1record_id,doi,title,year,venue,authors,abstract,citations,oa_pdf2https://openalex.org/W2025797685,10.1016/0166-0462(92)90039-4,Specification and estimation of hedonic housing price models,1992,Regional Science and Urban Economics,Ayşe Can,Alternative traditional and spatial autoregressive hedonic urban housing price models are offered corresponding to different conceptualizations of the housing price determination process. Some methodological issues relevant to their estimation are addressed that draw upon recent developments from spatial econometrics. These include the selection of the appropriate estimation strategy; the application of diagnostic tests for the detection of spatial dependence and heterogeneity; and the use of robust methods in the presence of heteroskedasticity.,582.0,31ce1eaf3983315cb017b5669a5fa56ba93a3f60d,10.1080/13658816.2013.865739,Geographically weighted regression with a non-Euclidean distance metric: a case study using hedonic house price data,2014,International Journal of Geographical Information Science,Binbin Lu; M. Charlton; P. Harris; A. Fotheringham,,387.0,http://eprints.maynoothuniversity.ie/7852/1/MC_hedon%202014.pdf4875451368628cb700ce5ad1403bfbc804f05ee97,10.1023/a:1007715917198,"The Construction of Residential Housing Price Indices: A Comparison of Repeat-Sales, Hedonic-Regression, and Hybrid Approaches",1997,,N. Wallace; R. Meese,,335.0,5a64864aa575b0c7e918a1b5361c1076e215cbb83,10.1016/j.cities.2018.11.016,"Analyzing housing prices in Shanghai with open data: Amenity, accessibility and urban structure",2019,Cities,Han-Duo Li; Y. Wei; Yangyi Wu; Guang Tian,"Abstract Skyrocketing housing prices in China's megacities have generated broad concerns. By integrating open data from Lianjia.com , Dianping.com , Mobike.com , and Baidu Map POI, we analyze spatial patterns of apartment prices and their association with local attributes in Shanghai. We find that Shanghai's residential market still has a monocentric structure because of the centralized distribution of public transport facilities and amenities. Hedonic models further confirm that structural attributes, accessibility, as well as public and private service amenities significantly shape the real estate market. These factors also are differentiated so as to form a pattern of concentric rings. In the inner-city and expanded inner-city areas, public service amenities such as parks, schools, hospitals, and banks, as well as private service amenities such as entertainment, shopping, and residential service facilities, boost housing prices. In the suburbs, better access to bike sharing, bus stops, and metro stations are the top preferences for apartment buyers. Our study also indicates that the Chinese government needs to make public and private services more accessible, not only spatially ",294.0,6doi_10_1016_j_eswa_2008_01_044,10.1016/j.eswa.2008.01.044,Determinants of house prices in Turkey: Hedonic regression versus artificial neural network,2009,Expert Systems with Applications,Hasan Selim,,271.0,7709fcaab6d20d6f11513f6e6e603dda5522fa4f4,10.2139/ssrn.1954507,Hedonic House Prices and Spatial Quantile Regression,2012,,Wen-Chi Liao; Xizhu Wang,,250.0,https://doi.org/10.2139/ssrn.1954507822e62fc82c4ed1c605cd41b5c6124856f4afd7c6,10.1007/s10640-013-9664-9,The Amenity Value of English Nature: A Hedonic Price Approach,2014,,S. Gibbons; S. Mourato; G. Resende,"Using a hedonic property price approach, we estimate the amenity value associated with proximity to habitats, designated areas, domestic gardens and other natural amenities in England. There is a long tradition of studies looking at the effect of environmental amenities and disamenities on property prices. But, to our knowledge, this is the first nationwide study of the value of proximity to a large number of natural amenities in England. We analysed 1 million housing transactions over 1996–2008 and considered a large number of environmental characteristics. Results reveal that the effects of many of these environmental variables are highly statistically significant, and are quite large in economic magnitude. Gardens, green space and areas of water within the census ward all attract a considerable positive price premium. There is also a strong positive effect from freshwater and flood plain locations, broadleaved woodland, coniferous woodland and enclosed farmland. Increasing distance to natural amenities such as rivers, National Parks and National Trust sites is unambiguously associated with a fall in house prices. Our preferred regression specifications control for unobserved lab",238.0,https://researchonline.lse.ac.uk/id/eprint/33594/1/sercdp0074.pdf9doi_10_1007_s00181_007_0152_3,10.1007/s00181-007-0152-3,Errors in variables and spatial effects in hedonic house price models of ambient air quality,2007,Empirical Economics,Luc Anselin; Nancy Lozano-Gracia,,227.0,10b51ae7fa8ad6ec948d8787f76cdf0f315d38c6f6,10.1177/0042098013492234,Spatial Heterogeneity in Hedonic House Price Models: The Case of Austria,2014,,M. Helbich; Wolfgang A. Brunauer; E. Vaz; P. Nijkamp,,202.0,http://papers.tinbergen.nl/13171.pdf11aa88fbd3f182c979314b712f589a572e8fe2cd2b,10.1016/j.ecolecon.2009.08.018,Flooding Risk And Housing Values: An Economic Assessment Of Environmental Hazard,2009,,V. E. Daniel; R. Florax; P. Rietveld,"Climate change, the ‘boom and bust’ cycles of rivers, and altered water resource management practice have caused significant changes in the spatial distribution of the risk of flooding. Hedonic pricing studies, predominantly for the US, have assessed the spatial incidence of risk and the associated implicit price of flooding risk. Using these implicit price estimates and their associated standard errors, we perform a meta-analysis and find that houses located in the 100-year floodplain have a –0.3 to –0.8% lower price. The actual occurrence of a flooding event or increased stringency in disclosure rules causes ex ante prices to differ from ex post prices, but these effects are small. The marginal willingness to pay for reduced risk exposure has increased over time, and it is slightly lower for areas with a higher per capita income. We show that obfuscating amenity effects and risk exposure associated with proximity to water causes systematic bias in the implicit price of flooding risk.",198.0,https://ageconsearch.umn.edu/record/7333/files/wp070002.pdf12doi_10_1080_17421770600661337,10.1080/17421770600661337,Interpolation of Air Quality Measures in Hedonic House Price Models: Spatial Aspects,2006,Spatial Economic Analysis,Luc Anselin; Julie Le Gallo,,198.0,13https://openalex.org/W1978712773,10.1111/1540-6229.00555,Nonparametric Estimation of Dynamic Hedonic Price Models and the Construction of Residential Housing Price Indices,1991,Real Estate Economics,Richard A. Meese; Nancy E. Wallace,"Parametric specifications for hedonic price equations are estimated using a data set from Alameda and San Francisco Counties and are compared to estimates using a nonparametric technique called locally weighted regression, LWR. LWR permits flexible estimation of the hedonic's curvature at median attributes and is less sensitive than standard regression techniques to the influence of unusual observations. The technique also avoids imposing a single functional form across time and municipalities. The LWR estimates of municipality‐specific hedonics are then used to obtain implicit prices for housing attributes and to derive municipality‐specific price indices. The results of extensive diagnostic checks of our technique are also reported.",197.0,14https://openalex.org/W1538333778,10.1111/j.1467-6419.2012.00731.x,"HEDONIC PRICE INDEXES FOR RESIDENTIAL HOUSING: A SURVEY, EVALUATION AND TAXONOMY",2012,Journal of Economic Surveys,Robert Hill,"Abstract Every house is different. It is important that house price indexes take account of these quality differences. Hedonic methods which express house prices as a function of a vector of characteristics (such as number of bedrooms and bathrooms, land area and location) are particularly useful for this purpose. I consider here some developments in the hedonic methodology, as it is applied in a housing context, that have occurred in the last three decades. A number of hedonic house price indexes are now available. However, it is often difficult to see how these indexes relate to each other. For this reason I attempt to impose some structure on the literature by developing a taxonomy of hedonic indexes, and then show how existing indexes fit into this taxonomy. Also discussed are some promising areas for future research in the hedonic field. In particular, greater use needs to be made of spatial econometric and nonparametric methods to exploit the increased availability of geospatial data. The main criticisms of the hedonic approach are evaluated and compared with those of the repeat‐sales and stratified median methods. The overall conclusion is that the advantages of the hedonic ",189.0,15234ac161f4d3a76cf9cb2ba5cd02e2402ab966c9,10.3390/ijgi7050168,Estimating the Performance of Random Forest versus Multiple Regression for Predicting Prices of the Apartments,2018,ISPRS Int. J. Geo Inf.,M. Čeh; M. Kilibarda; A. Lisec; B. Bajat,"The goal of this study is to analyse the predictive performance of the random forest machine learning technique in comparison to commonly used hedonic models based on multiple regression for the prediction of apartment prices. A data set that includes 7407 records of apartment transactions referring to real estate sales from 2008–2013 in the city of Ljubljana, the capital of Slovenia, was used in order to test and compare the predictive performances of both models. Apparent challenges faced during modelling included (1) the non-linear nature of the prediction assignment task; (2) input data being based on transactions occurring over a period of great price changes in Ljubljana whereby a 28% decline was noted in six consecutive testing years; and (3) the complex urban form of the case study area. Available explanatory variables, organised as a Geographic Information Systems (GIS) ready dataset, including the structural and age characteristics of the apartments as well as environmental and neighbourhood information were considered in the modelling procedure. All performance measures (R2 values, sales ratios, mean average percentage error (MAPE), coefficient of dispersion (COD)) revea",188.0,https://www.mdpi.com/2220-9964/7/5/168/pdf?version=154803660216c3ee68ff8676c1c2d9d02de39ca21dfb85b699dd,10.3390/ijgi7030104,Impacts of Street-Visible Greenery on Housing Prices: Evidence from a Hedonic Price Model and a Massive Street View Image Dataset in Beijing,2018,ISPRS Int. J. Geo Inf.,Yonglin Zhang; R. Dong,"Street greenery is a component of urban green infrastructure. By forming foundational green corridors in urban ecological systems, street greenery provides vital ecological, social, and cultural functions, and benefits the wellbeing of citizens. However, because of the difficulty of quantifying people’s visual perceptions, the impact of street-visible greenery on housing prices has not been fully studied. Using Beijing, which has a mature real estate market, as an example, this study evaluated 22,331 transactions in 2014 in 2370 private housing estates. We selected 25 variables that were classified into three categories—location, housing, and neighbourhood characteristics—and introduced an index called the horizontal green view index (HGVI) into a hedonic pricing model to measure the value of the visual perception of street greenery in neighbouring residential developments. The results show that (1) Beijing’s homebuyers would like to reside in residential units with a higher HGVI; (2) Beijing’s homebuyers favour larger lakes; and (3) Beijing’s housing prices were impacted by the spatial development patterns of the city centre and multiple business centres. We used computer vision t",170.0,https://www.mdpi.com/2220-9964/7/3/104/pdf?version=1521013192179544f4ac839e433b51f55da090f58729fbbf9919,10.3846/ijspm.2020.11544,A HOUSE PRICE VALUATION BASED ON THE RANDOM FOREST APPROACH: THE MASS APPRAISAL OF RESIDENTIAL PROPERTY IN SOUTH KOREA,2020,,Jengei Hong; Heeyoul Choi; Woo-sung Kim,"Mass appraisal is the standardized procedure of valuing a large number of properties at the same time and is commonly used to compute real estate tax. While a hedonic pricing model based on the ordinary least squares (OLS) linear regression has been employed as the traditional method in this process, the stability and accuracy of the model remain questionable. This paper investigates the features of a house price predictor based on the Random Forest (RF) method by comparing it with that of a conventional hedonic pricing model. We used apartment transaction data from the period of 2006 to 2017 in the district of Gangnam, one of the most developed areas in South Korea. Using a data set covering 40% of all transactions in the sample area, we demonstrate that the accuracy of a machine learning-based predictor can be surprisingly high. The average of percentage deviations between the predicted and the actual market price was found to be only around 5.5% in the RF predictor, whereas it was almost 20% in the OLS-based predictor. With the RF predictor, the probability of the predicted price being within 5% of its actual market price was 72%, while only about 17.5% of the regression-based p",154.0,https://doi.org/10.3846/ijspm.2020.1154418e222ea987e7bbbced53a7ac94960939e23155d8c,10.1093/reep/reaa001,Best Practices for Using Hedonic Property Value Models to Measure Willingness to Pay for Environmental Quality,2020,Review of Environmental Economics and Policy,Kelly C. Bishop; N. Kuminoff; H. Banzhaf; K. Boyle; Kathrine von Gravenitz; Jaren C. Pope; V. Smith; Christopher Timmins,"The hedonic property-value model has been refined over more than forty years to become one of the premier approaches to valuing environmental amenities. This article presents best practices for hedonic property-value modeling when the goal is to measure households’ willingness to pay (WTP) for a change in a spatially varying amenity. The starting point is a research design that identifies a source of exogenous variation in an amenity that is observable by prospective buyers (e.g., air quality). Data on the sales prices and physical attributes of houses, together with location-specific measures for amenities, are then used to estimate a housing-price function. Under ideal conditions, the derivative of this price function can be interpreted as indicating the amenity’s implicit price, which can then be used to calculate household marginal WTP for the amenity. In principle, this process is straightforward. In practice, modeling decisions must be made to define variables that measure sale prices and amenities and to select an econometric specification. Although the number of issues to address when developing a “best practices” study may seem daunting, the effort is both worthwhile and i",150.0,19doi_10_3844_ajassp_2004_193_201,10.3844/ajassp.2004.193.201,House Price Prediction: Hedonic Price Model vs. Artificial Neural Network,2004,American Journal of Applied Sciences,Visit Limsombunc; Christopher Gan; Minsoo Lee,,149.0,20https://openalex.org/W245041798,10.1016/j.landurbplan.2015.04.007,"Valuation of landscape amenities: A hedonic pricing analysis of housing rents in urban, suburban and periurban Switzerland",2015,Landscape and Urban Planning,Felix Schläpfer; Fabian Waltert; Lorena Segura; Felix Kienast,,149.0,21doi_10_1108_14635789710163793,10.1108/14635789710163793,Estimating the influence of transport on house prices: evidence from Hong Kong,1997,Journal of Property Valuation and Investment,H.M. So; R.Y.C. Tse; S. Ganesan,"Attempts to analyse the importance of transportation in determining house prices in Hong Kong. Residential property is sold as a package of inherent attributes that are valued by consumers and this analysis classifies them into the following categories: structural, physical and environmental. Specifically, these determinants of housing price include structural attributes such as size, age and floor level of the housing units; amenities such as accessibility to various means of transport; and factors determining the quality of the environment such as availability of recreational facilities. In this study, data were obtained from a large residential area in Hong Kong. Uses a Hedonic price model for estimating the importance of each of the defined utility‐bearing attributes on house prices.",146.0,22doi_10_1080_00420980220135545,10.1080/00420980220135545,Estimating Neighbourhood Effects in House Prices: Towards a New Hedonic Model Approach,2002,Urban Studies,Raymond Y. C. Tse,"A hedonic equation considers OLS models with independently and identically distributed errors. However, quality of property and location tend to exhibit highly auto-regressive correlation due to spatial dependence and heterogeneity. A modification is made to multiple regression analysis based on the land-rent concept so that the modified hedonic house price function can be determined. This paper develops a stochastic approach which is able to correct autocorrelation bias in the hedonic function. Others tend to model the spatial autocorrelation through the error terms, while this study models it through the constant term. The sample was orientated by location to reflect the neighbourhood effects. Thus the neighbourhood effects can be separated from the random disturbance. Our model, using data from Hong Kong, incorporates adjustments reflecting net floor area ratio, age, floor level, views, transport accessibility and amenities such as availability of recreational facilities. The stochastic model is a more flexible application of hedonic price regressions, making it an appealing alternative to spatial problems.",140.0,23936c6590606e5669e7af8c0cb16273ac696d2d36,10.1016/j.landusepol.2016.03.001,"Estimating the mediating effect of privately-supplied green space on the relationship between urban public green space and property value: Evidence from Shanghai, China",2016,,Xiao Yang; Zhigang Li; C. Webster,"Much of the housing in China’s cities built since the opening up of housing markets in the 1990s is organized in residential clubs, with neighbourhood civic goods and services constructed by private developers, financed by residents’ fees, managed by property-management companies and governed by resident associations. This means that there are now three important types of green space in Chinese cities: public green space (open-access parks), private green space (gardens, exclusive to a private home) and club green space (greenery exclusive to fee-paying estate residents). We ask a simple but profound question: how does this three-fold green space morphology and economy influence housing prices and, by implication, locational preferences in the city? More specifically, we test the hypothesis that the privately supplied green spaces withing club-communities substitute for publicly supplied green spaces in the public realm. We find evidence in support of this hypothesis, showing for example, that unlike other kinds of green space, public district parks have no measurable use value to Shanghai home-buyers, using a hedonic valuation model. If urban planners in China understood that thei",137.0,http://hdl.handle.net/10722/23158024https://openalex.org/W3118899449,10.1016/j.eswa.2021.114590,"Machine learning with explainability or spatial hedonics tools? An analysis of the asking prices in the housing market in Alicante, Spain",2021,Expert Systems with Applications,Juan Ramón Rico-Juan; Paloma Taltavull de La Paz,"Two sets of modelling tools are used to evaluate the precision of housing-price forecasts: machine learning and hedonic regression. Evidences on the prediction capacity of a range of methods points to the superiority of the random forest as it can calculate real-estate values with an error of less than 2%. This method also ranks the attributes that are most relevant to determining housing prices. Hedonic regression models are less precise but more robust as they can identify the housing attributes that most affect the level of housing prices. This empirical exercise adds new knowledge to the literature as it investigates the capacity of the random forest to identify the three dimensions of non-linearity which, from an economic theoretical point of view, would identify the reactions of different market agents. The intention of the robustness test is to check for these non-linear relationships using hedonic regression. The quantile tools also highlight non-linearities, depending on the price levels. The results show that a combination of techniques would add information on the unobservable (non-linear) relationships between housing prices and housing attributes on the real-estate mar",136.0,https://www.sciencedirect.com/science/article/pii/S0957417421000312/pdf259e73789b4a3462de8b6626ea39704e1db08403f8,10.1016/j.habitatint.2018.05.012,"Education quality, accessibility, and housing price: Does spatial heterogeneity exist in education capitalization?",2018,Habitat International,Hai-Zhen Wen; Yue Xiao; E. Hui; Ling Zhang,"Abstract Evaluating the capitalization effect of educational facilities via the real estate market has elicited considerable research attention. Although the spatial attribute of housing data is generally considered when constructing a hedonic price model, only a few studies investigated the spatial heterogeneity of educational capitalization in depth. To fill this gap, this study uses the housing data of 516 communities in Hangzhou, as well as constructs the hedonic price, spatial econometric and geographically weighted models to quantitatively evaluate the capitalization effect of educational facilities and explore whether space plays an important role in the capitalization of education. Results confirm that, from the perspective of educational quality or accessibility, kindergarten, primary school, junior high school, senior high school, and university significantly affect housing prices. Specifically, the quality of primary school and junior high school as well as the accessibility of university profoundly influence housing prices. The geographically weighted regression model (GWR) further reveals the existence of spatial heterogeneity in educational capitalization. Different t",127.0,http://hdl.handle.net/10397/7829626https://openalex.org/W864328887,10.1016/j.habitatint.2015.06.005,A study of the effect of a high-speed rail station on spatial variations in housing price based on the hedonic model,2015,Habitat International,Bin Geng; Haijun Bao; Ying Liang,,127.0,27eb2663068d73d32e83378e9ddd14f5caa58f11e6,10.1080/21681376.2019.1592699,"Location, location and professionalization: a multilevel hedonic analysis of Airbnb listing prices and revenue",2019,"Regional Studies, Regional Science",Robbin Deboosere; D. Kerrigan; D. Wachsmuth; A. El-geneidy,"ABSTRACT Hedonic modelling techniques have frequently been used to examine real estate valuation, and they have recently started to be applied to short-term rental valuation. Relying on a web-scraped data set of all Airbnb transactions in New York City (NYC) between August 2014 and September 2016, this paper presents the first hedonic regression model of Airbnb to take into account neighbourhood effects and to predict both average price per night and revenue generated by each listing. The model demonstrates that locational factors – above all, transit accessibility to jobs – and neighbourhood variation have a large impact on both price per night and monthly revenue, and further reveals how professionalization of the short-term rental market is driving more revenue to a narrower segment of hosts. Further, the findings suggest that Airbnb hosts earn a significant premium by converting long-term housing in accessible residential neighbourhoods into de facto Airbnb hotels. This premium incentivizes landlords and hosts with properties in accessible neighbourhoods to replace long-term tenants with short-term guests, forcing those in search of housing to less accessible neighbourhoods.",121.0,https://www.tandfonline.com/doi/pdf/10.1080/21681376.2019.1592699?needAccess=true28485efdd3d5d6971cc88e8a0452c2750fdc6fcf3a,10.1016/j.cities.2018.07.005,Does bus accessibility affect property prices?,2019,Cities,Lin-Chuan Yang; Jiang-Ping Zhou; Oliver F. Shyr; Da Huo,"Abstract Existing studies have yet reached consistent conclusions on accessibility benefits of buses. Most existing studies have been conducted in the context of the West, where bus patronage is generally low. In this study, we used a database of 22,586 secondhand residential properties in 358 residential estates in Xiamen, China to develop four non-spatial hedonic pricing models (one standard and three Box-Cox transformed) and two spatial econometric models to quantify the effects of bus accessibility on property prices and analyze how the introduction of spatial econometric models would influence estimates of such benefits. Our findings are as follows. (1) Access to bus stops is positively correlated with property prices. This outcome is in contrast with findings of mainstream research (or conventional wisdom). For every bus stop within 500 m, the price of a property is 0.5% higher, all else being equal. (2) Bus travel times to essential destinations significantly influence housing prices. (3) Spatial econometric models that account for spatial autocorrelation outperform traditional hedonic pricing models. A few robustness check analyses further guarantee the plausibility of this",121.0,296dc2ebbe4674c7be3c8b355e1b61705fcc6c1a2d,10.1016/j.tust.2022.104528,COVID-19 effects on property markets: The pandemic decreases the implicit price of metro accessibility,2022,Tunnelling and Underground Space Technology,Lin-Chuan Yang; Yuan Liang; Baojie He; Yi Lu; Z. Gou,"The metro (or underground railways) has become a backbone in the transit systems of many cities. It has numerous externalities, such as ameliorating traffic congestion and enhancing nearby property prices. Previous studies extensively focused on the relationship between metro accessibility and property prices and obtained various interesting findings and enriched practical implications. However, this relationship in the era of the coronavirus disease 2019 (COVID-19) and other epidemic shocks has not been investigated. Based on a unique property transaction dataset (including tens of thousands of transactions stretching from 2018 to 2020) in Chengdu, China, this study develops a battery of hedonic pricing models and difference-in-differences models to decipher the time-varying relationship between metro accessibility and residential property prices. The results show that the implicit price of metro accessibility modestly decreases in COVID-19, which can be explained by the declining role of the metro. In other words, the price gap between proximate and distant properties is narrowed, and the property price gradient is flattened. Specifically, the price elasticity of distance to the ",119.0,https://doi.org/10.1016/j.tust.2022.104528300479cb200b63ed215ca478f6e8431d745dfbbdfd,10.48044/jauf.2003.032,The Influence of Trees and Landscaping on Rental Rates at Office Buildings,2003,Arboriculture & urban forestry,Robert J. Laverne; K. Winson-Geideman,"The environmental and economic benefits of trees have been studied relative to a variety of interests including their influence on real estate value. This study investigates the effect of trees and landscaping on office rental rates, based on a comparison of 85 office buildings that comprise 270 individual and unique leases in the Cleveland, Ohio, U.S., metropolitan area. Data that describe the quantity, functionality, and quality of landscaping were gathered from each of the buildings including landscape maturity, the percentage of ground cover (trees, turf, pavement, etc.), and functional attributes (building shade, noise buffer, space definition, recreation, visual screen, and aesthetics). Multiple regression analysis in the form of a hedonic equation was conducted to isolate the economic effects of landscaping. Office attribute data including lease information, physical attributes, and distance variables were used to calibrate the basic model, and landscaping data were added to the hedonic equation to determine if individual and/or interactive variables had any effect on contracted rental rates. The individual analysis of the variables showed a strong positive effect for those ",119.0,https://joa.isa-arbor.com/request.asp?JournalID=1&ArticleID=105&Type=231https://openalex.org/W2022052296,10.1111/0017-4815.00171,Theoretical and Empirical Considerations Regarding Space in Hedonic Housing Price Model Applications,2001,Growth and Change,William M. Bowen; Brian A. Mikelbank; Dean M. Prestegaard,"Recent advances in spatial data analysis are making their way into a variety of applied research settings. Once purely the domain of specialists, increased availability of both spatial data and the software with which to handle them, spatial analysis techniques are diffusing into other areas of research. This article first details the rationale and need for spatial considerations in hedonic price models and focuses on the link between the context of the housing market and the statistical considerations necessary when dealing with spatial data. These issues are then explored via an application to the housing market of Cuyahoga County, Ohio. It was found, first, that explicit modeling of space is not always warranted. One of our two models shows no substantial signs of spatial misspecification. However, in the second model, where diagnostic tests call for the explicit modeling of space, some drastic differences were found between the space‐neglected model and the more correctly specified spatial hedonic model. This highlights the need to include spatial diagnostics as part of the standard model‐fitting procedure for hedonic house price applications.",119.0,32doi_10_1111_j_1467_9787_1987_tb01184_x,10.1111/j.1467-9787.1987.tb01184.x,"A HEDONIC MODEL OF INTERREGIONAL WAGES, RENTS, AND AMENITY VALUES*",1987,Journal of Regional Science,John P. Hoehn; Mark C. Berger; Glenn C. Blomquist,"ABSTRACT This paper develops a general multimarket hedonic model appropriate for a national, interregional study of wages, housing prices, and location‐specific amenities. The model encompasses the effects of interregional location, intraurban location, and city size. Typically, hedonic studies focus on a single market such as labor or housing and ignore interactions implicit in a more global compensation mechanism. Examination of the comparative statics of our model indicates that single‐market differentials are partial prices and are unreliable measures of amenity values in an interregional context. Unbiased amenity values are estimated for a comprehensive set of amenities using data on housing prices for 34,414 households and wages for 46,004 workers from the 1980 Census of Population and Housing . Statistically significant differences in housing prices and wages are found due to amenities.",118.0,33207a7853dab835931c7fe2776cb7964d5539d22f,10.3390/su11041144,The Effect of Sustainable Urban Planning and Slum Disamenity on The Value of Neighboring Residential Property: Application of The Hedonic Pricing Model in Rent Price Appraisal,2019,Sustainability,Touseef Hussain; J. Abbas; Zou Wei; M. Nurunnabi,"This study is the first to perform a focalized analysis on city development, sustainable urban planning, and the negative impact of slum area disamenity on property valuation in suburban and posh areas of the Islamabad region, Pakistan. Slums exist in almost every country in the world. However, in the process of urbanization and city development, researchers have focused merely on the crumbled infrastructure, crimes, and other social problems associated with slums. Studies have covered the adverse effects of these factors on property value, although this unmatched study is the first to examine the negative impact of slum proximity on the valuation of properties in the surrounding areas and on the rental value of houses located in Islamabad. The survey method is applied to obtain feedback from inhabitants, and the study incorporated the hedonic price model to assess rental values within a range of one kilometer from selected slum areas. The findings revealed that slum neighborhoods negatively impact sustainable house rental values, as compared with the rental values of houses located far away. Rents became higher as the distance from the slums increased. The results showed that havi",115.0,https://www.mdpi.com/2071-1050/11/4/1144/pdf?version=15507494573403ae226b461f39ce77988b8e944f5ba8259156d3,10.5198/jtlu.v3i2.117,Modelling hedonic residential rents for land use and transport simulation while considering spatial effects,2010,,Michael Löchl; K. Axhausen,"The application of UrbanSim requires land or real estate price data for the study area. These can be difficult to obtain, particularly when tax assessor data and data from commercial sources are unavailable. The article discusses an alternative method of data acquisition and applies hedonic modeling techniques in order to generate the required data. Many studies have highlighted that ordinary least square (OLS) regression approaches lack the ability to consider spatial dependency and spatial heterogeneity, consequently leading to biased and inefficient estimations. Therefore, a comprehensive data set is used for modeling residential asking rents by applying and comparing OLS, spatial autoregressive, and geographically weighted regression (GWR) techniques. The latter technique performed best with regard to model fit, but the issue of correlated coefficients favored a spatial simultaneous autoregressive model. Overall, the article reveals that when housing markets are a particular concern in UrbanSim applications, significant efforts are needed for the price data generation and modeling. The study concludes with further development potentials for UrbanSim.",115.0,https://www.jtlu.org/index.php/jtlu/article/download/117/11735https://openalex.org/W216611364,10.68479/001c.9464,Urban location and housing prices within a hedonic model,2008,The journal of regional analysis & policy,John R. Ottensmann; Seth B. Payton; Joyce Y. Man,"A measure of location relative to employment is often included in hedonic housing price models. This is most often distance to the center, based on the monocentric model, which does not consider the decentralization of employment in urban areas. This paper tests the performance of alternative measures of location, considering both distance and time to the center and to multiple employment centers and measures of accessibility to employment and change in accessibility. The measures using multiple employment centers and accessibility perform better than simple distance to the center, with the combination of accessibility to employment and change in accessibility doing best.",113.0,https://jrap.scholasticahq.com/article/9464.pdf36doi_10_1016_j_reseneeco_2004_11_003,10.1016/j.reseneeco.2004.11.003,The impact of oil and natural gas facilities on rural residential property values: a spatial hedonic analysis,2005,Resource and Energy Economics,Peter C. Boxall; Wing H. Chan; Melville L. McMillan,,113.0,37doi_10_1080_00420980120080880,10.1080/00420980120080880,Historic Preservation and Residential Property Values: An Analysis of Texas Cities,2001,Urban Studies,Robin M. Leichenko; N. Edward Coulson; David Listokin,"Designation of historic districts is increasingly used as a tool to revive or halt the deterioration of central-city neighbourhoods. While historic designation is generally thought to have a positive impact on property values, evidence on this issue is mixed. One limitation of previous research is that it typically focuses on historic neighbourhoods in one city and thus bases its conclusions on a very limited sample. This study expands upon previous work by examining the effects of designation on property values across a larger set of cities. The study employs hedonic regression models to estimate housing prices in historic districts and comparable neighbourhoods in nine Texas cities. Results suggest that, in most cases, historic designation is associated with higher property values.",110.0,38https://openalex.org/W2099932395,10.52324/001c.8197,The Hedonic Pricing Model Applied to the Housing Market of the City of Savannah and Its Savannah Historic Landmark District,2009,Review of Regional Studies,Richard J. Cebula,"This study applies a hedonic pricing model to the housing market of the City of Savannah, Georgia. The Savannah Historic Landmark District is located both in and adjacent to downtown Savannah. Of the 2,888 single-family homes for the period 2000-2005 for which data are available, 591 are located in the Historic District. The model of the real sales price of a single-family house in the City of Savannah environment reveals it is positively affected by the number of bathrooms, fireplaces, bedrooms, stories in structure, garage car spaces, square feet of finished living space, the presence of a deck, a private courtyard, a pool and/or hot-tub, an exterior construction of brick or stucco, the presence of an underground sprinkler system, and whether the house was new. Six spatial control variables are considered. Locations across from, or adjacent to, open space carry premia, as do locations on cul-de-sacs or lakes. Corner properties do not. In addition, proximity to an apartment complex is capitalized as a negative quantity, as do locations on a busy street. The real sales price of residential properties that closed during May or July tend to be higher. In addition, houses designated a",105.0,https://rrs.scholasticahq.com/article/8197.pdf39doi_10_1111_j_1467_8276_2005_00724_x,10.1111/j.1467-8276.2005.00724.x,The Amenity and Disamenity Impacts of Agriculture: Estimates from a Hedonic Pricing Model,2005,American Journal of Agricultural Economics,Richard C. Ready; Charles W. Abdalla,"Abstract The positive and negative externalities from farmland are increasingly a focus of public policy discussion about agriculture and land use. A GIS‐based hedonic pricing model shows that agricultural open space increases nearby residential property values, but larger‐scale animal operations and mushroom production have negative impacts. Animal production facilities with as few as 200 animal equivalent units reduce nearby property values, but larger facilities do not necessarily generate larger impacts. Because they tend to occur together, the negative impacts of animal agriculture and the positive impacts of open space must be simultaneously modeled to avoid omitted variable bias.",105.0,40https://openalex.org/W2933512823,10.1016/j.habitatint.2019.03.008,"Effects of floor level and landscape proximity on housing price: A hedonic analysis in Hangzhou, China",2019,Habitat International,Yue Xiao; Eddie C.M. Hui; Haizhen Wen,,103.0,417b4e7f35d7b3d5553757b7fef045645f4e3b8d8c,10.1016/j.landurbplan.2018.12.007,"Understanding the local impact of urban park plans and park typology on housing price: A case study of the Busan metropolitan region, Korea",2019,Landscape and Urban Planning,Hyunsoo Kim; Go-Eun Lee; Jaesong Lee; Yeol Choi,"Abstract The valuation of urban parks using hedonic pricing has been thoroughly documented in a number of studies set in many cities. Just as the value of existing parks can be estimated by investigating the relationship between housing prices and parks, the value of future parks can also be estimated using this approach. This study recognized that a series of planning processes and land use transitions to create urban parks not only influences the perceptions of real estate buyers but also the quality of the local environment. From the apartment sales data for the Busan metropolitan region of Korea, data on 11,498 sales of apartments within walking distance to planned parks (as well as existing parks) were collected. These data were applied in an analysis comprising three categories describing different planning contexts for the parks: “comprehensive plans,” “implementation plans,” and “completed parks.” A set of explanatory variables representing housing, park, and neighborhood