.pdf924853b2cc7395be3be4b8b06d9a7c41c8d5c94d07f,10.2139/ssrn.3820251,"Storm Surges, Informational Shocks, and the Price of Urban Real Estate: An Application to the Case of Hurricane Sandy",2017.0,Social Science Research Network,Jeffrey P. Cohen; Jason Barr; Eon-Ju Kim,"The impacts of a major hurricane on commercial and residential real estate can be devastating. Recent events in Houston (with Hurricane Harvey), Florida (with Hurricane Irma), and New York City (with Hurricane Sandy) are examples of how flooding damage can unexpectedly extend beyond the FEMA flood zones. Such surprises or shocks can provide property owners—including those that are not flooded—with new information about future flood risks, based on the difference of the property distance from the flood zone and the distance to the actual locations of flooding. We apply a new estimation strategy to quantify the effects of these shocks on property values, using information on repeat property sales to estimate a separate shock effect for each dry property. We demonstrate our approach with an application to non-flooded properties in New York City for Hurricane Sandy. We find that, in general, houses, apartments and commercial properties show the most price volatility within the older, denser urban core, mostly in those neighborhoods that appear to be gentrifying.",58.0,https://doi.org/10.2139/ssrn.3820251925afae52890ded337b244b3c7beaaac0c09c979894,10.1016/j.red.2013.06.002,Saving up or settling down: home ownership over the life cycle,2014.0,,Jonathan Halket; Santhanagopalan Vasudev,"In a Bewley model with endogenous price volatility, home ownership and mobility across locations and jobs, we assess the contribution of financial constraints, housing illiquidities and house price risk to home ownership over the life cycle. The model can explain the rise in home ownership and fall in mobility over the life cycle. While some households rent due to borrowing constraints in the mortgage market, factors that affect propensities to save and move, such as risky house values and transactions costs, are equally important determinants of the ownership rate.",58.0,https://www.sciencedirect.com/science/article/pii/S1094202513000379/pdf92610e0fc02c89d8eaa6aecdf9a2f6b0d6102826e6e,10.1109/icacccn.2018.8748660,Comparative study of various training algorithms of artificial neural network,2018.0,"2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN)",P. Jaiswal; Nikhil Kumar Gupta; A. Ambikapathy,"The idea of creating intelligent system has fascinated us with the advent of computer. The artificial neural network is a methodology for the development of intelligent system which can emulate as humans. Increasingly, new algorithms are researched for better efficiency and accuracy. Thereby, this paper examines the performance of different training algorithms for artificial neural network in the feedforward backpropagation architecture. The training algorithms are designed and executed on MATLAB R2017a for the analysis. The various training algorithms are analyzed to find the accuracy level between desired and actual results. The analysis is executed on house price prediction dataset from Kaggle.",58.0,927d8c87cc08989aa18ef8ce3ceef8820a2d4729f14,10.1007/s10109-010-0114-8,Spatial error correction and cointegration in nonstationary panel data: regional house prices in Israel,2010.0,Journal of Geographical Systems,M. Beenstock; D. Felsenstein,,58.0,928dd49cd697eb69d36b20cd89ea27129203f2b69b6,10.5296/rae.v6i1.4946,House Price Bubbles in China,2014.0,,Ting Lan,"This paper uses a vector of macroeconomic and monetary policy fundamental variables to investigate the existence of speculative bubbles on national residential house market in China over the period from Mar.1998 to Feb.2013.In the past few years, except the quantitative easing policy was implemented in USA, many monetary policy instruments also have been used on the asset markets in China, such as expansionary of monetary supply and lower benchmark interest rate and lending rate. These led to the hyperinflation happened in China and property price increased dramatically after 2009. Because of the booming in the real estate industry, we are interested in whether there is a housing bubble existing in the market. Three sets of bubble attributes are examined, including unit root test and co-integration procedures, we find no evidence of rational bubbles in the national housing market. The tests for duration dependence in the negative returns on house prices suggest that China housing market is not affected by rational bubbles. Overall, this essay proposes monetary policy and macroeconomic variables are important factors for the increasing of housing prices. It is also necessary for mon",57.0,https://doi.org/10.5296/rae.v6i1.4946929701c45f31cecbf5d47133602b1615224e335f272,10.5815/ijieeb.2020.02.03,House Price Prediction Modeling Using Machine Learning,2020.0,International Journal of Information Engineering and Electronic Business,M. Thamarai; S. Malarvizhi,"—Machine Learning is seeing its growth more rapidly in this decade. Many applications and algorithms evolve in Machine Learning day to day. One such application found in journals is house price prediction. House prices are increasing every year which has necessitated the modeling of house price prediction. These models constructed, help the customers to purchase a house suitable for their need. Proposed work makes use of the attributes or features of the houses such as number of bedrooms available in the house, age of the house, travelling facility from the location, school facility available nearby the houses and Shopping malls available nearby the house location. House availability based on desired features of the house and house price prediction are modeled in the proposed work and the model is constructed for a small town in West Godavari district of Andhrapradesh. The work involves decision tree classification, decision tree regression and multiple linear regression and is implemented using Scikit-Learn Machine Learning Tool.",57.0,http://www.mecs-press.org/ijieeb/ijieeb-v12-n2/IJIEEB-V12-N2-3.pdf9305fa9d46d7189b4924cd83c4c0db71d5a2d72d43e,10.2139/ssrn.3465010,The Assessment Gap: Racial Inequalities in Property Taxation,2020.0,Social Science Research Network,C. Avenancio-León; Troup Howard,"We use panel data covering 118 million homes in the United States, merged with geolocation detail for 75,000 taxing entities, to document a nationwide ""assessment gap"" which leads local governments to place a disproportionate fiscal burden on racial and ethnic minorities. We show that holding jurisdictions and property tax rates fixed, black and Hispanic residents nonetheless face a 10-13% higher tax burden for the same bundle of public services. This assessment gap arises through two channels. First, property assessments are less sensitive to neighborhood attributes than market prices are. This generates racially correlated spatial variation in tax burden within jurisdiction. Second, appeals behavior and appeals outcomes differ by race. This results in higher assessment growth rates for minority residents. We propose an alternate approach for constructing assessments based on small-geography home price indexes, and show that this reduces inequality by at least 55-70%.",57.0,https://doi.org/10.2139/ssrn.3465010931e56be712ef342a2d9d81ecace456c5736603be69,10.3390/su11205792,"Exploring the Severity of Factors Influencing Sustainable Affordable Housing Choice: Evidence from Abuja, Nigeria",2019.0,Sustainability,I. S. Ezennia; Ş. Hoşkara,"It is a shared global experience that a house which is already expensive will become even more costly. This experience is partly because housing supply has always failed to satisfy demand. In many developing countries, the issues of affordable housing supply center on shortage and poor distribution. Recent studies on this subject reveal that distribution-related problems can be addressed through choice reconciliations. Therefore, understanding how housing affordability problems affect housing choice enables a broader interpretation of the issue. Thus, critical in housing policy making and implementation, as well as towards sustainable development/delivery of affordable housing programs. In Nigeria, housing choice has never been investigated, neither has it been studied within the framework of sustainability. It is not a common strategy to incorporate sustainability into the concept of affordable housing choice. However, integrating sustainability into the concept of affordable housing choice allows for the introduction of wide-ranging and broader criteria such as environmental and social factors, which are routinely neglected in housing choice literature. Therefore, this study aims",56.0,https://www.mdpi.com/2071-1050/11/20/5792/pdf?version=15713977649322c6aa426311a917d6df3d982bc45a425ffd2d62f,10.17016/ifdp.2011.1037,Are recoveries from banking and financial crises really so different,2011.0,,Greg Howard; R. Martin; B. Wilson,"This paper studies the behavior of recoveries from recessions across 59 advanced and emerging market economies over the past 40 years. Focusing specifically on the performance of output after the recession trough, we find little or no difference in the pace of output growth across types of recessions. In particular, banking and financial crisis do not affect the strength of the economic rebound, although these recessions are more severe, implying a sizable output loss. However, recovery does change with some characteristics of recession. Recoveries tend to be faster following deeper recessions, especially in emerging markets, and tend to be slower following long recessions. Most recessions are associated with a slowing, if not outright decline in house prices, but recessions with large declines in house prices also tend to have slower recoveries. Long recessions and those associated with poor housing-market outcomes can lead to sustained output losses relative to pre-crisis trends. Consistent with microeconomic studies showing permanent income loss to job-losing workers during recessions, we find that the sustained deviation in output from trend is associated with a reduction in la",56.0,https://doi.org/10.17016/ifdp.2011.103793348fe379d80519fbf670baf2989a14bc4c4f36883,10.3390/rs11243047,"Sensitivity