characteristics was selected, with additional remarks regarding the planning specifications that might influence apartment buyers’ perceptions, such as the park type and the age of a plan, as defined in th",102.0,4200fe81644f944eeadcdbef9deb3f1be4026fb701,10.1016/j.jue.2010.08.007,Maximum Likelihood Estimation and Lagrange Multiplier Tests for Panel Seemingly Unrelated Regressions with Spatial Lag and Spatial Errors: An Application to Hedonic Housing Prices in Paris,2010,Social Science Research Network,B. Baltagi; G. Bresson,This paper proposes maximum likelihood estimators for panel seemingly unrelated regressions with both spatial lag and spatial error components. We study the general case where spatial effects are incorporated via spatial errors terms and via a spatial lag dependent variable and where the heterogeneity in the panel is incorporated via an error component specification. We generalize the approach of Wang and Kockelman (2007) and propose joint and conditional Lagrange Multiplier tests for spatial autocorrelation and random effects for this spatial SUR panel model. The small sample performance of the proposed estimators and tests are examined using Monte Carlo experiments. An empirical application to hedonic housing prices in Paris illustrates these methods. The proposed specification uses a system of three SUR equations corresponding to three types of flats within 80 districts of Paris over the period 1990-2003. We test for spatial effects and heterogeneity and find reasonable estimates of the shadow prices for housing characteristics.,99.0,https://docs.iza.org/dp5227.pdf43doi_10_1108_14635789810221760,10.1108/14635789810221760,A hedonic price model of office rents,1998,Journal of Property Valuation and Investment,Neil Dunse; Colin Jones,"The primary objective of this study is to apply hedonic regression techniques to an office market to identify and quantify the significant contribution of the different attributes to office rents. This technique is widely used in the analysis of housing markets but an extensive literature review reveals little application in commercial property markets. The study analyses a sample of 477 asking rents, together with a series of locational and physical attributes, for the City of Glasgow. The results explain approximately 60 per cent of variation in rents across the city, emphasizing the importance of age and location as principal determinants of rents.",98.0,44https://openalex.org/W2735574852,10.1016/j.habitatint.2017.07.002,Spatial and hedonic analysis of housing prices in Shanghai,2017,Habitat International,Zezhou Huang; Ruishan Chen; Di Xu; Wei Zhou,,97.0,45doi_10_3141_2115_16,10.3141/2115-16,Effects of Transportation Accessibility on Residential Property Values,2009,Transportation Research Record: Journal of the Transportation Research Board,L. Miguel Martínez; José Manuel Viegas,"The aim of this paper is to examine the relationship between the availability of transportation infrastructure and services and the pattern of house prices in an urban area and to assess whether public investment in transportation can modify residential property values. This study was developed for the Lisbon, Portugal, metropolitan area (LMA) as part of a broader study that intends to develop new value-capture financing schemes for public transportation in the LMA. The paper focuses on three central municipalities in Portugal (Amadora, Lisbon, and Odivelas), where these effects could be more easily measured because of the existence of a significant variability of public transportation services. The paper tries to determine, with different spatial hedonic pricing models, the extent to which access to transportation infrastructure currently is capitalized into house prices and isolates the influence of three different transportation infrastructures: metro, rail, and road. The results suggest that the proximity to one or two metro lines leads to significant property value changes. Results further indicate that the classic hedonic price model (ordinary least-squares estimation) leads ",96.0,46doi_10_1111_j_1475_4959_2010_00358_x,10.1111/j.1475-4959.2010.00358.x,Amenities and disamenities: a hedonic analysis of the heterogeneous urban landscape in Shenzhen (China),2010,The Geographical Journal,WENDY Y CHEN; C Y JIM,"Landscape amenities and disamenities are important factors for households in making residence decision. This study presents a hedonic analysis of the amenity and disamenity effects arising from the heterogeneous urban landscape in a Chinese city. The sample is composed of 358 apartment characteristics and transaction data collected directly from home owners in the central built‐up area of Shenzhen. Four types of urban landscapes were included, namely urban parks, residential gardens, Shenzhen Bay, and urban villages. We applied a three‐dimensional model (availability, accessibility, and visibility) to estimate the amenity–disamenity effects of these urban landscape features. The results indicated that residential gardens were the most attractive landscape (an average increase of 17.2% of housing price) and urban villages had disamenity effects (a decrease of 3.72% for visibility and 2.5% for availability). The visibility of landscape was more valued than the accessibility. The lower weight accorded to the availability variable suggested: both benefits and possible negative impacts related to urban parks and Shenzhen Bay could be embodied in home buyers' behaviour; and the unavoidab",96.0,47533c2c721c2b35f202c1717973ea840a091e6823,10.1080/07474938.2014.944791,Hedonic Regressions and the Decomposition of a House Price Index into Land and Structure Components,2015,,W. Diewert; J. de Haan; R. Hendriks,,93.0,48https://openalex.org/W3172667994,10.1016/j.habitatint.2021.102374,"Addressing the macroeconomic and hedonic determinants of housing prices in Beijing Metropolitan Area, China",2021,Habitat International,Jinlong Duan; Guangjin Tian; Lan Yang; Tao Zhou,,86.0,497b29c36e620db272e042f7b9f343c676a2038678,10.2139/ssrn.3835931,Interpretable Machine Learning for Real Estate Market Analysis,2022,Social Science Research Network,Felix Lorenz; Jonas Willwersch; Marcelo Cajias; F. Fuerst,"Machine Learning (ML) excels at most predictive tasks but its complex nonparametric structure renders it less useful for inference and out-of sample predictions. This article aims to elucidate and enhance the analytical capabilities of ML in real estate through Interpretable ML (IML). Specifically, we compare a hedonic ML approach to a set of model-agnostic interpretation meth-ods. Our results suggest that IML methods permit a peek into the black box of algorithmic decision making by showing the web of associative relationships between variables in greater resolution. In our empirical applications, we confirm that size and age are the most important rent drivers. Further analysis reveals that certain bundles of hedonic characteristics, such as large apartments in historic buildings with balconies located in affluent neighborhoods, attract higher rents than adding up the contributions of each hedonic characteristic. Building age is shown to exhibit a U-shaped pattern in that both the youngest and oldest buildings attract the highest rents. Besides revealing valuable distance decay functions for spatial variables, IML methods",84.0,https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=383593150https://openalex.org/W2036354859,10.3846/1648-715x.2008.12.125-138,HEDONIC ANALYSIS OF PRICE IN THE ISTANBUL HOUSING MARKET,2008,International Journal of Strategic Property Management,Berna Keskin,"The purpose of this paper is to explore the factors that affect housing prices in Istanbul. A hedonic price model is employed in order to examine housing price determinants with respect to property characteristics, socio‐economic characteristics, neighbourhood quality characteristics, and locational factors. The results reveal that housing prices are affected by these factors: living area size, being in a low storey building, being in a secured site (with swimming pool and garage), and age of the building. In addition to these determinants, the length of time the inhabitants have lived in Istanbul, the average income of the household, neighbour satisfaction and earthquake risk of the area have effects on the residential prices in Istanbul. Further research is suggested by constructing a second model that includes neighbourhood dummy variables as a proxy for submarkets, and a multi‐level modelling framework will be employed in order to analyse the urban housing submarket system. Santrauka Šiame darbe siekiama išnagrinėti veiksnius, kurie daro įtaką būsto kainoms Stambule. Pa si tel kus hedoninį kainų modelį, tyrinėjami būsto kainas lemiantys veiksniai, atsižvelgiant į nekilnojamojo ",82.0,https://journals.vilniustech.lt/index.php/IJSPM/article/download/6761/5842513f8df2d3649e2138cb1c3f4664e236a6d4e282c6,10.1080/09599916.2019.1587489,A machine learning approach to big data regression analysis of real estate prices for inferential and predictive purposes,2019,Journal of Property Research,J. Pérez-Rave; J. C. Correa-Morales; Favián González-Echavarría,"ABSTRACT The hedonic price regressions have mainly been used for inference. In contrast, machine learning employed on big data has a great potential for prediction. To contribute to the integration of these two strategies, this article proposes a machine learning approach to the regression analysis of big data, viz. real estate prices, for both inferential and predictive purposes. The methodology incorporates a new procedure of selecting variables, called ‘incremental sample with resampling’ (MINREM). The methodology is tested on two cases. The first is data from web advertisements selling used homes in Colombia (61,826 observations). The second considers the data (58,888 observations) from a sample of the Metropolitan American Housing Survey 2011 obtained and prepared by a reference study. The methodology consists of two stages. The first chooses the important variables under MINREM; the second focuses on the traditional training and validation procedure for machine learning, adding three activities. In both test cases, the methodology shows its value for obtaining highly parsimonious and stable models for different sample sizes, as well as taking advantage of the inferential and ",82.0,52doi_10_1111_j_1467_8489_2009_00464_x,10.1111/j.1467-8489.2009.00464.x,"Capitalized amenity value of urban wetlands: a hedonic property price approach to urban wetlands in Perth, Western Australia*",2009,Australian Journal of Agricultural and Resource Economics,Sorada Tapsuwan; Gordon Ingram; Michael Burton; Donna Brennan,"Up to 60 per cent of potable water supplied to Perth, Western Australia, is extracted from the groundwater system that lies below the northern part of the metropolitan area. Many of the urban wetlands are groundwater‐dependent and excessive groundwater extraction and climate change have resulted in a decline in water levels in the wetlands. In order to inform decisions on conserving existing urban wetlands, it is beneficial to be able to estimate the economic value of the urban wetlands. Applying the Hedonic Property Price approach to value urban wetlands, we found that distance to the nearest wetland and the number of wetlands within 1.5 km of a property significantly influence house sales price. For a property that is 943 m away from the nearest wetland, which is the average distance to the wetland in this study, reducing the wetland distance by 1 m will increase the property price by AU$42.40. Similarly, the existence of an additional wetland within 1.5 km of the property will increase the sales price by AU$6976. For a randomly selected wetland, assuming a 20 ha isolated circular wetland surrounded by uniform density housing, the total sales premium to surrounding properties was",81.0,53https://openalex.org/W2073483673,10.1631/jzus.2005.a0907,"Hedonic price analysis of urban housing: An empirical research on Hangzhou, China",2005,Journal of Zhejiang University. Science A,Haizhen Wen; Shenghua Jia; Guo Xiao-yu,The hedonic price model is widely applied to study the urban housing market because of the heterogeneity of housing products. Literature indicated that the hedonic price theory mainly includes two parts: Lancaster's partiality theory and Rosen's characteristic market equilibrium analysis. This paper chose 18 characteristics as independent variables and set up a linear hedonic price model for Hangzhou City. The model was tested with 2473 housing samples and field survey data of 290 housing communities. This research found that 14 out of 18 characteristics had significant influence on housing price. They were classified into 5 groups according to their impact degree.,81.0,5414eecd7db66f7a02fa146490275ce97a19765a1a,10.5198/jtlu.v5i2.261,"The impact of a new light rail system on single-family property values in Charlotte, North Carolina",2012,,Si-Si Yan; Eric Delmelle; Michael Duncan,"This paper examines the impact of a new light rail system on single-family housing values in Charlotte, North Carolina, from 1997 to 2008. We use a Hedonic Price Analysis (HPA) to estimate how proximity to light rail, housing characteristics, and spatial components (at a block group level) affect single-family housing values. The same method is applied to each of the four time periods (t1, t2, t3, t4) that coincide with the pre-planning, planning, construction, and operation phase of the light rail system. We observe a trend that suggests a greater desirability to live closer to a light rail station as the transit system becomes operational.",79.0,https://www.jtlu.org/index.php/jtlu/article/download/261/24255d956659c01d343fed17ef54a0b1e248a34a32995,10.3846/ijspm.2018.5220,THE EFFECT OF URBAN GREEN SPACES ON HOUSE PRICES IN WARSAW,2018,International Journal of Strategic Property Management,R. Trojanek; Michał Głuszak; Justyna Tanas,"In the paper, we analysed the impact of proximity to urban green areas on apartment prices in Warsaw. The data-set contained in 43 075 geo-coded apartment transactions for the years 2010 to 2015. In this research, the hedonic method was used in Ordinary Least Squares (OLS), Weighted Least Squares (WLS) and Median Quantile Regression (Median QR) models. We found substantial evidence that proximity to an urban green area is positively linked with apartment prices. On an average presence of a green area within 100 meters from an apartment increases the price of a dwelling by 2,8% to 3,1%. The effect of park/forest proximity on house prices is more significant for newer apartments than those built before 1989. We found that proximity to a park or a forest is particularly important (and has a higher implicit price as a result) in the case of buildings constructed after 1989. The impact of an urban green was particularly high in the case of a post-transformation housing estate. Close vicinity (less than 100 m distance) to an urban green increased the sales prices of apartments in new residential buildings by 8,0–8,6%, depending on a model.",77.0,https://journals.vgtu.lt/index.php/IJSPM/article/download/5220/4511569f54d680959ac9d4fcb8cc9685e7ba284a46863e,10.1016/j.habitatint.2020.102309,Unraveling the impact of TOD on housing rental prices and implications on spatial planning: A comparative analysis of five Chinese megacities,2021,,Shiliang Su; Jiangyue Zhang; Shen-Jing He; Hui Zhang; Li-Rong Hu; Meng-Jun Kang,"Abstract Transit Oriented Development (TOD), as a widely practiced planning strategy toward urban sustainability, commonly refers to the integration of transport and land use in the form of an integrated transit station area surrounded by compact urban development and high-quality walkable environment. Although policymakers are very enthusiastic about the potential of TOD in boosting the development of real estate market and livable neighborhoods, how TOD characteristics affect housing rental prices has not well been gauged with empirical data. Taking advantage of online housing platforms, this paper attempts to fill this gap through explicitly unraveling the impact of TOD on housing rental prices across five major Chinese megacities (Beijing, Shanghai, Shenzhen, Hangzhou and Wuhan). We first propose a conceptual framework to explain why and how TOD impacts housing rental prices. TODs are then delineated in the five megacities and T-test confirms that TOD housing properties present significant higher rental prices than non-TOD ones. Spatial hedonic modeling is employed to identify the relationship between TOD characteristics (e.g., metro station, neighborhood and synergy) and housi",75.0,https://doi.org/10.1016/j.habitatint.2020.1023095732007d35f6d268c7eddb9da425d9ab76c27790d5,10.3390/su11061741,Daily Accessed Street Greenery and Housing Price: Measuring Economic Performance of Human-Scale Streetscapes via New Urban Data,2019,Sustainability,Yu Ye; Hanting Xie; Jia Fang; Hetao Jiang; De Wang,"The protective effects of street greenery on ecological, psychological, and behavioral phenomena have been well recognized. Nevertheless, the potential economic effect of daily accessed street greenery, i.e., a human-scale and perceptual-oriented quality focusing on exposure to street greenery in people’s daily lives, has not been fully studied because a quantitative measuring of this human-scale indicator is hard to achieve. This study was an attempt in this direction with the help of new urban data and new analytical tools. Shanghai, which has a mature real estate market, was selected for study, and the housing prices of 1395 private neighborhoods in its city center were collected. We selected more than forty variables that were classified under five categories—location features, distances to the closest facilities, density of facilities within a certain radius, housing and neighborhood features, and daily accessed street greenery—in a hedonic pricing model. The distance and density of facilities were computed through a massive number of points-of-interest and a geographical information system. The visible street greenery was collected from Baidu street view images and then measu",74.0,https://www.mdpi.com/2071-1050/11/6/1741/pdf?version=155349255058https://openalex.org/W2146903892,10.1787/5kghzxpt6g6f-en,Hedonic Price Indexes for Housing,2011,OECD statistics working papers,Robert Hill,"Every house is different. It is important that house price indexes take account of these quality differences. Hedonic methods which express house prices as a function of a vector of characteristics (such as number of bedrooms and bathrooms, land area and location) are particularly useful for this purpose. In this report I consider some of the developments in the hedonic methodology, as it is applied in a housing context, that have occurred in the last three decades. A number of hedonic house price indexes are now available. However, it is often difficult to see how these indexes relate to each other. For this reason the paper attempts to impose some structure on the literature by developing a taxonomy of hedonic methods, and then show how existing methods fit into this taxonomy. Also discussed are some promising areas for future research in the hedonic field, particularly the use of geospatial data and nonparametric methods for better capturing the impact of location on house prices. The main criticisms of the hedonic approach are evaluated and compared with the repeat sales and stratified median methods. The overall conclusion is that the advantages of the hedonic approach outweig",74.0,https://www.oecd-ilibrary.org/hedonic-price-indexes-for-housing_5kghzxpt6g6f.pdf?itemId=%2Fcontent%2Fpaper%2F5kghzxpt6g6f-en&mimeType=pdf59doi_10_1111_j_1467_8489_2009_00483_x,10.1111/j.1467-8489.2009.00483.x,Flood prone risk and amenity values: a spatial hedonic analysis,2010,Australian Journal of Agricultural and Resource Economics,Oshadhi Samarasinghe; Basil Sharp,"This study examines the impact of flood‐hazard zone location on residential property prices. The study utilises data from over 2000 private residential property sales occurred during 2006 in North Shore City, New Zealand. A spatial autoregressive hedonic model is developed to provide efficient estimates of the marginal effect of flood prone risks on property prices. Results suggest that the sale price of a residential property within a flood prone area is lower than an equivalent property outside the flood prone area. The flood plain location discount is reduced by the release of public information regarding flood risk.",70.0,6094fbafbf54ef86d253f2f443242c534210a408bb,10.3390/ijgi6110358,Exploring Determinants of Housing Prices in Beijing: An Enhanced Hedonic Regression with Open Access POI Data,2017,ISPRS Int. J. Geo Inf.,Yixiong Xiao; Xiang Chen; Qiang Li; Xi Yu; Jin Chen; Jing Guo,"The housing market in Chinese metropolises have become inflated significantly over the last decade. In addition to an economic upturn and housing policies that have potentially fueled the real estate bubble, factors that have contributed to the spatial heterogeneity of housing prices can be dictated by the amenity value in the proximity of communities, such as accessibility to business centers and transportation hubs. In the past, scholars have employed the hedonic pricing model to quantify the amenity value in relation to structural, locational, and environmental variables. These studies, however, are limited by two methodological obstacles that are relatively difficult to overcome. The first pertains to difficulty of data collection in regions where geospatial datasets are strictly controlled and limited. The second refers to the spatial autocorrelation effect inherent in the hedonic analysis. Using Beijing, China as a case study, we addressed these two issues by (1) collecting residential housing and urban amenity data in terms of Points of Interest (POIs) through web-crawling on open access platforms; and (2) eliminating the spatial autocorrelation effect using the Eigenvector ",69.0,https://www.mdpi.com/2220-9964/6/11/358/pdf?version=15107613886181a04e1846b05e56d8bfbaaa1a71fdc6101f269a,10.1016/j.compenvurbsys.2013.01.001,Boosting the predictive accuracy of urban hedonic house price models through airborne laser scanning,2013,"Computers, Environment and Urban Systems",M. Helbich; A. Jochem; Werner Mücke; B. Höfle,"This paper introduces an integrative approach to hedonic house price modeling which utilizes high density 3D airborne laser scanning (ALS) data. In general, it is shown that extracting exploratory variables using 3D analysis – thus explicitly considering high-rise buildings, shadowing effects, etc. – is crucial in complex urban environments and is limited in well-established raster-based modeling. This is fundamental in large-scale urban analyses where essential determinants influencing real estate prices are constantly missing and are not accessible in official and mass appraiser databases. More specifically, the advantages of this methodology are demonstrated by means of a novel and economically important externality, namely incoming solar radiation, derived separately for each flat. Findings from an empirical case study in Vienna, Austria, applying a non-linear generalized additive hedonic model, suggest that solar radiation is significantly capitalized in flat prices. A model comparison clearly proves that the hedonic model accounting for ALS-based solar radiation performs significantly superior. Compared to a model without this externality, it increases the model’s explanatory",68.0,https://www.sciencedirect.com/science/article/pii/S0198971513000021/pdf6292adc3800ede8fb7f518a0daf2ec05f5a0f71e8f,10.1016/j.tra.2018.07.015,The impact of accessibility by public transport on real estate values: A comparison between the cities of Rome and Santander,2019,Transportation Research Part A: Policy and Practice,Rubén Cordera; P. Coppola; L. dell'Olio; Angel Ibeas,"Abstract Empirical evidence supports the hypothesis that greater accessibility to opportunities can have a positive impact on real estate values. However, this capitalisation of the benefits of accessibility could vary between different study areas. This research estimates hedonic and spatial hedonic models in two urban areas to compare if differences can be found in the impact accessibility using public transport has on residential property values. The two study areas chosen for comparison are a medium sized city without any major mobility problems (Santander, Spain) and a very large city with major congestion problems (Rome, Italy). The estimated hedonic models have considered the possible presence of spatial effects, a common occurrence with real estate data which may generate dependency in the residuals of hedonic models. Accessibility has been measured using two types of indicators: relative and gravity based. The results confirm that accessibility was a positive factor on property prices in both cities, although in Santander this was only true using the relative indicator to the city centre. These results are relevant for supporting the introduction of value capture policies ",67.0,http://hdl.handle.net/10902/18146633c3cee5be2c3e34192bd9f0eb856c38c4a3b7dfe,10.1016/j.ecolecon.2016.12.014,Modeling the Property Price Impact of Water Quality in 14 Chesapeake Bay Counties,2017,,P. Walsh; C. Griffiths; D. Guignet; H. Klemick,"The Chesapeake Bay and its tributaries provide a range of recreational and aesthetic amenities, such as swimming, fishing, boating, wildlife viewing, and scenic vistas. Living in close proximity to the Bay improves access to these amenities and should be capitalized into local housing markets. We investigate these impacts in the largest hedonic analysis of water quality ever completed, with over 200,000 property sales across 14 Maryland counties. We use a spatially explicit water quality dataset, along with a wealth of landscape, economic, geographic, and demographic variables. These data allow a comprehensive exploration of the value of water quality, while controlling for a multitude of other influences. We also estimate several variants of the models most popular in current literature, with a focus on the temporal average of water quality. In comparing 1 year and 3 year averages, the 3 year averages generally have a larger implicit price. Overall, results indicate that water quality improvements in the Bay, such as those required by EPA’s Total Maximum Daily Load, could yield significant benefits to waterfront and near-waterfront homeowners.",66.0,http://ageconsearch.umn.edu/record/28093064115590307d7614e58b0632f3f2d7d95d56e44b06,10.1016/j.landurbplan.2010.01.003,The value of public and private green spaces under water restrictions.,2010,,D. MacDonald; N. Crossman; P. Mahmoudi; Laura O. Taylor; D. Summers; P. Boxall,"Numerous studies have been published that consider the relationship between open spaces and property values. In this study, we examine the potential impact of water restrictions on the value of different types of green space. Restrictions on the use of water on outdoor areas are a popular means for governments or utilities to limit water use in urban areas. In this paper, a hedonic pricing model is used to analyse the effects that increasingly severe water restrictions might have on the perceived value of public and private green spaces in Adelaide, South Australia. A hedonic pricing model is estimated that contains housing characteristics, neighbourhood amenities, fixed effects to control for unobserved neighbourhood characteristics and temporal control variables for inflation. The findings suggest that water restrictions are not having a significant impact of the value of outdoor spaces on private properties. There are indications that substitutions may be occurring with the proximity to playgrounds, which are watered more regularly, becoming significant with increasing severity of water restrictions. However, close proximity to large public parks with trails for walking which re",65.0,https://figshare.com/articles/journal_contribution/The_value_of_public_and_private_green_spaces_under_water_restrictions/2292870265189b47b9aba8e6b396e9b904d6c9b1ed0fd64137,10.1016/j.apgeog.2021.102474,"Are people happier in locations of high property value? Spatial temporal analytics of activity frequency, public sentiment and housing price using twitter data",2021,Applied Geography,Mark Junjie Tan; Cheng-He Guan,"Abstract The rise of social networking platforms provides opportunities to examine the relationship between public emotion and housing price. This study investigates frequency and places of visits, population sentiment, and housing price using 8.7 million tweets retrieved from Manhattan, New York City in 2019. We implemented kernel density estimation, Getis-Ord Gi hot spot analysis, and spatial lagged hedonic pricing models to identify the location variation of sentiment levels. The results show: (1) the spatial clustering of tweets frequency was highly related to land use types in places such as parks, financial districts, and train stations; (2) high sentiment levels coincided with high frequency clusters and higher positive sentiment is associated with higher housing price; and (3) sentiment level was significantly associated with housing price and building structure, amenities, and proximity to landmarks all had significant influences on housing price. The study indicates that a population with higher concentration of happiness correlates to higher property value and provides an innovative perspective to understand public sentiment in relation to housing price using social medi",65.0,https://www.sciencedirect.com/science/article/pii/S0143622821000904/pdf66doi_10_1007_bf01257055,10.1007/bf01257055,Valuation of education and crime neighborhood characteristics through hedonic housing prices,1982,Population and Environment,Robin A. Dubin; Allen C. Goodman,,65.0,670462b0d87ab72b3c90375cd7f1b22600ca9530ef,10.3386/w24826,Sorting or Steering: The Effects of Housing Discrimination on Neighborhood Choice,2018,,P. Christensen; Christopher Timmins,"Housing discrimination is illegal. However, paired-tester audit experiments have revealed evidence of discrimination in the interactions between potential buyers and real estate agents, raising concern about whether certain groups are systematically excluded from the beneficial effects of healthy neighborhoods. Using data from HUD’s most recent Housing Discrimination Study and micro-level data on key attributes of neighborhoods in 28 US cities, we find strong evidence of discrimination in the characteristics of neighborhoods towards which individuals are steered. Conditional upon the characteristics of the house suggested by the audit tester, minorities are significantly more likely to be steered towards neighborhoods with less economic opportunity and greater exposures to crime and local pollutants. We find that holding locational preferences or income constant, discriminatory steering alone can contribute substantially to the disproportionate number of minority households found in high poverty neighborhoods in the United States. The steering effect is also large enough to fully explain the differential in proximity to Superfund sites among African American mothers. These results ",64.0,https://doi.org/10.3386/w248266827f607f5625634531b0f4d7b0bff5ac0eef6f1cf,10.1002/cpe.7342,House price prediction using hedonic pricing model and machine learning techniques,2022,Concurrency and Computation,John F. W. Zaki; Anand Nayyar; Surjeet Dalal; Z. H. Ali,"The problem with property valuation is that it is extremely complex. It is difficult to objectively model the pricing process or fairly estimate a property value. Many factors can contribute to this complexity such as spatial and time factors. Evaluators and researchers have been trying to model the process for centuries. Up until recently, when computer‐aided valuation systems provided better solutions in the data evaluation and real estate valuation. Nevertheless, they may suffer from low transparency, inaccuracy, and inefficiency. This work explores the ability of machine learning techniques (MLTs) in enhancing economic activities by increasing the accuracy of house price prediction. In this article, XGBoost algorithm has been integrated with outlier sum‐statistic (OS) approach. In the real estate industry, the price of property plays a crucial role in economic growth. The research attempts to predict the price of a house using MLTs. Here, the price of the property is predicted using Extreme Gradient (XG) boosting algorithm and hedonic regression pricing. Both XGBoost and hedonic pricing models use 13 variables as inputs to predict house prices. The contribution of this research",64.0,69doi_10_3141_1617_05,10.3141/1617-05,Measuring the Impact of Light Rail Systems on Single-Family Home Values: A Hedonic Approach with Geographic Information System Application,1998,Transportation Research Record: Journal of the Transportation Research Board,Hong Chen; Anthony Rufolo; Kenneth J. Dueker,"In theory, proximity to light rail transit (LRT) may have two different effects on residential property values. On the one hand, accessibility (proximity to LRT stations) may increase property values. On the other hand, nuisance effects (proximity to the LRT line and stations) may decrease property values. Existing empirical studies are inconclusive, and failure to separate the effects of accessibility from the nuisance effects may explain some of the ambiguity. An examination is presented of the impact of the light rail system (MAX) in Portland, Oregon, on single-family home values using distance to rail stations as a proxy for accessibility and distance to the line itself as a proxy for nuisance effects. Geographic information system techniques are employed to create spatial-related variables and merge data from various sources. The study results confirm the hypothesis that the light rail has both a positive effect (accessibility effect) and a negative effect (nuisance effect) on single-family home values. The positive effect dominates the negative effect, which implies a declining price gradient as one moves away from LRT stations for several hundred meters. Without controlling ",62.0,704c53c838b261f766e30461ed3f7727eff8ab53bd,10.1016/j.ufug.2020.126968,Do landscape amenities impact private housing rental prices? A hierarchical hedonic modeling approach based on semantic and sentimental analysis of online housing advertisements across five Chinese megacities,2021,,Shiliang Su; Shen-Jing He; Chenxi Sun; Hui Zhang; Li-Rong Hu; Meng-Jun Kang,"Abstract Real estate premium associated with landscape amenities is a well-studied topic with a primary focus on housing prices. Presumably, the willingness-to-pay for landscape amenities should be very different between homeowners and tenants. Thus far, how landscape amenities affect residential rental prices is not well understood. This paper takes advantage of the big data of online housing advertisements to unravel how landscape amenities are capitalized into rental prices across five Chinese megacities (Beijing, Shanghai, Shenzhen, Hangzhou and Wuhan). Natural language processing, the latent Dirichlet allocation in particular, is first employed to semantically analyze the geo-textual advertisements. It reveals that ‘landscape amenities’ is a typical topic and ‘park’ is a typical component for housing advertisements in the five megacities. The lexicon-based sentimental analysis further shows that the strength of the sentiments associated with the ‘landscape amenities’ varies with cities. A series of hierarchical hedonic models based on the extracted semantic and sentimental aspects are then established for each megacity after segmenting the rental market into submarkets. The ca",61.0,https://doi.org/10.1016/j.ufug.2020.12696871e71760b25631f15b2ea003f09c4561c103cee9cd,10.1016/j.ufug.2020.126643,The capitalized amenity of green infrastructure in single-family housing values: An application of the spatial hedonic pricing method,2020,,Wonmin Sohn; Hyun Kim; Jun-Hyun Kim; Ming-Han Li,"Abstract The environmental benefits of having retention/detention ponds as major stormwater management facilities in a neighborhood have been well documented since the adoption of green infrastructure strategies in early 1990s. However, the capitalization effect of stormwater treatment ponds in real estate values still remains unclear. This study developed classic hedonic pricing and spatial econometric models to examine the capitalization effects of neighborhood-level detention and retention ponds using both cross-sectional and longitudinal housing prices. The housing market value from 2007 to 2016 was assessed in four subdivisions in Houston, Texas. A subdivision, located in the upper neighborhood, had retention ponds which were converted from detention ponds in 2011, while three subdivisions in the lower neighborhood had detention ponds over the same study period. The study results show that living near retention ponds has positive capitalization impacts on single-family housing prices, not only cross-sectionally but also longitudinally. In contrast, maintaining detention ponds depreciates housing values, and living nearby lowers the price increase over a decade. The findings in",61.0,7212b4963bb172fda67892a04e3394ee9a51acfa8f,10.1016/j.sbspro.2015.01.069,Sustainable Urban Regeneration: GIS and Hedonic Pricing Method in Determining the Value of Green Space in Housing Area,2015,,N. M. Noor; M. Asmawi; Alias Abdullah,"Abstract 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 an 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.",60.0,https://www.sciencedirect.com/science/article/pii/S1877042815000841/pdf730a14f4d05e3188bbfdf21ba4b01775bf34ad8efd,10.1080/09599916.2022.2070525,House price prediction with gradient boosted trees under different loss functions,2022,Journal of Property Research,A. Hjort; J. Pensar; I. Scheel; D. E. Sommervoll,"ABSTRACT Many banks and credit institutions are required to assess the value of dwellings in their mortgage portfolio. This valuation often relies on an Automated Valuation Model (AVM). Moreover, these institutions often report the models accuracy by two numbers: The fraction of predictions within and range from the true values. Until recently, AVMs tended to be hedonic regression models, but lately machine learning approaches like random forest and gradient boosted trees have been increasingly applied. Both the traditional approaches and the machine learning approaches rely on minimising mean squared prediction error, and not the number of predictions in the and range. We investigate whether introducing a loss function closer to the AVMs actual loss measure improves performance in machine learning approaches, specifically for a gradient boosted tree approach. This loss function yields an improvement from to of predictions within of the true value on a data set of transactions from the Norwegian housing market between 2013 and 2015, with the biggest improvements in performance coming from the lower price segments. We also find that a weighted average of models with different loss f",59.0,https://www.tandfonline.com/doi/pdf/10.1080/09599916.2022.2070525?needAccess=true748ed28a93a8c3390974e66a132ecf943129cc00ae,10.3390/land12040740,The Use of Machine Learning in Real Estate Research,2023,Land,L. Choy; Winky K.O. Ho,"This research seeks to demonstrate how machine learning, a branch of artificial intelligence, is able to deliver more accurate pricing predictions, using the real estate market as an example. Utilizing 24,936 housing transaction records, this paper employs Extra Trees (ET), k–Nearest Neighbors (KNN), and Random Forest (RF) to predict property prices and then compares their results with those of a hedonic price model. In particular, this paper uses a feature (property age x square footage) instead of property age in order to isolate the effect of land depreciation on property prices. Our results suggest that these three algorithms markedly outperform the traditional statistical techniques in terms of explanatory power and error minimization. Machine learning is expected to play an increasing role in shaping our future. However, it may raise questions about the privacy, fairness, and job displacement issues. It is therefore important to pay close attention to the ethical implications of machine learning and ensure that the technology is used responsibly and ethically. Researchers, legislators, and industry players must work together to create appropriate standards and legislation to ",59.0,https://www.mdpi.com/2073-445X/12/4/740/pdf?version=1679729459752def53551f0b77c0d6c9fbd5809017b264dd8b37,10.3390/su10072254,"Subway Opening, Traffic Accessibility, and Housing Prices: A Quantile Hedonic Analysis in Hangzhou, China",2018,Sustainability,Hai-Zhen Wen; Zaiyuan Gui; Chuan-Hao Tian; Yue Xiao; Li Fang,"Most existing studies empirically investigated the impact of rail transit on housing prices using the traditional hedonic price model, which is based on ordinary least squares (OLS). This method can estimate only the average implicit prices of housing characteristics and may ignore possible heterogeneous impacts of rail transit at different housing price levels. As a useful supplement to OLS regression, quantile regression can measure how implicit prices of explanatory variables vary across different price levels, thereby providing a comprehensive picture of the relationship between housing characteristics and prices. By using Hangzhou, China as an example, this study adopts the traditional hedonic price model and quantile regression model to investigate the capitalization effect of a new subway line on housing prices. Empirical results suggest the significant impacts of accessibility to subway stations. The average housing price within 2 km of the station is 2.1% to 6.1% higher than those outside. We also find that the impacts of the subway differ significantly across the distribution of housing prices, wherein the absolute value of estimated coefficients increased from 0.023 for ",58.0,https://www.mdpi.com/2071-1050/10/7/2254/pdf?version=153033330376785b667fea806d3201075b6a22735a5107b1764b,10.3390/jrfm14030108,Housing Market in the Time of Pandemic: A Price Gradient Analysis from the COVID-19 Epicentre in China,2021,Journal of Risk and Financial Management,Ka-Shing Cheung; Chung Yim Edward Yiu; Chuyi Xiong,"While the outbreak of the COVID-19 disease has caused asset markets to experience an unprecedented spike of risk and uncertainty worldwide, the real estate market in many global cities appears to be immune to the adverse effects. How does COVID-19 affect urban housing markets? This study is a first attempt to identify the pandemic’s impact on house prices by applying a price gradient analysis to the COVID-19 epicentre in China. Considering microlevel housing transaction data in 62 areas from nine districts in Wuhan City from January 2019 to July 2020, the hedonic pricing and the price gradient models suggest that there was, respectively, a 4.8% and a 5.0–7.0% year-on-year fall in house prices immediately after the pandemic outbreak. Although house prices rebounded after the lockdown period, the gradient models show that the price gradients were flattened from the epicentre to the urban peripherals. The price premiums in high-density areas were also substantially discounted after the city’s lockdown. Our findings are robust to different model specifications. The implication is that the risk associated with the pandemic is localised and transitory in nature. People may be able to int",58.0,https://www.mdpi.com/1911-8074/14/3/108/pdf?version=16149447187771cf08b7d5a393eff36a9fc1961b4497a5a0639e,10.1016/j.tranpol.2016.04.016,Transit premium and rent segmentation: A spatial quantile hedonic analysis of Shanghai Metro,2016,,Yiming Wang; Su-Wei Feng; Zhongwei Deng; Shuangyu Cheng,"When measuring the betterment effect of public transit, most of the existing econometric research tends to use residential property price data and to focus on the conditional mean rather than the conditional variance in terms of the implicit price premium paid for access to public transit. However, because property sale price partly reflects speculation on future capital gains, it sheds little light on the renters' willingness-to-pay for living near public transportation facilities, let alone the variation in rent premium for transit proximity. We in this paper employ a spatial quantile hedonic regression method to gauge the rental impact of metro stations on a large sample of two-bedroom-one-bathroom (2b1b) apartments across 2575 residential complex communities (or “xiaoqu” in mandarin Chinese) in Shanghai, China, as observed between December 2012 and January 2013. We find: a) a community’s geographic adjacency to the nearest Shanghai Metro station tends to correlate positively with the xiaoqu’s average asking rent of 2b1b apartments, indicating a significant rent premium for transit proximity; b) although the transit premium fluctuates across the different rent levels, the variat",57.0,https://research-information.bris.ac.uk/en/publications/e7e501c6-906d-4307-a598-1155f55bb67878doi_10_1080_0042098975691,10.1080/0042098975691,The Choice of Functional Form and Variables in the Hedonic Price Model in Seoul,1997,Urban Studies,Serim Huh; Seung-Jun Kwak,"This study demonstrates that the important part of exploring the proper functional form of the hedonic price model would include investigating a dissimilar and unique hedonic price structure when the hedonic price model is applied to different housing markets. Based on the adjustment to the usual technique necessitated by the regional and cultural setting of Seoul, the criteria for significance of implicit price, root-mean-square-percentage-error, and the log-likelihood ratio test are applied to the choice of a useful functional form. We conclude that investigating the structure of a local housing market and choosing proper variables reflecting regional and cultural characteristics, both key parts of such a study, require significant adjustment to the reality of Seoul.",57.0,79https://openalex.org/W1220857210,10.1007/s11146-015-9520-5,Estimating School Proximity Effects on Housing Prices: the Importance of Robust Spatial Controls in Hedonic Estimations,2015,The Journal of Real Estate Finance and Economics,Vivek Sah; Stephen J. Conroy; Andrew Narwold,,57.0,80https://openalex.org/W1530358632,10.57938/e55da0fe-d130-415d-9a5d-7bbc07c329a1,The Hedonic Price Method in Real Estate and Housing Market Research: A Review of the Literature,2010,Research Online (University of Wollongong),Shanaka Herath; Günther Maier,"The Hedonic Price Method (HPM), also known as hedonic regression, is used for estimating the value of a commodity or the demand for a commodity. The HPM has been extensively used in real estate and housing market research in the recent past. In this paper, we discuss theoretical and methodological developments related to hedonic regression and undertake an examination of use of this methodology in the recent real estate and housing literature. We first define the HPM, and explain the fundamentals behind the methodology. The idea behind the HPM is that the commodities are characterized by their constitute properties, hence the value of a commodity can be calculated by adding up the estimated values of its separate properties. In the second part of the paper, we emphasise that the heterogeneous nature of real estate property justifies the use of HPM for estimating their value or demand. We also take a stock of most cited empirical studies on real estate and housing using the HPM, and classify those into several categories. The classification indicates that neighbourhood characteristics of real estate are relatively over-researched as a determinant of price or rent. It also shows that",55.0,https://ro.uow.edu.au/buspapers/97181b3ec523ce2f4119ea59d806bdaeb62c8215fe9a8,10.1016/j.ecolecon.2016.04.016,The implicit value of tree cover in the U.S.: A meta-analysis of hedonic property value studies,2016,,S. D. Siriwardena; K. Boyle; T. Holmes; P. Wiseman,"Trees in residential neighborhoods and communities provide benefits for homeowners that are capitalized into residential property values. In this paper, we collected data from hedonic property value studies and merged these data with ancillary spatial data describing forest and socio-economic characteristics surrounding each study area to conduct a meta-analysis of the impact of tree canopy cover on the value of residential properties. The meta-analysis suggests that property-level tree cover of about 30% and county-level tree cover of about 38% maximize the implicit price of tree cover in property values. Currently, tree cover in the original study areas was about 14%, on average, around or near study properties. The empirical results, therefore suggest under investment of tree cover on private property from the perspective of individual property owners and from a societal perspective. The findings also have implications for community forest programs regarding planting trees and protection of mature trees to address potential changes in tree abundance, species diversity and stand age due to development and climate change.",55.0,https://vtechworks.lib.vt.edu/bitstream/10919/97854/1/1-s2.0-S0921800916304293-main.pdf82doi_10_3141_2038_15,10.3141/2038-15,Rail Transit and Residential Land Use in Developing Countries,2007,Transportation Research Record: Journal of the Transportation Research Board,Saksith Chalermpong,"The effects of public transit improvements on residential land use in general, and on residential property prices in particular, have not been well investigated in developing countries. Such an understanding is necessary for the formulation of value capture policies, which can be instrumental in the financing of transit infrastructure. In this paper past studies on the effect of transit improvements on property prices in developing countries are reviewed, and the hedonic models are developed to examine this relationship in Bangkok, Thailand. Spatial regression models are estimated with data on multifamily residential properties near the Bangkok transit system's stations. Estimation results show that the premium of transit accessibility is approximately $10 for every meter closer to a station, and the price elasticity with respect to the distance to the nearest station is roughly −0.09. These findings are consistent with the range found in past studies from other developing countries. The substantial premium of transit accessibility implies that there is a great potential for the use of value capture policies to raise additional funds for investments in Bangkok's transit system.",55.0,83b121420dcb875a5d76f925fc24cb35e5144952a8,10.3390/ijgi8060249,An Application of the Spatial Autocorrelation Method on the Change of Real Estate Prices in Taitung City,2019,ISPRS Int. J. Geo Inf.,Wen-Ching Wang; Yu-Ju Chang; Hsueh-Ching Wang,"The main purpose of this paper is to use regression models to explore the factors affecting housing prices as well as apply spatial aggregation to explore the changes of urban space prices. This study collected data in Taitung City from the year 2013 to 2017, including 3533 real estate transaction price records. The hedonic price method, spatial lag model and spatial error model were used to conduct global spatial self-correlation tests to explore the performance of house price variables and space price aggregation. We compare the three models by R² and Akaike Information Criterion (AIC) to determine the spatial self-correlation ability performance, and explore the spatial distribution of prices and the changes of price regions from the regional local indicators of spatial association spatial distribution map. Actual analysis results show an improvement in the ability to interpret real estate prices through the feature price mode from the R² value assessment, the spatial delay model and the spatial error model. Performance from the AIC values show that the difference of the spatial delay model is smaller than that of the feature price model and the spatial model, demonstrating a be",54.0,https://www.mdpi.com/2220-9964/8/6/249/pdf?version=15615440028412ff1a3635d6a4f3f37d0eb8f15532fcfcd91dc7,10.1016/j.landurbplan.2018.11.002,Does converting abandoned railways to greenways impact neighboring housing prices?,2019,Landscape and Urban Planning,Youngre Noh,"Abstract This research examines the housing market before and after abandoned railways are converted into greenways. Two different hedonic pricing models are employed to analyze changes in the impact and trend of the change—spatial regressions for before and after the conversion and the Adjusted Interrupted Time Series-Difference in Differences (AITS-DID) model. Analyzing 2005–2012 single-family home sale transactions in the City of Whittier, California the results show that converting the abandoned railway into a greenway increases property values. Upon the completion of the greenway, the positive association with the greenway proximity increased in both models. The premium also exists in the pre-conversion period. The sellers’ and buyers’ expectation of the greenway being an amenity factored into the housing market even during the construction of the greenway. After the conversion, properties near the greenway experienced a negative trend in their value.",54.0,85doi_10_1068_a160389,10.1068/a160389,The Demand for Local Amenity: An Hedonic Price Analysis,1984,Environment and Planning A: Economy and Space,P B McLeod,"In this paper the author investigates the demand for housing characteristics and proximity to local amenities in Perth, Western Australia. By application of hedonic price theory to a sample of house transactions the implicit prices for individual characteristics are estimated and used to estimate inverse demand curves for these characteristics in a second stage analysis. The results confirm the importance of proximity of river, parks, and highways in determining house prices. River views are found to be particularly important being valued at 28% of average selling price. From the inverse demand curves income elasticities of willingness to pay are found to range from 1.0 for age of house to 0.43 for proximity to the river.",54.0,862114280dfee3fff9589a23f49f10ea5ae9717da5,10.1016/j.jtrangeo.2017.05.002,"Anticipation and post-construction impact of a metro extension on residential values: The case of Laval (Canada), 1995–2013",2017,,N. Devaux; Jean Dubé; P. Apparicio,"The application of hedonic pricing models has a long history in estimating the externalities associated with urban infrastructure, such as public transportation. However, results accuracy crucially depends on methodological and empirical considerations such as: i) presence of spatial latent component (spatial autocorrelation); ii) temporal breaks related to different periods over which the infrastructure is built; and iii) heterogeneity of the effect along the line and stations. This paper aims to assess the impact of Montreal's metro extension to the suburb city of Laval (announced in 1998 and started operating in 2007). A spatial difference-in-difference (SDID) estimator based on a repeated sales approach is used to isolate the impact of the proximity to the new infrastructure on single-family house prices depending on the implementation phases and the stations. The results suggest that among the three new infrastructures, only one shows a positive impact of proximity after the first operation of the transit service. The study results tend to relativize the sometimes high expectations in terms of economic impacts of such a project, at least for residential properties.",53.0,https://espace.inrs.ca/id/eprint/5148/1/devaux-2017-anticipation.pdf87https://openalex.org/W2063469316,10.2307/2109495,"Search, Hedonic Prices and Housing Demand",1992,The Review of Economics and Statistics,Sunwoong Kim,"The conventional model of the housing market does not take into account the search process for a suitable housing unit. Based on a dynamic search theory, this paper develops and estimates a truncated regression model of the rental housing market with stochastic and unobserved truncation points. The author's model provides a joint estimation of the hedonic rice and the reservation rent equations. The results turn out to be superior to the ordinary least squares estimates of either the traditional housing demand function or the hedonic price equation. Copyright 1992 by MIT Press.",52.0,88https://openalex.org/W2086455107,10.1080/17421772.2011.647058,"Spatial Interactions in Hedonic Pricing Models: The Urban Housing Market of Aveiro, Portugal",2012,Spatial Economic Analysis,Arnab Bhattacharjee; Eduardo Castro; João Lourenço Marques,"Spatial heterogeneity, spatial dependence and spatial scale constitute key features of spatial analysis of housing markets. However, the common practice of modelling spatial dependence as being generated by spatial interactions through a known spatial weights matrix is often not satisfactory. While existing estimators of spatial weights matrices are based on repeat sales or panel data, this paper takes the approach to a cross-section setting. Specifically, based on an a priori definition of housing submarkets and the assumption of a multifactor model, we develop maximum likelihood methodology to estimate hedonic models that facilitate understanding of both spatial heterogeneity and spatial interactions. The methodology, based on statistical orthogonal factor analysis, applied to the urban housing market of Aveiro (Portugal) at two different spatial scales, provides exciting inferences on the spatial structure of the housing market. RÉSUMÉ L'hétérogénéité spatiale, la dépendance spatiale et l’échelle spatiale sont des caractéristiques clé de l'analyse spatiale dans les marchés de l'immobilier. Toutefois, la pratique habituelle de la modélisation de la dépendance spatiale comme étant",51.0,898564e4b728dd78f29cb312a5df0919573806bcac,10.3390/land10050533,Understanding the Effects of Influential Factors on Housing Prices by Combining Extreme Gradient Boosting and a Hedonic Price Model (XGBoost-HPM),2021,Land,Sheng Li; Yi Jiang; Shui-Song Ke; Ke Nie; Chao Wu,"The characteristics of housing and location conditions are the main drivers of spatial differences in housing prices, which is a topic attracting high interest in both real estate and geography research. One of the most popular models, the hedonic price model (HPM), has limitations in identifying nonlinear relationships and distinguishing the importance of influential factors. Therefore, extreme gradient boosting (XGBoost), a popular machine learning technology, and the HPM were combined to analyse the comprehensive effects of influential factors on housing prices. XGBoost was employed to identify the importance order of factors and HPM was adopted to reveal the value of the original non-market priced influential factors. The results showed that combining the two models can lead to good performance and increase understanding of the spatial variations in housing prices. Our work found that (1) the five most important variables for Shenzhen housing prices were distance to city centre, green view index, population density, property management fee and economic level; (2) space quality at the human scale had important effects on housing prices; and (3) some traditional factors, especial",51.0,https://doi.org/10.3390/land1005053390e7545aa69fd7e3b0b4fddbe8806b08519280a674,10.3141/2245-16,Analysis of House Prices to Assess Economic Impacts of New Public Transport Infrastructure,2011,,Lucía Mejía Dorantes; A. Páez; J. M. Vassallo,"Transportation infrastructure is known to affect the value of real estate property by virtue of changes in accessibility. The impact of transportation facilities is highly localized as well, and it is possible that spillover effects result from the capitalization of accessibility. The objective of this study was to review the theoretical background related to spatial hedonic models and the opportunities that they provided to evaluate the effect of new transportation infrastructure. An empirical case study is presented: the Madrid Metro Line 12, known as Metrosur, in the region of Madrid, Spain. The effect of proximity to metro stations on housing prices was evaluated. The analysis took into account a host of variables, including structure, location, and neighborhood and made use of three modeling approaches: linear regression estimation with ordinary least squares, spatial error, and spatial lag. The results indicated that better accessibility to Metrosur stations had a positive impact on real estate values and that the effect was marked in cases in which a house was for sale. The results also showed the presence of submarkets, which were well defined by geographic boundaries, and ",51.0,http://oa.upm.es/11288/91https://openalex.org/W2054876535,10.1080/14765280802283584,The impacts of distance to CBD on housing prices in Shanghai: a hedonic analysis,2008,Journal of Chinese Economic and Business Studies,Jie Chen; Qianjin Hao,"It is widely recognized that location is the primary determining factor of housing price. But to what extent the variation of housing price in Shanghai can be explained by the locational factor has not been empirically examined. In this paper, we examine the power of applying the hedonic method to the spatial-statistical analysis of housing prices in Shanghai. The data we use covers all new commercial residential housings sold in Shanghai during July 2004 and June 2006. The main focus in this paper is to examine the effect of geographical distance to city centre on the selling price of residential housings in Shanghai. We also discuss how the price gradient varies at different directions in Shanghai. Finally, we demonstrate the importance of applying quality control on the development of a housing price index. The statistical methodology and empirical results obtained in this paper carry interesting implications for other cities in China as well.",51.0,92doi_10_1108_14635789910258543,10.1108/14635789910258543,Property valuation and the structure of urban housing markets,1999,Journal of Property Investment & Finance,Craig Watkins,"Since the 1980s UK academics have promoted the use of multiple regression analysis in property valuation. Recently, however, there has been growing recognition that regression models will be subject to aggregation bias if they fail to accommodate the existence of housing market segmentation (submarkets). In this study, we compare the empirical performance of a standard hedonic house price regression model for the city of Glasgow with a segmented model which recognises the importance of understanding the underlying market structure and, in particular, the existence of submarkets for different dwelling types. The results show that the (weighted) standard error of the segmented model is significantly lower than that of the market wide model. Consequently, we propose a two‐stage approach to the application of MRA techniques to residential valuation. First, following traditional institutional analysis of housing markets, the market should be subdivided into distinct structurally differentiated market segments. These segments can usefully be identified by principal components factor analysis which allows the identification of the most important common components in the housing bundle. Se",50.0,93doi_10_1080_00420980123880,10.1080/00420980123880,Estimating Distance Gradients for Apartment Properties,2001,Urban Studies,Bo Söderberg; Christian Janssen,"The effect of distance from the city centre on selling price, tax assessment and gross income is investigated for income property in proximity to the city centre. Hedonic estimation with a multiplicative model specification is used to estimate the relationship between property characteristics on the one hand and price, assessment and income on the other. The sample consists of centrally located apartment buildings in downtown Stockholm sold during a recent three-year period. The application is specific to Stockholm, but the methodology and the insights gained are general. The results include the estimation of price gradients for the dependent variables. The models are used for estimating the implicit capitalisation rates in the property market as a function of the distance to the centre. We also estimated where the market appears to place the city centre as implied by the observations. Although no rent gradient was found, we were able to detect a significant negative price gradient. The former is reasonable considering the rent control ordinances. The latter indicates the existence of a negative land rent gradient.",49.0,94doi_10_1108_14635780010345436,10.1108/14635780010345436,The modelling of housing submarkets,2000,Journal of Property Investment & Finance,Mike Fletcher; Paul Gallimore; Jean Mangan,"This paper is concerned as to whether it is more appropriate to use aggregate or disaggregate models in forecasting house prices using hedonic modelling. It is accepted that the implicit pricing of some of the attributes is not stable between locations, property types and ages but it is argued that this can be effectively modelled with an aggregate method. The models are developed using a dataset of nearly 18,000 transactions in the UK Midlands region in 1994. The comparative performance of these models is then considered using two approaches. Chow tests of the error differences between actual price and the price predicted by the models suggest that the submarket models lead to statistically significant, though small, improvements. A second approach, using comparison of the root mean square errors, is conducted on the models’ forecasts for a 10 per cent sample of nearly 2,000 transactions excluded from the modelling process. This shows little practical difference in the forecasting ability between the two approaches. Great care needs to be taken over sample size if a disaggregate model is used.",49.0,9511bc1af65e14adf56639e39c8676a428bbf594d3,10.1007/s10109-017-0257-y,Housing price prediction: parametric versus semi-parametric spatial hedonic models,2018,Journal of Geographical Systems,J. Montero; R. Mínguez; G. Fernández-Avilés,,49.0,96https://openalex.org/W4385633781,10.1016/j.eswa.2023.121059,Improving hedonic housing price models by integrating optimal accessibility indices into regression and random forest analyses,2023,Expert Systems with Applications,David Rey-Blanco; Jose Luis Zofio; Julio González Arias,"Location indices are key in explaining variation in house prices. However, the definition of comprehensive indices capturing all locational features, along with their efficient and timely calculation, is usually one of the most complex dimensions of house price modeling. Existing difficulties result in partial location specifications, mostly due to three hurdles: (1) there is not a consensus on the best method to construct these indices, (2) what features (variables) to include: labor, demographic, commuting, etc., and (3) its creation requires granular and updated datasets. We introduce a methodology based on computer algorithms to create car and walk accessibility indices that address the previous concerns and capture location interactions among a wide range of variables. The selection of variables is based on an automated search of the best performing utility bearing gravitational accessibility indices for price prediction. Once these optimal indices are obtained, the method applies principal components analysis to secure their orthogonality. Using a unique dataset from a leading real estate portal in Europe, we illustrate and test for the city of Madrid their applicability in s",48.0,97doi_10_1108_14635780010324321,10.1108/14635780010324321,The application of surface generated interpolation models for the prediction of residential property values,2000,Journal of Property Investment & Finance,William J. McCluskey; William G. Deddis; Ian G. Lamont; Richard A. Borst,The aim of this paper is to attempt to measure the effect of location on residential house prices and to endeavour to integrate spatial and aspatial data in terms of developing a hybrid predictive model. The research methodology investigates the traditional hedonic approach to modelling location using multiple regression techniques. Alternative approaches are considered which specifically model the spatial distribution of house prices with the objective of developing location adjustment factors. These approaches are based on the development of surface response techniques such as inverse distance weighting and universal kriging. The results generated from the surfaces created are then calibrated within MRA.,47.0,9836572daa8a6c3c80138f6f664accd90e8ca11808,10.3390/su11205605,EPC Green Premium in Two Different European Climate Zones: A Comparative Study between Barcelona and Turin,2019,Sustainability,Federico Dell’Anna; M. Bravi; Carlos Marmolejo-Duarte; M. Bottero; Ai Chen,"Energy performance certificates (EPCs) are important tools aimed at improving buildings’ energy performance. They play a central role in the context of the Energy Performance of Buildings Directive (EPBD) which asks member states (MS) to take the necessary measures to establish a complete certification system. In this study, an application of the hedonic price method (HPM) assessing the effect of energy labels derived from the EPC on real estate market value is presented. The estimation methodology was applied to two European cities characterized by different climate conditions. The analysis was based on two datasets of listing prices referring to multi-family residential markets in Turin (Italy) and Barcelona (Spain). Four models for each dataset were applied to capture the marginal price of green attributes, but also to control for the spatial autocorrelation among values. The findings showed how the EPC has been applied in the two countries and how it has influenced the real estate market. Turin’s buyers pay more attention to the EPC label, while in Barcelona, they value much more single characteristics, such as air conditioning and a swimming pool, considered popular attributes",46.0,https://www.mdpi.com/2071-1050/11/20/5605/pdf?version=1571814661990f5576ed54667ae3880c744236fb522e112902ad,10.1016/j.landusepol.2019.02.024,The changing face of environmental amenities: Heterogeneity across housing submarkets and time,2019,Land Use Policy,M. Fernandez; S. Bucaram,"Abstract The value of environmental amenities has been studied for decades in the hedonic housing prices literature. Numerous studies have found that amenities such as marine, river and woodland habitats, national and regional reserves, urban parks, or wetlands contribute positively on the formation of housing prices. Work is scarce when considering heterogeneity across submarkets and time. Auckland, New Zealand’s largest city, has a unique landscape with open spaces, waterways, coastal areas and volcanic features. Local housing market is highly segmented and the city has gone through a bust, recovery and boom cycle in the last decade. This paper incorporates heterogeneity across submarkets and time, and examines how they affect the capitalisation of amenities into housing prices. We construct a dataset of about 280 thousand sale transactions between 2000 and 2016 in Auckland and estimate hedonic models based on unconditional quantile regressions. We find diverse capitalisation patterns across housing submarkets. Beaches may add price premiums of 5.1% in houses in the upper-end of the distribution, but also price discounts of 2.1% in houses in the lower-end of the distribution. We ",46.0,100doi_10_1007_s10640_008_9221_0,10.1007/s10640-008-9221-0,A Spatial Hedonic Approach to Assess the Impact of Swine Production on Residential Property Values,2008,Environmental and Resource Economics,Jungik Kim; Peter Goldsmith,,46.0,101620cbd7217ca28bcea726920009e42496a17ea8b,10.68479/001c.7941,"The Impact of Brownfields on Residential Property Values in Cincinnati, Ohio: A Spatial Hedonic Approach",2012,Journal of Regional Analysis & Policy,Oana Mihaescu; Rainer Vom Hofe,"This paper empirically assesses the impact brownfield sites have on market values of102 single-family residential properties. Using three different hedonic model specifications, Ordinary Least Squares and Spatial Autoregressive and Spatial Error Models, this study shows that properties located less than 1,000 feet from a brownfield site experience a significant depreciation in property values. As expected, spatial dependence among real estate property values is present, meaning that the two spatial hedonic model specifications are superior to the Ordinary Least Squares specification. The study contributes to the relevant real estate and urban economics literature by determining the negative impact brownfield sites have on the value of single-family residential properties in our study region in Cincinnati, Ohio, by explicitly accounting for the phenomenon of spatial dependence in the dependent variable and by addressing the declining influence of brownfield sites on property values in a nonlinear relationship",45.0,https://jrap.scholasticahq.com/article/7941.pdf103doi_10_1029_92wr02995,10.1029/92wr02995,Water source as a housing characteristic: Hedonic property valuation and willingness to pay for water,1993,Water Resources Research,J. H. North; C. C. Griffin,"Using data from a large representative sample of rural households in one region of the Philippines, we estimate the determinants of the rental value of dwellings using the bid‐rent approach to the hedonic price model. Our particular interest is in the relative valuation these households place on owning a private source of water and distance to a public or communal source. We find that low‐, middle‐, and high‐income households value an in‐house piped water source highly relative to other characteristics of their homes. Middle‐ and high‐income households value a deep well or piped water in the yard, although at a substantially lower level than piped water in the house. It is somewhat surprising to find that, except in the case of high‐income families, households appear to gain little or no utility from having a communal source of water, such as a river, lake, or public tap, closer to their homes. As a consequence, public water policies that emphasize improving the quality and proximity of communal sources would be inappropriate for the region represented by this sample.",45.0,104doi_10_1002_jae_3950020103,10.1002/jae.3950020103,A Bayesian approach to assessing the robustness of hedonic property value studies,1987,Journal of Applied Econometrics,Scott E. Atkinson; Thomas D. Crocker,"Abstract Hedonic price models are widely employed to estimate implicit prices for bundled attributes. Residential property value studies dominate these applications. Using a representative cross‐sectional property value data set, we employ Bayesian methods to translate a range of priors in covariate selection typical of hedonic property value studies into a range of posterior estimates. We also formulate priors regarding measurement error in individual covariates and compute the ranges of resulting posterior means. Finally, we empirically demonstrate that a greater and more systematic use of prior information drawn from one's own data and from other studies can break the collinearity deadlock in this data.",44.0,105https://openalex.org/W1580883067,10.1002/jae.2377,Hedonic Housing Prices in Paris: An Unbalanced Spatial Lag Pseudo‐Panel Model with Nested Random Effects,2014,Journal of Applied Econometrics,Badi H. Baltagi; Georges Bresson; Jean‐Michel Etienne,"Summary This paper estimates a hedonic housing model based on flats sold in the city of Paris over the period 1990–2003. This is done using maximum likelihood estimation, taking into account the nested structure of the data. Paris is historically divided into 20 arrondissements, each divided into four quartiers (quarters), which in turn contain between 15 and 169 blocks (îlot, in French) per quartier. This is an unbalanced pseudo‒panel data containing 156,896 transactions. Despite the richness of the data, many neighborhood characteristics are not observed, and we attempt to capture these neighborhood spillover effects using a spatial lag model. Using likelihood ratio tests, we find significant spatial lag effects as well as significant nested random error effects. The empirical results show that the hedonic housing estimates and the corresponding marginal effects are affected by taking into account the nested aspects of the Paris housing data as well as the spatial neighborhood effects.Copyright © 2014 John Wiley & Sons, Ltd.",43.0,106doi_10_1111_j_1475_4932_2009_00544_x,10.1111/j.1475-4932.2009.00544.x,Australian House Prices: A Comparison of Hedonic and Repeat‐Sales Measures*,2009,Economic Record,JAMES HANSEN,"House prices are difficult to measure due to changes in the composition of properties sold through time and changes in the quality of housing. I explore whether these issues affect simple measures of house prices, and whether regression‐based measures provide an accurate alternative to measuring pure house price changes in Australia. Using unit record data for Australia's three largest cities, regression‐based approaches provide a more accurate estimate of pure price changes than a median, and are comparable, with around half of the variation in prices growth explained. These results confirm that regression‐based measures are useful for measuring house price changes in Australia.",43.0,107fc9d39b019f0526d9688d6cea3c777de313aea1d,10.1016/j.landusepol.2014.08.012,"Factors influencing the value of houses: Estimates for the city of Cagliari, Italy",2015,,C. Zoppi; M. Argiolas; S. Lai,"Abstract The aim of this paper is to analyze the relationship between housing values and a set of determinants, related both to the urban environment and to the structural characteristics of the housing market, in the metropolitan area of Cagliari. In order to achieve this aim, a sample of residential properties spread across the urban context was taken into account. For every single residential unit we study the value of houses, identified as their estimated value, cadastral value, rent value, value supplied by the National Observatory on Real Estate Market, and finally sale value as related to factors which are identified as relevant variables in several studies concerning the real estate market. The adopted approach implies data collection concerning value and characteristics of houses. The resulting dataset is geocoded and spatially analyzed, in order to identify spatial autocorrelation of the value of houses and its correlations with respect to the characteristics of houses through the hedonic approach. The methodological approach can be easily replicated and exported with reference to other Italian and European urban contexts and results could be straightforwardly comparable.",42.0,https://iris.unica.it/bitstream/11584/79435/5/LUP_2015%20Zoppi_Argiolas_Lai_Factorsinfluencing_valueofhouses_postprint.pdf108doi_10_1002_jae_1022,10.1002/jae.1022,Semiparametric hedonic price models: assessing the effects of agricultural nonpoint source pollution,2008,Journal of Applied Econometrics,Christophe Bontemps; Michel Simioni; Yves Surry,"Abstract In the area of environmental analysis using hedonic price models, we investigate the performance of various nonparametric and semiparametric specifications. The proposed model specifications are made up of two parts: a linear component for house characteristics and a non‐(semi)parametric component representing the nonlinear influence of environmental indicators on house prices. We adopt a general‐to‐specific search procedure, based on recent specification tests comparing the proposed specifications with a fully nonparametric benchmark model, to select the best model specification. An application of these semiparametric models to rural districts indicates that pollution resulting from intensive livestock farming has a significant nonlinear impact on house prices. Copyright © 2008 John Wiley & Sons, Ltd.",42.0,109doi_10_1111_j_1538_4632_1993_tb00277_x,10.1111/j.1538-4632.1993.tb00277.x,Apartment Rents: Another Challenge to the Monocentric Model,1993,Geographical Analysis,Irving Hoch; Paul Waddell,Extension of hedonic modeling strategy to the case of apartment rents in the Dallas region reveals the influence of a complex network of activity centers and highway axes. Nodes