Analysis of Machine Learning Models for the Mass Appraisal of Real Estate. Case Study of Residential Units in Nicosia, Cyprus",2019.0,Remote Sensing,T. Dimopoulos; N. Bakas,"A recent study of property valuation literature indicated that the vast majority of researchers and academics in the field of real estate are focusing on Mass Appraisals rather than on the further development of the existing valuation methods. Researchers are using a variety of mathematical models used within the field of Machine Learning, which are applied to real estate valuations with high accuracy. On the other hand, it appears that professional valuers do not use these sophisticated models during daily practice, rather they operate using the traditional five methods. The Department of Lands and Surveys in Cyprus recently published the property values (General Valuation) for taxation purposes which were calculated by applying a hybrid model based on the Cost approach with the use of regression analysis in order to quantify the specific parameters of each property. In this paper, the authors propose a number of algorithms based on Artificial Intelligence and Machine Learning approaches that improve the accuracy of these results significantly. The aim of this work is to investigate the capabilities of such models and how they can be used for the mass appraisal of properties, to h",56.0,https://www.mdpi.com/2072-4292/11/24/3047/pdf?version=15765742079347670a6d2dc2183fc23719395205238727f178317,10.1007/bf03399267,Spatial Estimation of the Impact of Airport Noise on Residential Housing Prices,2008.0,,M. Salvi,"SummaryThe paper applies spatial econometric techniques to measure the impact of airport noise on the price of single-family homes in the Zurich Airport area. We exploit a large database of geo-referenced noise measurements to investigate the reaction of prices to different noise metrics. The particular institutional setting of Zurich Airport, with changing patterns of runways configurations allows to distinguish the impact of noise at different times of the day. The use of neighborhood fixed-effects is compared to the results given by a costlier modelling strategy involving a rich set of location descriptors. The paper documents the impact of airport noise on housing prices. In the base model specification the Noise Discount Index is 0.97% with typical discounts in the range of −2% to −8%. Accounting for the spatiality of the data has little effect on the results.",56.0,https://sjes.springeropen.com/counter/pdf/10.1007/BF03399267.pdf935af211038551df170f6d2c4176cb3b8bb3124bd2b,10.1002/pam.20180,Does a more centralized urban form raise housing prices?,2006.0,Journal of policy analysis and management,Robert W. Wassmer; Michelle C. Baass,"This paper examines the relationship between various quantitative measures of urban centralization and urban housing prices through the use of a 2000 data set from the 452 Census designated urbanized areas in the United States. An empirical study of this type is necessary because: (1) the theoretical influence of creating more centralized urban areas-or what many would consider less “sprawl”-on what people pay for housing is indeterminate, (2) now popular “Smart Growth” policies advocate more centralized urban areas, and (3) some have argued that a cost of this centralization is an increase in the price of homes. After controlling for differences across United States urbanized areas in residents' economic status and demographics, number and type of households, climate, household growth, nonresidential land uses, and the structural characteristics of houses, we find that a more centralized area exhibits a lower median home value and percentage of homes in an upper-end price category. Therefore, we offer no evidence to support the contention that a successful effort to further centralize an urban area raises the price of homes in that urban area. © 2006 by the Association for Public ",56.0,9365bcfb772a2f546c3887de2fcf0652512074252b5,10.1016/j.jue.2019.103183,Valuing primary schools in urban China,2020.0,,Jimmy Chan; Xian Fang; Zhi Wang; Xianhua Zai; Qing-Hua Zhang,"Abstract We study the effect of school quality on housing prices in urban China. Our objective is to provide an estimate of the school-quality premium based on the best available data. To account for unobserved neighborhood characteristics, we adopt the boundary-discontinuity design of Black (1999) and the matching strategy proposed by Fack and Grenet (2010). The results suggest that parents value public primary schools that have outstanding records in academic tournaments. The school-quality premium is highly non-linear. While a tournament superstar—a school above the 90th percentile in tournament performance—causes housing prices in its neighborhood to increase by 14 percent, or about 430,000 RMB, the price difference between non-superstar schools is small.",56.0,937379df465c6aeb5281a95180bae733a686cf48c72,10.3390/ijerph17249578,The Diversified Impacts of Urban Morphology on Land Surface Temperature among Urban Functional Zones,2020.0,International Journal of Environmental Research and Public Health,Sihang Gao; Q. Zhan; Chen Yang; Hui-Min Liu,"Local warming induced by rapid urbanization has been threatening residents’ health, raising significant concerns among urban planners. Local climate zone (LCZ), a widely accepted approach to reclassify the urban area, which is helpful to propose planning strategies for mitigating local warming, has been well documented in recent years. Based on the LCZ framework, many scholars have carried out diversified extensions in urban zoning research in recent years, in which urban functional zone (UFZ) is a typical perspective because it directly takes into account the impacts of human activities. UFZs, widely used in urban planning and management, were chosen as the basic unit of this study to explore the spatial heterogeneity in the relationship between landscape composition, urban morphology, urban functions, and land surface temperature (LST). Global regression including ordinary least square regression (OLS) and random forest regression (RF) were used to model the landscape-LST correlations to screen indicators to participate in following spatial regression. The spatial regression including semi-parametric geographically weighted regression (SGWR) and multiscale geographically weighted",55.0,https://www.mdpi.com/1660-4601/17/24/9578/pdf?version=16087788169385a20099b886037c89faf7e2c27dc79f1bb23c77b,10.1007/s11146-007-9068-0,Developing a House Price Index for The Netherlands: A Practical Application of Weighted Repeat Sales,2008.0,,S. Jansen; P. D. de Vries; H. Coolen; C. J. M. Lamain; P. Boelhouwer,"This paper describes the development of a house price index that has been introduced in May 2005 in The Netherlands. This monthly index, called Woningwaarde Index Kadaster (House Price Index Kadaster), is designed to detect changes in the price of the overall stock of owner-occupied homes. Fifty-five indices are calculated: one overall index, four regional indices, 12 provincial indices and 38 indices based on combinations of region/province and dwelling type. We used Case and Shiller’s geometric Weighted Repeat Sales Model to calculate monthly house price indices. We used recorded data on the sales of over 500,000 owner-occupied homes in The Netherlands, all representing repeat sales between January 1993 and December 2006. The accuracy of the index was determined using the 95% confidence interval. We observed that accuracy might become a problem in smaller sub samples. Revision volatility was explored by comparing the index values computed from all available data until December 2005 with the index values computed from the data available until December 2006. Our analysis showed that revision volatility does not seem to be a major problem to the index. We also explored heteroskedast",55.0,https://link.springer.com/content/pdf/10.1007/s11146-007-9068-0.pdf93986850f9a65707081682a05c861afe1b350f27bdc,10.3390/ijgi11010057,"Multiscale Effects of Multimodal Public Facilities Accessibility on Housing Prices Based on MGWR: A Case Study of Wuhan, China",2022.0,ISPRS Int. J. Geo Inf.,Ling-Bo Liu; Hanchen Yu; Jie Zhao; Hao Wu; Zheng-Hong Peng; Ru Wang,"The layout of public service facilities and their accessibility are important factors affecting spatial justice. Previous studies have verified the positive influence of public facilities accessibility on house prices; however, the spatial scale of the impact of various public facilities accessibility on house prices is not yet clear. This study takes transportation analysis zone of Wuhan city as the spatial unit, measure the public facilities accessibility of schools, hospitals, green space, and public transit stations with four kinds of accessibility models such as the nearest distance, real time travel cost, kernel density, and two step floating catchment area (2SFCA), and explores the multiscale effect of public services accessibility on house prices with multiscale geographically weighted regression model. The results show that the differentiated scale effect not only exists among different public facility accessibilities, but also exists in different accessibility models of the same sort of facility. The article also suggests that different facilities should adopt its appropriate accessibility model. This study provides insights into spatial heterogeneity of urban public serv",55.0,https://www.mdpi.com/2220-9964/11/1/57/pdf?version=16454169209407e1237edb65235bfef25870fbb6044444f05f3db,10.1080/00167223.2020.1769492,Understanding the spatiality of short-term rentals in Spain: Airbnb and the intensification of the commodification of housing,2020.0,,A. Gutiérrez; A. Domènech,"ABSTRACT This article analyses the spatiality of the proliferation of short-term rentals in Spain. It was based on geolocalised data for all the Airbnb listings in the country. A multiscale analysis enabled us to identify the socio-economic, tourism market and housing stock variables that have had the greatest influence on the proliferation of short-term rental offers. The results obtained confirmed a pattern of concentration that validates our central hypothesis: the uneven distribution of Airbnb listings has a strong spatial correlation with the potential for generating new profits in the housing market. At national level, the urban areas with the highest concentration of Airbnb listings are those with the highest tourist demand. These are the largest cities, coastal tourist regions and archipelagos. At the city level, clusters of Airbnb concentrations are located in central areas where short-term rentals tend to be more expensive. They are also located in working-class neighbourhoods with lower housing prices with great potential for investors due to their proximity to tourist sites. These findings provide new evidence of how the so-called sharing economy is playing a central ro",55.0,9412abefce4c5ff51d8b92674d56e24b59fbc250a8c,10.1016/j.scs.2021.102815,Understanding the public's behavior in adopting green stormwater infrastructure,2021.0,Sustainable cities and society,J. Ureta; M. Motallebi; A. Scaroni; S. Lovelace; J. Ureta,"Abstract Green stormwater infrastructure (GSI) is promoted to sustainably manage stormwater in the United States. Aside from mitigating floods, it provides other ecosystem services such as improved water quality, scenic beauty, and an increase in property values of surrounding houses, among others. Because of the importance of community participation in the success of GSI, we investigated the factors affecting the household's intention to adopt GSI practices on their properties. We sent out an online survey to the coastal residents from eight coastal counties of South Carolina. The final samples included 1,031 residents. Using generalized ordered logit models (GOLM), we assessed the factors affecting their level of intention to adopt three common GSI practices— rain gardens, rooftop disconnection, and rain barrels. We also applied logit regression to identify the determinants of their intention to adopt one or more GSI practices. Household characteristics such as age, house ownership, property flooding history, and perception of flooding impacts and stormwater management were found to be significant in most of the models. On the other hand, only a few adoption barriers and ES becam",54.0,https://doi.org/10.1016/j.scs.2021.1028159425de9e8821ee86c8334e081845db441acc6908c65,10.4054/demres.2012.26.18,"Demography, foreclosure, and crime: Assessing spatial heterogeneity in contemporary models of neighborhood crime rates",2012.0,,Ashley N. Arnio; E. Baumer,"The present research evaluates the possibility of spatial heterogeneity in the effects on neighborhood crime rates of both traditional demographic indicators—immigrant concentration, racial composition, socioeconomic disadvantage, and residential instability—and a contemporary aspect of housing transition—foreclosure rates—that has garnered significant attention in recent scholarship. Geographically weighted regression results indicate significant variation across Chicago census tracts in the estimates of logged percent black, immigrant context, and foreclosure for both robbery and burglary rates. The observed effects of socioeconomic disadvantage on robbery rates and residential stability on burglary rates also are found to vary across local neighborhood clusters in Chicago. Visual inspection of these effects illuminates the importance of supplementing current approaches by “thinking locally” when developing theoretical explanations and empirical models of how demographic context shapes crime rates.",54.0,https://www.demographic-research.org/volumes/vol26/18/26-18.pdf9438b9278471358ff729ac08010b9bafea03f36c01e,10.1023/b:real.0000035311.59920.74,House Prices and the Structure of Local Government: An Application of Spatial Statistics,2004.0,,David M. Brasington,,54.0,https://autopapers.ssrn.com/sol3/papers.cfm?abstract_id=4887879449dee5cc3800299f7ddccac6e92a83eef1058fd76,10.1016/0094-1190(91)90047-b,Housing price functions and ownership capitalization rates,1991.0,,P. Linneman; R. Voith,,54.0,945f81bc1054404b8eeb2451a9734de6bea4c12025e,10.1016/j.jclepro.2018.12.208,"A clean energy assessment of early adopters in electric vehicle and solar photovoltaic technology: Geospatial, political and socio-demographic trends in New York",2019.0,Journal of Cleaner Production,K. Araújo; Janice L. Boucher; Omkar Aphale,"Abstract We studied electric vehicles and solar photovoltaic technology diffusion in the State of New York to shed light on the attributes of early adopters of clean energy. Using geospatial, regression, and cluster analyses of zip code level and county indicators, we analyzed trends with locational, political and socio-demographic profiles to identify areas of convergence and divergence in adoption patterns. In line with elements of the literature, we confirmed the importance of income and median home value for a relatively under-studied region in early-staged, electric vehicle and solar photovoltaic technology adoption. We also found that political orientation and age tendencies are more nuanced and less predictive. However, we noted key, adoptive tendencies among those aged 30-44 and above 59 for solar photovoltaics. Moreover, southeastern counties near New York City, particularly on Long Island, are identified as critical niches in the early-staged diffusion of clean energy. This study highlights observed tendencies from diverse methodological approaches in clean technology diffusion, providing a basis for a fuller set of technology and policy studies for New York or similarly-",53.0,946ed97bfd2b48f7586809493df9f0a9bc9831e6602,10.2139/ssrn.800505,On Some Fiscal Effects on Mortgage Debt Growth in the EU,2005.0,Social Science Research Network,Guido Wolswijk,"This paper analyses some fiscal aspects of mortgage debt in the EU. It first describes the main fiscal instruments that governments use to affect mortgage-financed home-ownership. In the empirical part, real mortgage debt growth is analysed for 15 EU countries using pooled regressions. Fiscal effects are included via after-tax interest rates. Other factors shown to be relevant for mortgage debt growth are house prices, financial deregulation, and stock markets while the effects of household income and inflation are less evident. Finally, the role of structural fiscal measures in reducing housing market volatility is highlighted. JEL Classification: E51, E62, G21, H31, R21",53.0,https://doi.org/10.2139/ssrn.800505947dc2ece59e489c5f26399fb818ccb118e52c00937,10.2139/ssrn.1333646,Determinants of House Prices in Nine Asia-Pacific Economies,2012.0,,Eloisa T. Glindro; Tientip Subhanij; Jessica Szeto; Hai-Bin Zhu,,53.0,https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=1333646948d1bd80466d984d465e1c21776f00f4af4c4f4a7d,10.1016/j.regsciurbeco.2017.12.008,"Fading premiums: The effect of light rail on residential property values in Minneapolis, Minnesota",2018.0,,Clemens A. Pilgram; Sarah E. West,,53.0,949ecfbd4f221f2607f0dc44fd822acca3a0aad5db5,10.1093/jue/juw006,What’s scale got to do with it? Models for urban tree canopy,2016.0,,D. Locke; Shawn M. Landry; J. Grove; R. R. Chowdhury,"The uneven provisioning of ecosystem services has important policy implications; yet the spatial heterogeneity of tree canopy remains understudied. Private residential lands are important to the future of Philadelphia’s urban forest because a majority of the existing and possible tree canopy is located on residential land uses. This article examines the spatial distribution of tree canopy in Philadelphia, PA and its social correlates. How are existing tree canopy and opportunities for additional tree canopy distributed across the city of Philadelphia and with respect to three explanations: (i) population density, (ii) the social stratification luxury effect, and 3) lifestyle characteristics of residents? This study used spatial autoregressive regression (SAR), geographically weighted regression (GWR) and multilevel modeling (MLM) to evaluate population density, social stratification luxury effect, and lifestyle characteristics as explanations of the spatial distribution of existing and possible tree canopy, and simultaneously evaluate the efficacy of different statistical analysis techniques. To control for spatial autocorrelation, SAR models were estimated, GWR models were fit to ",52.0,https://doi.org/10.1093/jue/juw00695092c6963c3246805bb84132f8128c03895cd61f26,10.1080/02673037.2018.1447093,Houses without people and people without houses: a cultural and institutional exploration of an Italian paradox,2019.0,,Martina Gentili; J. Hoekstra,"Abstract According to basic economics, when vacancy rates rise, house prices should decrease and vice versa, responding to supply and demand mechanisms. However, previous studies have observed that, before the economic crisis, this was not the case in Spain and Malta. It has been questioned whether this paradox is a Mediterranean phenomenon or simply the result of isolated cases of malfunctioning housing market. This paper contributes to this discussion by reviewing the pre-crisis housing market of a third case study: Italy. A Mediterranean housing system perspective is used to analyse the paradox, and methodological issues regarding the definition and measurement of vacancy are addressed. Moreover, the paper explores the consequences of the high Italian vacancy rate within a context of housing shortages and affordability problems. We argue that a better understanding of the characteristics and implications of vacancy is necessary in order to be able to implement sustainable housing and planning policies.",52.0,https://www.tandfonline.com/doi/pdf/10.1080/02673037.2018.1447093?needAccess=true95182b1a7bbbca62c379a144ada2c95b782c6d6aa48,10.5753/eniac.2019.9300,Housing Prices Prediction with a Deep Learning and Random Forest Ensemble,2019.0,Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC 2019),Bruno Klaus de Aquino Afonso; L. Melo; Willian Oliveira; S. Sousa; L. Berton,"The development of a housing prices prediction model can assist a house seller or a real estate agent to make better-informed decisions based on house price valuation. Only a few works report the use of machine learning (ML) algorithms to predict the values of properties in Brazil. This study analyzes a dataset composed of 12,223,582 housing advertisements, collected from Brazilian websites from 2015 to 2018. Each instance comprises twenty-four features of five different data types: integer, date, string, float, and image. To predict the property prices, we ensemble two different ML architectures, based on Random Forest (RF) and Recurrent Neural Networks (RNN). This study demonstrates that enriching the dataset and combining different ML approaches can be a better alternative for prediction of housing prices in Brazil.",52.0,https://sol.sbc.org.br/index.php/eniac/article/download/9300/92029523c4c92aaf0ec1b8ccdb97d7fa27a50bde3d403fc,10.1111/1468-2427.12873,"The Limits of Homeownership: Racial Capitalism, Black Wealth, and the Appreciation Gap in Atlanta",2020.0,,Scott N. Markley; Taylor J. Hafley; Coleman A. Allums; Steven R. Holloway; Hee Cheol Chung,"Abstract In the wake of the 2007?08 housing crash, the Black?white wealth gap reached a staggering 20 to 1. Since then, a growing chorus of influential voices has proposed measures to increase the Black homeownership rate as a means to narrow the gap. Others, however, have argued that the uneven racial geography of home price appreciation necessarily restricts the degree to which Black households, in the aggregate, can build wealth via homeownership. We aim to contribute to these debates by theorizing a racial appreciation gap as a central feature of urban housing markets under racial capitalism, and analyzing how neighborhood racial and income characteristics have structured home price appreciation from before the height of the housing boom (2000?03) to its post-crisis recovery (2014?16). Focusing on the two counties that encompass Atlanta, Georgia, USA?an area famous for Black prosperity?we find that a neighborhood's racial composition has a more salient impact on home price change than its income. Results indicate that when a place is marked as Black, this may itself inhibit home price appreciation, suggesting that an enduring racial appreciation gap may limit the potential for ",52.0,953eb3d446d75c0272b0527038e815e4665036e338f,10.1080/13658816.2021.1912348,Multiscale geographically and temporally weighted regression with a unilateral temporal weighting scheme and its application in the analysis of spatiotemporal characteristics of house prices in Beijing,2021.0,International Journal of Geographical Information Science,Zhi Zhang; Jing Li; T. Fung; Hua-Yi Yu; Chang-Lin Mei; Y. Leung; Yu Zhou,"ABSTRACT Geographically and temporally weighted regression (GTWR) has been demonstrated as an effective tool for exploring spatiotemporal data under spatial and temporal heterogeneity. Exploiting the advantages of the two most popular GTWR methods, we propose an alternative GTWR with a good balance between complexity and interpretability via a unilateral temporal weighting scheme called unilateral GTWR (UGTWR). When compared to the other two popular GTWR methods, the simulation experiment shows that UGTWR has comparable estimation accuracy and model fit, but it is more efficient. Furthermore, we propose its multiscale extension, coined multiscale UGTWR (MUGTWR), to characterize the spatiotemporal dynamic regression relationships at multiple scales. The proposed MUGTWR was applied to the analysis of house prices in the period of 2014–2018 in Beijing as a case study. Our analysis reveals that MUGTWR can effectively capture different levels of spatiotemporal heterogeneity in selected factors affecting house prices at different scales. Therefore, this study is useful for the formulation of housing policy in which the spatiotemporal dynamics of house prices with respect to specific fact",52.0,954b7506479e2c541d11b93d743a0bb14b9ec3d972e,10.5089/9781455200634.001.a001,House Price Determinants in Selected Countries of the Former Soviet Union,2010.0,Social Science Research Network,V. Stepanyan; T. Poghosyan; Aidyn Bibolov,"This paper analyses the recent boom-bust cycle in the housing markets of selected Former Soviet Union (FSU) countries. The analysis is based on a newly constructed database on house prices in the FSU countries. Our estimations suggest that house price developments can largely be explained by the dynamics of fundamentals, such as GDP, remittances, and external financing. Overall, we find that deviations of house prices from their fundamentals have not been pronounced, suggesting that house price bubbles have not been formed in the FSU countries.",52.0,https://www.elibrary.imf.org/downloadpdf/journals/001/2010/104/001.2010.issue-104-en.xml955aa3a5dad2f154b6feedfacd5da79dbc5de126334,10.1371/journal.pone.0193225,"Relationship between race and community water and sewer service in North Carolina, USA",2018.0,PLoS ONE,H. Leker; Jacqueline MacDonald Gibson,"Previous evidence has identified potential racial disparities in access to community water and sewer service in peri-urban areas adjacent to North Carolina municipalities. We performed the first quantitative, multi-county analysis of these disparities. Using publicly available data, we identified areas bordering municipalities and lacking community water and/or sewer service in 75 North Carolina counties. Logistic regression was performed to evaluate the relationship between race and access to service in peri-urban areas, controlling for population density, median home value, urban status, and percent white in the adjacent municipality. In the peri-urban areas analyzed, 67% of the population lacked community sewer service, and 33% lacked community water service. In areas other than those with no black residents, odds of having community water service (p<0.01) or at least one of the two services (p<0.05) were highest for census blocks with a small proportion of black residents and lowest in 100% black census blocks, though this trend did not hold for access to community sewer service alone. For example, odds of community water service were 85% higher in areas that were greater than ",51.0,https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0193225&type=printable95698bcbf414a6463aa7e59b7ba24a7a2078696453f,10.1016/j.jtrangeo.2019.102617,"Understanding the role of urban form in explaining transportation and recreational walking among children in a logistic GWR model: A spatial analysis in Istanbul, Turkey",2020.0,,Ayse Ozbil Torun; Kenan Göçer; D. Yesiltepe; Görsev Argın,"This study aims to examine associations between urban form factors generally, and street network configuration in particular, and walking for different purposes among children in Istanbul, Turkey. Parents of randomly selected students (ages 12–16) at 20 middle schools (N = 917) completed questionnaires about their socio-economic characteristics and the frequency of their children's walking for recreational and for transportation purposes in their neighbourhood during a typical day. The environment around 400 m of participants' homes was evaluated through GIS-based parcel-level land-use data and segment-based street connectivity measures calculated using space syntax techniques. Logistic geographically weighted regression models were estimated to measure the desired associations while adjusting for socio-economic characteristics. Results demonstrate a marginal association between urban form measures and walking behaviour but only in certain peripheral parts of the city. More importantly, increased directional accessibility, which identifies the extent to which more street length is accessible within few direction changes, is associated with higher odds of recreational walking in par",51.0,http://nrl.northumbria.ac.uk/id/eprint/41748/1/Ozbil_accepted.pdf95794e8429bbb04afd13430240262e81ff09ecccb38,10.3390/ijerph19105798,"Assessing Inequity in Green Space Exposure toward a “15-Minute City” in Zhengzhou, China: Using Deep Learning and Urban Big Data",2022.0,International Journal of Environmental Research and Public Health,Jing-Jing Luo; Shi-Yan Zhai; Genxin Song; Xin-Xin He; Hong-Quan Song; Jing Chen; Huan Liu; Yu-Ke Feng,"Green space exposure is considered an important aspect of a livable environment and human well-being. It is often regarded as an indicator of social justice. However, due to the difficulties in obtaining green space exposure data from a ground-based view, an effective evaluation of the green space exposure inequity at the community level remains challenging. In this study, we presented a green space exposure inequity assessment framework, integrating the Green View Index (GVI), deep learning, spatial statistical analysis methods, and urban rental price big data to analyze green space exposure inequity at the community level toward a “15-minute city” in Zhengzhou, China. The results showed that green space exposure inequality is evident among residential communities. The areas in the old city were with relatively high GVI and the new city districts were with relatively low GVI. Moreover, a spatially uneven association was observed between the degree of green space exposure and housing prices. Especially, the wealthier communities in the new city districts benefit from low green space, compared to disadvantaged communities in the old city. The findings provide valuable insights for p",51.0,https://www.mdpi.com/1660-4601/19/10/5798/pdf?version=1652855946958d4979b0847198cc7b7900e5a0c165a6d490c4d7b,10.2139/ssrn.3867764,Does Building New Housing Cause Displacement?: The Supply and Demand Effects of Construction in San Francisco,2021.0,Social Science Research Network,K. Pennington,"San Francisco is gentrifying rapidly as an influx of high-income newcomers drives up housing prices and displaces lower-income incumbent residents. In theory, increasing the supply of housing should mitigate increases in rents. However, new construction could also increase demand for nearby housing by improving neighborhood quality. The net impact on nearby rents depends on the relative sizes of these supply and demand effects. This paper identifies the causal impact of new construction on nearby rents, displacement, and gentrification by exploiting random variation in the location of new construction induced by serious building fires. I combine parcel-level data on fires and new construction with an original dataset of historic Craigslist rents and panel data on individual migration histories to test the impact of proximity to new construction. I find