other than the CBD exert greater influence on rents than the CBD and amenity variables and externalities have both positive and negative effects. These findings demand reevaluation of the place normally assigned to higher‐density rental housing in urban models.,42.0,110https://openalex.org/W1732885445,10.2139/ssrn.357280,Hedonic House Prices Without Characteristics: The Case of New Multiunit Housing,2003,SSRN Electronic Journal,Olympia Bover; Pilar Velilla,,42.0,1111e477c1562d4467a99a2399d7841699999b36461,10.1177/2399808320924678,A new toolkit for land value analysis and scenario planning,2020,,C. Pettit; Y. Shi; H. Han; M. Rittenbruch; M. Foth; S. Lieske; R. van den Nouwelant; P. Mitchell; S. Leao; B. Christensen; M. Jamal,"Abstract In the digital era of big data, data analytics and smart cities, a new generation of planning support systems is emerging. The Rapid Analytics Interactive Scenario Explorer is a novel planning support system developed to help planners and policy-makers determine the likely land value uplift associated with the provision of new city infrastructure. The Rapid Analytics Interactive Scenario Explorer toolkit was developed following a user-centred research approach including iterative design, prototyping and evaluation. Tool development was informed by user inputs obtained through a series of co-design workshops with two end-user groups: land valuers and urban planners. The paper outlines the underlying technical architecture of the toolkit, which has the ability to perform rapid calculations and visualise the results, for the end-users, through an online mapping interface. The toolkit incorporates an ensemble of hedonic pricing models to calculate and visualise value uplift and so enable the user to explore what if? scenarios. The toolkit has been validated through an iterative case study approach. Use cases were related to two policy areas: property and land valuation process",40.0,https://eprints.qut.edu.au/200099/1/Raise_Cupum_EnvPlanB_Anon_resubmission_III_FINAL.pdf1128d5f6b09f9058fc5a131a22d58a856d18ce849c7,10.1016/j.jue.2020.103299,Information value of property description: A Machine learning approach,2021,Journal of Urban Economics,Lily Shen; Stephen L. Ross,"Abstract This paper employs machine learning to quantify the value of “soft” information contained in real estate property descriptions. Textual descriptions contain information that traditional hedonic attributes cannot capture. A one standard deviation increase in the uniqueness of a property based on this “soft” information leads to a 15% increase in property sale price in a hedonic price model and a 10% increase in a repeat sales price model. The effects in the hedonic model appear to arise through two channels: the unobserved quality of the housing unit, and the market power of the housing unit relative to competing properties. The effects in the repeat sales model appear to be driven entirely by the market power of the unit. Further, an annual hedonic price index ignoring our measure of unobserved quality overstates real estate prices by between 10% to 23% and mistimes the stabilization of housing prices following the Great Recession. Similar, but smaller effects, are observed for the repeat sales price index.",40.0,https://media.economics.uconn.edu/working/2019-20R.pdf11391a343b71c11d4139d2606d6c4d1c5fc64cbc6c3,10.3390/su11061551,Estimation of Housing Price Variations Using Spatio-Temporal Data,2019,Sustainability,Jorge Chica-Olmo; Rafael Cano-Guervos; M. Chica-Rivas,"This paper proposes a hedonic regression model to estimate housing prices and the spatial variability of prices over multiple years. Using the model, maps are obtained that represent areas of the city where there have been positive or negative changes in housing prices. The regression-cokriging (RCK) method is used to predict housing prices. The results are compared to the cokriging with external drift (CKED) model, also known as universal cokriging (UCK). To apply the model, heterotopic data of homes for sale at different moments in time are used. The procedure is applied to predict the spatial variability of housing prices in multi-years and to obtain isovalue maps of these variations for the city of Granada, Spain. The research is useful for the fields of urban studies, economics, real estate, real estate valuations, urban planning, and for scholars.",40.0,https://www.mdpi.com/2071-1050/11/6/1551/pdf?version=15528929521141f80ef1e59c386528f3aed3976e5123743fb999a,10.3390/su6052946,Estimation of Hedonic Single-Family House Price Function Considering Neighborhood Effect Variables,2014,,C. Shimizu,"In the formulation of hedonic models, in addition to locational factors and building structures which affect the house prices, the generation of the omitted variable bias is thought to occur in cases when local environmental variables and the individual characteristics of house buyers are not taken into consideration. However, since it is difficult to obtain local environmental information in a small neighborhood unit and to observe individual characteristics of house buyers, these variables have not been sufficiently considered in previous studies. We demonstrated that non-negligible levels of omitted variable bias are generated if these variables are not considered.",40.0,https://www.mdpi.com/2071-1050/6/5/2946/pdf?version=1424778226115doi_10_1111_j_1752_1688_1989_tb03095_x,10.1111/j.1752-1688.1989.tb03095.x,HEDONIC PRICE ANALYSIS OF THE EFFECT OF A FLOODPLAIN ON PROPERTY VALUES<sup>1</sup>,1989,JAWRA Journal of the American Water Resources Association,William A. Donnelly,"ABSTRACT: The effect of a floodplain location on the market value for property is controversial, with the conventional wisdom being that buyers are myopic. Previous parametric and nonparametric statistical tests have proven inconclusive in deciding the issue. Herein, a theoretical model, that of hedonic price indexes, is posited and tested, using housing sales characteristics data obtained from a Multi‐List Service cooperative. This study suggests that home buyers do adjust the purchase price for houses within a floodplain, and this amounts to, on average, just over 12 percent. The data are from a small midwestern town in which the last severe flooding occurred a decade ago.",39.0,11641c05e4c190bfd812f576bb4bc53a0c147331a7d,10.1007/s11146-022-09915-y,Accounting for Spatial Autocorrelation in Algorithm-Driven Hedonic Models: A Spatial Cross-Validation Approach,2022,Journal of real estate finance and economics,Juergen Deppner; Marcelo Cajias,"Data-driven machine learning algorithms have initiated a paradigm shift in hedonic house price and rent modeling through their ability to capture highly complex and non-monotonic relationships. Their superior accuracy compared to parametric model alternatives has been demonstrated repeatedly in the literature. However, the statistical independence of the data implicitly assumed by resampling-based error estimates is unlikely to hold in a real estate context as price-formation processes in property markets are inherently spatial, which leads to spatial dependence structures in the data. When performing conventional cross-validation techniques for model selection and model assessment, spatial dependence between training and test data may lead to undetected overfitting and overoptimistic perception of predictive power. This study sheds light on the bias in cross-validation errors of tree-based algorithms induced by spatial autocorrelation and proposes a bias-reduced spatial cross-validation strategy. The findings confirm that error estimates from non-spatial resampling methods are overly optimistic, whereas spatially conscious techniques are more dependable and can increase generaliza",38.0,https://link.springer.com/content/pdf/10.1007/s11146-022-09915-y.pdf11714e58b039b814fec5aea6bab9494c7be78da4c6a,10.1016/j.cstp.2019.07.001,Public transport accessibility and housing value uplift: Evidence from the Docklands light railway in London,2019,Case Studies on Transport Policy,Zhe Song; Meng-Qiu Cao; Ting-Ting Han; R. Hickman,"Abstract Public transport infrastructure is essential to city development, improving accessibility and allowing people to engage in activities, allowing travel by environmentally-friendly modes, and also creating economic benefits. This study investigates the impacts of public transport accessibility on development, examining changes in housing prices, and applying hedonic modelling. London’s Docklands Light Railway (DLR) is selected as a case study. The findings show that residential properties in station catchment areas of the south-eastern and northern branches of the DLR have a premium respectively of 0.352% and 0.093% per 100 m proximity to a station. By assessing inclusive variables, it is found that housing value is also determined by the property’s own features and the neighbourhood, particularly the property tenure. The detected housing value uplift implies that the provision of good public transport is crucial in policy making, especially in areas with poor public transport accessibility. Moreover, since transport investment is partly capitalised in housing projects, we suggest that future transport infrastructure investment and housing development should be set within a ",38.0,https://doi.org/10.1016/j.cstp.2019.07.001118doi_10_1111_j_1467_8276_2009_01316_x,10.1111/j.1467-8276.2009.01316.x,Riparian Buffers and Hedonic Prices: A Quasi‐Experimental Analysis of Residential Property Values in the Neuse River Basin,2009,American Journal of Agricultural Economics,Okmyung Bin; Craig E. Landry; Gregory F. Meyer,"Abstract Riparian buffers, the strips of vegetation along banks of rivers and streams, have been proposed as a key instrument to protect water quality in the United States. Riparian buffers impose a restriction on the use of private property limiting harvest and development, but buffers can also provide for aesthetic and recreational benefits that may accrue to property owners. With data from the Neuse River Basin in North Carolina, this study attempts to provide empirical evidence on the effect of a mandatory buffer rule on the value of riparian properties. Spatial autoregressive hedonic models are estimated within a quasi‐experimental framework using the imposition of the buffer rule as the treatment and nonriparian properties as a control group. Results indicate that a riparian property generally commands a high premium. We find no evidence, however, that the mandatory buffer rule has had a significant impact on riparian property values when compared with the control group.",38.0,119c63f29dcdec077b7ee126d8f2c6b0bcc6611e6a7,10.3846/1648715x.2016.1247021,"Spatial heterogeneity in implicit housing prices: evidence from Hangzhou, China",2017,,Hai-Zhen Wen; Yilan Jin; Ling Zhang,"Estimated coefficients in hedonic price models are generally assumed to be constant throughout the entire study area. However, increasing evidence reveals that the marginal prices of housing characteristics may vary over space and that the spatial heterogeneity problem in implicit housing prices should be given attention. Taking Hangzhou, China, as an example, this study uses the micro data of 603 residential communities in 2014 to examine spatial heterogeneity in implicit housing prices. On the basis of the traditional hedonic price model, we establish spatial expansion and geographically weighted regression (GWR) models for comparative analysis. Results show that the spatial expansion and GWR models have excellent goodness of fit and can improve the traditional hedonic price model. The mixed geographically weighted regression (MGWR) model further reveals that the implicit prices of nine housing characteristics vary significantly over space and that the impacts of the four remaining housing characteristics on housing prices are fixed throughout the entire study area. Unlike the traditional hedonic price model and spatial expansion model, the GWR/MGWR model has the unique advantage",37.0,https://journals.vgtu.lt/index.php/IJSPM/article/download/1857/1473120cd99a0fbc76cb055e07c755cb0ebc5cc72ce08dc,10.1017/s1068280500007462,"Valuing Rural Recreation Amenities: Hedonic Prices for Vacation Rental Houses at Deep Creek Lake, Maryland",2010,Agricultural and Resource Economics Review,Jon P. Nelson,"Hedonic prices are estimated for summer and winter rentals for vacation houses located near a lake and ski-golf resort in rural western Maryland. Regressions for weekly rents are conditioned on house size, quality, and recreation features including lakefront proximity and ski-slope access. Percentage effects and marginal implicit prices indicate that access to recreation is reflected importantly in rental offers. Evaluated at the means, lakefront locations command a premium of $1,100–1,200 per week, and the premium for ski-slope access is $500–600 per week. Unit recreation values are about $18 per person per day for a lakefront location with a private dock and $7 per person per day for a ski-slope location. There are small differences in the unit values for three real estate management agencies. Although there is evidence of spatial correlation in ordinary least squares residuals, estimation of spatial-lag and spatial-error models does not yield substantial changes in the empirical results.",36.0,https://ageconsearch.umn.edu/record/95645/files/nelson%20-%20current.pdf121b729f1ea3a070ae8bbf197217888faa02da19f88,10.1590/s0101-41612005000200001,Mercado imobiliário e amenidades urbanas: a view through the window,2005,,B. Hermann; E. Haddad,"In this article, we use a hedonic equation to estimate the implicit prices of urban amenities based on housing market data for the city of Sao Paulo. We test two different specifications, one with the original independent variables, and another with factors to correct for multicollinearity. In addition to the traditional monocentric model, we include an accessibility vector for a duocentric city. A criterion to select the appropriate environmental variables based on residual spatial interpolation is introduced. We conclude that proximity to train stations, green areas and strict residential zones raise rents, while criminality reduces them.",36.0,https://www.scielo.br/j/ee/a/CyfrFXBJJvyKZ7TSYZ7BkmS/?lang=pt&format=pdf122143364046dd7a54d45a268a8a86fe9aa8757e980,10.1016/j.scitotenv.2018.08.439,"How do households perceive flood-risk? The impact of flooding on the cost of accommodation in Dublin, Ireland.",2019,Science of the Total Environment,F. Pilla; Salem S. Gharbia; Ronan C. Lyons,"Climate change and human behaviour, such as building on floodplains, are increasing the incidence of floods in urban areas. This paper investigates the relationship between flood risk and residential accommodation costs, both sales and rental, using a detailed dataset of over 650,000 sale and rental listings in Dublin, Ireland over the period 2006-2015. These are combined with detailed data for the Dodder river on 1% flood risk and past flooding events. Research to date suggested that the lack of a persistent effect may have an impact on buyers' and sellers' risk perceptions by changing with the prevalence of hazard events and that homebuyers are unaware of flood risks and insurance requirements when bidding on properties. Using hedonic regression techniques, the presented work shows opposite results: flood events are found to have a negative impact, particularly on sale prices, while being at 1% risk has no effect once past flood events are controlled for. For past flood events, however, there is evidence to suggest that this impacts on property values, certainly in the areas affected and up to 200 m away. Before the institutional flood risk maps were published, the assessment was",35.0,https://zenodo.org/record/35015291233d555b719dcd66f5b773ee480ecb47ce9229f3fe,10.28991/esj-2020-01250,Estimation of Residential Property Market Price: Comparison of Artificial Neural Networks and Hedonic Pricing Model,2020,Emerging Science Journal,Michaela Štubňová; Marta Urbaníková; J. Hudáková; V. Papcunová,"The correct real estate property price estimation is significant not only in the real estate market but also in the banking sector for collateral loans and the insurance sector for property insurance. The paper focuses on both traditional and advanced methods for real estate property valuation. Attention is paid to the analysis of the accuracy of valuation models. From traditional methods, a regression model is used for residential property price estimation, which represents the hedonic approach. Modern advanced valuation methods are represented by the artificial neural network, which is one of the soft computing techniques. The results of both methods in residential property market price estimation are compared. The analysis is performed using data on residential properties sold on the real estate market in the city of Nitra in the Slovak Republic. To estimate the residential property prices, artificial neural networks trained with the Levenberg-Marquart learning algorithm, the Bayesian Regularization learning algorithm, and the Scaled Conjugate Gradient learning algorithm, and the regression pricing model are used. Among the constructed neural networks, the best results are achie",35.0,https://ijournalse.org/index.php/ESJ/article/download/425/pdf124275ba36694510670b966960c4ff3436b3081cc78,10.3846/1648715x.2015.1122668,Using multiple criteria decision analysis (MCDA) to assist in estimating residential housing values,2016,,F. Ferreira; Ronald W. Spahr; Mark A. Sunderman,Considerable literature exists regarding the complexity of the residential real estate appraisal process and the methods employed to determine initial listing prices as estimates of intrinsic market prices. Deviations in residential real estate intrinsic values occur due to a multiplicity of attributes and explanatory factors requiring consideration. We conduct a panel study using a Multiple Criteria Decision Analysis (MCDA) based framework that utilizes the skills and knowledge of a panel of residential real estate professionals (i.e. appraisers and realtors). We demonstrate how cognitive mapping and the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) may assist in estimating appropriate offer/sale prices and strengthening current valuation approaches such as using comparables and/or hedonic modeling. The managerial implications of our MCDA-based framework and some avenues for future research are also presented.,35.0,https://journals.vgtu.lt/index.php/IJSPM/article/download/2096/16911257ff3891712d8f4e4350bef70731a3e0b7d6018d2,10.1155/2016/1478413,The Impact of Subway Lines on Residential Property Values in Tianjin: An Empirical Study Based on Hedonic Pricing Model,2016,,Hui Sun; Yu-Ning Wang; Qing-Bo Li,"The construction of subways has an external impact on the urban environment. Among them, the most important acceleration function lies in the property values of housing near subway stations. Tianjin, the largest open coastal city in Northern China, is selected as the subject of the research in this paper by virtue of its unique background. The Hedonic Pricing Model is used in analysing the change in the value of the properties located within 1,000 metres of completed subway line 3 stations. Using the theories of land rent and land location, and a model of the impact of urban traffic on the surrounding real estate prices, we analyse the sphere of influence of Tianjin Metro Line 3 on real estate prices. Finally, the paper stresses the importance of urban construction and subway building and finds that different development strategies should be used according to the characteristics of the subway in various regions of the city.",35.0,http://downloads.hindawi.com/journals/ddns/2016/1478413.pdf12653f863bd54970307af93c0ba10a947b3b65b890a,10.13128/aestimum-15459,The impact of Energy Performance Certificate level on house listing prices. First evidence from Italian real estate,2015,Aestimum,E. Fregonara; D. Rolando; P. Semeraro; M. Vella,"The recent dispositions related to the energy performance of buildings, launched by the European Directives 2002/91/EC and 2010/31/EU, turned attention to the Energy Performance Certificate (EPC). The aim of this study is to investigate the economic effects of the recent Italian statutory provisions related to energy performance of buildings on listing behaviour. With this aim an hedonic regression analysis is performed, in order to measure the impact of EPC level on listing prices. The study, based on a set of more than 500 housing property asset collected in 2012 from real estate advertisements websites, is focused on the Turin real estate market as a case study. Furthermore this paper contributes to the early limited literature on implication of the impact of EPC level on Italian housing market, representing one of the first systematic evidence about the energy certifications in the housing listing prices. ",35.0,https://doi.org/10.13128/aestimum-15459127doi_10_1111_1540_6229_00435,10.1111/1540-6229.00435,Explaining the Variability of Apartment Rents,1987,Real Estate Economics,Karl L. Guntermann; Stefan Norrbin,"The research reported here uses regression analysis to analyze rent variations in a sample of apartment data from the Phoenix metropolitan area. Many of the variables used in hedonic price studies of houses are found to be significant in explaining variations in apartment rent. There are differences between hedonic studies of houses and apartments particularly with respect to common area features or amenities. The analysis of various submarkets also produced interesting results. Various uses can be made of the results of this and similar studies by appraisers (market‐derived adjustments), property managers (setting rents) and feasibility analysts (the design of apartment projects).",35.0,128doi_10_1111_j_1467_9787_1990_tb00083_x,10.1111/j.1467-9787.1990.tb00083.x,"HEDONIC PRICES, IDENTIFICATION, AND THE DEMAND FOR PUBLIC SAFETY*",1990,Journal of Regional Science,David E. Clark; James C. Cosgrove,"ABSTRACT In this paper, we use a two‐stage intercity hedonic model to estimate household demand for public safety. This approach is shown to readily address the identification problem inherent in the hedonic model. Data from the 1980 Public Use Microdata Sample are used to estimate a willingness‐to‐pay function for the public‐safety good. Income is found to be the primary determinant of willingness to pay. Indeed, the influence of income outweighs the combined impact of family life‐cycle considerations.",35.0,129https://openalex.org/W2592948154,10.4018/ijaeis.2017040105,Hedonic Analysis of Housing Sales Prices with Semiparametric Methods,2017,International Journal of Agricultural and Environmental Information Systems,Vincenzo Del Giudice; Benedetto Manganelli; Pierfrancesco De Paola,"This study estimates a hedonic price function using a semiparametric regression based on Penalized Spline Smoothing, and compares the price prediction performance with conventional parametric models. The excellent results obtained show that the semiparametric models allow to obtain a significant improvement in the prediction of housing sales prices.",35.0,1309239fae8c12b9552340025fdad9ef01817eb21b9,10.1016/j.enpol.2020.111830,Valuation of energy performance certificates in the rental market – Professionals vs. nonprofessionals,2020,,Aras Khazal; O. Sønstebø,"Abstract The implementation of Energy Performance Certificates (EPCs) is expected to reduce energy consumption and carbon emissions by providing actors with information that can be used to make better-informed decisions. This paper is the first to investigate EPCs in the Norwegian residential rental market. Applying the hedonic multilevel approach using information from some 440,000 rental contracts over the period of 2011–2018, we find that labeled dwellings have a premium compared with non-labeled dwellings, and that the premium is increasing with a higher EPC-label. We further define two classes of lessors – professional (real estate agents) and nonprofessionals (homeowners) – to study potential heterogeneity in EPC valuation and find that professionals assign higher rents compared with nonprofessionals. Dwellings with high energy efficiency are associated with a higher premium if rented out by a professional, a significant part of which stemming from higher EPC valuation. The results are robust to a number of heterogeneity analyses and after controlling for sample selection bias and unobserved locational heterogeneity. The findings of this paper signify the necessity to increas",34.0,https://www.sciencedirect.com/science/article/pii/S0301421520305474/pdf131892b455253708392fa1d374a50e37bf898d2c0ed,10.1145/3409501.3409543,Spatial Prediction of Housing Prices in Beijing Using Machine Learning Algorithms,2020,HPCCT/BDAI,Ziyue Yan; Lu Zong,"The real estate industry places key influence on almost every aspect of social economy given its great financing capacity and prolonged upstream and downstream industry chain. Therefore, predicting housing prices is regarded as an emerging topic in the recent decades. Hedonic Regression and Machine Learning Algorithms are two main methods in this field. This study aims to explore the important explanatory features and determine an accurate mechanism to implement spatial prediction of housing prices in Beijing by incorporating a list of machine learning techniques, including XGBoost, linear regression, Random Forest Regression, Ridge and Lasso Model, bagging and boosting, based on the housing price and features data in Beijing, China. Our result shows that compared to traditional hedonic method, machine learning methods demonstrate significant improvements on the accuracy of estimation despite that they are more time-costly. Moreover, it is found that XGBoost is the most accurate model in explaining and prediciting the spatial dynamics of housing prices in Beijing.",34.0,132https://openalex.org/W3131980259,10.9734/ajeba/2021/v21i130345,Combining Housing Price Forecasts Generated Separately by Hedonic and Artificial Neural Network Models,2021,Asian Journal of Economics Business and Accounting,Salvatore Joseph Terregrossa; Mohammed Hussein Ibadi,"Aims: A) To enhance accuracy in forecasting housing unit prices by forming combinations of component forecasts generated separately by hedonic and artificial neural network models; B) To help ascertain whether a constrained or unconstrained linear combining model achieves superior forecasting performance. Place and Duration of the Study: Department of Business Administration, Istanbul Aydin University, Istanbul 34295, Turkey; from 2019 to 2020. Study Design: A cross sectional data set of housing unit prices and corresponding housing unit attributes and characteristics is formed and then randomly divided into two segments: in sample (80%) and out of sample (20%). Three different methods (hedonic, artificial neural network and combining) are then employed to process the same in sample data set, and generate out of sample forecasts. The three forecasting methods are then tested and compared. Methodology: Out of sample combination forecasts are formed with component forecast weights generated by in sample weighted least squares (WLS) regression of realized price against in sample component forecasts. Four types of regressions are run: unconstrained, with and without a constant; constra",33.0,13322e82268886340b6c1cc50c47f0a5c1511dc8e02,10.3390/resources3010031,A Meta-Analysis of Hedonic Studies to Assess the Property Value Effects of Low Impact Development,2014,,Marisa J. Mazzotta; Elena Y. Besedin; A. Speers,"Stormwater runoff from urban areas is a significant source of water pollution in the United States. Many states are promoting low impact development (LID) practices, which provide a variety of direct and ancillary ecosystem services. We describe a meta-analysis designed to evaluate the property value benefits of LID practices that reduce impervious surfaces and increase vegetated areas in developments, and present an example application to a hypothetical land use scenario. From the many hedonic property valuation studies of the benefits of general open space, we identified 35 studies that valued open spaces that were similar in nature to the small, dispersed open spaces characteristic of LID. The meta-regression estimates the percent change in a home’s value for an observed percent change in open space within a specific radius of a parcel, based on changes expected to result from LID approaches that increase green spaces. Our results indicate that the design and characteristics of a project affect the magnitude of benefits, and that values decline with distance. More broadly, the meta-analysis shows percent change and proximity are robust determinants of household willingness to pa",33.0,https://www.mdpi.com/2079-9276/3/1/31/pdf?version=139029069313439f8b5119ab63b41236467364d52b44c282cb98c,10.1186/s40537-020-00348-z,Impact of rail transit station proximity to commercial property prices: utilizing big data in urban real estate,2020,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",33.0,https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-020-00348-z13591adc77e3ed0a0c3cdebd9547cf3d57d8d7ea529,10.5399/osu/jtrf.47.3.2146,Hedonic Value of Transit Accessibility: An Empirical Analysis in a Small Urban Area,2012,,X. Cao; J. Hough,"Many programs of the SAFETEA-LU have pointed to improving transit services and individuals' accessibility in small urban areas. Urban economic theory suggests that improving accessibility by investing in transportation has the potential to drive up bids for land. However, will the improved transit accessibility in small urban areas increase property values? A number of studies have investigated the impact of rail transit on home sales but produced mixed results. Further, few studies have explored how transit influences the lease rate of apartments. This question is more relevant because transit accessibility tends to have a greater impact on apartment dwellers than home owners. Using about 400 apartment dwellers in Fargo, North Dakota, this study developed a hedonic price model to determine implicit price of proximity to bus routes. We found a negative impact of bus transit on apartment rent after controlling for other factors, however. We speculated that in a small urban area, this negative relationship could be mainly attributable to spurious relationships from other causal factors, as well as nuisance effects of bus transit itself.",33.0,http://ageconsearch.umn.edu/record/206969136eb83365b4894fa9c413cfdff9bdf069881dad3ad,10.1108/jerer-01-2018-0008,Examining the spatial relationship between environmental health factors and house prices,2018,Journal of European Real Estate Research,M. McCord; Sean Macintyre; P. Bidanset; D. Lo; P. Davis,"137Purpose138Air quality, noise and proximity to urban infrastructure can arguably have an important impact on the quality of life. Environmental quality (the price of good health) has become a central tenet for consumer choice in urban locales when deciding on a residential neighbourhood. Unlike the market for most tangible goods, the market for environmental quality does not yield an observable per unit price effect. As no explicit price exists for a unit of environmental quality, this paper aims to use the housing market to derive its implicit price and test whether these constituent elements of health and well-being are indeed capitalised into property prices and thus implicitly priced in the market place.139140141Design/methodology/approach142A considerable number of studies have used hedonic pricing models by incorporating spatial effects to assess the impact of air quality, noise and proximity to noise pollutants on property market pricing. This study presents a spatial analysis of air quality and noise pollution and their association with house prices, using 2,501 sale transactions for the period 2013. To assess the impact of the pollutants, three different spatial modelling approaches",32.0,https://pure.ulster.ac.uk/ws/files/79628073/Environment_paper_Accepted_1_.pdf143209262be38512f50c59a1e1a17a127f87440b419,10.1016/j.jclepro.2019.119828,"Environmental risk and housing price: An empirical study of Nanjing, China",2020,,Jing-Yi Dai; Pei Lv; Zong-Wei Ma; J. Bi; Ting Wen,"Abstract Some previous studies have investigated the impact of environmental risk on housing price, which focused mainly on a certain type of environmental risk. Studies are lacking on the associations between housing price and total environmental risks considering various types of risks within a city. We conducted an empirical study in Nanjing, China. We first assessed the spatially resolved accidental risks of chemical-industrial enterprises, gas stations, expressways, and the cumulative risks of soil heavy metal pollution and atmospheric PM2.5 pollution. We then derived the total environmental risks in Nanjing. Finally, we applied the hedonic price model to investigate the impacts of total and specific environmental risks on housing price. The results show that the higher environmental risks of gas stations and chemical enterprises were associated with lower housing prices. In addition, associations between housing price and the environmental risks of expressways and atmospheric PM2.5 were positive. The different associations for different risks led to an inverted U-shaped association between housing price and total environmental risk. In areas with lower total environmental ris",32.0,https://doi.org/10.1016/j.jclepro.2019.119828144f8260edb97a0dbb7c5a255fca59c10da9cde8ca8,10.1007/s00181-020-01992-3,Real estate listings and their usefulness for hedonic regressions,2020,Empirical Economics,Jens Kolbe; Rainer Schulz; Martin Wersing; A. Werwatz,"Real estate platforms provide a new source of data which has already been used as a substitute for transaction data in hedonic regression applications. This paper asks whether it is valid to do so in the established research areas of (1) willingness to pay estimation, (2) automated valuations, and (3) price index construction. It therefore compares listings and transaction data and regression results derived from them. We find that ask prices stochastically dominate sale prices, mainly because the composition of characteristics differs between the two data sets. But estimates of implicit prices also differ. As a result, willingness to pay estimates from listings data can be widely off when compared with estimates from transaction data. Listings data are not very useful to predict market values of individual houses either, as these predictions suffer from upward bias and large error variance. We find, however, that an ask price index complements a sale price index, as it is useful for nowcasting.",32.0,https://link.springer.com/content/pdf/10.1007/s00181-020-01992-3.pdf145d3ebec9b203b23c07ab512a07b63f593180cf2bf,10.3390/su11020534,How Does Urban Rail Transit Influence Residential Property Values? Evidence from An Emerging Chinese Megacity,2019,Sustainability,Dongfang Zhang; Jing-Juan Jiao,"Urban rail transit (URT) plays crucial economic, social, and environmental roles and may generate positive externalities that can influence the residential property values (RPVs) in real estate markets. Little attention has been given to exploring the impacts with respect to both the spatial and temporal perspectives. This paper explores the impacts of URT on the RPVs of 480 gated communities with respect to the spatial and temporal dimensions using the hedonic price model and a panel data set from Zhengzhou for 2012–2016. The results show the following: (1) URT does have a significant positive impact on the RPVs in all the selected years from 2012 to 2016, and the influencing strength was a “U-shape” with the increased travel time to the nearest URT stations in most of the selected years. Specially, there is quite some interaction between the temporal and spatial dimensions. (2) The influencing strength of URT during its early stages of planning and construction was higher than that during the operation periods, which is quite different from previous research that uses these first-tier cities such as Beijing and Shanghai in China. (3) Regarding the operating period, the influencin",31.0,https://www.mdpi.com/2071-1050/11/2/534/pdf?version=1547977056146doi_10_1080_0042098984033,10.1080/0042098984033,"Affordability, Housing Demand and Housing Policy in Urban India",1998,Urban Studies,Piyush Tiwari; Jyoti Parikh,Designing housing policies and programmes requires a careful estimation of household affordability and demand for housing. The efficiency of housing subsidies would depend on price elasticities of housing demand. Different households have different perceptions of housing demand based on their economic and demographic factors. We estimate the demand function of housing for urban India using step econometric analysis. The first step estimates the hedonic price index for states and in the second step the demand for housing is estimated as a function of economic and household characteristics. The problem of multicollinearity is observed with the data. Ridge regressions are used to correct for multicollinearity and to obtain efficient estimates. The results indicate that the housing demand is inelastic with respect to income and price. The income elasticity is 0.75 while price elasticity is slightly less than — 1. A further analysis to estimate income and price elasticities for different income classes as well as states has also been carried out. We comment on the efficiency of housing subsidies based on our results. The paper concludes with some policy questions.,31.0,1473bc07102108772a3252ac84ff32747d85447e553,10.5539/jsd.v4n1p246,The Impact of Neighbourhood Churches on House Prices,2011,,G. Babawale; Y. Adewunmi,"This study extends literature that empirically investigates the impact of neighborhood churches on residential property values with particular reference to selected areas in Lagos metropolis. The hypothesis that proximity to a church has no effect (positive or negative) on house prices is tested with a standard hedonic pricing model using a sample of 450 rented apartments (flats) across the study areas. The results followed the more common belief that neighborhood churches, particularly the large ones, impact negatively on the values of nearby residential properties. It further revealed that where more powerful positive externalities exist in close proximity, the negative effects of churches, even the large ones, on residential property values can be neutralized or even overshadowed. Among others, the results of the study is expected to bring to light the social and economic implications of churches located within residential neighborhoods in the study area and thereby assist urban planners, the courts and real estate valuers in resolving the debate on the nuisance versus amenity effects of neighborhood churches.",30.0,https://ccsenet.org/journal/index.php/jsd/article/download/9251/6813148doi_10_1111_1467_8470_00041,10.1111/1467-8470.00041,The Value of an Ocean View: an Example of Hedonic Property Amenity Valuation,1998,Australian Geographical Studies,Rob Fraser; Geoff Spencer,"This paper presents a method of quantifying variation in quality in an amenity as a component of an hedonic property amenity valuation. The paper considers the residential land amenity of an ocean view, a situation where there is typically substantial variation in the quality of the view between sites. The method is effectively a scoring system based on three sub‐characteristics of the ocean view. It is illustrated by application to a coastal housing subdivision in Western Australia. The results provide an estimate of the increase in the sale price of a site attributable to the quality of the site’s ocean view. The method has a potential role in coastal land use management decisions.",30.0,149doi_10_1080_0042098975538,10.1080/0042098975538,The Contribution of Environmental Amenities to Low-income Housing: A Comparative Study of Bangkok and Jakarta,1997,Urban Studies,Randall Crane; Amrita Daniere; Stacy Harwood,Central and local governments and their creditors are increasingly interested in cost recovery for public services. These strategies have two aims: increasing revenues and making a better connection between benefits received and consumer bills. This paper estimates a hedonic model for household-level data in a rare contrast of slums in two Asian mega-cities to provide comparative information about how the poor value environmental amenities and basic infrastructure access. The results suggest that slum housing prices do reflect differentials in public service access and that rough estimates of the value of access can be cheaply and usefully obtained for planning purposes.,30.0,15021199d311319fd0034523954fb23eaaf34739428,10.3390/buildings7040112,Assessing the Impact of Urban Improvement on Housing Values: A Hedonic Pricing and Multi-Attribute Analysis Model for the Historic Centre of Venice,2017,,P. Rosato; M. Breil; C. Giupponi; Raul Berto,"The Hedonic Pricing Method is one of the principal assessment methods for evaluating services and resources not normally exchanged on the market. However, the method is often unable to account for the great variety of qualities in an urban context and faces scarce and heterogeneous market data. This paper presents a model for the valuation of benefits generated by environmental and urban improvement investments adopting a mixed hedonic-multi-attribute procedure for modeling a value function of urban real estate values. The peculiarity of the model is that the independent variables are aggregated indicators, which synthetize more detailed characteristics. Using the expertise of real estate agents, all relevant variables influencing real estate values were weighted and synthetized in a set of cardinal indicators. Next, market prices were used to calibrate a hedonic function that transforms the cardinal indicators into real estate values. The valuation model was integrated into a GIS for mapping the housing value, and its variation induced by urban investment. The proposed model pointed out plausible and robust results, in particular, the possibility to use any available information, ",29.0,https://doi.org/10.3390/buildings7040112151a92228482b7a06b809bf2dfb8c7f68cd194a7200,10.1108/jerer-03-2016-0014,Modelling the impact of earthquake activity on real estate values: a multi-level approach,2017,,Berna Keskin; Richard Dunning; Craig Watkins,"Purpose 152 153 154 155 156This paper aims to explore the impact of a recent earthquake activity on house prices and their spatial distribution in the Istanbul housing market. 