that rents fall by 2% for parcels within 100m of new construction. Renters’ risk of being displaced to a lower-income neighborhood falls by 17%. Both effects decay linearly to zero within 1.5km. Next, I show evidence of a hyperlocal demand effect, with building renovations and business turnover spiking and then returning to zero afte",51.0,9599a50e24dd292bac7b184d5a0654bb5efeed6506b,10.22214/ijraset.2023.49031,House Prices Advanced Regression Techniques,2023.0,International Journal for Research in Applied Science and Engineering Technology,G. Kumar; K. Rayudu; Gutta Ajay Kumar; T. Satish,"Abstract: The real estate industry is seeing an increase in the use of data mining. The capacity of data mining to extricate helpful data from crude information makes it especially helpful for anticipating home estimations, essential housing characteristics, and a great many different elements. Homeowners and the real estate industry frequently feel anxious about price swings, according to research. The most useful models and important criteria for predicting home values are examined in a literature review. The adoption of Random Forest and XGBoost as the most effective models in comparison to others was confirmed by this study's findings. Additionally, our data suggest that locational and structural characteristics are significant forecasting variables for housing values. In order to identify the most effective machine learning model for conducting a study in this field and the most significant factors that influence home prices, this study will be very helpful, particularly to housing developers and academics.",51.0,https://doi.org/10.22214/ijraset.2023.49031960ea051a846b87b42df135baa5991acc87446ff742,10.1086/701189,The Distributional Effects of Building Energy Codes,2019.0,Journal of the Association of Environmental and Resource Economists,Chris Bruegge; T. Deryugina; Erica Myers,"We evaluate the distributional consequences of building energy codes for home characteristics, energy use, and home value. We exploit spatial variation in California’s code strictness created by building climate zones, combined with information on over 350,000 homes located within 3 kilometers of climate zone borders. Our key findings are that stricter codes create a nontrivial reduction in homes’ square footage and the number of bedrooms at the lower end of the income distribution. On a per-dwelling basis, we observe energy use reductions only in the second lowest income quintile, driven by decreases in square footage. Energy use per square foot actually increases in the bottom quintile. Home values of lower-income households fall, while those of high-income households rise, suggesting that building energy codes result in more undesirable distortions for lower-income households.",51.0,https://doi.org/10.3386/w24211961493645a0fe1cde4bb62cfe299ca0eb4e8d73913f,10.1016/j.neucom.2020.05.013,Multi-source urban data fusion for property value assessment: A case study in Philadelphia,2020.0,Neurocomputing,Junchi Bin; Bryan Gardiner; Eric Li; Zheng Liu,"Abstract The property value assessment in the real estate market still remains as a challenges due to incomplete and insufficient information, as well as the lack of efficient algorithms. House attributes, such as size and number of bedrooms, are currently being employed to perform the estimation by professional appraisers and researchers. Numerous algorithms have been proposed; however, a better assessment performance is still expected by the market. Nowadays, there are more available relevant data from various sources in urban areas, which have a potential impact on the house value. In this paper, we propose to fuse urban data, i.e., metadata and imagery data, with house attributes to unveil the market value of the property in Philadelphia. Specifically, two deep neural networks, i.e., metadata fusion network and image appraiser, are proposed to extract the representations, i.e., expected levels, from metadata and street-view images, respectively. A boosted regression tree (BRT) is adapted to estimate the market values of houses with the fused metadata and expected levels. The experimental results with the data collected from the city of Philadelphia demonstrate the effectiveness",51.0,962b3f95d2e8853587bd9a49c78a82e9f7633ee5f43,10.1016/j.landusepol.2020.104843,Meta-analysis of the relationship between high quality basic education resources and housing prices,2020.0,Land Use Policy,Jingke Zhang; Huan Li; Jin-Mann S Lin; Wei Zheng; Heng Li; Zhi-Gang Chen,"Abstract There are many studies examining the school district housing premium, and conclusions regarding the premium are quite diverse. Therefore, it is necessary to conduct an integrated analysis of the relevant literatures to determine the factors causing the premium, and to explore logically the relationship between housing prices and high quality basic education resources. Based on this goal, a theoretical framework is designed to analyze the incremental effect of high quality basic education resources on housing prices. Using the meta-analysis method, this study discusses the problem of the Chinese school district housing premium based on three aspects of education, namely location, stage, and characteristics. The study finds that education resources in the compulsory education stage have a positive impact (5.5 %) on housing prices. Compared with distance and quantity, the quality of schools has the highest premium rate, which is 7.2 %. The premium rate of education resources in non-first-tier cities (5.8 %) is higher than that in first-tier cities (2.8 %). We conclude that the connection between compulsory education and household registration is the key driving force behind t",51.0,9634a0acdf50829f97ff01b28637540fc0644f80f05,10.1155/2021/7678931,Housing Price Prediction Based on Multiple Linear Regression,2021.0,Scientific Programming,Qing-Qi Zhang,"In this paper, the author first analyzes the major factors affecting housing prices with Spearman correlation coefficient, selects significant factors influencing general housing prices, and conducts a combined analysis algorithm. Then, the author establishes a multiple linear regression model for housing price prediction and applies the data set of real estate prices in Boston to test the method. Through the data analysis and test in this paper, it can be summarized that the multiple linear regression model can effectively predict and analyze the housing price to some extent, while the algorithm can still be improved through more advanced machine learning methods.",51.0,https://downloads.hindawi.com/journals/sp/2021/7678931.pdf964d9eeeda23aaf8076d68a02f0ccbe888af0cbd6d6,10.1057/ces.2013.3,House Price Determinants: Fundamentals and Underlying Factors,2013.0,Comparative Economic Studies,Bernardina Algieri,,51.0,9659c3ea6cb26bd264ba7b2bdfebc7b4f2d654b2e3c,10.1111/jori.12041,THE CAPITALIZATION OF INSURANCE PREMIUMS IN HOUSE PRICES,2015.0,,Charles M. Nyce; Randy E. Dumm; G. Sirmans; Greg T. Smersh,,51.0,966ff44f88f316b03c89fe84d3f2b8a8239efdfbc23,10.1016/j.envres.2015.09.005,Exposures to Walkability and Particulate Air Pollution in a Nationwide Cohort of Women,2015.0,Environmental Research,Peter James; J. Hart; F. Laden,"Background Features of neighborhoods associated with walkability (i.e., connectivity, accessibility, and density) may also be correlated with levels of ambient air pollution, which would attenuate the health benefits of walkability. Objectives We examined the relationship between neighborhood walkability and ambient air pollution in a cross-sectional analysis of a cohort study spanning the entire United States using residence-level exposure assessment for ambient air pollution and the built environment. Methods Using data from the Nurses’ Health Study, we used linear regression to estimate the association between a neighborhood walkability index, combining neighborhood intersection count, business count, and population density (defined from Census data, infoUSA business data, and StreetMap USA data), and air pollution, defined from a GIS-based spatiotemporal PM2.5 model. Results After adjustment for Census tract median income, median home value, and percent with no high school education, the highest tertile of walkability index, intersection count, business count, and population density was associated with a with 1.58 (95% CI 1.54, 1.62), 1.20 (95% CI 1.16, 1.24), 1.31 (95% CI 1.27",50.0,https://europepmc.org/articles/pmc4627661?pdf=render967cd69590227b7b60c7294847cb3856e4ac385fdfd,10.3390/stats4040051,The One Standard Error Rule for Model Selection: Does It Work?,2021.0,Stats,Yuchen Chen; Yu-Hong Yang,"Previous research provided a lot of discussion on the selection of regularization parameters when it comes to the application of regularization methods for high-dimensional regression. The popular “One Standard Error Rule” (1se rule) used with cross validation (CV) is to select the most parsimonious model whose prediction error is not much worse than the minimum CV error. This paper examines the validity of the 1se rule from a theoretical angle and also studies its estimation accuracy and performances in applications of regression estimation and variable selection, particularly for Lasso in a regression framework. Our theoretical result shows that when a regression procedure produces the regression estimator converging relatively fast to the true regression function, the standard error estimation formula in the 1se rule is justified asymptotically. The numerical results show the following: 1. the 1se rule in general does not necessarily provide a good estimation for the intended standard deviation of the cross validation error. The estimation bias can be 50–100% upwards or downwards in various situations; 2. the results tend to support that 1se rule usually outperforms the regular ",50.0,https://www.mdpi.com/2571-905X/4/4/51/pdf?version=163611291796845417204479a5850c2510bc9e5015067a303505e,10.1093/jrsssb/qkad051,Autoregressive optimal transport models,2021.0,Journal of The Royal Statistical Society Series B-statistical Methodology,Changbo Zhu; Hans-Georg Müller,"Abstract Series of univariate distributions indexed by equally spaced time points are ubiquitous in applications and their analysis constitutes one of the challenges of the emerging field of distributional data analysis. To quantify such distributional time series, we propose a class of intrinsic autoregressive models that operate in the space of optimal transport maps. The autoregressive transport models that we introduce here are based on regressing optimal transport maps on each other, where predictors can be transport maps from an overall barycenter to a current distribution or transport maps between past consecutive distributions of the distributional time series. Autoregressive transport models and their associated distributional regression models specify the link between predictor and response transport maps by moving along geodesics in Wasserstein space. These models emerge as natural extensions of the classical autoregressive models in Euclidean space. Unique stationary solutions of autoregressive transport models are shown to exist under a geometric moment contraction condition of Wu & Shao [(2004) Limit theorems for iterated random functions. Journal of Applied Probabili",50.0,https://academic.oup.com/jrsssb/advance-article-pdf/doi/10.1093/jrsssb/qkad051/50496188/qkad051.pdf96970b8597ace5c2ed75b53775dbf05e8993f4c0ae8,10.5539/ass.v11n24p26,Exploring the Elements of Housing Price in Malaysia,2015.0,,A. Osmadi; E. M. Kamal; Hasnanywati Hassan; Hamizah Abdul Fattah,"This informative study explores the elements of housing price in Malaysia and found the price is affected by many factors. This study of great practical significance has shown that house prices are determined by the demand for attributes, not only of the dwelling units themselves, but also of the region in which the units are located. There are many structural, neighborhood and locational attributes that could have brought impacts on house prices (Chin, Chau, & Ng, 2004). Structural characteristics, location-specific factors, and neighbourhood characteristics may define various sub-markets. Sub-markets may be defined by structure type (e.g. single-family detached, row house, town home, and condominium), by structural characteristics (property age housing consumers may have strong preferences for newly constructed properties or for historic properties), or by neighbourhood characteristics (e.g., public education and public safety). Results show that the housing price in Malaysia evidently depends on population, demand and supply, location, physical characteristic, accessibility, developer, cost of material and income. It is also influenced by neighbourhood factors as people nowadays ",50.0,https://doi.org/10.5539/ass.v11n24p26970bae9b8ab3715be53c7aa888a38dcc8386c6c7bd0,10.3390/land2010037,"Mapping Urbanization Dynamics in Major Cities of Colombia, Ecuador, Perú, and Bolivia Using Night-Time Satellite Imagery",2013.0,,Isabel K. Parés-Ramos; Nora L. Álvarez-Berríos; T. Aide,"By 2050, 90% of the population in Latin America will live in cities, but there is a lack of up-to-date spatial information about the urban extent and patterns of urbanization in cities of this region. In this study, we analyzed population growth, urban density and urbanization dynamics between 1992 and 2009 in the major cities of Bolivia, Colombia, Ecuador and Peru using Google Earth and DMSP/OLS night-time lights imagery. We used Google Earth to map the urban extent, and time series of night-time lights to analyze spatial patterns of urban development. The dominant urban development patterns were: high-density compact in Bogota, Cali, Guayaquil, and Medellin; high-density expansive growth in La Paz/El Alto; low-density expansive in Quito and Santa Cruz; and a mix of high-density compact and suburban growth in Lima. Urban growth occurred largely along the periphery of cities, influenced by the local landscape and by demographic and socioeconomic factors such as immigration and housing prices. Urban density in Colombia (>20,000 per/km 2 ) was among the highest in the world. Future growth in the region will probably be characterized by densification and slow urban expansion. This stu",50.0,https://www.mdpi.com/2073-445X/2/1/37/pdf?version=136362188597127ff1f321f9af0c4cde01a0270b5cbf6a46f22e4,10.3386/w29909,Housing Market Expectations,2022.0,Social Science Research Network,Theresa Kuchler; Monika Piazzesi; Johannes Stroebel,"We review the recent literature on the determinants and effects of housing market expectations. We begin by providing an overview of existing surveys that elicit housing market expectations, and discuss how those surveys may be expanded in the future. We then document a number of facts about time-series and cross-sectional patterns of housing market expectations in these survey data, before summarizing research that has studied how individuals form these expectations. Housing market expectations are strongly influenced by recently observed house price changes, by personally or locally observed house price changes, by house price changes observed in a person’s social network, and by current home ownership status. Similarly, experienced house price volatility affects expectations uncertainty. We also summarize recent work that documents how differences in housing market expectations translate into differences in individuals’ housing market behaviors, including their home purchasing and mortgage financing decisions. Finally, we highlight research on how expectations affect aggregate outcomes in the housing market.",50.0,https://www.econstor.eu/bitstream/10419/260795/1/cesifo1_wp9665.pdf97274da7d0584f54f7463f565a726cbfdddc677be74,10.1109/ssci44817.2019.9002790,Deep Learning with XGBoost for Real Estate Appraisal,2019.0,IEEE Symposium Series on Computational Intelligence,Yun Zhao; Girija Chetty; D. Tran,"Real estate appraisal is an important tool for evaluating property values when purchasing, selling, insuring, lending or taxing on residency properties. The traditional way to do real estate appraisal is to analyse recent sales data with basic information, such as bedrooms, bathrooms, land-size, and suburb to estimate house price prediction by comparing and selecting similar properties to the property that is being evaluated. Real estate agents are widely using this method for their clients to help them determine a price to list when selling a home or a price to offer when buying a home. However, the traditional method is very subjective and depends heavily on the experience and knowledge of real estate agents and two different agents might come up with different estimate prices. Today, machine learning and deep learning techniques provide an objective, advanced and robust option, making the joint analysis of tabular data combined with visual content possible. We are interested in estimating the real estate prices like real estate agents. In this paper, we examine to use deep learning combining with extreme Gradient Boosting (XGBoost) for real estate appraisal, by analysing histori",50.0,973d49940e654798b6c3add5a41a2b26efe2e0bd946,10.1214/07-ba205,Geographically Assisted Elicitation of Expert Opinion for Regression Models,2007.0,,R. Denham; K. Mengersen,"One of the perceived strengths of Bayesian modelling is the ability to include prior information. Although objective or noninformative priors might be preferred in some situations, in many other applications the Bayesian framework offers a real opportunity to formally combine data with information available from experts. The question addressed in this paper is how to elicit this information in a form suitable for prior modelling. Particular attention is paid to geographic data for which maps might be used to assist in the elicitation. Two case studies are used to illustrate the methodology: estimation of city house prices and prediction of presence of a rare species.",50.0,https://projecteuclid.org/journals/bayesian-analysis/volume-2/issue-1/Geographically-assisted-elicitation-of-expert-opinion-for-regression-models/10.1214/07-BA205.pdf974bf2ce0873edcdea36b23810f61082e5e36869935,10.1108/jfm-02-2016-0003,Critical determinants of residential property value: professionals’ perspective,2016.0,,R. Abidoye; A. Chan,,50.0,http://ira.lib.polyu.edu.hk/bitstream/10397/103506/1/Abidoye_Critical_Determinants_Residential.pdf975e0dd2db3bcc3623520a36b368fc2a69760ef50e3,10.1186/s12939-019-1114-z,"Homeownership status and risk of food insecurity: examining the role of housing debt, housing expenditure and housing asset using a cross-sectional population-based survey of Canadian households",2020.0,International Journal for Equity in Health,A. Fafard St-Germain; V. Tarasuk,"BackgroundHousehold food insecurity is a potent marker of material deprivation with adverse health consequences. Studies have repeatedly found a strong, independent relationship between owning a home and lower vulnerability to food insecurity in Canada and elsewhere, but the reasons for this relationship are poorly understood. We aimed to examine the influence of housing asset, housing debt and housing expenditure on the relationship between homeownership status and food insecurity in Canada.MethodsCross-sectional data on food insecurity, housing tenure and expenditures, home value, income and sociodemographic characteristics were derived from the 2010 Survey of Household Spending, a population-based survey. Multivariable logistic regression models were conducted to estimate odds ratios of food insecurity among households of all incomes (n = 10,815) and those with lower incomes (n = 5547).ResultsFood insecurity prevalence was highest among market renters (28.5%), followed by homeowners with a mortgage (11.6%) and mortgage-free homeowners (4.3%). Homeowners with a mortgage (OR: 0.51, 95% CI: 0.39–0.68) and those without a mortgage (OR: 0.23, 95% CI: 0.16–0.35) had substantially lowe",49.0,https://equityhealthj.biomedcentral.com/track/pdf/10.1186/s12939-019-1114-z976922f5555789cdf49df4166cffea465eb648e6690,10.1016/j.envres.2022.112982,Exploring spatial heterogeneity and environmental injustices in exposure to flood hazards using geographically weighted regression.,2022.0,Environmental Research,Liton Chakraborty; H. Rus; D. Henstra; J. Thistlethwaite; A. Minano; D. Scott,"This study explores flood-related environmental injustices by deconstructing racial, ethnic, and socio-demographic disparities and spatial heterogeneity in