157 158 159 160 161Design/methodology/approach 162 163 164 165 166The paper uses a multi-level approach within an event study framework to model changes in the pattern of house prices in Istanbul. The model allows the isolation of the effects of earthquake risk and explores the differential impact in different submarkets in two study periods – one before (2007) and one after (2012) recent earthquake activity in the Van region, which although in Eastern Turkey served to alter the perceptions of risk through the wider geographic region. 167 168 169 170 171Findings 172 173 174 175 176The analysis shows that there are variations in the size of price discounts in submarkets resulting from the differential influence of a recent earthquake activity on perceived risk of damage. The model results show that the spatial impacts of these changes are not transmitted evenly across the study area. Rather it is clear that submarkets at the cheaper end of the market have proportionately larger negative impacts on real estate values. 177 178 179 180 181Research limitations/implications",28.0,https://doi.org/10.1108/jerer-03-2016-0014182https://openalex.org/W2616641670,10.11113/ijbes.v4.n2.182,A model to Estimate the Implicit Values of Housing Attributes by Applying the Hedonic Pricing Method,2017,International Journal of Built Environment and Sustainability,TD Randeniya; T.K.G.P. Ranasinghe; Susantha Amarawickrama,"Many scholars focused on the location based attributes rather than the non-location factors in decision making on land prices. Further, new research studies have identified the importance of the non-location attributes with the location factors. Many studies suggest that, many attributes exist which affects the housing price. Since the attributes involved and dominant for a particular case differs from one situation to the other, there cannot be an exact list of attributes. Yet, identification of factors that determine housing price and their relationships and the level of influence have poorly understood in planning and property development in the context of Sri Lanka. This study attempts to address what make householders to decide on housing price and application of hedonic pricing approach to estimate the implicit price of housing attributes in context of Sri Lanka. A sample study of selected fifty (50) single house transactions in Maharagama urban neighborhood area has been utilized to illustrate the applicability of the hedonic pricing model. As a methodology, correlation analysis has been carried out to study the degree of relationship between the housing price and the indepe",28.0,https://ijbes.utm.my/index.php/ijbes/article/download/182/991837a87d94cbb2a1bb3af93865c70eaef38f5783daa,10.5539/ijef.v6n3p188,Hedonic Modeling for a Growing Housing Market: Valuation of Apartments in Complexes,2014,,Ebubekir Ayan; H. C. Erkin,"The share of apartment complexes in housing stock of major cities in the developing world has been increasing. They represent a different housing submarket whose growing importance necessitates further research. Using survey data on transaction records of real estate agents, we employ a hedonic pricing model to explore the factors influencing apartment prices in the Metropolitan Izmit area. The site of a major reconstruction effort following a strong earthquake, Izmit has been in the forefront of the changes taking place in the Turkish real estate sector in particular, and in urban housing in general. We aim to get better estimates by focusing the study on apartment complexes in Metropolitan Izmit, the major submarket in the area. The results reveal that structural characteristics of an apartment as well as amenities provided in an apartment complex are important determinants of price. Air quality and proximity to a good public school have a major effect on price as well. The findings suggest that the submarket could be segmented further geographically.",28.0,https://ccsenet.org/journal/index.php/ijef/article/download/32619/19717184doi_10_1029_2002wr001799,10.1029/2002wr001799,Estimating the benefits of maintaining adequate lake levels to homeowners using the hedonic property method,2003,Water Resources Research,John Loomis; Marvin Feldman,"The hedonic property method was used to estimate residents' economic benefits from maintaining high and stable lake levels at Lake Almanor, California. Nearly a thousand property transactions over a 14‐year period from 1987 to 2001 were analyzed. The linear hedonic property regression explained more than 60% of the variation in‐house prices. Property prices were negatively and significantly related to the number of linear feet of exposed lake shoreline. Each additional one foot of exposed shoreline reduces the property price by $108–$119. A view of the lake added nearly $31,000 to house prices, while lakefront properties sold for $209,000 more than non‐lake front properties.",28.0,1850ed3e215f7a2e67852574cd78c3b11af4fa25db9,10.3390/ijgi11020125,Spatial Determinants of Real Estate Appraisals in The Netherlands: A Machine Learning Approach,2022,ISPRS Int. J. Geo Inf.,Evert Guliker; E. Folmer; M. V. van Sinderen,"With the rapidly increasing house prices in the Netherlands, there is a growing need for more localised value predictions for mortgage collaterals within the financial sector. Many existing studies focus on modelling house prices for an individual city; however, these models are often not interesting for mortgage lenders with assets spread out all over the country. That is why, with the current abundance of national geospatial datasets, this paper implements and compares three hedonic pricing models (linear regression, geographically weighted regression, and extreme gradient boosting—XGBoost) to model real estate appraisals values for five large municipalities in different parts of the Netherlands. The appraisal values used to train the model are provided by Stater N.V., which is the largest mortgage service provider in the Netherlands. Out of the three implemented models, the XGBoost model has the highest accuracy. XGBoost can explain 83% of the variance with an RMSE of €65,312, an MAE of €43,625, and an MAPE of 6.35% across the five municipalities. The two most important variables in the model are the total living area and taxation value, which were taken from publicly available ",27.0,https://www.mdpi.com/2220-9964/11/2/125/pdf?version=1645666843186e850976f9910ac8fabbdd623b7b0dd635731d387,10.1016/j.tranpol.2014.02.020,Estimation of the global impacts of aviation-related noise using an income-based approach,2014,,Q. He; Christoph Wollersheim; M. Locke; I. Waitz,"Current practices for assessing the monetary impacts of aviation noise typically use hedonic pricing methods that estimate noise-induced property value depreciation. However, this approach requires detailed knowledge of local housing markets, which is not readily available at a fine resolution for most airport regions around the world. This paper proposes a new noise monetization method based on citylevel personal income, which is often more widely available. Underlying the approach is a meta-analysis of 63 hedonic pricing studies from eight countries, conducted between 1970 and 2010, which is used to derive a general relationship between average city-level personal income and the Willingness to Pay for noise abatement. Applying the new model to income, noise, and population data for 181 airports worldwide, the global capitalized monetary impacts of commercial aviation noise in 2005 are estimated to be $23.8 billion, with a Net Present Value of $36.5 billion between 2005 and 2035 when a 3.5% discount rate is applied. Comparison with previous results based on real estate data yields a difference of � 34.2% worldwide and � 9.8% for the 95 US airports in the analysis. The main advanta",27.0,https://doi.org/10.1016/j.tranpol.2014.02.020187092ae2ef0445c6bd08465b1ed419197cb233e1dd,10.3390/land12020496,Housing Prices and the Characteristics of Nearby Green Space: Does Landscape Pattern Index Matter? Evidence from Metropolitan Area,2023,Land,Yi-Yi Chen; Colin Jones; N. Dunse; Enquan Li; Ye Liu,"This study aimed to examine the association between housing prices and green space characteristics with a special focus on exploring the effects of the shape pattern index. The research was based on a hedonic price model across two main distance buffers from residential properties to urban green spaces. Green spaces were characterized by size and shape measured by a landscape shape index (LSI). This study was based on 16,222 housing transaction data obtained from the website of real estate agencies during December 2019 in the Metropolitan Area of Beijing. Linear regression and semi-log regression analysis were used to examine the associations between independent housing and neighborhood characteristic variables and housing prices. The results suggested that a one-unit increase in the natural logarithm of the landscape shape index (LSI) can increase housing prices by 4% (5543 CNY ≈ 826 USD). Such marginal effects were more pronounced for residences located close to urban green spaces and tended to decay as the distance from residences to green spaces increased. Additional analysis captured the marginal effects of the natural logarithm of the landscape shape index (LSI > 1.3) on achi",27.0,https://www.mdpi.com/2073-445X/12/2/496/pdf?version=16765420291880c6b87c025c954f94994a5ebd85d7fd8b3110928,10.1016/j.eap.2019.04.013,"Valuing bushfire risk to homeowners: Hedonic property values study in Queensland, Australia",2019,Economic Analysis and Policy,W. Athukorala; W. Martin; C. Wilson; D. Rajapaksa,"Bushfires are a common occurrence and are an inevitable natural event in many regions of Australia in most years. Despite the dangers of such bushfires to nearby properties and human life, humans continue to live in close proximity to bushfire prone areas. The pertinent questions asked in this study are whether residents are aware of the dangers of living in such areas- and if so, is it reflected in lower property values? Such residents have the choice of either discounting the risks of bushfires in their neighbourhoods or deciding to pay more to live in bushfire areas for the positive amenity values afforded by forested bushland settings. Buyers paying a premium price to live in close proximity to green space are well documented in hedonic property (HP) values studies. We examine this phenomenon using data available for forested bushfire prone areas in the immediate environs of the city of Brisbane, Queensland, Australia using an HP values approach. For this study sales data of 1028 houses in four suburbs are used. The regression results clearly show that residents in fact are paying more to be close to green space (forested areas) which is also clearly identified as bushfire pron",27.0,https://eprints.qut.edu.au/129175/1/Valuing%20bushfire%20risk%20to%20homeowners.pdf18993167f8d04c2132bc9a724e067aad82010189af8,10.4028/www.scientific.net/amm.587-589.2176,The Effects of Noise Pollution Produced by Road Traffic of Naples Beltway on Residential Real Estate Values,2014,,V. del Giudice; P. De Paola,"Noise pollution generated by road traffic represents a damage factor for property values when sound pressure levels exceeds normal tolerability limit. In fact, noise emissions over the normal tolerability limit cause a real estate values reduction and lower marketability in terms of willingness to pay by traders. In this study the effects of noise pollution produced by road traffic of Naples Beltway on residential real estate values for a central urban area have been evaluated. These economic effects were evaluated using an econometric analysis of property prices (Land Price Analysis) based on a hedonic price function built through a semiparametric additive model (Penalized Spline Semiparametric Method) and applied to a sample of defined residential real estate market of Naples. In line with indications provided by wide literature examined, for increase of an sound level unit (expressed in dB) it was verified that average depreciation percentage for real estate values ranges from 0,30% (diurnal emissions) to 0,33% (nocturnal emissions).",27.0,https://doi.org/10.4028/www.scientific.net/amm.587-589.217619040db7ec14662e50651b0e9424355f26bf4758a29,10.2139/ssrn.1783627,Commercial and Residential Land Prices Across the United States,2010,,Joseph B. Nichols; Stephen D. Oliner; Michael R. Mulhall,"We use a national dataset of land sales to construct land price indexes for 23 MSAs in the United States and for the aggregate of those MSAs. We construct the price indexes by estimating hedonic regressions with a large sample of land transactions dating back to the mid-1990s. The regressions feature a flexible method of controlling for spatial price patterns within an MSA. The resulting price indexes show a dramatic increase in both commercial and residential land prices over several years prior to their peak in 2006-07 and a steep descent since then. These fluctuations in land prices are considerably larger than those in well-known indexes of commercial real estate and house prices. Because those existing indexes price a bundle of land and structures, this comparison implies that land prices have been more volatile than structures prices over this period.",27.0,https://doi.org/10.2139/ssrn.1783627191https://openalex.org/W3136516155,10.1061/(asce)up.1943-5444.0000698,"Determinants of Housing Prices in Dalian City, China: Empirical Study Based on Hedonic Price Model",2021,Journal of Urban Planning and Development,Huanhuan Luo; Shengchuan Zhao; Ronghan Yao,"Housing price is one of the most popular topics in urban studies. Among all the determinants of housing price, transportation accessibility is an essential factor that people often consider when purchasing a house. Using a semilogarithmic hedonic price model, this paper discusses the effects of structural attributes and accessibility of neighboring destinations on housing prices. The study area targets the core urban area of Dalian city, China. The data used in this study consist of sales prices of commercial apartments and houses and the geographic coordinates of corresponding residential areas. Estimation results of the hedonic price model show that structural attributes and accessibility to neighboring destinations significantly affect housing prices. The most influential factors to housing prices are the location of apartment or house, the nearby quality of higher education resources, and proximity to public transit service. These findings are significant for real estate developers, urban planners, and transportation planners to better understand the real estate market and to promote transit-oriented development.",27.0,192fb9d007b500b1eff5cd9c2ed633d123752bd4215,10.3390/su13052838,EPC Labels and Building Features: Spatial Implications over Housing Prices,2021,,Alice Barreca; E. Fregonara; D. Rolando,"The influence of building or dwelling energy performance on the real estate market dynamics and pricing processes is deeply explored, due to the fact that energy efficiency improvement is one of the fundamental reasons for retrofitting the existing housing stock. Nevertheless, the joint effect produced by the building energy performance and the architectural, typological, and physical-technical attributes seems poorly studied. Thus, the aim of this work is to investigate the influence of both energy performance and diverse features on property prices, by performing spatial analyses on a sample of housing properties listed on Turin’s real estate market and on different sub-samples. In particular, Exploratory Spatial Data Analyses (ESDA) statistics, standard hedonic price models (Ordinary Least Squares—OLS) and Spatial Error Models (SEM) are firstly applied on the whole data sample, and then on three different sub-samples: two territorial clusters and a sub-sample representative of the most energy inefficient buildings constructed between 1946 and 1990. Results demonstrate that Energy Performance Certificate (EPC) labels are gaining power in influencing price variations, contrary to ",26.0,https://www.mdpi.com/2071-1050/13/5/2838/pdf?version=16151697131931cc9771f869ec8b0800957a96eb1404558abe9ef,10.1080/14043858.2015.1009674,Does crime in parks affect apartment prices?,2015,,Asifa Iqbal; V. Ceccato,"A park is a desirable feature when people are purchasing a property. Buyers are ready to pay more for properties surrounded by natural amenities, such as a pleasant park. However, if a park is targeted by crime and disorder, then it may have a negative effect on people's appraisal. The aim of this study is to reach a better understanding of how parks and crime rates affect housing prices taking into account residential properties and parks type. Stockholm, the capital of Sweden, is used as the case study. The methodology has two stages. An extensive field work was performed in a selected number of parks to help characterize the parks in Stockholm. This information was gathered with secondary data about parks using Geographic Information System. This pre-assessment was later followed by the analysis of 2008s apartment sales using hedonic modelling to assess the effect of parks alone and in combination with crime rates. Results suggest that the effect of parks on prices vary by park type (increased with, e.g. features of cultural and national interest and decreased with ball games or boating facilities) while an aggregated measure of parks lowers overall apartment prices. More intere",26.0,http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-167789194ed70211601abf752ae75e8476f975841dd967b22,10.1111/jiec.12957,An integrated model of real estate market responses to coastal flooding,2019,Journal of Industrial Ecology,Handi Chandra‐Putra; C. Andrews,"Understanding and improving how humans adapt to climate change are priorities in our research community, and coastal settlements are good places to study adaptation. Severe storm events and sea‐level rise are threatening coastal communities with increasing levels of flood damage. Because ownership of coastal assets is distributed among many private and public actors, both individual property owners and public officials must take adaptive actions. This paper introduces an integrated agent‐based and hedonic pricing modeling system to simulate coastal real estate market performance under non‐equilibrium conditions that reflect the effects of storm events. The modeling system, which is used for policy analysis, is calibrated to conditions in two towns in Monmouth County, New Jersey, USA, which were badly damaged by Hurricane Sandy in 2012. The key findings are that (a) coastal real estate markets capitalize flood risk into property values but this discount diminishes rapidly as time passes between storm events, and (b) there is a distinct equity versus efficiency tradeoff in designing public policies to reduce the cost to society of coastal flooding. Stringent regulation of building pr",26.0,195f6b6ae5a55fb1e133be96a1e4c3e22714c234c4e,10.1108/jpif-07-2019-0093,Property valuation: the hedonic pricing model – location and housing submarkets,2019,Journal of Property Investment & Finance,G. Lisi,"196Purpose197The purpose of this paper is to comment upon the use of hedonic pricing models for the valuation of property. This model can be particularly useful for some housing markets.198199200Design/methodology/approach201This Education Briefing is an explanation of the how hedonic pricing can be useful in looking at the effect of “location” on the house prices within different submarkets using the Italian real estate market as an example.202203204Findings205Although, this case study is relatively straightforward, it shows how the application of the market approach can provide insights in cases where the comparable properties belong to different submarkets with relatively few transactions.206207208Practical implications209In cases of mass appraisals, hedonic pricing models can provide a broad indication of value across submarkets.210211212Originality/value213This paper develops a general framework that connects multiple regression analysis, direct comparison model and submarket binary variables.214",25.0,215doi_10_1108_02637470110366202,10.1108/02637470110366202,An application of the hedonic price model with uncertain attribute ‐ The case of the People’s Republic of China,2001,Property Management,Zan Yang,"The implicit prices of housing characteristics concerning the physical structure, location, environment and the risk of construction quality in China are examined in this paper. The hedonic price model with uncertainty of construction quality is adopted. Data is collected from the Beijing residential market. The results indicate that consumers have different preferences for choosing residences in the different parts of Beijing and the marginal price of public facilities is negative. The most important preference suggests households in Beijing are willing to pay additional expenditures to protect themselves from low construction quality. An obvious political implication of this study is that further residential reform should be accompanied by improved construction quality under legal supervision and by encouraging real estate developers to allocate units according to the preferences of households.",25.0,216e13b244754a8414a178e49afae995b23f640983e,10.1007/s11769-015-0788-4,"A GIS-based spatial analysis of housing price and road density in proximity to urban lakes in Wuhan City, China",2015,Chinese Geographical Science,Zuo Zhang; Shukui Tan; Wenwu Tang,"As one of the essential urban open spaces, lakes usually contribute immensely to the quality of residents′ daily lives. Different from hedonic approach employed in existing researches on urban open spaces in China, this paper integrates housing price surface with road density to analyze the spatial characteristics in proximity to urban lakes in Wuhan City, China. With the expansion of Wuhan City, urban lakes became polluted, they shrunk or even disappeared, leading to unfavorable conditions for sustainable development of the city. To better understand the spatial relationship between the city and lakes, we classify the urban lakes in Wuhan central area into ′lakes in the urban center′ and ′lakes in urban fringe′. Based on housing price surface we explore the spatial characteristics in proximity to different lakes and differences between the lakes. We also use Geographic Information System (GIS) tool to calculate road density as a supplementary indicator to reflect the accessibility in proximity to urban lakes. The results indicate that relative independence exists between different towns, and the spatial characteristics are different depending on scales and locations. In most of ca",24.0,http://egeoscien.neigae.ac.cn/EN/10.1007/s11769-015-0788-421797d31b8093c5c6178a384923fff83f7d3b389378,10.3390/su12031097,The Economic Effects of Climate Change Adaptation Measures: Evidence from Miami-Dade County and New York City,2020,,Seung Kyum Kim,"This research examines the economic impact of climate change adaptation measures on the housing markets of two representative coastal cities in the United States located along the Atlantic Ocean. The results shed light on how adaptation measures and investments influence housing values and local real estate markets with respect to their place-based and local forms of implementation. Numerous quantitative approaches, with the use of geospatial data, panel-data hedonic regressions, and difference-in-differences analyses, are used to examine changes in property values associated with climate adaptation measures and the dynamics of risk perception. The results also signal how risk perception and hurricane characteristics are reflected in housing markets, thereby shedding light on the effects of anticipatory and reactive adaptation strategies on property values in these coastal communities. Collectively, the study suggests which adaptation strategies and characteristics can contribute to maximizing both community resilience and economic benefits against the weather extremes caused by climate change.",24.0,https://www.mdpi.com/2071-1050/12/3/1097/pdf?version=158142646421823f395af193b39ce5b0d86122a8c897cee7b565b,10.14716/ijtech.v10i1.975,A Comparison of Bandwidth and Kernel Function Selection in Geographically Weighted Regression for House Valuation,2019,International Journal of Technology,J. Yacim; D. Boshoff,"The study examines the influence of four spatial weighting functions and bandwidths on the performance of geographically weighted regression (GWR), including fixed Gaussian and bi-square adaptive kernel functions, and adaptive Gaussian and bi-square kernel functions relative to the global hedonic ordinary least squares (OLS) models. A demonstration of the techniques using data on 3.232 house sales in Cape Town suggests that the Gaussian-shaped adaptive kernel bandwidth provides a better fit, spatial patterns and predictive accuracy than the other schemes used in GWR. Thus, we conclude that the Gaussian shape with both fixed and adaptive kernel functions provides a suitable framework for house price valuation in Cape Town.",24.0,https://doi.org/10.14716/ijtech.v10i1.975219doi_10_1016_j_landusepol_2006_07_003,10.1016/j.landusepol.2006.07.003,Environmental amenities and territorial anchorage in the recreational-housing rental market: A hedonic approach with French data,2007,Land Use Policy,Amedee Mollard; Tina Rambonilaza; Dominique Vollet,,24.0,220f42358328768bfba6d89075e5cb2a70ecc456d8c,10.1108/jerer-06-2020-0033,Energy performance certificates and house prices: a quantile regression approach,2020,Journal of European Real Estate Research,M. McCord; M. Haran; P. Davis; John McCord,"PurposeA number of studies have investigated the relationship between energy performance certificates (EPCs) and house prices. A majority of studies have tended to model energy performance pricing effects within a traditional hedonic conditional mean estimate model. There has been limited analysis that has accounted for the relationship between EPCs and the effects across the pricing distribution. Moreover, there has been limited research examining the “standard cost improvements EPC score”, or “potential score”. Therefore, this paper aims to quantify and measure the dynamic effects of EPCs on house prices across the price spectrum and account for standardised cost-effective retrofit improvements.Design/methodology/approachExisting EPC studies produce one coefficient for the entirety of the pricing distribution, culminating in a single marginal implicit price effect. The approach within this study applies a quantile regression approach to empirically estimate how quantiles of house prices respond differently to unitary changes in the proximal effects of EPCs and structural property characteristics across the conditional distribution of house prices. Using a data set of 1,476 achiev",23.0,https://pure.ulster.ac.uk/en/publications/ebc00a44-6d16-49cb-9e0b-9a05022b37612219c7b2eaba767769a138e2eee57dcf072ba93d657,10.1365/s41056-022-00063-1,From human business to machine learning—methods for automating real estate appraisals and their practical implications,2022,Zeitschrift für Immobilienökonomie,Moritz Stang; Bastian Krämer; Cathrine Nagl; W. Schäfers,"Until recently, in most countries, the use of Automated Valuation Models (AVMs) in the lending process was only allowed for support purposes, and not as the sole value-determining tool. However, this is currently changing, and regulators around the world are actively discussing the approval of AVMs. But the discussion is generally limited to AVMs that are based on already established methods such as an automation of the traditional sales comparison approach or linear regressions. Modern machine learning approaches are almost completely excluded from the debate. Accordingly, this study contributes to the discussion on why AVMs based on machine learning approaches should also be considered. For this purpose, an automation of the sales comparison method by using filters and similarity functions, two hedonic price functions, namely an OLS model and a GAM model, as well as a XGBoost machine learning approach, are applied to a dataset of 1.2 million residential properties across Germany. We find that the machine learning method XGBoost offers the overall best performance regarding the accuracy of estimations. Practical application shows that optimization of the established methods—OLS an",23.0,https://link.springer.com/content/pdf/10.1365/s41056-022-00063-1.pdf22235e9cf817db8c35d9d40580566f6516793f3cc92,10.1080/00330124.2020.1818586,"Sea Level Rise, Homeownership, and Residential Real Estate Markets in South Florida",2020,Professional Geographer,Xin-Yu Fu; J. Nijman,"This article builds on a small but rapidly growing body of research that seeks to determine the impact of sea level rise on the pricing of residential properties. Through a spatial hedonic regression analysis of real estate markets in two Florida counties (Miami–Dade and Pinellas), we assess the influence of different exposure levels on market discounts. Our article stands out in terms of its focus on two comparative case studies and its differentiation between properties that are primary homes versus nonprimary homes. We find that generally discounts are positively associated with exposure levels and overall Miami–Dade experiences higher discounts than Pinellas due to the former’s lower average elevations. We also observe different market behaviors of primary versus nonprimary home buyers and these are partially dependent on affluence. In Miami–Dade, price discounts are less for highly priced properties purchased by nonprimary owners. We attribute this to different buying motives and risk tolerance of affluent nonprimary homeowners. We argue that nonprimary ownership, particularly in high-end waterfront residential real estate, is tempering gradual market adaptation to sea level r",23.0,https://www.tandfonline.com/doi/pdf/10.1080/00330124.2020.1818586?needAccess=true22328afe169f4e2851e590b8152147dbd5bb4ee90f0,10.2139/ssrn.3764334,Quality of Life in Chinese Cities,2021,Social Science Research Network,Tiechou Shi; Wenzhang Zhu; Shi-He Fu,"Abstract The Rosen-Roback spatial equilibrium theory states that cross-city variations in wages and housing prices reflect urban residents' willingness to pay for urban amenities or quality of life. This paper is the first to quantify and rank the quality of life in Chinese cities based on the Rosen-Roback model. Using the 2005 1% Population Intercensus Survey data, we estimate the wage and housing hedonic models. The coefficients of urban amenity variables in both hedonic models are considered the implicit prices of amenities and are used as the weights to compute the quality of life for each prefecture-level city in China. In general, provincial capital cities and cities with nice weather, good air quality, and accessible public transit have high quality of life. We also find that urban quality of life is positively associated with the subjective well-being of urban residents.",23.0,https://doi.org/10.2139/ssrn.376433422402b5387f9679dc6d340d34b2c07dc617e35c96d3,10.3368/le.98.2.050120-0062r1,"Property Values, Water Quality, and Benefit Transfer: A Nationwide Meta-analysis",2021,Land Economics,D. Guignet; M. Heberling; M. Papenfus; O. Griot,"We construct a comprehensive, publicly available meta-dataset based on 36 hedonic studies that examine the effects of water quality on housing values in the United States. The meta-dataset includes 656 unique estimates and entails a cluster structure that accounts for price effects at different distances. Focusing on water clarity, we estimate reduced-form meta-regressions that account for within-market dependence, statistical precision, housing market and waterbody heterogeneity, publication bias, and methodological practices. Although we find evidence of systematic heterogeneity, the out-of-sample transfer errors are large. We discuss the implications for benefit transfer and future work to improve transfer performance.",23.0,http://le.uwpress.org/content/98/2/191.full.pdf225https://openalex.org/W1984311241,10.1111/j.1467-9787.2010.00679.x,"SPATIAL MULTIPLIERS IN HEDONIC ANALYSIS: A COMMENT ON “SPATIAL HEDONIC MODELS OF AIRPORT NOISE, PROXIMITY, AND HOUSING PRICES”*",2010,Journal of Regional Science,Seiji S.C. Steimetz,"ABSTRACT This note draws upon the spatial-hedonic analysis of Cohen and Coughlin to clarify the role of spatial multipliers in regression specification and benefits measurement, and to demonstrate the appropriate calculation of these benefits from dummy-variable coefficients in semi-logarithmic spatial-lag models.",23.0,226fb4a9d346ea610ca53c0dfb682b8000a6c7b0f50,10.1108/bepam-07-2018-0100,Driving forces for the US residential housing price: a predictive analysis,2019,Built Environment Project and Asset Management,A. Jafari; Reza Akhavian,"227Purpose228The purpose of this paper is to determine the key characteristics that determine housing prices in the USA. Data analytical models capable of predicting the driving forces of housing prices can be extremely useful in the built environment and real estate decision-making processes.229230231Design/methodology/approach232A data set of 13,771 houses is extracted from the 2013 American Housing Survey (AHS) data and used to develop a Hedonic Pricing Method (HPM). Besides, a data set of 22 houses in the city of San Francisco, CA is extracted from Redfin real estate brokerage database and used to test and validate the model. A correlation analysis is performed and a stepwise regression model is developed. Also, the best subsets regression model is selected to be used in HPM and a semi-log HPM is proposed to reduce the problem of heteroscedasticity.233234235Findings236Results show that the main driving force for housing transaction price in the USA is the square footage of the unit, followed by its location, and its number of bathrooms and bedrooms. The results also show that the impact of neighborhood characteristics (such as distance to open spaces and business centers) on the housing prices is ",22.0,237a752c51f13c5e37c5feed697560c5fef4264a957,10.3390/ijgi12060228,The Spatial Effect of Accessibility to Public Service Facilities on Housing Prices: Highlighting the Housing Equity,2023,ISPRS Int. J. Geo Inf.,Peiheng Yu; E. Yung; E. H. Chan; Shujin Zhang; Si-Qiang Wang; Yi-Yun Chen,"Understanding how public service accessibility is related to housing prices is crucial to housing equity, yet the heterogeneous capitalisation effect remains unknown. This study aims to investigate the spatial effect of public service accessibility on housing prices in rapidly urbanising regions. Here, we propose a novel methodological framework that integrates the hedonic price model, geographical detector model and the spatial association detector model to understand housing equity issues. The rapidly rising housing prices, vastly transformed urban planning and heterogeneous land use patterns make the urban centre of Wuhan a typical case study. High-value units of public service accessibility are concentrated in built-up areas, while low-value units are located at the urban fringe. The results indicate that larger public services have more significant clustering effects than smaller ones. Recreational, medical, educational and financial facilities all have capitalisation effects on housing prices. Both the geographical detector model and the spatial association detector model could identify the drivers of housing prices, but the explanatory power of the latter is greater and coul",22.0,https://www.mdpi.com/2220-9964/12/6/228/pdf?version=168568356623875d0711aebd70fde400d1a6a49265e443bbe1884,10.1016/j.jum.2020.02.001,"The value of environmental (dis)amenities in the urban housing market: Evidence from Khulna, Bangladesh",2020,,Md. Sariful Islam; Ruqaiya Hossain; M. Morshed; S. Afrin,"Abstract Pressure of rapid urbanization on abiotic environmental parameters in the residential blocks is one of the major challenges of city corporation authorities in Bangladesh. Environmental degradation often reduces property value in the housing market. However, the studies attempted to assess the value of environmental amenities and dis-amenities in the housing market of Bangladesh are scarce. Hence, this study examines the economic value of environmental (dis)amenities in the housing market of Khulna city, Bangladesh. Hedonic pricing method was used to assess the value of four environmental attributes - ventilation, open space, waterlogging and landfill by waste in the housing market. The study found these environmental attributes explain the variation of house rents significantly. Environmental amenities–a hundred-meter reduction in proximity to open space leads to a 2 percent increase in rent while a one discrete unit increase in a 5-point ventilation improvement scale from very poor to excellent results in 5.4 rent increase–are found as rent booster in the urban housing market. In contrast, waterlogging and landfill by waste reduce house rents by 3.7 and 9.8 percent for on",22.0,https://www.sciencedirect.com/science/article/pii/S2226585619301943/pdf2391950348121562529d3183e92ed15bbac58b18e4d,10.3390/su10124720,Price Determinants and GIS Analysis of the Housing Market in Vietnam: The Cases of Ho Chi Minh City and Hanoi,2018,Sustainability,You Seok Chung; Ducksu Seo; Jaehwan Kim,"Since the introduction of the Doi Moi economic reform in 1986, the real estate market in Vietnam has witnessed a sharp increase in foreign investment inflows and a remarkable growth in the housing market, particularly for high-rise apartments in large cities. This study investigates the determinants of apartment prices in Ho Chi Minh City (HCMC) and Hanoi, the two most representative cities in Vietnam. The spatial distribution of apartments and their price determinants were addressed by the spatial analysis of Geographic Information System (GIS) and the hedonic model. The price determinants of both cities were closely associated with downtown-related factors; moreover, the externalities of urbanization affected each city. While HCMC was more related to the locational attributes of urban amenities and community density as well as programs because of unmanaged urbanization, Hanoi was more related to housing attributes, since the majority of apartment projects were developed under urban infrastructure development supported by the central government. Apartment cluster maps of each city clearly show the contrast of housing distribution. Our findings clarify the impact of government poli",22.0,https://www.mdpi.com/2071-1050/10/12/4720/pdf?version=154452873424043d34a3cb07ebe23b958a009b21ab082b8ff0225,10.3390/w8120577,Canals vs. Streams: To What Extent Do Water Quality and Proximity Affect Real Estate Values? A Hedonic Approach Analysis,2016,,Federico Bonetti; S. Corsi; L. Orsi; I. De Noni,"The presence of and proximity to water influences human settlement decisions, because water has been able to characterize the environment and affect human health since prehistoric times. Many scholars have studied the effects of environmental amenities on the real estate market; however, only a few of them have explored the effects of water. This study stresses the role of water with a focus on the dichotomy between artificial and natural waterways (canals vs. streams), which involves managerial and qualitative differences. A hedonic approach, based on a large web scraped and geo-referenced dataset of 10,530 observations, is used to analyze the effect of water proximity and quality on residential housing prices in the province of Milan (Italy). Our main results show a significant but conflicting impact of water proximity on real estate value: reducing the canal distance, we observe an increase in the residential housing sale price, in urban more than peri-urban environments; in contrast, reducing the stream distance, our results show decreases in property value. Moreover, a significant moderating effect of water quality on distance from streams is identifiable.",22.0,https://www.mdpi.com/2073-4441/8/12/577/pdf?version=1481019706241doi_10_1080_00420989550012997,10.1080/00420989550012997,Determinants of Bargaining Outcome in Single-family Housing Transactions: An Empirical Examination,1995,Urban Studies,Shunfeng Song,"Using a hedonic regression model, this paper examines determinants of bargaining outcome in single-family housing transactions. It divides potential factors into three broad categories: dwelling attributes, site amenities, and seller's and buyer's characteristics. Results with use of 1990 data for the Reno-Sparks area in Nevada show that bargaining outcome is determined by seller's asking price, buyer's household income, and some of the dwelling attributes and site amenities. This paper concludes that factors affecting housing price do not necessarily affect bargaining outcome, and first-time home buyers do not statistically bargain less than repeat home buyers.",22.0,242d8cad4f02e195d2dfd70c7decbae7ee10f7f3fe9,10.1016/j.sbspro.2014.12.198,The Effects of Environmental Quality on Residential Choice Location,2014,,Vincenza Chiarazzo; P. Coppola; L. dell'Olio; Angel Ibeas; M. Ottomanelli,"Abstract The aim of this research is to investigate the effects of environmental conditions in a given area on the residential location and the consequences on urban sprawl and accessibility. In particular, the study focuses on the effects of environmental quality and landscaping on property values. To this aim, the paper presents some hedonic Multiple Linear Regression models (MLR) estimating the housing price in metropolitan areas as a function of real-estate, environmental and accessibility variables. The hedonic models have been estimated using data collected in the province of Taranto (South-Italy) where the biggest steel factory in Europe (namely, ILVA), and one of the most important industrial port in the Mediterranean Sea are located. The set of considered variables were carried out from a location choice survey and hedonic regression estimators are presented to verify to what extent a relationship between the accessibility conditions, environmental context and the dwelling market values does exist. The results indicate that the inclusion, in the model specification, of the environmental variables between zones fit the data significantly better.",21.0,https://doi.org/10.1016/j.sbspro.2014.12.1982430ff4eb143517f757d1f3f4078cf390068474a83a,10.1177/0042098020982508,"Big data, accessibility and urban house prices",2021,Urban studies,Steven C. Bourassa; M. Hoesli; Louis A. Merlin; John L. Renne,"Big data applications are attracting increasing interest among urban researchers. One unexplored question is whether the inclusion of big data accessibility indices improves the accuracy of hedonic price models used for residential property valuation. This paper compares a big data index with an index derived from a regional travel demand model developed by local transportation planning agencies and traditional measures of accessibility defined as distances to employment centres. Controls for submarkets and a combined spatial autoregressive and spatial error model are also assessed as tools for capturing the value of location. Using single-family residential transactions from the Miami, Florida, metropolitan area, the study’s main conclusion is that the big data accessibility measure does not add meaningful explanatory or predictive power. In contrast, the spatial autoregressive and error model outperforms the other options considered.",21.0,https://aura.abdn.ac.uk/bitstream/2164/15444/1/Bourassa_et_al_US_BigDataAccessibility_AAM.pdf244f326d0249d4fa4d2ec6af5feb9cf6966a73ca545,10.52324/001c.11643,The Impact of Sea Level Rise on Real Estate Prices in Coastal Georgia,2020,,Jason Beck; Meimei Lin,"This paper adopts a hedonic pricing model to study the impact of vulnerability to inundation from sea level rise on home prices in Savannah, Georgia. We find that homes most at risk from sea level rise are associated with an approximate 3.1 percent price discount. The results are consistent with prior studies, which uses data from different locations in U.S. coastal areas. We also find that the discount is more significant in our later sample period, indicating that house buyers may be becoming more aware of the climate risk. This paper contributes to the understanding of house pricing factors in the study area regarding the sea level rise effects.",21.0,https://rrs.scholasticahq.com/article/11643.pdf245c6596bf9f58b7a0c2ddb8899dc4885cfd2da75bb,10.2139/ssrn.2533017,A New Hedonic Regression for Real Estate Prices Applied to the Singapore Residential Market,2014,,Liang Jiang; Peter C. B. Phillips; Jun Yu,,21.0,https://doi.org/10.2139/ssrn.2533017246905a3854a270ed33499b6e478e8376f155a10423,10.1108/17538271311306020,The importance of unobserved attributes in hedonic house price models,2013,,Liv Osland,,21.0,247d2e98410b6600677abd93f5aba6364bed32c9fab,10.3390/su12041497,"Research on the Sustainable Development of Urban Housing Price Based on Transport Accessibility: A Case Study of Xi’an, China",2020,Sustainability,Chaochen Xue; Yongfeng Ju; Shuguang Li; Qilong Zhou,"The development of a real estate economy is beneficial to urban stability. A method of real estate price prediction based on transport accessibility is proposed. The method adds bus accessibility and metro accessibility into the model, which has higher prediction accuracy than the traditional model. Firstly, bus accessibility and metro accessibility are calculated according to the space syntax theory. Then, four models, the traditional hedonic price model (HPM) with transport accessibility, the traditional hedonic price model without transport accessibility, the random forest (RF) model with transport accessibility, and the random forest model without transport accessibility, are introduced. Finally, the four models are compared and analyzed in terms of precision and importance of index contributions. Taking Xi ’an, China, as an example, the experimental results show that the transport accessibility calculated based on space syntax can accurately represent the transport convenience in an urban space structure. Furthermore, it has a great influence on the contribution of indexes in the model. With the introduction of bus accessibility and metro accessibility, the accuracy of the rea",20.0,https://www.mdpi.com/2071-1050/12/4/1497/pdf248545cf326ccb3a54be5fbf23c4d0d594ed51df62f,10.1145/3567430,Tackling the Accuracy-Interpretability Trade-off: Interpretable Deep Learning Models for Satellite Image-based Real Estate Appraisal,2022,ACM Transactions on Management Information Systems,Jan-Peter Kucklick; Oliver Müller,"Deep learning models fuel many modern decision support systems, because they typically provide high predictive performance. Among other domains, deep learning is used in real-estate appraisal, where it allows extending the analysis from hard facts only (e.g., size, age) to also consider more implicit information about the location or appearance of houses in the form of image data. However, one downside of deep learning models is their intransparent mechanic of decision making, which leads to a trade-off between accuracy and interpretability. This limits their applicability for tasks where a justification of the decision is necessary. Therefore, in this article, we first combine different perspectives on interpretability into a multi-dimensional framework for a socio-technical perspective on explainable artificial intelligence. Second, we measure the performance gains of using multi-view deep learning, which leverages additional image data (satellite images) for real estate appraisal. Third, we propose and test a novel post hoc explainability method called Grad-Ram. This modified version of Grad-Cam mitigates the intransparency of convolutional neural networks for predicting continu",20.0,249doi_10_1108_02637470410544986,10.1108/02637470410544986,Comparing hedonic models for estimating and forecasting house prices,2004,Property Management,Mike Fletcher; Jean Mangan; Emily Raeburn,"In published work on hedonic house price estimation it is not uncommon to examine some of the conditions required for the estimators to have desirable properties such as minimum variance and unbiasedness, in particular spatial autocorrelation. However, other conditions that can give rise to similar difficulties with the estimates are often ignored. If these technical conditions are not met, it is sometimes because the model is misspecified in some way. This paper argues that a wider range of diagnostic statistics should be used in the specification search for a good model, in particular, but not exclusively, those concerned with predictive stability. The paper illustrates this approach by examining both in‐sample and out‐of‐sample diagnostic tests of various specifications of a hedonic house price model using data taken from the sale of over 1,600 properties in the Midlands of the UK in 1999/2000. The models investigated include various specifications of the dependent and independent variables, including models that are non‐linear in the parameters. The paper concludes that such statistics can often help in model selection and should be more widely employed.",20.0,250b6401bedb59a7356e471bfe6cba4b53c93fef01d,10.1017/s0163548400004118,Land Use Conflicts in the Coastal Zone: An Approach for the Analysis of the Opportunity Costs of Protecting Coastal Resources,1984,,S. F. Edwards; G. Anderson,"The implicit price (hedonic) equation for the housing market in a coastal town in southern Rhode Island was estimated using a conditional Box-Cox maximum likelihood procedure. Linear, log-linear, and semi-log functional forms were rejected with 95% confidence. Estimates of marginal implicit prices for water related attributes (view of, frontage on, and proximity to a coastal salt water pond) derived from these rejected models were quite different from those determined from the optimal functional form. This result has important ramifications for public policy, as is shown in an example, since these attributes were found to be highly valued in the housing market.",20.0,http://ageconsearch.umn.edu/record/15927025110775abe80013ecff14e229bbec570dc6a870392,10.1016/j.jhe.2018.04.003,What contributes to the rising house prices in Beijing? A decomposition approach,2018,Journal of Housing Economics,Lei Zhang; Yi-Min Yi,"The average real house price in Beijing rose by roughly 41.8% between 2012 and 2015, and the appreciation differs across low- versus high-priced homes. The rising house price might be caused by changes in the characteristics of housing units, and it might also be induced by the changing returns to housing characteristics in the underlying hedonic price functions. In this paper, we use a comprehensive housing transaction dataset and analyze the changes in the distribution of house prices over time through a decomposition approach. The result of Oaxaca-Blinder mean decomposition suggests that the proportion of the price gap between 2012 and 2015 due to altered returns over time is greater than the proportion caused by changes in housing characteristics. The quantile decomposition shows that the decomposition effects are heterogenous across the complete distribution of house prices. We also find that low-priced homeowners are exposed to a decline in house prices, while there are deteriorating housing conditions from 2012 to 2015. The high-priced homeowners experience an improvement in living conditions, but a rise in house prices.",20.0,252d95b158824a0f257011222a22aaa46512eb5e45d,10.1080/19491247.2022.2059844,Supply side effects of the Berlin rent freeze,2022,International Journal of Housing Policy,Pekka Sagner; M. Voigtländer,"Abstract On 23 February 2020, the Berlin Senate introduced the Berlin rent freeze (‘Mietendeckel’). The law was repealed on 25 March 2021. The Berlin rent freeze was an unprecedented market intervention in the German housing market. We analyse how the rent cap part of the legislation which fixed rents at below market levels affected the supply side in the short term. We find rent decreases accompanied by decreases in supply five times as large. We further investigate spillover effects on the purchase market, regionally heterogeneous effects as well as different effects by dwelling characteristics. We find the rent freeze did not have spillover effects on dwellings for sale which point to a ‘wait-and-see-attitude’ on the investors’ side. We make use of a rich dataset of real estate advertisements and employ hedonic difference-in-difference and triple-difference estimation strategies.",20.0,253ca8fe51f6511f9c68a26ff0f5e3e41a356497cee,10.1080/19498276.2021.1915663,Green Premium: What is the Implied Prognosis for Sustainability?,2020,The Journal of Sustainable Real Estate,K. Addae-Dapaah; J. Wilkinson,"We live in a world where economic considerations underpin almost every decision to determine our social priorities. It is not surprising then that sustainability has fast become, among other things, economic advocacy. This has led to a proliferation of studies to establish the provenance of green premium to provide impetus for sustainable real estate development to drive the sustainability agenda. The extant literature is replete with studies that conclude that green buildings, which are a proxy for sustainable real estate, command a green premium notwithstanding disagreement about the size of the green premium. We revisit the green premium debate by analysing BREEAM certified office buildings (proxy for green buildings) in the Greater London area to ascertain the prevalence of green premium to answer the following questions: is the premium truly green (green-magic)? What prognosis does green premium provide for sustainability? The study uses quantitative analysis (hedonic model to analyse 2,842 CoStar transaction data from 2008 to 2018 inclusive and psychographic analysis based on primary data from a questionnaire survey of approximately 450 BREEAM certified building owners and oc",19.0,https://doi.org/10.1080/19498276.2021.19156632541462a807ace2b4c97b7b8368ffbe3a1c694cd0f7,10.1145/3442381.3449967,Integrating Floor Plans into Hedonic Models for Rent Price Appraisal,2021,The Web Conference,K. Solovev; Nicolas Pröllochs,"Online real estate platforms have become significant marketplaces facilitating users’ search for an apartment or a house. Yet it remains challenging to accurately appraise a property’s value. Prior works have primarily studied real estate valuation based on hedonic price models that take structured data into account while accompanying unstructured data is typically ignored. In this study, we investigate to what extent an automated visual analysis of apartment floor plans on online real estate platforms can enhance hedonic rent price appraisal. We propose a tailored two-staged deep learning approach to learn price-relevant designs of floor plans from historical price data. Subsequently, we integrate the floor plan predictions into hedonic rent price models that account for both structural and locational characteristics of an apartment. Our empirical analysis based on a unique dataset of 9,174 real estate listings suggests that current hedonic models underutilize the available data. We find that (1) the visual design of floor plans has significant explanatory power regarding rent prices – even after controlling for structural and locational apartment characteristics, and (2) harnessi",19.0,https://doi.org/10.1145/3442381.34499672557ee843b18f0fa45518c49c8fc64c9e24875d34e0,10.1016/j.landurbplan.2019.103644,Shared landscapes increase condominium unit selling price in a high-density city,2019,,Richard N. Belcher; Ester Suen; Sacha Menz; T. Schroepfer,"Abstract High-density buildings can benefit city sustainability by reducing expansion into biodiverse and often public natural ecosystems, reducing travel-time to work-and-play and improving energy efficiency. However, city densification can also remove vegetation which provides ecosystem services that enhance resident's wellbeing. Some architects design shared landscapes on and around large-scale buildings which are excludable to the public, like private gardens, but can be rivalrous between residents, like parks. This potentially mitigates public vegetation and subsequent ecosystem service loss. However, little evidence exists on whether condominium unit buyers pay more for shared landscapes. To address this knowledge gap, we used the hedonic pricing method to explain condominium unit resale value with unbuilt and vegetated space, accounting for other price determinants, spatial and temporal random effects using a robust regression. Leaf area above 184 m2 and unbuilt area (condominium estate area minus the building footprint) above 62.3 m2 per person had significant positive effects on condominium unit selling price. This provides evidence that economic returns can be gained by h",19.0,2560fc6edd4df184c789fc1f8ba8aa41e33271577cf,10.1177/0042098020926034,"The association between residential housing prices, bicycle infrastructure and ridership volumes",2020,,L. Conrow; S. Mooney; E. Wentz,"City officials and planners have shown increased interest in pedestrian- and bicycle-friendly designs aimed at addressing urban problems such as traffic congestion, pollution, sprawl and housing availability. An important planning consideration is the economic impact associated with existing or planned infrastructure, especially in relation to home property values. In this study, we use measures of infrastructure and ridership to evaluate the relationship between bicycling infrastructure and activity and single-family home values in Tempe, Arizona. We apply a hedonic modelling approach and find that bicycle infrastructure density is positively associated with home sale price, while ridership density around home locations has no significant relationship with sale price. Our results inform discourse related to the potential economic values of residential bicycle infrastructure, especially in areas where property tax is a source of local public finance revenue. We show that the characteristics of bicycle-friendly design may be the same characteristics valued by homebuyers and the resulting increased home sale values may lead to increased property tax revenue in Tempe, Arizona.",19.0,257doi_10_1068_a190059,10.1068/a190059,Households' Utilities and Hedonic Prices for Inner-City Homes,1987,Environment and Planning A: Economy and Space,A G Phipps,"The housing-consumption preferences of a sample of inner-city owner-occupants in Saskatoon are recovered from their unconstrained residential preferences for housing and neighbourhood types. These unconstrained utilities are quantitatively compared with implicit prices for the same housing and neighborhood types, computed from a hedonic housing price model. A first finding is that the households preferred the levels of eight of the twelve residential attributes that were also the higher priced. In contrast, a second finding was that their unconstrained utilities were negatively monotonically related to the hedonic price scales for four attributes, neighborhood housing, renovation/basement, age of construction, and family life cycle of the neighborhood people. The salience of these four divergences between the scales of value, in terms of future land-use and social change in inner-city neighborhoods, is discussed.",19.0,25841b49c5dc53c1cf4bbb9bcbcdbfb056f93548daa,10.1016/j.tranpol.2018.04.010,The impact of undesirable externalities on residential property values: spatial regressive models and an empirical study,2019,Transport Policy,Rubén Cordera; Vincenza Chiarazzo; M. Ottomanelli; L. dell'Olio; Angel Ibeas,"Abstract Pollutant emissions, noise and other externalities generated by heavy infrastructures, might impact negatively on real estate values. To test this effect, this paper presents the results of an analysis based on Hedonic Linear Regression, Spatial Hedonic Linear Regression and Hedonic Geographically Weighted Regression models, carried out for the study case of the province of Taranto (Italy). The biggest steel factory in Europe is located here, and some population movements have been observed in relation to the high levels of pollution in the areas close to the factory. The variables used to measure the impact of externalities are of two types: objective indicators such as the distance from the industrial area and the levels of NO2 and PM10, and subjective indicators such as the level of pollution and noise perceived by the population. Results show that the distance from factory was a positive factor in the real estate prices although not always clearly significant, and among pollution indicators, only high levels of NO2 had a negative effect. The accessibility to employment did not prove to be a significant variable in the real estate prices, which indicates that factors re",18.0,http://hdl.handle.net/10902/18147259f7706520c16282ce45762d71f0f70e12f4ece18b,10.3390/land12091660,"Valuing the Accessibility of Green Spaces in the Housing Market: A Spatial Hedonic Analysis in Shanghai, China",2023,Land,Shenglin Ben; He Zhu; Jia-Jun Lu; Renfeng Wang,"As a crucial determinant of urban livability, the importance of access to high-quality green spaces has long been recognized for achieving sustainable urbanization. In urban areas, higher values are usually placed in residential properties with higher accessibility to green spaces. Using housing transaction data from as many as 3388 residential communities in Shanghai coupled with high-resolution satellite data of urban green spaces, we comprehensively examine the relationship between residential property values and the accessibility of both community-owned and public green spaces. We find, in instrumental-variable estimations, that: (1) home prices, on average, increase by 0.17% if the overall green space accessibility rises by 1%; and that (2) a 1% increase in the green ratio within a community raises property values by 0.46%. Moreover, the number of accessible green spaces, area of accessible green spaces, and distance to the nearest green spaces have positive impacts on home values separately. We also find strong spatial dependence in urban green spaces and unobserved price determinants, as well as heterogeneity by location, property value, and housing type. Our empirical findi",18.0,https://www.mdpi.com/2073-445X/12/9/1660/pdf?version=1692929478260doi_10_3917_reru_092_0369,10.3917/reru.092.0369,Formation des prix immobiliers et consentements à payer pour une amélioration de l'environnement urbain : l'exemple rennais,2009,Revue d’Économie Régionale & Urbaine,Marc Baudry; Alain Guengant; Sophie Larribeau; Matthieu Leprince,"Ce travail a pour objectif d’illustrer l’apport de la théorie économique et des méthodes économétriques, plus particulièrement l’économétrie spatiale, à la conception et à l’évaluation d’opérations de renouvellement urbain. Dans ce but, l’approche par les prix hédoniques est retenue. Elle procède en deux temps. Dans un premier temps, sont identifiées, parmi un ensemble de caractéristiques de localisation données a priori, celles qui exercent un rôle discriminant sur la valeur des logements. Dans un second temps, les consentements à payer des habitants pour une amélioration des caractéristiques discriminantes sont calculés. L’application aux mutations d’appartements à Rennes entre les années 1994 et 2001 montre qu’il existe des externalités de voisinage significatives qui justifient une intervention publique. Les consentements à payer pour une amélioration des caractéristiques environnementales discriminantes apparaissent assez hétérogènes entre individus et variables d’une caractéristique à l’autre.",18.0,261d314c6a46f6ceb0fcf338474e9546ec201a241b3,10.1080/15623599.2019.1695097,"Effects of locations, structures and neighbourhoods to housing price: an empirical study in Shanghai, China",2019,International Journal of Construction Management,V. Tam; I. Fung; Jing Wang; Mingxue Ma,"Abstract Since Chinese housing market has been reformed, the increasing housing price has been a focus of the whole society. Shanghai, as the economic and financial center in China, is one of the cities which have the highest housing price. However, the high housing price has gradually become an important economic problem, as it could create huge challenges to maintain a healthy real estate industry in China. A comprehensive understanding of the relationship between housing market and its impactors is in need to control the housing price. This paper will focus on Shanghai housing market and analyse relationship between 12 housing characteristics and housing price, using hedonic price model. It is found that the 12 housing characteristics impact Shanghai housing price differently. This paper could provide newest and largest amount of data as references to researchers and investors who concern about Shanghai housing market, and help government to formulate a proper housing price policy.",18.0,262e17e99d6a6d0b06b64aed7569511e112085a9a42,10.3390/ijgi10020044,"Estimating the Impacts of Proximity to Public Transportation on Residential Property Values: An Empirical Analysis for Hartford and Stamford Areas, Connecticut",2021,ISPRS Int. J. Geo Inf.,Bo Zhang; Wei-Dong Li; N. Lownes; Chuan-Rong Zhang,"Public transit infrastructure may increase residential property values by improving accessibility and reducing commute expenses in urban areas. Prior studies have investigated the impacts of the proximity to public transportation on property values and obtained mixed conclusions. Many of these studies were focused on one transit mode for a single city. In this study, a hedonic pricing model is constructed to investigate the impacts of commuter rail/Bus Rapid Transit (BRT) and bus lines separately in two different areas: the Stamford area (Stamford–Darien–New Canaan) and the Hartford area (Hartford–West Hartford–East Hartford), Connecticut. Comparison of the results from Ordinary Least Square and Geographically Weighted Regression (GWR) indicates that estimation accuracy can be improved by considering local variation. Results from GWR show that impacts of proximity to bus and rail/BRT on property values vary spatially in the Hartford area. Negative impacts of bus stops are found in downtown Hartford and positive impacts in the west and east sides of Hartford. Impacts from rail/BRT are relatively minor compared with bus lines, partly due to the relatively recent launching of the BRT ",17.0,https://www.mdpi.com/2220-9964/10/2/44/pdf?version=16111337792636a71c3c2c308a0bc3c08e4953d48f0528096b578,10.3390/math9070783,"Artificial Neural Network, Quantile and Semi-Log Regression Modelling of Mass Appraisal in Housing",2021,Mathematics,Jose Torres-Pruñonosa; Pablo García-Estévez; Camilo Prado-Román,"We used a large sample of 188,652 properties, which represented 4.88% of the total housing stock in Catalonia from 1994 to 2013, to make a comparison between different real estate valuation methods based on artificial neural networks (ANNs), quantile regressions (QRs) and semi-log regressions (SLRs). A literature gap in regard to the comparison between ANN and QR modelling of hedonic prices in housing was identified, with this article being the first paper to include this comparison. Therefore, this study aimed to answer (1) whether QR valuation modelling of hedonic prices in the housing market is an alternative to ANNs, (2) whether it is confirmed that ANNs produce better results than SLRs when assessing housing in Catalonia, and (3) which of the three mass appraisal models should be used by Spanish banks to assess real estate. The results suggested that the ANNs and SLRs obtained similar and better performances than the QRs and that the SLRs performed better when the datasets were smaller. Therefore, (1) QRs were not found to be an alternative to ANNs, (2) it could not be confirmed whether ANNs performed better than SLRs when assessing properties in Catalonia and (3) whereas smal",17.0,https://www.mdpi.com/2227-7390/9/7/783/pdf?version=16179405812645cf7ffdc50779ba179e5d6c37bf66eba2f4f8109,10.5198/jtlu.v5i1.251,The value capture potential of the Lisbon Subway,2012,,L. Martinez; J. Viegas,"This paper tries to build on traditional value capture measures, to estimate the potential of application of some of these mechanisms to the Lisbon subway, examining their ability to contribute to cover the financial costs of the system operation and development. The study will just focus on the municipality of Lisbon where this system mainly operates. This research uses spatial hedonic pricing models of the real estate of the region, calibrated on previous stages of the study, to asses, to which extent, transportation infrastructure is currently capitalised into the real estate market. The paper uses a Monte Carlo simulation procedure to estimate a synthetic population of residential and non residential properties that matches the census blocks statistics, allowing, measuring the subway valuation for each synthetic property and aggregate the results for the whole municipality. This potential value capture estimate is then used to estimate an annual tax that could be charged under different value capture measures configurations (i.e. land value tax, special assessment). The results suggest that there is a significant potential of the use of this instrument to finance the subway inf",17.0,https://www.jtlu.org/index.php/jtlu/article/download/251/2072651a18b0a2989548006da6847a281b5c4164757bcc,10.1177/0042098019896977,"The spatial varying relationship between services of the train network and residential property values in Melbourne, Australia",2020,,Qian-Yao Li; Junwu Wang; J. Callanan; Binbin Lu; Zeng Guo,"This study investigates the spatial effects of the service frequency and transport interchange facilities of rail stations on residential property values for the entire metropolitan train network in Melbourne. Residential properties are classified as either detached or attached dwellings. Given that a traditional hedonic price model cannot handle the spatial dependence and spatial non-stationarity of the housing market, several geographically weighted regression (GWR) models are used and multicollinearity is considered; the model with the Euclidean distance metric outperforms others. Results indicate that the service frequency and facilities of the stations influence the residential property values in a spatially variable way. For every 1 km closer to the train stations, an increase in the frequency of the train services per unit results in a change in the residential property values ranging from −4.01% to 2.71%; an improvement in the transport interchange facilities per unit results in a change in the residential property values ranging from −29.93% to 47.04%. Crime and retail activities that indirectly affect the relationship between rail stations and residential property values ",17.0,26602982ed8d13a3bc1ca01b6daff3b9f8333423220,10.1108/ijhma-01-2022-0013,The relationship between macroeconomic variables on residential property price: case study in Malaysia before and during COVID-19,2023,International Journal of Housing Markets and Analysis,Siti Hafsah Zulkarnain; Abdol Samad Nawi,"267Purpose268The purpose of this study is to analyse numerous aspects affecting residential property price in Malaysia against macroeconomics issues such as gross domestic product (GDP), exchange rate, unemployment and wage.269270271Design/methodology/approach272The hedonic pricing model has been adopted as econometric model for this research to investigate the relationship between residential property price against macroeconomics indicator. The data for residential property price and macroeconomic variables were collected from 1991 to 2019. Multiple linear regression had been adopted to find the relationship between the dependent and independent variables.273274275Findings276The result shows that the GDP has a significant positive impact on residential property price, while exchange rate has no significant impact although it was positive. In addition, the unemployment rate has a significant impact on the residential property price and has a negative relationship. Similar to the wage that shows the negative relationship with residential property prices. Moreover, during the pandemic COVID-19 in Malaysia, this research shows a more transparent view of the relationship between residential property price",17.0,27731188458b5f63429fc1a7cde16aa1e428105d775,10.3390/su141711021,"Hedonic Pricing of Houses in Megacities Pre- and Post-COVID-19: A Case Study of Shanghai, China",2022,Sustainability,Yu-Jiao Chen; Zheng Luo,"Housing price is one of the most concerning issues to the public worldwide. Studying the spatial characteristics of Shanghai’s housing prices and their explanatory factors is of great practical significance, for Shanghai is the largest city in China and serves as the national economic center and a global financial hub. By crawling the point of interest (POI) data from the Lianjia Real Estate and Gaode Map in the past decade and applying the multiscale geographically-weighted regression (MGWR) model, this study deeply explores the spatial characteristics of housing prices and their main influencing variables in Shanghai before and after the COVID-19 pandemic. Results show that housing prices in Shanghai kept rising even under the shock of the pandemic, especially in high-priced housing. After the pandemic, Shanghai’s housing price market polarization intensified. In addition, housing prices are very sensitive to location and have strong spatial heterogeneity. The influencing effects of different explanatory factors vary perceptibly in spatial heterogeneity as well as pre- and post- COVID-19.",17.0,https://www.mdpi.com/2071-1050/14/17/11021/pdf?version=1662426981278f8f77ddfaeaa028ca11286c74729edeab5b8f1c6,10.1086/689201,The Implicit Price of Aquatic Grasses,2014,Marine Resource Economics,D. Guignet; C. Griffiths; H. Klemick; P. Walsh,"ABSTRACT Submerged aquatic vegetation (SAV) in the Chesapeake Bay is well below half of its historic levels, largely due to excessive nutrient and sediment loads degrading water quality. SAV provides important ecosystem functions, many of which are beneficial to local residents. To understand the implicit value residents place on SAV and the ecosystem services it provides, we undertake a hedonic property value study using residential transactions in 11 Maryland counties adjacent to the Chesapeake Bay. These data are matched to highresolution maps of SAV coverage. We pose a quasi-experimental comparison and examine how the prices of homes near the waterfront vary with the presence of SAV. On average, waterfront and near-waterfront homes within 200 meters of the shore sell at about a 6.5% premium when SAV is present. Applying these estimates to the 185,000-acre SAV attainment goal suggests total property value gains on the order of $436 million. JEL Codes: Q51, Q53.",17.0,http://ageconsearch.umn.edu/record/2809222795673fe7c4959c2dc455da07c77c14efc15cca030,10.1016/j.seta.2021.101182,The effect of LEED certification on office rental values in China,2021,,Weilin Li; Guanyu Fang; Liu Yang,"Abstract With the increasing awareness of environmental protection, the real estate sector has proposed green buildings to achieve the sustainability of the building environment. Although the advantages of these sustainable features of green buildings are apparent, the effect of green buildings on the real estate economic values in China is not evident. This study aims to investigate whether and to what extent LEED certification can impact the rental values of the office market in China. This study analyzes an overall sample of China comprising 50 LEED-certified and 50 non-LEED offices and two local samples of Shanghai and Beijing each, based on a hedonic price model. The results suggest that the rental premium for LEED-certified in the China sample is 19.5%, while that in Shanghai and Beijing samples are 25.5% and 20.8%, respectively. Furthermore, other variables, such as utilization time, floors, construction area, building class, and GDP, are also correlated with rental values. As an early study on the impact of green certifications on the Chinese real estate market, this research provides investors with empirical data to evaluate the investment value of introducing green certif",17.0,28085ef5e533b05b7fdfa0d30e4429b6c6891b5b434,10.1016/j.eap.2019.09.004,Implementing hedonic pricing models for valuing the visual impact of wind farms in Greece,2019,,Konstantinos Skenteris; S. Mirasgedis; Christos Tourkolias,"Abstract Although wind energy is a pollution-free and infinitely sustainable form of energy, there is considerable concern over certain environmental effects resulting from its development. Criticism focuses primarily on the visual impact of wind turbines and transmission lines, which may result in perceived deterioration of the landscape and also harm other economic activities such as tourism and real estate. This study applies the hedonic pricing method to estimate the value of environmental externalities associated with large-scale exploitation of wind power at a local level. It examines the characteristics of approximately 1,800 sales of single-family homes surrounding 17 existing wind facilities in two Greek islands, namely Evia and Kefalonia. Four different hedonic price models are developed and applied, with diverging results in the two areas. We find that in Evia, the per unit floor area sales price decreased for dwellings located within a 2 km radius of the wind farms, while in Kefalonia, the distance of the house to the wind turbines had no statistically significant effect on the sales price.",17.0,281doi_10_3406_ecop_1995_5766,10.3406/ecop.1995.5766,Prix hédoniques et estimation d'un modèle structurel d'offre et de demande de caractéristiques,1995,Économie & prévision,Olivier Marchand; Eric Skhiri,"Hedonic Prices and a Structural Model Estimate of the Supply and Demand of Characteristics: Application to the French Rental Housing Market, by Olivier Marchand and Eric