the areal extent of fluvial, pluvial, and coastal flooding across Canada. The study integrates Canada's 100-year Flood Map of JBA Risk Management with the 2016 national census-based socioeconomic data to investigate whether traditionally recognized vulnerable groups and communities are exposed inequitably to inland (e.g., fluvial and pluvial) and coastal flood hazards. Social vulnerability was represented by neighbourhood-level socioeconomic deprivation, including economic insecurity and instability indices. Statistical analyses include bivariate correlation and a series of non-spatial and spatial regression techniques, including ordinary least squares, binary logistic regression, and simultaneous autoregressive models. The study emphasizes the quest for the most appropriate methodological framework to analyze flood-related socioeconomic inequities in Canada. Strong evidence of spatial effects has motivated the study to test for the spatial heterogeneity of covariates by employing geographically weighted regression (GWR) on cont",49.0,9772a44bb043dbd9f38f90dcc1724ac4fbd811467df,10.1108/ijhma-11-2018-0095,Predicting property price index using artificial intelligence techniques,2019.0,International Journal of Housing Markets and Analysis,R. Abidoye; A. Chan; Funmilayo Adenike Abidoye; O. Oshodi,"978Purpose979Booms and bubbles are inevitable in the real estate industry. Loss of profits, bankruptcy and economic slowdown are indicators of the adverse effects of fluctuations in property prices. Models providing a reliable forecast of property prices are vital for mitigating the effects of these variations. Hence, this study aims to investigate the use of artificial intelligence (AI) for the prediction of property price index (PPI).980981982Design/methodology/approach983Information on the variables that influence property prices was collected from reliable sources in Hong Kong. The data were fitted to an autoregressive integrated moving average (ARIMA), artificial neural network (ANN) and support vector machine (SVM) models. Subsequently, the developed models were used to generate out-of-sample predictions of property prices.984985986Findings987Based on the prediction evaluation metrics, it was revealed that the ANN model outperformed the SVM and ARIMA models. It was also found that interest rate, unemployment rate and household size are the three most significant variables that could influence the prices of properties in the study area.988989990Practical implications991The findings of this study provide ",49.0,http://ira.lib.polyu.edu.hk/bitstream/10397/103286/1/Chan_Predicting_Property_Price.pdf992b4ede98e9a5ed90f1aec4bfb2250df2d80ad6f62,10.1016/j.jimonfin.2017.11.009,Macroprudential policy and household wealth inequality,2017.0,Journal of International Money and Finance,J. Carpantier; J. Olivera; P. Van Kerm,"Macroprudential policies, such as caps on loan-to-value (LTV) ratios, have become part of the policy paradigm in emerging markets and advanced countries alike. Given that housing is the most important asset in household portfolios, relaxing or tightening access to mortgages may affect the distribution of household wealth in the country. In a stylised model we show that the final level of wealth inequality depends on the size of the LTV ratio, housing prices, credit cost and the strength of a bequest motive; ultimately with no unequivocal effect of LTV ratios on wealth inequality. These trade-offs are illustrated with estimations of ""Gini Recentered Influence Function"" regressions on household survey data from 12 Eurozone countries that participated in the first wave of the Household Finance and Consumption Survey (HFCS). The results show that, among the households with active mortgages, high LTV ratios at the time of acquisition are related to high contributions to wealth inequality today, while house price increases are negatively related to inequality contributions. A proxy for the strength of bequest motives tends to be negatively related with wealth inequality, but credit cost ",49.0,https://orbilu.uni.lu/bitstream/10993/35055/1/macroprudential-policy-and-household-wealth-inequality.pdf99328f9e7960bb44faf3b17e4b3d979d4c04042231f,10.1080/00343404.2015.1135239,Amenities and the attraction of Dutch cities,2017.0,,H. Garretsen; G. Marlet,"ABSTRACT Amenities and the attraction of Dutch cities. Regional Studies. Research on the relevance of amenities for urban wages, jobs or housing prices has mainly focused on the case of US cities. In many (European) countries, the labour and housing markets function, however, rather differently than in the case of the United States. As a result, amenities may affect urban labour or housing markets differently. In addition, in European countries the proximity of cities is such that spatial interdependencies between cities have to be taken into account as well. By using a very rich dataset, this paper analyses the relationship between urban amenities, agglomeration and housing prices for the case of a highly urbanized European country, the Netherlands. It finds that Dutch cities that combine a favourable job location with a variety of urban amenities have significantly higher housing prices. Relatively safe cities, offering a variety of history and cultural events, as well as good restaurants, also have significantly higher housing prices.",49.0,https://figshare.com/articles/journal_contribution/Amenities_and_the_attraction_of_Dutch_cities/3692052994d239ad5e9d60f4d43b8a5f3f85ce9e9d5c0cc1e6,10.1016/j.jhtm.2020.08.015,"Drivers of Airbnb prices according to property/room type, season and location: A regression approach",2020.0,,A. Voltes-Dorta; A. J. Sánchez-Medina,"Abstract While past studies on Airbnb pricing highlight the importance of room features, host characteristics and location factors, little has been investigated about whether these factors are the same across different property/room types, locations and seasons. To fill that gap, this paper presents a study about the drivers of Airbnb prices in Bristol using ordinary least squares (OLS) and geographically-weighted regression (GWR) methods. The estimated models exhibit sharply different levels of goodness-of-fit, suggesting that the prices of different room types might not be explained by the same set of price factors. The results also uncover statistically significant differences between the price determinants of apartments and house listings and reveal spatial patterns in the price effects. These findings have implications for price setting and the assessment of competition. Future studies should account for potential differences across property/room types, as well as to consider the spatial variability of the estimated coefficients.",49.0,https://www.sciencedirect.com/science/article/pii/S1447677020302023995d3f5d2e946fa2e04afd103e43bd4ac3506bc1def,10.1016/j.jempfin.2021.10.003,Housing market spillovers through the lens of transaction volume: A new spillover index approach,2021.0,Journal of Empirical Finance,Jian Yang; Menghua Tong; Zi-Liang Yu,"Abstract Proposing and applying a new spillover index approach based on data-determined structural vector autoregression to measure connectedness, we examine the daily housing market information transmission via transaction volume among Chinese city-level housing markets from 2009 to 2018. We document substantial information transmission on Chinese housing markets even within one day and find that the role a city-level housing market may play in the information transmission network resembles a pattern observed on other financial markets, which can be generally classified into three distinctive groups: prime senders, exchange centers, and prime receivers. City hierarchy and some fundamental economic factors, such as GDP per capita and average wage, appear to be significant determinants of such a pattern. The findings extend the existing voluminous literature solely based on housing prices or price volatility spillovers and shed new light on the China’s government intervention strategy on the housing market.",49.0,https://discovery.ucl.ac.uk/10143341/1/Housing%20Market%20Spillovers_JEF.pdf996658598c8692029c7de140a118321ac538c74484d,10.1016/j.eswa.2023.120981,A hybrid machine learning framework for forecasting house price,2023.0,Expert systems with applications,Choujun Zhan; Yonglin Liu; Zeqiong Wu; Mingde Zhao; Tommy W. S. Chow,,49.0,9978f7f978c1a71b33ff3cad035e07eb2bd731fa378,10.5194/bg-12-3993-2015,Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks,2015.0,,U. Mishra; W. Riley,"Abstract. The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data set with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spati",48.0,https://bg.copernicus.org/articles/12/3993/2015/bg-12-3993-2015.pdf9984e8f399d00e0d27a3fea640e4cd6e6aa1f99bdff,10.1186/2052-4374-26-1,The Relationship between Injury and Socioeconomic Status in Reference to the Fourth Korean National Health and Nutrition Examination Survey,2014.0,Annals of Occupational and Environmental Medicine,Sung-Kyung Kim; Hyocher Kim; Kyungsuk Lee; Hee-Tae Kang; S. Oh; S. Ko,"ObjectivesThis study aims to investigate the relationship between the total injury experience rate and socioeconomic status based on the fourth Korea National Health and Nutrition Examination Survey (KNHANES).MethodsBy analyzing data from the fourth KNHANES conducted from 2007 to 2009, we estimated the injury experience rate according to socioeconomic status, including the occupational characteristics of 11,837 subjects. Setting the injury experience rate as a dependent variable and socioeconomic status as an independent variable, we performed logistic regression to calculate odds ratios reflecting the likelihood of injury according to socioeconomic status while controlling for relevant covariates.ResultsIn 797 subjects who had injury experience over the past 1 year, 290 persons (36.4%) had a work-related injury. As their income, home value, and educational status increased, their injury experiences decreased. Among occupational groups, the craft, equipment, machine operating, and assembling workers showed the highest rate (10.6%) of injury experience, and the lowest rate (5.7%) was found in the unemployed group. After adjusting for the confounding variables, the experience of inju",48.0,http://aoemj.org/Synapse/Data/PDFData/2022AOEM/aoem-26-1.pdf9997a2aa8abd0a46aef4d2764b9be20a90b7ccab90b,10.1080/01431161.2019.1615655,An estimation of housing vacancy rate using NPP-VIIRS night-time light data and OpenStreetMap data,2019.0,International Journal of Remote Sensing,Luyao Wang; Hong Fan; Yankun Wang,"ABSTRACT As an informative proxy measure for a range of socio-economic variables, satellite-derived night-time light (NTL) data have been widely used to investigate the diverse anthropogenic activities and reveal urbanization development. Due to the rapid increase of Chinese urbanization rate, from 25.3% in 1987 to 58.5% in 2017, and ‘crazy expansion’ of city space, the sick phenomenon – ‘Ghost Town’ – has been brought out, generally defined as places with high housing vacancy rate (HVR), which will cause the huge waste of the limited land source in China. To investigate the HVR of urban areas in China, this study attempts to establish a hybrid model combining data derived from National Polar-Orbiting Partnership–Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL sensors with OpenStreetMap (OSM) data. By distinguishing non-residential areas and introducing detailed residential building information, we proposed a novel HVR estimation model, thus realizing the estimation of HVR in 31 Chinese provincial cities with different development levels (Tier 1–Tier 3). The results showed the average HVR of Tier 2 cities (0.204) was higher than that of Tier 1 cities (0.189) and Tier 3 ci",48.0,1000f61c4f35646e9ef30ce01738d2aff61669f39c98,10.3390/ijerph13121215,Ground Level PM2.5 Estimates over China Using Satellite-Based Geographically Weighted Regression (GWR) Models Are Improved by Including NO2 and Enhanced Vegetation Index (EVI),2016.0,International Journal of Environmental Research and Public Health,Tian-Hao Zhang; W. Gong; Wei Wang; Yu-Xi Ji; Zhongmin Zhu; Yu-Si Huang,"Highly accurate data on the spatial distribution of ambient fine particulate matter (<2.5 μm: PM2.5) is currently quite limited in China. By introducing NO2 and Enhanced Vegetation Index (EVI) into the Geographically Weighted Regression (GWR) model, a newly developed GWR model combined with a fused Aerosol Optical Depth (AOD) product and meteorological parameters could explain approximately 87% of the variability in the corresponding PM2.5 mass concentrations. There existed obvious increase in the estimation accuracy against the original GWR model without NO2 and EVI, where cross-validation R2 increased from 0.77 to 0.87. Both models tended to overestimate when measurement is low and underestimate when high, where the exact boundary value depended greatly on the dependent variable. There was still severe PM2.5 pollution in many residential areas until 2015; however, policy-driven energy conservation and emission reduction not only reduced the severity of PM2.5 pollution but also its spatial range, to a certain extent, from 2014 to 2015. The accuracy of satellite-derived PM2.5 still has limitations for regions with insufficient ground monitoring stations and desert areas. Generally,",48.0,https://www.mdpi.com/1660-4601/13/12/1215/pdf?version=14811249781001e60f9cee9e891e3cc7a257a212c22090143f5ea5,10.3390/ijgi9060346,"Modelling Housing Rents Using Spatial Autoregressive Geographically Weighted Regression: A Case Study in Cracow, Poland",2020.0,ISPRS Int. J. Geo Inf.,Mateusz Tomal,"The proportion of tenants will undoubtedly rise in Poland, where at present, the ownership housing model is very dominant. As a result, the rental housing market in Poland is currently under-researched in comparison with owner-occupancy. In order to narrow this research gap, this study attempts to identify the determinants affecting rental prices in Cracow. The latter were obtained from the internet platform otodom.pl using the web scraping technique. To identify rent determinants, ordinary least squares (OLS) regression and spatial econometric methods were used. In particular, traditional spatial autoregressive model (SAR) and spatial autoregressive geographically weighted regression (GWR-SAR) were employed, which made it possible to take into account the spatial heterogeneity of the parameters of determinants and the spatially changing spatial autocorrelation of housing rents. In-depth analysis of rent determinants using the GWR-SAR model exposed the complexity of the rental market in Cracow. Estimates of the above model revealed that many local markets can be identified in Cracow, with different factors shaping housing rents. However, one can identify some determinants that are ",48.0,https://www.mdpi.com/2220-9964/9/6/346/pdf?version=15911755801002847b1cb35b461e5b1c155b24ea0bbdc93b3d9d4a,10.1080/24694452.2021.1935208,Beyond Distance Decay: Discover Homophily in Spatially Embedded Social Networks,2021.0,Annals of the American Association of Geographers,Yang Xu; P. Santi; C. Ratti,"Existing studies suggest distance decay as an important geographic property of online social networks. Namely, social interactions are more likely to occur among people who are closer in physical space. Limited effort has been devoted so far, however, to quantifying the impact of homophily forces on social network structures. In this study, we provide a quantitative understanding of the joint impact of geographic distance and people’s socioeconomic characteristics on their interaction patterns. By coupling large-scale mobile phone, income, and housing price data sets in Singapore, we reconstruct a spatially embedded social network that captures the cell phone communications of millions of phone users in the city. By associating phone users with their estimated residence, we introduce two indicators (communication intensity and friendship probability) to examine the cell phone interactions among places with various housing price values. Our findings suggest that, after controlling for distance, similar places tend to have relatively higher communication intensity than dissimilar ones, confirming a significant homophily effect as a determinant of communication intensity. When the ana",48.0,100382e1892b4686150976e38ede4dc1c536d906c605,10.1016/j.cities.2021.103145,Spatial heterogeneity in spillover effect of air pollution on housing prices: Evidence from China,2021.0,,Haiyong Zhang; Jie Chen; Zhen Wang,"Abstract This paper analyzes how the spatial spillover effects of air pollution on city-level average housing prices vary with geographical, atmospheric and institutional factors in China. By using the panel data of Chinese major cities over the period 2005–2015, our empirical estimations show that: first, the negative spatial externality of transboundary neighboring air pollution on housing prices is significant only when the distance between cities is less than 200 km, and the impact magnitude significantly declines with distance; second, the spillover effect of air pollution is sensitive to wind direction; third, the negative externality of air pollution on housing prices is significantly aggravated where there is higher ventilation intensity between the cities and lower effectiveness levels relating to local environmental governance. These findings are robust to differing model settings and differing indicators for key variables. Our estimate suggests that, on average, a doubling of the total imported air pollutants from neighboring cities less than 100 km distant will be likely to reduce local housing prices by 6%. The paper concludes with policy suggestions on how to mitigate",48.0,100471fe66595c78203bde395eb777963e89d6c03b0a,10.1080/10835547.2018.12091505,Impact of Artificial Neural Networks Training Algorithms on Accurate Prediction of Property Values,2018.0,Journal of Real Estate Research,Joseph Awoamim Yacim; D. Boshoff,"This study extended the use of artificial neural networks (ANNs) training algorithms in mass appraisal. The goal was to verify the comparative performance of ANNs with linear, semi-log, and log-log models. The methods were applied to a dataset of 3,232 single-family dwellings sold in Cape Town, South Africa. The results reveal that the semi-log model and the Levenberg-Marquardt trained artificial neural networks (LMANNs) performed best in their respective categories. The best performing models were tested in terms of prediction accuracy within the 10% and 20% of the assessed values, performance, and reliability ranking, and explicit explainability ranking order. The LMANNs outperform the semi-log model in the first two tests, but fail the explainability ranking order test. The results demonstrate the semi-log model as the most preferred technique due to its simplicity, consistency, transparency, locational advantage, and ease of application within the mass appraisal environment. The black box nature of th...",48.0,10055878aa0d0ee07f2648258d26477fe3dd9fd13f04,10.1080/00222216.2019.1637704,Impact on property values of distance to parks and open spaces: An update of U.S. studies in the new millennium,2020.0,Journal of Leisure Research,J. Crompton; S. Nicholls,"Abstract The review of 33 studies generally confirmed findings from a 2001 review: House values rose as proximity to a park increased; properties immediately adjacent to a park sometimes had a lower premium than dwellings a block or two away from it; larger parks had higher premiums, and their influence extended over a longer distance; and substantially greater premiums accrued from passive than from active parks. The results suggested a premium of 8%–10% on properties adjacent to a passive park is a reasonable point of departure, which is lower than suggested by previous guidelines. Four additional insights emerged: Percentage premiums were higher for (a) multifamily or small lots than for single-family homes or large lots and (b) for permanently protected lands than for developable lands; recognition was frequently lacking (c) the heterogeneity of open space and (d) differentials among submarkets. Six managerial conclusions and five guidelines for future research are offered.",48.0,1006e90c1618193e23838606cbca3759d3e6518426eb,10.1145/3195106.3195133,House Prices Prediction with Machine Learning Algorithms,2018.0,International Conference on Machine Learning and Computing,Chenchen Fan; Z. Cui; Xiao-Feng Zhong,,48.0,1007