Skhiri . This hedonic price analysis is one of the first to be made of the French rental housing market. The data are taken from cross-sectional surveys in eight French towns (excluding the Paris area). A Box-Cox transformation is used to obtain the best functional form. The hedonic regression is found to be fairly satisfactory with 66% of variance explained by the model. Furthermore, a structural model of the supply and demand of characteristics is validated. The problem of simultaneity is solved by using the town dummy as an instrumental variable. We therefore make the first attempt to estimate the factors of the supply and demand of characteristics in France.",17.0,282doi_10_3917_reco_645_0883,10.3917/reco.645.0883,La contribution des effets de voisinage à la formation des prix du logement,2013,Revue économique,Aurélien Décamps; Frédéric Gaschet,"Cet article se propose d’évaluer le rôle des effets de voisinage dans la formation des prix du logement, en prenant appui sur l’exemple de l’agglomération bordelaise. Compte tenu des limites des approches hédoniques traditionnelles dans la prise en compte de ces effets, nous mettons en œuvre une modélisation hédonique multiniveaux permettant une décomposition de la variance due aux différents déterminants identifiés par la théorie économique, à deux échelles spatiales. Les résultats confirment le rôle significatif joué par les effets de voisinage dans la formation des prix immobiliers, de même que la primauté de ces déterminants sur les facteurs traditionnels d’accessibilité intra-urbaine.",17.0,283https://openalex.org/W2170495952,10.1111/1540-6229.00432,Economic Effects of Racial Integration: An Analysis of Hedonic Housing Prices and the Willingness to Pay,1987,Real Estate Economics,Stuart A. Gabriel,"This study evaluates household economic effects stemming from neighborhood racial integration in Oakland, California. To that end, housing market data are applied to estimate hedonic price and willingness‐to‐pay functions for neighborhood racial composition. Results of the analysis indicate the problematic nature of the constant willingness‐to‐pay assumption and suggest this standard method may underestimate the household economic effects of racial integration. The paper concludes with implications for neighborhood integration policy.",17.0,284a483774defcbadf7676aaa742f594af28562b13a,10.1108/ijhma-11-2022-0172,Predictability of Belgian residential real estate rents using tree-based ML models and IML techniques,2023,International Journal of Housing Markets and Analysis,Ian Lenaers; K. Boudt; L. De Moor,"285Purpose286The purpose is twofold. First, this study aims to establish that black box tree-based machine learning (ML) models have better predictive performance than a standard linear regression (LR) hedonic model for rent prediction. Second, it shows the added value of analyzing tree-based ML models with interpretable machine learning (IML) techniques.287288289Design/methodology/approach290Data on Belgian residential rental properties were collected. Tree-based ML models, random forest regression and eXtreme gradient boosting regression were applied to derive rent prediction models to compare predictive performance with a LR model. Interpretations of the tree-based models regarding important factors in predicting rent were made using SHapley Additive exPlanations (SHAP) feature importance (FI) plots and SHAP summary plots.291292293Findings294Results indicate that tree-based models perform better than a LR model for Belgian residential rent prediction. The SHAP FI plots agree that asking price, cadastral income, surface livable, number of bedrooms, number of bathrooms and variables measuring the proximity to points of interest are dominant predictors. The direction of relationships between rent and ",16.0,https://biblio.ugent.be/publication/01HHQGWGR372B5AP17MNYSHQ4T/file/01HHQH5547HMY0M017VDZ0QBVV.pdf295ac12b67b8c5e189983ceb5febdcf0b91db7f62d2,10.1016/j.landusepol.2020.105183,Identifying the effects of a land-use policy on willingness to pay for open space using an endogenous switching regression model,2021,,Yang Cao; B. Swallow; F. Qiu,"Abstract An open space offers a stream of economic, social and environmental benefits. Population growth and extensive forms of economic growth have encroached onto large amounts of open space, converting forests, parks, grasslands and crop fields to developed uses, including residential, commercial and industrial. Analysts have used hedonic pricing techniques to estimate the capitalization of the values of open space into residential property values and the effects of changes in land-use policies on property values. Few of those studies have considered the possibility that property transactions may not occur randomly under different policy regimes. House sellers, buyers and developers respond to land use policies in their sale and purchase behaviors, thus changing the portfolio of houses for which sales data are available in a particular period. Such non-randomness can further bias the policy assessment using regression analysis. We address this issue by estimating the effects of a new development policy on WTP for open space as well as property values while correcting the selection bias that can arise as the result of self-selection. The empirical case is the Town of Okotoks, Alb",16.0,2960bee27f0f1df00b7835293cf262907481dcc1292,10.3390/su11092709,Interaction of Public Transport Accessibility and Residential Property Values Using Smart Card Data,2019,Sustainability,Amarin Siripanich; T. Rashidi; Emily K. M. Moylan,"This study examines the relationship between residential property values and accessibility indicators derived from transit smart card data. The use of smart card data to estimate accessibility indicators for explaining the housing market has not yet been explored in the literature. Hence, this paper employs information from Brisbane, Australia’s “go card” and corresponding property data to develop residential property hedonic pricing models using an ordinary least square (OLS) model, a spatial lagged model (SL), a spatial error model (SE), and a geographically weighted regression (GWR). Due to the systematic coincidence between location and price similarities, these spatial econometric models yield superior goodness-of-fit over the OLS model. Using the proposed definition of public transit accessibility in this study, it was found that properties located in well-connected, well-serviced, and accessible locations generally experience premiums in their values. The results indicate that there is value added to the property market from the public investment in public transport services and infrastructure, which supports the adoption of transit funding mechanisms, such as value-capture ",16.0,https://www.mdpi.com/2071-1050/11/9/2709/pdf29729456dec57d29a749c11421568db5457ce686cfd,10.7764/rdlc.18.1.156,The evolution of energy efficiency impact on housing prices. An analysis for Metropolitan Barcelona,2019,Revista de la Construcción,Carlos Marmolejo-Duarte; Ai Chen,"The Energy Performance of Buildings Directive has it made mandatory to include an energy performance certificate (EPC) on real estate advertisements so as to promote efficient properties. Previous research has found a positive correlation between residential prices and EPC’s energy ranks; nonetheless, the analysis of the evolution of such impact for the same market is still pending. This paper tries to shed light on this issue by analyzing the evolution of prices of the second largest urban agglomeration in Spain. In doing so, a pooled hedonic model is carried out departing from selling listing prices of apartments and a set of locative control variables. Results suggest that in a short period the energy premium for multifamily houses has positively evolved. As a result, a sharped market differentiation arises between inefficient and energy saving dwellings. Such findings have significant implications for the construction and real estate industry, since higher selling prices may compensate for higher building costs coming from energy efficient technologies.",16.0,https://revistadelaconstruccion.uc.cl/index.php/RDLC/article/download/2019/2093298219a22b5256e870526111fcb3590a1cdecfe7240,10.3390/urbansci9020032,Comparative Analysis of Advanced Models for Predicting Housing Prices: A Review,2025,Urban Science,Inmaculada Moreno-Foronda; M. Sánchez-Martínez; M. Pareja-Eastaway,"Understanding the determinants of housing price movements is an ongoing subject of debate. Estimating these determinants becomes a valuable tool for predicting price trends and mitigating the risks of market volatility. This article presents a systematic review analyzing studies that compare various machine learning (ML) tools with hedonic regression, aiming to assess whether real estate price predictions based on mathematical techniques and artificial intelligence enhance the accuracy of hedonic price models used for valuing residential properties. ML models (neural networks, decision trees, random forests, among others) provide high predictive capacity and greater explanatory power due to the better fit of their statistical measures. However, hedonic regression models, while less precise, are more robust, as they can identify the housing attributes that most influence price levels. These attributes include the property’s location, its internal features, and the distance from the property to city centers.",16.0,https://www.mdpi.com/2413-8851/9/2/32/pdf?version=1738315009299https://openalex.org/W2889948534,10.1080/09599916.2018.1510428,Hedonic pricing and the spatial structure of housing data – an application to Berlin,2018,Journal of Property Research,Sören Gröbel; Lorenz Thomschke,"Housing prices are largely determined by physical location. By applying the outsample prediction accuracy of rental prices as evaluation criteria, we examine whether the choice of the hedonic model additionally depends on the spatial structure of housing data, i.e. accounting for locational effects by either district fixed effects or spatial econometric modelling. Our results show that a generalised spatio-temporal model outperforms a district fixed effects model only if the spatial density – the weighted mean distance to nearest neighbours – is relatively small. Moreover, we use the required density thresholds to deduce a pseudo indifference curve, thereby showing that the ratio of the weighted spatial distance-to-the mean district diameter increases with the mean sample size per district. This emphasises the role of data structure and district choices for model selection. Differences in data can thereby serve as an explanation for contradictory findings in literature, whether spatial econometric methods or simple district fixed effects are used.",16.0,300https://openalex.org/W2765508957,10.20965/jaciii.2017.p1040,Housing Market Hedonic Price Study Based on Boosting Regression Tree,2017,Journal of Advanced Computational Intelligence and Intelligent Informatics,Guangtong Gu; Bing Xu,"Based on the purchase price data of new real estate markets three cities in China, Beijing, Shanghai, and Guangzhou, including architectural features, neighborhood property features, and location features, in this study a boosting regression tree model was built to study the factors and the influence path of housing prices from the microcosmic perspective. First, a classical hedonic price model was constructed to analyze and compare the significant effect factors on housing prices in the market segments of the three cities. Second, the gradient boosting regression tree method that is proposed in this paper was applied to the three markets in combination to analyze the influence paths and factors and the importance of the type of housing hedonic price. The influence paths of housing hedonic prices and decision tree rules are visualized. The significant housing features are effectively extracted. Finally, we present three main conclusions and several suggestions for policy makers to improve urban functions while stabilizing real estate prices.",16.0,3015969eaa11840cbf2194d8cc2d24399e4a440a8b6,10.1080/10511482.2020.1768573,The Commodity Effects of Decommodification: Community Land Trusts and Neighborhood Property Values,2020,,Katharine L. Nelson; J. DeFilippis; Richard Kruger; Olivia Williams; Joseph Pierce; Deborah G. Martin; Azadeh Hadizadeh Esfahani,"ABSTRACT This article explores the impacts of community land trust (CLT) properties on the real estate prices of nearby homes through a case study of a relatively large CLT in Minneapolis, Minnesota. We use hedonic regression and a difference-in-difference estimation with spatial error correction to measure price effects. The number of developments citywide is insufficient to yield significant results. However, we find evidence that clustering CLTs stemmed the decline in sales prices during the foreclosure crisis. The introduction of the first nearby CLT had no measurable price impact, but each additional CLT was associated with a 5% higher sales price in North Minneapolis, and 3% higher in Central Minneapolis. In the postrecession period, we estimate that the introduction of CLTs in North Minneapolis was associated with a 10.9% increase in nearby sales prices. These results suggest that, contrary to common assumptions, price effects are strongest when affordable properties are spatially clustered.",16.0,302doi_10_1068_a42422,10.1068/a42422,Spatial Variation in Job Accessibility and Gender: An Intraregional Analysis using Hedonic House-Price Estimation,2010,Environment and Planning A: Economy and Space,Liv Osland,"Using data on single-family detached houses from a Norwegian region, in this paper I study the existence of gender differences in estimated labour-market accessibility between locations. Different specifications of a gravity-based job-accessibility measure are included in hedonic house-price models. I test for significant gender-related differences in the distance-deterrence parameters found in the labour-market accessibility indicator. The estimated distance-deterrence parameters are lower for women than for men. This difference is, however, not significant, given the data. The main gender-related differences relate to the spatial variation in job accessibility as measured here. The supply of relevant jobs is significantly higher for women in the administrative centres of municipalities in the area, and significantly higher for men outside these administrative centres. The attractive forces of the centres could be relevant as an explanation of differentiated gender-related commuting patterns.",16.0,3031eecd785e1bace005f982d0271dc15d2de2dee67,10.1177/15270025211018258,The Amenity Value of Sports Facilities: Evidence From the Staples Center in Los Angeles,2021,,Zachary T. Keeler; H. Stephens; B. Humphreys,"U.S. cities have recently experienced a boom in new sports facility construction. Although these facilities can provide benefits to local residents, they may also generate negative externalities, making dwellings near a facility less desirable. Using a hedonic spatial difference-in-differences model, we analyze the impact of proximity to the Staples Center, a sports and entertainment venue in downtown Los Angeles, California, on house prices. Results indicate that the arena opening increased nearby house prices and that there were also positive “anticipation” effects associated with the announcement of the new arena location and local government approval.",16.0,304ba26780937630bfce76ea1bcc89a7777faa87ed0,10.1080/01621459.2021.1928512,Earthquake Risk Embedded in Property Prices: Evidence From Five Japanese Cities,2018,Journal of the American Statistical Association,Masako Ikefuji; R. Laeven; J. Magnus; Y. Yue,"Abstract We analyze the impact of short-run (90 days) and long-run (30 years) earthquake risk on real estate transaction prices in five Japanese cities (Tokyo, Osaka, Nagoya, Fukuoka, and Sapporo), using quarterly data over the period 2006–2015. We exploit a rich panel dataset (331,343 observations) with property characteristics, ward attractiveness information, macroeconomic variables, and long-run seismic hazard data, supplemented with short-run earthquake probabilities generated from a seismic excitation model using historical earthquake occurrences. We design a hedonic property price model that allows for subjective probability weighting, employ a multivariate error components structure, and develop associated maximum likelihood estimation and variance computation procedures. Our approach enables us to identify the total compensation for earthquake risk embedded in property prices, to decompose this into pieces stemming from short-run and long-run risk, and to distinguish between objective and subjectively weighted (“distorted”) earthquake probabilities. We find that objective long-run earthquake probabilities have a statistically significant negative impact on property prices,",15.0,https://www.tandfonline.com/doi/pdf/10.1080/01621459.2021.1928512?needAccess=true30598c105ab42ddbb39da40f571a9e40579ebb0b16f,10.1111/jors.12591,The impact of the Coronavirus pandemic on New York City real estate: First evidence,2021,Journal of Regional Science,Jeffrey P. Cohen; Felix L. Friedt; Jackson P. Lautier,"Abstract We investigate whether pandemic‐induced contagion disamenities and income effects arising due to COVID‐related unemployment adversely affected real estate prices of one‐ or two‐family owner‐occupied properties across New York City (NYC). First, ordinary least squares hedonic results indicate that greater COVID case numbers are concentrated in neighborhoods with lower‐valued properties. Second, we use a repeat‐sales approach for the period 2003–2020, and we find that both the possibility of contagion and pandemic‐induced income effects adversely impacted home sale prices. Estimates suggest sale prices fell by roughly $60,000 or around 8% in response to both of the following: 1000 additional infections per 100,000 residents and a 10‐percentage point increase in unemployment in a given Modified Zip Code Tabulation Area (MODZCTA). These price effects were more pronounced during the second wave of infections. On the basis of cumulative MODZCTA infection rates through 2020, the estimated COVID‐19 price discount ranged from approximately 1% to 50% in the most affected neighborhoods, and averaged 14%. The contagion effect intensified in the more affluent, but less densely populate",15.0,https://doi.org/10.2139/ssrn.39591053063ec2ac18b08d08915cc9352c65b189a38bf753c7,10.3390/su12041361,Impacts of Tourism Demand on Retail Property Prices in a Shopping Destination,2020,Sustainability,Yan Liu; Lin-Chuan Yang; Wing-Chau Kwong,"Understanding the relationship between tourism demand and retail property prices is of great significance to tourist destinations, especially shopping destinations. The increase in tourism demand may alter the implicit prices of certain retail property characteristics (e.g., age and accessibility to transit). This study examines how tourism demand (measured by tourist volume) affects retail property prices in the tourist precinct of a shopping destination, namely Hong Kong. The implementation of the policy Individual Visit Scheme (IVS) in 2003 in Hong Kong has substantially increased tourist shoppers from Mainland China, and it is used as a quasi-natural experiment of the increased tourist volume. Spatial and non-spatial hedonic pricing models are developed based on the ground-floor retail property transaction data of Causeway Bay, Hong Kong before and after the IVS (1993–2011). The findings of this study are as follows. (1) Accessibility to transit has a larger positive price effect after the implementation of the IVS. (2) The implicit price of accessibility to accommodation facilities is not significantly altered by the implementation of the IVS. (3) Age has a larger negative pri",15.0,https://www.mdpi.com/2071-1050/12/4/1361/pdf?version=158268552630764dfaa2aa1a654cc7f99d9bcfe48fe64fb8f2e32,10.1108/ijbpa-01-2019-0003,Housing attributes and relative house prices in Ghana,2019,International Journal of Building Pathology and Adaptation,D. Owusu-Manu; D. Edwards; K. A. Donkor-Hyiaman; R. Asiedu; M. Hosseini; E. Obiri-Yeboah,"308Purpose309The study of house prices has become more relevant in recent times after the global financial crisis. Using a housing data set from three regions of Ghana (collated from real estate agents), the purpose of this paper is to estimate the relative importance of housing attributes to house prices.310311312Design/methodology/approach313The hedonic regression analysis conducted indicates that location is the most powerful determinant of house prices. Other relevant factors are the number of bedrooms, the number of floors, the total floor area, land size, age of the house and luxury finishing.314315316Findings317The implications of these results are many. Policy wise, the study provides an evidence-based empirical study that supports the need for better urban planning to improve communities, which in turn is associated with house price appreciations. Homeowners, investors and creditors, particularly mortgage lenders could be the immediate beneficiaries. Drawing on this, improved urban planning could mitigate strategic defaults that results from house prices falling below mortgage loan balances. This is important for financial market stability.318319320Originality/value321The paper provides a comprehensi",15.0,https://figshare.com/articles/journal_contribution/Housing_attributes_and_relative_house_prices_in_Ghana/207505273225d7a30b7e8bf20b9b96939772873f83a5c2ed73b,10.3390/land10060630,"How Are Urban Green Spaces and Residential Development Related? A Synopsis of Multi-Perspective Analyses for Leipzig, Germany",2021,,N. Schwarz; A. Haase; D. Haase; N. Kabisch; S. Kabisch; V. Liebelt; D. Rink; M. Strohbach; J. Welz; M. Wolff,"The relationship between urban green spaces (UGS) and residential development is complex: UGS have positive and negative immediate impacts on residents’ well-being, residential location choice, housing, and land markets. Property owners and real estate agents might consider how prospective clients perceive UGS and act accordingly, while urban planners influence UGS location and management as well as aim at steering the built environment. Typically, studies focus on one of these perspectives at a time. Here, we provide a synopsis of results from studies, taking different perspectives for a single case study: Leipzig, Germany. We summarise and discuss the findings of eight studies on UGS and residential development. In detail, these studies focus on spatial pattern analysis, hedonic pricing analysis, mixed-methods studies on experts’ perspectives, surveys, and choice experiments exploring residents’ perceptions of UGS. We reflect on the feasibility of deriving a synthesis out of these independent studies and to what extent context matters. We conclude that both triangulating of data and methods, as well as long-term and context-sensitive studies are needed to explain the interlinkage",15.0,https://www.mdpi.com/2073-445X/10/6/630/pdf?version=16237447583231ec90095d66eda9040a9f61dc0098382a32b2d1c,10.1016/j.sbspro.2011.07.025,"Empirical Comparison of the Various Spatial Prediction Models: in Spatial Econometrics, Spatial Statistics, and Semiparametric Statistics",2011,,H. Seya; M. Tsutsumi; Yasushi Yoshida; Yuichiro Kawaguchi,"This study compares the performance of various spatial prediction models which consider spatial dependence among the real estate data in spatial econometrics, spatial statistics, and semiparametric statistics. Thus far, surprisingly few researches have been conducted from this perspective. This study employs the dataset of apartment rent in the Tokyo 23 wards for empirical comparison. This study in particular focuses on a geoadditive model which considers both spatial dependence and nonlinearity of a hedonic function, and suggests the predictive performance of this method superior to those of the traditional methods like kriging or EM type algorithm.",15.0,https://www.sciencedirect.com/science/article/pii/S1877042811013486/pdf3243f462deaffad7fe742db08cf3bb6e2c5576862af,10.1002/soej.12328,Capitalization of Flood Insurance and Risk Perceptions in Housing Prices: An Empirical Agent‐Based Model Approach,2019,Southern Economic Journal,Koen Koning; T. Filatova; Okmyung Bin,"Federally regulated or insured lenders in the United States are mandated to require flood insurance on properties that are located in areas at high risk of flooding. Despite the existence of this mandatory flood insurance requirement, take‐up rates for flood insurance have been low, and the federal government's exposure to uninsured property losses from flooding remains substantial. Meanwhile, the value of capital at risk varies significantly with flood events and changing risk perceptions, which necessitates mechanisms that stabilize these dynamics. In this article we discuss how a scenario of complete insurance uptake, under various risk attitudes, affects the value of properties in the 100‐year and 500‐year flood zones. Our results indicate that an increase in flood insurance uptake may provide such a mechanism by lowering the value of capital at risk in the flood zone consistently, independent of homeowners' risk attitudes. We apply an empirical adaptive agent‐based model to examine the capitalization of insurance costs, risk premiums, and their interaction in housing prices. Our approach combines widely‐used empirical hedonic analysis with the computational economic framework.",14.0,https://ris.utwente.nl/ws/files/100376393/Koning_et_al_2019_Southern_Economic_Journal.pdf325cd8943898d5984332955ed82898601bc92e663e7,10.5755/j01.erem.75.2.22823,Hedonic Analysis of Housing Prices and Development in Kaunas: Heritage Aspect,2019,"Aplinkos tyrimai, inzinerija ir vadyba / Environmental Research, Engineering and Management",Kastytis Rudokas; M. Landauskas; Odeta Viliūnienė; Indrė Gražulevičiūtė-Vileniškė,"The urban economists have stressed the importance of various amenities for the attractiveness of urban areas for residents and businesses and built cultural heritage can be considered as one of such amenities, the benefits of which should not be overlooked. This research was aimed to analyze the influence of heritage aspect including the heritage status or features of the building and the historic built environment in general on the real estate prices and development in Kaunas using hedonic price method. Two sets of data were collected for the analysis - general, including heritage buildings and including new construction since 2013. The research has demonstrated that heritage status and the year of construction (as older buildings can be considered having heritage features) have no significant positive influence on the real estate prices. Meanwhile, the location, heritage context and the architectural distinctiveness of new architecture have a direct influence on the real estate prices. The heritage context correlates with architectural quality of new construction as well. This reveals the benefits of heritage context both for the real estate developers and households; however, th",14.0,https://erem.ktu.lt/index.php/erem/article/download/22823/127293263a92fdb08b92ec67fd8389e1d7fffc7e37a98148,10.3390/su14169916,"Does Park Size Affect Green Gentrification? Insights from Chongqing, China",2022,Sustainability,Bo Wang; Shou-Kui He; Weiwen Ma,"International studies have shown that urban parks lead to rising residential prices and, consequently, gentrification effects. However, the studies on whether the size of the park drives gentrification are controversial. In this article, using the insight from Chongqing China, a hedonic price model is used to evaluate the influence of park size on residential prices, a geographically weighted regression model is employed to explore the spatial differentiation characteristics of park premiums, and a questionnaire survey is conducted to study residential socio-economic characteristics and attitudes toward green gentrification. We find that park premium is a strong predictor of gentrification, while park size is not. Most medium and large parks do not lead to green gentrification. The parks with high premiums that will lead to green gentrification are a small percentage of parks, only about 20% in Chongqing, China. Green gentrification in China is not due to the crowding out of low-income by middle- and high-income residents, but mainly due to the filtering of the real estate market. These findings provide new explanations for the relationship between parks and gentrification.",14.0,https://www.mdpi.com/2071-1050/14/16/9916/pdf?version=1660273381327008c3229443d60b36b8e1525b5af0589f63eb75d,10.1016/j.eeh.2012.10.003,"Real Estate Prices in Beijing, 1644 to 1840",2012,,D. Raff; Susan M. Wachter; Se Yan,"This paper provides the first estimates of housing price movements for Beijing in late pre-modern China. We hand-collect from archival sources transaction prices and other house attribute information from the 498 surviving house sale contracts for Beijing during the first two centuries of the Qing Dynasty (1644-1840), a long period without major wars, political turmoil, or significant institutional change in the Chinese capital. We use hedonic methods to construct a real estate price index for Beijing for the period. The regression analysis explains a major proportion of the variance of housing prices. We find that house prices grew steadily for the first half-century of the Qing Dynasty and declined afterwards in both nominal and real terms through the late eighteenth century. Nominal prices grew starting in the late eighteenth century and declined from the early nineteenth century through 1840. But these price changes occurred with contemporaneous price changes in basic measures of the cost of living: there was little change in real terms to the end of our period.",14.0,https://repository.upenn.edu/bitstreams/ea740473-6760-4f51-ae54-5261a6283ed4/download32823a821c97160e852a6c2dd5c6097aa79bfac7ed3,10.1080/15140326.2022.2045466,Prediction and analysis of residential house price using a flexible spatiotemporal model,2022,Journal of Applied Economics,Lu Wang; Guang-Xing Wang; Huan Yu; Fei Wang,"ABSTRACT House price prediction has traditionally been approached using linear or spatial linear hedonic models and focused on big cities. In this study, we developed a flexible spatiotemporal model (FSTM) to explore the spatiotemporal characteristics of the residential house price and the impact factors in middle-small cities. The FSTM integrated both spatial and temporal components of the residential house price, accounted for its spatiotemporal characteristics, and reproduced its spatial variability and temporal trends. The results showed that the governmental policy had a significant influence on the house price and led to the characteristics being different from those in big cities. The significant factors also included the density of roads, the density of banks, density of supermarkets, the area used by public and user shared area within a building. This study implied that FSTM provided the potential for spatiotemporal prediction of the residential house price in the middle-small cities.",14.0,https://www.tandfonline.com/doi/pdf/10.1080/15140326.2022.2045466?needAccess=true3291ee131410ca179386f41599713edbfbc437a9c82,10.2139/ssrn.3784779,The Financial Impact of Healthy Buildings: Rental Prices and Market Dynamics in Commercial Office,2021,Social Science Research Network,Natasha Sadikin; Irmak Turan; Andrea M. Chegut,"While the benefits of healthy spaces have long been qualitatively understood and appreciated, it has not been financially analyzed to derive their value and impact on economic decision-making. We use CompStak and Healthy Building public databases from Fitwel and WELL to operationalize a real estate hedonic model in order to ascertain the value of healthy spaces on the effective rent of offices spaces in ten cities within the United States: Atlanta, Boston, Chicago, Denver, Los Angeles, New York, Philadelphia, San Francisco, Seattle, and Washington DC. 330We find that healthy building effective rents transact between 4.4 and 7.7% more per square foot than their nearby non-certified and non-registered peers. This premium for healthy spaces is independent of all other factors, such as LEED certification, building age, renovation, lease duration, and submarket. These results indicate that healthy buildings are seen as an asset that correlates with employee or tenant well-being and productivity.",14.0,https://doi.org/10.2139/ssrn.37847793311c1f68420485e15e36e9afff78c3e2e41c2706c3,10.1016/j.landusepol.2019.104283,Hedonic valuation of harmful algal bloom pollution: Why econometrics matters?,2019,,A. Osseni; F. Bareille; P. Dupraz,"Abstract Harmful algal bloom (HAB) pollution is a major environmental threat worldwide. This is the case in Brittany, where approximately half of the coastal municipalities has been polluted in the two last decades. This pollution affects the welfare of the population by decreasing the accessibility of beaches for several professional and recreational users (anglers, walkers, joggers, etc.). Here, we estimated the willingness to pay (WTP) to reduce HAB pollution levels using the hedonic pricing method for the particular case of the Breton rural housing market between 2010 and 2012. We found that, on average, residents that were located 20 km from a polluted beach were willing to pay approximately 208€/inhabitant/year to reduce HABs to the minimal observed levels on Breton seacoasts. This estimate controlled for three sources of identified potential biases biathat may affect the quality of the estimation: the agricultural characteristics of upstream watersheds, the spatial unobserved heterogeneity and the adjacency effects. Indeed, the estimated WTP was 18% to 46% higher than the WTP that was estimated with a nonspatialized econometric model that did not account for these features. ",14.0,332https://openalex.org/W2559910546,10.3917/redp.265.0921,Environmental Spillovers and their Impacts on Housing Prices: A Spatial Hedonic Analysis,2016,Revue d économie politique,Masha Maslianskaïa-Pautrel; Catherine Baumont,"Nous analysons dans cette recherche la dimension spatiale de l’impact des facteurs environnementaux sur les valeurs immobilières. L’estimation de modèles hédoniques spatiaux sert de base à cette évaluation environnementale. La dimension spatiale peut être interprétée en termes de spillovers locaux ou globaux. L’analyse empirique est réalisée sur l’estuaire de la Loire. Nous nous intéressons plus particulièrement aux caractéristiques naturelles ou plus artificialisées des caractéristiques environnementales de ce territoire (zones humides, cours d’eau, front de mer, bruit). Nous montrons que les valeurs estimées des prix implicites dépendent du modèle spatial estimé. Ces prix implicites ne se réduisent pas à la valeur estimée du coefficient et ils combinent un effet de rétroaction et un effet de propagation.",14.0,https://shs.cairn.info/article/REDP_265_0921/pdf?lang=fr333doi_10_1080_02827580500463813,10.1080/02827580500463813,Determinants of hunting rental prices: A hedonic analysis,2006,Scandinavian Journal of Forest Research,Henrik Meilby; Niels Strange; Bo Jellesmark Thorsen; Finn Helles,,14.0,334doi_10_1080_08920750903398287,10.1080/08920750903398287,Estimating a Payment Vehicle for Financing Nourishment of Residential Beaches using a Spatial-Lag Hedonic Property Price Model,2010,Coastal Management,O. Ashton Morgan; Stuart E. Hamilton,,14.0,335bbcac4e23aa0600736c86b5afc4b2b403c215ecb,10.1145/3366423.3380086,One Picture Is Worth a Thousand Words? The Pricing Power of Images in e-Commerce,2020,The Web Conference,Christof Naumzik; S. Feuerriegel,"In e-commerce, product presentations, and particularly images, are known to provide important information for user decision-making, and yet the relationship between images and prices has not been studied. To close this research gap, we suggest a tailored web mining framework, since one must quantify the relative contribution of image content in describing prices ceteris paribus. That is, one must account for the fact that such images inherently depict heterogeneous products. In order to isolate the pricing power of image content, we suggest a three-stage framework involving deep learning and statistical inference. Our empirical evaluation draws upon a comprehensive dataset of more than 20,000 online real estate listings. We find that the image content describes a large portion of the variance in prices, even when controlling for location and common characteristics of apartments. A one standard deviation in the image variable is associated with a increase in price. By utilizing a carefully designed instrumental variables estimation, we further set out to obtain causal estimates. Our empirical findings contribute to theory by quantifying the hedonic value of images and thus establish",13.0,https://www.research-collection.ethz.ch/bitstream/20.500.11850/423144/1/3366423.3380086.pdf336doi_10_4000_cybergeo_22644,10.4000/cybergeo.22644,La dynamique spatio-temporelle des prix immobiliers à différentes échelles : le cas des appartements anciens à Paris (1990-2003),2011,Cybergeo,Marianne Guérois; Renaud Le Goix,"Cet article vise à aborder la complexité des mutations urbaines en cours et propose une expérimentation méthodologique appliquée aux valeurs immobilières. Celles-ci traduisent non seulement les caractéristiques intrinsèques d’un logement, mais aussi les qualités d’un lieu, évaluées et perçues à différents échelons (situation dans l’agglomération, caractéristiques du quartier et de la rue). L’évolution des prix est de plus un puissant déterminant du tri social qui s’opère dans les cœurs urbains. Afin de dégager l’intérêt d’une telle investigation expérimentale à fine échelle, nous présentons dans cet article une analyse spatiale des valeurs immobilières des logements dans Paris intra-muros entre 1990 et 2003. Dans un contexte de baisse puis de hausse soutenue des prix à partir de 1997, il s’agit d’analyser le jeu des réajustements spatiaux des valeurs immobilières afin d’identifier les dynamiques de dépréciation et de valorisation relatives qui sont à l’œuvre. Nous dégageons tout d’abord différents profils d’évolution des prix sur cette décennie, en prêtant attention à leur inscription spatiale. Nous abordons ensuite la dynamique des discontinuités de cette géographie des prix, en s",13.0,33706ca25121eb89d8f4bb646bfbfaee4e41c525aac,10.1016/j.habitatint.2014.06.004,Development of price models for architectural and environmental quality for residential developments in Hong Kong,2014,Habitat International,Y. Fung; W. Lee,"Factors affecting a residential unit's price are always of interest to homebuyers and building developers, especially in a city like Hong Kong which is known for expensive housing. Literature review indicates that the governing factors can be categorized into architectural and environmental attributes. Among different methods commonly used for pricing, the hedonic price approach is viewed as the most suitable. However, the successful use of this method requires that homebuyers know and choose the attributes. Whilst choosing architectural attributes are not a problem for homebuyers, the same does not apply to environmental attributes. Previous studies by the authors have proposed some simple indicators for quantifying the environmental attributes. Based upon the developed performance indicators and the transaction records of two representative housing estates (Royal Ascot = RA and City One Shatin = COS), details of the properties, including transaction prices, architectural particulars and environmental characteristics were numerically transformed for the hedonic price analysis. The analysis results revealed that the willingness to pay (percentage of house price in parenthesis) for ",13.0,https://www.ncbi.nlm.nih.gov/pmc/articles/71242643383845f7f46a787eef3c1aeb726c76713c028e3477,10.3390/buildings10030044,Exploring the Influence of an Urban Water System on Housing Prices: Case Study of Zhengzhou,2020,Buildings,Junjie Li; Yaduo Hu; Chunlu Liu,"A good living environment is the foundation of sustainable housing. Exploring the external influence of environmental factors on housing prices is one of the key issues in the field of real estate research; however, the current study of the urban water landscape on the spillover effect of housing prices is not sufficient. Taking the Zhengzhou residential market as an example, this paper analyzes the effect of an urban water system on residential prices by constructing the traditional Hedonic price model, spatial lag model (SLM) and geographically weighted regression model (GWR) by selecting the main water system and 678 points of residential data in the main urban area. The results show that the accessibility of rivers and lakes and the width and water quality of rivers have a significant effect on residential prices, and the impact of lakes is greater than that of rivers. The spatial heterogeneity of the water system effect is further revealed by adopting spatial lag model and geographically weighted regression model, and the effect of the water system is gradually reduced from the eastern urban area to the western urban area. The results of this study are of great practical signi",13.0,https://www.mdpi.com/2075-5309/10/3/44/pdf?version=1585273118339doi_10_1080_00420989550012645,10.1080/00420989550012645,A Hedonic Analysis of Rent and Rental Revenue in the Subsidised and Unsubsidised Housing Sectors in Geneva,1995,Urban Studies,Sandra Buchel; Martin Hoesli,"In this paper, an analysis is made of what would be the rent difference for the tenants of subsidised units if these units were rented as unsubsidised units. Furthermore, the existence of any pecuniary disadvantage for the owner of a subsidised unit is investigated by considering his rental revenue (i.e. the amount paid by the tenant and the subsidy). It is found that there exists a premium between an unsubsidised and a subsidised unit when using the amount paid by the tenant (i.e. the rent) as the dependent variable. Also, the subsidy system in Geneva has an influence on the pricing of each characteristic of a unit. Furthermore, it is found that when using rental revenue as the dependent variable, both sub-samples can be used in a single hedonic equation. Thus, owners of subsidised units are not at a disadvantage due to the granting of a subsidy. As a result, Geneva's subsidy system matches the goals of agents on both the demand and supply sides.",13.0,340doi_10_1111_j_1467_9787_1992_tb00177_x,10.1111/j.1467-9787.1992.tb00177.x,THE EXCHANGEABILITY OF HEDONIC PROPERTY PRICE STUDIES*,1992,Journal of Regional Science,Scott E. Atkinson; Thomas D. Crocker,"ABSTRACT. Observations drawn from multiple markets are essential to the construction of indices of housing costs and to measures of demand for housing attributes. It is not evident when multiple markets exist or whether such markets exist for some attributes but not for others. We test for multiple markets by using Bayesian methods to assess the transferability (random exchangeability) of entire hedonic price expressions from one site and time to another, the transferability of hedonic price functions for particular attributes, and the degrees of similarity that hedonic price functions must have in order to be transferable. In our illustrations, price functions for structural housing attributes are generally transferable; prices for neighborhood attributes are not. Therefore, in our illustrations, the desired price indices and demand functions should be estimable for neighborhood attributes, but not for structural ones.",13.0,341028976180a5f01c74d70cc4e37e97dadb10004c7,10.1080/23754931.2018.1446354,"Estimation of Spatial Association Between Housing Price and Local Environmental Amenities in Kolkata, India Using Hedonic Local Regression",2018,,M. Bera; B. Mondal; Gour Dolui; Suman Chakraborti,,13.0,342f0e2a90043f28e95183b413e12ee2feb4ec1201f,10.3390/urbansci2010014,Spatial Heterogeneity of Sustainable Transportation Offer Values: A Comparative Analysis of Nantes Urban and Periurban/Rural Areas (France),2018,,J. Bulteau; T. Feuillet; Rémy Le Boennec,"Innovative solutions have been implemented to promote sustainable mobility in urban areas. In the Nantes area (northwestern part of France), alternatives to single-occupant car use have increased in the past few years. In the urban area, there is an efficient public transport supply, including tramways and a "" busway "" (Bus Rapid Transit), as well as bike-sharing services. In periurban and rural areas, there are carpool areas, regional buses and the new "" tram-train "" lines. In this article, we focus on the impact on house prices of these "" sustainable "" transportation infrastructures and policies, in order to evaluate their values. The implicit price of these sustainable transport offers was estimated through hedonic price functions describing the Nantes urban and periurban/rural housing markets. Spatial regression models (SAR, SEM, SDM and GWR) were carried out to capture the effect of both spatial autocorrelation and spatial heterogeneity. The results show patterns of spatial heterogeneity of transportation offer implicit prices at two scales: (i) between urban and periurban/rural areas, as well as (ii) within each territory. In the urban area, the distance to such offers was si",12.0,https://www.mdpi.com/2413-8851/2/1/14/pdf?version=1517991895343bdc985e8a13246dd1f7bc208bec5d9c9e462b32d,10.1515/jbnst-2020-0001,"Regional Real Estate Price Indices for Germany, 2008 – 2019: RWI–GEO–REDX",2020,,Larissa Klick; S. Schaffner,"An important issue in the current German public and political discourse is the development of housing prices. Sharply increasing rent and purchasing prices, shortage of living space in urban areas and rural exodus are some of the discussed problems. Despite its topicality, few indices are available on the recent development of housing prices in Germany. To fill this gap, the RWIGEO-REDX dataset quantifies regional differences in house purchase, apartment rent and purchase prices on the level of districts (Kreise, NUTS 3-level) and municipalities (Gemeindeverband, LAU 1-level) as well as labor market areas defined by RWI (2018). The RWI-GEO-REDX combines a comprehensive up-to-date dataset and a hedonic price regression setup controlling for the property’s quality to capture various features of the sales and rent prices beyond the observation of average prices. We end up with regional price indices relative to the German mean capturing regional differences, the region-specific time trend as well as the national development over time. The RWI-GEO-REDX covers indices for apartment purchase, house purchase and rental apartments. All three categories are available on labor market region,",12.0,https://www.degruyter.com/document/doi/10.1515/jbnst-2020-0001/pdf344951ad433b8bf216c39485ecaadba7cb296d726e6,10.2139/ssrn.4044171,Coming of Age: Renovation Premiums in Housing Markets,2022,Social Science Research Network,Mari Olsen Mamre; D. E. Sommervoll,"We rely on novel textual analysis of real estate listings and identify renovated dwellings in a dataset of Norwegian transactions to estimate the renovation premium in an urban housing market. The renovation premium is estimated in a hedonic framework by classical regression approaches and a random forest algorithm. The strength of the latter is that it allows for a more complex interplay between the renovation premium and explanatory variables. We estimate a significant positive renovation premium of 5–7 percent for renovated dwellings and a negative premium of 9–10 percent for unmaintained/neglected dwellings. These averages mask significant variations in these premiums over time, particularly, a counter-cyclical effect. Omitting renovation information also has implications for estimated short-term house price growth. Unmaintained dwellings tend to transact more in the fourth quarter, indicating that parts of the seasonal price variation reported in the literature are due to compositional variation with respect to renovation. This composition effect bias price movement estimates downward, if uncontrolled for, as unmaintained dwellings transact at significantly lower prices.",12.0,https://doi.org/10.2139/ssrn.4044171345c7b242d28013321bceaeef0f994fd2d0dab032c0,10.4067/s0718-915x2013000200009,Implicit Prices in Urban Real Estate Valuation,2013,,J. Nuñez Tabales; F. R. Rey Carmona; J. M. C. Y. Ocerin,"Econometric hedonic models encounter several theoretical and practical difficulties when applied to the real estate market, such as downward biases in the estimation of hedonic prices, subjective decisions in the measurement process of categorical attributes, frontier problems related to an imperfect information framework and uniequational specification. Many of these are linked to the parametric approach. Artificial Neural Networks (ANN) provide an attractive alternative: better dwelling prices estimates, avoidance of bias at different market segments, direct use of categorical data and full use of the information available. The price to be paid is the difficulties in the economic interpretation of network parameters. Nowadays, if the final objective to produce better estimates of the transaction prices, this methodology show lower errors, provided of a broad representative database of sales are recorded. A case study is presented for a medium size city in the South of Spain. Keywords: Urban Economics; Hedonic Models; Neural Networks.",12.0,http://www.scielo.cl/pdf/rconst/v12n2/art09.pdf3460f88c3ee1b9c25f3d6602c7c07d55400a39f254b,10.5198/jtlu.2023.2199,End of the line: The impact of new suburban rail stations on housing prices,2023,Journal of Transport and Land Use,Rhea Acuña,"This study leverages the staggered opening of new Metro stations in a suburb of Washington, DC to estimate the impact of proximity to public rail transit on housing prices. Both hedonic and repeat sales models indicate that housing prices increase as distance increases, suggesting that living near public transportation in Prince George’s County is primarily viewed as a disamenity. For properties at one mile from the nearest station, the preferred repeat sales model estimates a marginal price increase of 4.6 percent for a one-mile increase in distance. I argue that the suburban environment may be key in explaining the results. In the suburbs, a greater share of the population relies on automobiles, and rail stations are typically equipped with large parking lots. The suburban environment allows households the opportunity to both benefit from public transportation access and mitigate the negative externalities associated with living right next to the station.",12.0,https://jtlu.org/index.php/jtlu/article/download/2199/1678347281b355bd08bd1b8b228829d9c97b819d0d2a4d1,10.23917/jep.v14i1.150,IMPACT OF AIR POLLUTION ON PROPERTY VALUES : A HEDONIC PRICE STUDY,2013,,Endah Saptutyningsih,"The main purpose of this study is the calculation of implicit prices of the environmental level of air quality in Yogyakarta on the basis of housing property prices. By means of Geographical Information System, the housing property prices characterized from the area which have highest air pollution level in province of Yogyakarta. Carbon monoxide is used as the pollution variable. The methodological framework for estimation is based on a hedonic price model. This approach establishes a relationship between the price of a marketable good (e.g. housing) and the amenities and characteristics this good contains. Therefore, if variations in air pollution levels occur, then households would change their behavior in an economic way by offering more money for housing located in highly improved environmental areas. The hedonic regression results that the housing price decrease while increasing the level of air contamination such substance as carbon monoxide.",12.0,https://journals.ums.ac.id/index.php/JEP/article/download/150/1403481746638ba682894ded3ef6e1c902371141e8fdc3,10.1017/s0163548400003125,Benefits From Urban Open Space and Recreational Parks: A Case Study,1982,,John K. Hagerty; T. Stevens; P. Allen; T. More,"The hedonic pricing technique was used to measure that component of house price attributable to proximity to a city park, using data on sale prices and characteristics of houses in Worcester, MA. Aggregation of these residual values over all houses in the neighborhood of a park provided an estimate of the value of the park, to which was added an estimate of recreation benefits from extrazonal users. '!he policy question of park system development or contraction was addressed by comparing these benefits with operating costs to gain a net measure of parkland value.",12.0,http://ageconsearch.umn.edu/record/159780349doi_10_1017_s1355770x10000483,10.1017/s1355770x10000483,The value of air quality and crime in Chile: a hedonic wage approach,2011,Environment and Development Economics,FELIPE VÁSQUEZ LAVÍN; JORGE DRESDNER; RENATO AGUILAR,"ABSTRACT We estimate the implicit prices of the crime rate and airborne pollution in Chile, using spatially compensating price differentials in the housing and labor markets. We evaluate empirically the impact of different estimation strategies for the wage and rent equations, on the economic value of these two amenities. The results show that increments in the crime rate or in air pollution have a negative impact on welfare and that the estimated welfare measures and their variances are sensitive to selection bias, endogenous amenities and clustering effects. In contrast, the welfare measures do not seem to be very sensitive to the simultaneity bias.",12.0,3500673312b87f831db0e8e225f6af8e3580731fb3a,10.3390/ijgi14100391,Exploration of Differences in Housing Price Determinants Based on Street View Imagery and the Geographical-XGBoost Model: Improving Quality of Life for Residents and Through-Travelers,2025,ISPRS Int. J. Geo Inf.,Shengbei Zhou; Qian Ji; Longhao Zhang; Jun Wu; Peng-Bo Li; Yu-Qiao Zhang,"Street design quality and socio-economic factors jointly influence housing prices, but their intertwined effects and spatial variations remain under-quantified. Housing prices not only reflect residents’ neighborhood experiences but also stem from the spillover value of public streets perceived and used by different users. This study takes Tianjin as a case and views the street environment as an immediate experience proxy for through-travelers, combining street view images and crowdsourced perception data to extract both subjective and objective indicators of the street environment, and integrating neighborhood and location characteristics. We use Geographical-XGBoost to evaluate the relative contributions of multiple factors to housing prices and their spatial variations. The results show that incorporating both subjective and objective street information into the Hedonic Pricing Model (HPM) improves its explanatory power, while local modeling with G-XGBoost further reveals significant heterogeneity in the strength and direction of effects across different locations. The results indicate that incorporating both subjective and objective street information into the HPM enhances expl",11.0,https://doi.org/10.3390/ijgi14100391351c06fa148231445294eaedf84018f8406f81aef76,10.1108/ijhma-11-2020-0140,Information transparency and pricing strategy in the Scottish housing market,2021,,D. Lo; Nan Liu; M. McCord; M. Haran,"352Purpose353Information transparency is crucially important in price setting in real estate, particularly when information asymmetry is concerned. This paper aims to examine how a change in government policy in relation to information disclosure and transparency impacts residential real estate price discovery. Specially, this paper investigates how real estate traders determined asking prices in the context of the Scottish housing market before and after the implementation of the Home Report, which aimed to prevent artificially low asking prices.354355356Design/methodology/approach357This paper uses spatial lag hedonic pricing models to empirically observe how residential asking prices are determined by property sellers in response to a change in government policy that is designed to enhance market transparency. It uses over 79,000 transaction data of the Aberdeen residential market for the period of Q2 1998 to Q2 2013 to test the models.358359360Findings361The empirical findings provide some novel insights in relation to the price determination within the residential market in Scotland. The spatial lag models suggest that spatial autocorrelation in property prices has increased since the Home Report",11.0,https://pure.ulster.ac.uk/en/publications/f3cbd6be-6056-4beb-a95e-d9d147657fe83620a600c8337f12c953d7aab40b543dec7ee64afff,10.1108/ijhma-12-2018-0099,"Analysis of housing prices in Petaling district, Malaysia using functional relationship model",2019,International Journal of Housing Markets and Analysis,Y. Chang; Wei Cheng Choong; S. Y. Looi; W. Pan; Hong Lip Goh,"363Purpose364The purpose of this paper is to analyse and predict the housing prices in Petaling district, Malaysia and its six sub-regions with a set of housing attributes using functional relationship model.365366367Design/methodology/approach368A new multiple unreplicated linear functional relationship model with both the response and explanatory variables are subject to errors is proposed. A total of 41,750 housing transacted records from November 2008 to February 2016 were used in this study. These data were divided into 70% training and 30% testing sets for each of the selected sub-regions. Individual housing price was regressed on nine housing attributes.369370371Findings372The results showed the proposed model has better fitting ability and prediction accuracy as compared to the hedonic model or multiple linear regression. The proposed model achieved at least 20% and 40% of predictions that have less than 5% and 10% deviations from the actual transacted housing prices, respectively. House buyers in these sub-regions showed similar preferences on most of the housing attributes, except for residents in Shah Alam who preferred to stay far away from shopping malls, and leasehold houses in Sri Kemba",11.0,373cb483fb0d918a1319e85e2a75c1ed330c7c67582,10.5194/piahs-382-703-2020,The effect of land subsidence on real estate values,2020,,W. Willemsen; S. Kok; O. Kuik,"Abstract. Land subsidence in the Netherlands, mainly occurring in its western and374northern peat and clay soils, causes significant damage to houses and375infrastructure, estimated at EUR 17 billion until 2050, through differential settlement of shallow foundations, negative skin friction and376fungal decay of timber piles. Various studies and reports both in The377Netherlands and abroad have addressed the potential economic impacts of378subsidence on houses: yet, these studies lack spatially detailed data and379instead rely on generic assumptions on expected damage restoration costs. By using a hedonic pricing model, this study examines the impact of subsidence on housing prices in the Dutch cities of Rotterdam and Gouda. In contrast to earlier studies, subsidence and its impact on property values are examined at house level. We test for the effect of subsidence with data related to (i) general (uniform) subsidence (mm yr −1 ), (ii) differential subsidence of a building and (iii) subsidence of the surrounding area in relation to the house. Results show that uniform subsidence has the largest impact on property values with approximately −6 %, while “differential” and “surrounding” subsidence",11.0,https://piahs.copernicus.org/articles/382/703/2020/piahs-382-703-2020.pdf3803c431080281acc52da88de4a535c6c62cbc7d68b,10.1108/ijhma-04-2022-0063,Determinant residential real estate of millennial generation in adapting housing microfinance case Indonesia chapter,2022,International Journal of Housing Markets and Analysis,Ahmad Subagyo; Akhmad Syari’udin; Akhmad Yunani,"381Purpose382This study aims to analyze the variables that affect residential real estate demand by millennials based on hedonic demand functions.383384385Design/methodology/approach386The method of analysis in this study is robust regression ordinary least square using cross-sectional data from Indonesian Family Survey Wave 5 (IFLS-5) with a sample of 1.672 households of male married millennials.387388389Findings390The aspect of millennial generation characteristics is significant on the variables of income, number of dependents, education level and presence of millennial generation in urban and rural areas. While the variable of age of the millennial generation does not significantly influence expenditure for residential real estate. All aspects of the millennial generation’s spending behavior consisting of spending on food consumption, education, health, telephone and internet, transportation, recreation and the variable of the presence of urban and rural millennial generations significantly affect the spending of the millennial generation for residential real estate with the assumption of ceteris paribus.391392393Research limitations/implications394The implication of this study brings together the charact",11.0,39578763be000cac6c28c0629b4c2e5fffb2f7f7fde,10.3390/land11060931,Factors Affecting Spatial Autocorrelation in Residential Property Prices,2022,Land,D. Lo; Wing-Chau Kwong; S. Wong; M. McCord; M. Haran,"Within housing literature, the presence of spatial autocorrelation (S.A.) in housing prices is typically examined horizontally in a two-dimensional setting. However, in the context of apartment buildings, there is also a vertical component of S.A. for housing units located on different floor levels. This paper therefore explores the determinants of both horizontal and vertical S.A. within residential property prices. First, we posit that S.A. in housing prices is a consequence of the price discovery process of real estate, in which property traders acquire price information from recent market transactions (i.e., comparables) to value a subject property. Furthermore, we contend that the extent to which property traders rely on comparables to determine housing prices is governed by the liquidity and volatility conditions of the market, which in turn affects the magnitude of the S.A. By developing and testing several spatial autoregressive hedonic models using open market transaction data for the Hong Kong residential property market, we find that market liquidity tends to increase both vertical and horizontal S.A., whilst market volatility is more prone to increase vertical S.A. but ",11.0,https://www.mdpi.com/2073-445X/11/6/931/pdf?version=1655461164396https://openalex.org/W3120566130,10.1108/ijhma-08-2020-0100,Hedonic housing prices and environmental quality in Lebanon,2021,International Journal of Housing Markets and Analysis,Walid Marrouch; Nagham Sayour,"Purpose This study aims to examine the impact of local air pollution on housing prices in Lebanon. Design/methodology/approach The authors apply a hedonic pricing approach using a unique data set from Lebanon. To account for non-linearities in pricing, the authors use three different functional regression forms for the hedonic model approach. The authors also deal with potential omitted variable bias by estimating a hedonic frontier specification. Findings The authors find that, in all specifications, air pollution negatively and significantly affects housing prices. The estimated marginal willingness to pay for a one microgram per cubic meter change in particulate matter (PM10) concentration ranges between 2.88% and 3.18% of mean housing prices. The authors also provide evidence of a negative pricing gradient away from the city center, landing support for the monocentric urban development hypothesis. Research limitations/implications Given the lack of a data set linking household socioeconomic characteristics with housing data, the authors only consider the first-stage hedonic model. Practical implications The proposed hedonic pricing regression approximates a housing pricing equa",11.0,3979c989fd3c2e77418653894f62cb739b34103685d,10.1108/pm-04-2020-0022,Hedonic valuation of apartments in Kenya,2020,,Raphael M. Kieti; Walter Ogolla,"This paper applies the hedonic pricing model (HPM) approach to identify critical determinants of apartment value and employs the technique to develop a valuation model that can accurately estimate the value of apartments.,The research employed a case study design that was limited to transaction sales and attribute data of apartments in Nyali estate, Mombasa County in Kenya. A sample of 120 sales of apartments obtained from registered real estate firms was analyzed using quantitative methods.,According to the study results, the hedonic valuation model developed comprises four critical determinants of apartment value, namely, number of parking lots, presence of swimming pool, age of apartment and provision of balcony. The hedonic model was tested and found to be accurate and reliable in estimating apartment value.,The model will improve accuracy, reliability and efficiency in valuation. The application of the model in the valuation of apartments is, however, limited to the case study area where the data are obtained. The scope of application of the model may be improved by increasing the sample size to include apartment sales data from other estates in Mombasa County.,Previous studie",11.0,398doi_10_1002_isaf_287,10.1002/isaf.287,Hedonic price models and indices based on boosting applied to the Dutch housing market,2007,"Intelligent Systems in Accounting, Finance and Management",Martijn Kagie; Michiel Van Wezel,"Abstract We create a hedonic price model for house prices for six geographical submarkets in the Netherlands. Our model is based on a recent data‐mining technique called boosting. Boosting is an ensemble technique that combines multiple models, in our case decision trees, into a combined prediction. Boosting enables capturing of complex nonlinear relationships and interaction effects between input variables. We report mean relative errors and mean absolute error for all regions and compare our models with a standard linear regression approach. Our model improves prediction performance by up to 39% compared with linear regression and by up to 20% compared with a log‐linear regression model. Next, we interpret the boosted models: we determine the most influential characteristics and graphically depict the relationship between the most important input variables and the house price. We find the size of the house to be the most important input for all but one region, and find some interesting nonlinear relationships between inputs and price. Finally, we construct hedonic price indices and compare these with the mean and median index and find that these indices differ notably in the urba",11.0,399c19ed129a24c047505aa3dddb7314d74b4bcf99a,10.1080/14445921.2021.1961182,What is in a name? A modern interpretation from housing price in Hong Kong,2021,Pacific Rim Property Research Journal,Na Li; R. Li; Ruihui Pu,"ABSTRACT Hong Kong is a metropolitan city. Owing to its historical background as a former British colony, it is characterised by a mixture of Chinese and Western cultures. While most housing estates’ names are bilingual in Chinese and English, many recent large scale housing estates have an English name only. Do housing estates with an English name only associate with higher prices than bilingual ones? To the best of our knowledge, none have studied that before. We attempted to fill this research gap. Four large-scale residential projects in Yuen Long District were selected, two are bilingual and two have English names only. 253,605 data points, including macroeconomic variables and housing characteristics, were included in this study. The results of the hedonic price model showed that properties with English names only were associated with a higher price than bilingual ones. We also utilised a long short-term memory (LSTM) housing price prediction model to predict housing price. Our research results show that housing estates with English names only are associated with higher housing price. It provides a new perspective on real estate housing estates’ brand management and provide a",11.0,400676cfbcad902fd4f757e99e1b954f340855ba093,10.2139/ssrn.3671981,Convergent Validity of Satellite and Secchi Disk Measures of Water Clarity in Hedonic Models,2021,Land Economics,David M. Wolf; Thomas Kemp,"Budget-constrained environmental agencies across the United States are limited in their ability to monitor water quality changes using traditional in situ sampling. Satellite-based monitoring systems represent a lower-cost alternative. It is unclear, however, how this transition will impact nonmarket valuation estimates of perceived water quality. To answer this question, we merge housing information with Secchi depth and satellite estimates of water clarity from over 100 lakes in Wisconsin. A comparison of hedonic price functions reveals satellite estimates of water clarity provide a stronger statistical fit of housing price and produce implicit prices up to 11% larger in magnitude.",11.0,401doi_10_1016_j_jhe_2010_04_004,10.1016/j.jhe.2010.04.004,The political economy of housing prices: Hedonic pricing with regression discontinuity,2010,Journal of Housing Economics,Eddie D.W. Sue; Wei-Kang Wong,,11.0,402a5be9ee170a2dc90e3da1bee990cebe15e48012a,10.1108/ijhma-03-2023-0041,The impact of energy certificates on sales and rental prices: a comparative analysis,2023,International Journal of Housing Markets and Analysis,Alesia Gerassimenko; Laurens Defau; L. De Moor,"403Purpose404The current literature on energy certificates shows that Energy Performance Certificate labels have an important effect on real estate prices. However, interestingly, the limited studies that address the rental market find significantly lower price premiums than the sales market. The purpose of this paper is to add to this literature, by doing a comparative analysis of price premiums in the sales and rental market in Flanders (Belgium).405406407Design/methodology/approach408This study uses a hedonic regression model to analyze 177,670 real estate listings between 2016 and 2021. The data is provided by Immoweb – the largest online real estate platform in Belgium. The data set was divided in sold and rented properties: the authors evaluated 126,217 sales listings and 51,453 rent listings.409410411Findings412The results confirm that energy efficient properties generate a price premium, but that this premium is significantly larger in the sales market than in the rental market. In addition, the findings indicate that both investors and landlords could benefit strongly from renovating dwellings – especially when renovating from an F label to an A label.413414415Originality/value416Previous research fo",10.0,https://biblio.vub.ac.be/vubirfiles/96247361/AAM_IJHMA_03_2023_0041.PDF41716a83cfe14b5d47a23932ae476c695260eab1e5c,10.3390/ijerph19042147,What Is the Effect of Cultural Greenway Projects in High-Density Urban Municipalities? Assessing the Public Living Desire near the Cultural Greenway in Central Beijing,2022,International Journal of Environmental Research and Public Health,Hai-Yun Xu; Fan Fu; Mengyi Miao,"Cultural greenway projects (CGPs) are widely regarded as an urban planning approach which connects open green spaces and sites of sociocultural value to provide access to living, working and recreational spaces and enhance local social well-being. This paper examines the impact of such CGPs on public living desire before and after a given project is completed through analyzing housing prices in the surrounding area. We deployed a hedonic pricing model (HPM) and differences in differences (DID) model to analyze and record any changes in housing market trends that may have been caused by such a cultural greenway project. Via analysis of single-family home sale transactions in central Beijing from 2013 to 2017, we found substantial evidence that proximity to a cultural greenway project is positively linked with rising property prices. Once complete, CGPs were similarly associated with positive increases per HPM and DID modeling. Our results revealed that the distance to greenway contributed significantly positive impact on the housing market after the cultural greenway project completed. Moreover, our result indicated that once a CGP was open to the public, it increased the price of p",10.0,https://www.mdpi.com/1660-4601/19/4/2147/pdf?version=1645069913418eb83972cd040998a7f0e60c77ea37896ff8f21fc,10.2495/bim190261,BUILDING INFORMATION MODELING POTENTIAL FOR AN ENHANCED REAL ESTATE VALUATION APPROACH BASED ON THE HEDONIC METHOD,2019,,Siham El Yamani; M. Ettarid; R. Hajji,"Housing valuation is a process of determining an accurate estimate of the market price of a property. Current methods and tools are mainly based on sales prices comparison with recent transactions, which is the major method applied in the taxation and cadastre services in Morocco. However, housing properties are in general heterogenous and unique in their shapes, construction materials, orientation, location and other environmental factors. These parameters are taken into consideration by the hedonic pricing method. Many of the researches about housing valuation are based on the geographical location as the main spatial factor affecting the property value. 2D GIS (Geographic Information System) applications used in this respect are limited in terms of communicating efficiently the complexity of a 3D building structure and modeling accurately environmental factors. Such factors could only be considered through 3D modeling and building information modeling (BIM). In this paper, we will try, through a brief review, to point out the weaknesses and drawbacks of the conventional valuation methods. Then, we will demonstrate the BIM potential in real valuation as an emerging technology and",10.0,http://www.witpress.com/Secure/elibrary/papers/BIM19/BIM19026FU1.pdf41953d1b6d48e64b056e88ebabd287c3f06ec3b559d,10.1371/journal.pone.0318701,Comparing automated valuation models for real estate assessment in the Santiago Metropolitan Region: A study on machine learning algorithms and hedonic pricing with spatial adjustments.,2025,PLoS ONE,Jocelyn Tapia; Nicolas Chavez-Garzon; R. Pezoa; Paulina Suarez-Aldunate; M. Pilleux,"This study compares the precision and interpretability of two automated valuation models for evaluating the real estate market in the Santiago Metropolitan Region of Chile: machine learning algorithms, specifically LightGBM, and hedonic prices with spatial adjustments (SAR). Traditional residence attributes, such as housing amenities and proximity to services, were considered alongside visual information extracted from images using Convolutional Neural Networks (CNN). The research evaluates the influence of each model characteristic on performance metrics and identifies the relative importance of attributes using the SHapley Additive exPlanations (SHAP) algorithm. The results demonstrate the positive impact of image-based variables on performance metrics, showing that the introduction of visual information can considerably reduce error margins when estimating housing prices. In addition, the SHAP algorithm reveals complex non-linear interactions between price and crucial variables such as total surface area and neighborhood attributes, highlighting the importance of using methods that can capture these effects. Likewise, both LightGBM and SAR models indicate that variables that hav",10.0,https://doi.org/10.1371/journal.pone.0318701420aa81dc840f8ab6c12b272e830117706e34b5a89a,10.1007/s11356-023-31668-1,Fresh air in the city: the impact of air pollution on the pricing of real estate,2024,Environmental science and pollution research international,Oktawia Miłuch; K. Kopczewska,"This study investigates the impact of ambient air pollution on housing prices in Warsaw, Poland, by examining spatial dependencies. The high concentration of particulate matter (PM_10, PM_2.5 and PM_1) is expected to reduce real estate values. Using a hedonic model with approximately 15,000 observations and a spatial error model, we did not find evidence of this impact. Standard and premium housing submarkets differ in price determinants, but both are insensitive to environmental issues. This could be explained by the lack of comprehensive intra-urban historical information on air pollution, which limits investors’ rationality and their ability to properly value real estate based on environmental issues. Additionally, measurement and aggregation issues, along with low pollution variability within the city, may contribute to the insignificance of this information in real estate sales prices. Our empirical research confirms a strong link between air pollution and weather conditions within the city, where low temperatures and low-speed southern winds worsen contamination levels, while high temperatures and westerly winds improve air quality. Furthermore, we find that incorporating pol",10.0,https://link.springer.com/content/pdf/10.1007/s11356-023-31668-1.pdf421https://openalex.org/W3123066559,10.20955/wp.2006.026,"Spatial Hedonic Models of Airport Noise, Proximity, and Housing Prices",2006,,Cletus C. Coughlin; Jeffrey P. Cohen,"Despite the refrain that housing prices are determined by ""location, location, and location,"" few studies of airport noise and housing prices have incorporated spatial econometric techniques.We compare various spatial econometric models and estimation methods in a hedonic price framework to examine the impact of noise on 2003 housing values near the Atlanta airport.Spatial effects are best captured by a model including both spatial autocorrelation and autoregressive parameters estimated by a generalized moments approach.In our preferred model, houses located in an area in which noise disrupts normal activities (defined by a day-night sound level of 70-75 decibels) sell for 20.8 percent less than houses located where noise does not disrupt normal activities (defined by a day-night sound level below 65 decibels).The inclusion of spatial effects magnifies the negative price impacts of airport noise.Finally, after controlling for noise, houses farther from the airport sell for less; the price elasticity with respect to distance is -0.15, implying that airport proximity is an amenity.",10.0,https://s3.amazonaws.com/real.stlouisfed.org/wp/2006/2006-026.pdf422af0839d7ffcae17d3f1555a0f9c6c80746ab0265,10.1108/ijhma-04-2019-0042,Modeling of residential property rents in Somalia using two-stage modeling,2019,International Journal of Housing Markets and Analysis,M. Nor; T. A. Masron; Sharif Yusuf Gedi,"423Purpose424Real estate is one of the fundamental growth engines for developing economies as it contributes urbanization and infrastructure development. In recent years, Somalia has witnessed massive real estate development in both housing and commercial buildings. The purpose of this study is twofold. First, the study examines the determinants of residential property rents. Second, it investigates whether residential property rents are fairly valued.425426427Design/methodology/approach428This study uses two-stage modeling. A hedonic regression model is used in the first stage, while an artificial neural network is applied in the second stage.429430431Findings432After analysis, this study established that size, location and security of a residential property have a significant influence on its monthly rents. Alternatively, the study identified that residential property rents are not fairly valued in Mogadishu and overvaluation is more frequent than undervaluation.433434435Originality/value436This implies that Somalia’s real estate industry is more speculative-driven than real demand-driven. Though Somali real estate is an infant industry with huge potentials in the long run, it may end up disastrously follow",10.0,4370c30a3a4592f6ad208346291b6dc026399d89ceb,10.1016/j.econmod.2021.03.010,A Time-Varying Hedonic Approach to quantifying the effects of loss aversion on house prices,2021,,Ryan Greenaway-McGrevy; Kade Sorensen,"Abstract Loss aversion is a widely-recognized cognitive bias that can affect house price determination. Existing empirical approaches to quantify its effects require hedonic methods to predict what prices would be in the absence of loss aversion. However, conventional methods for making this counterfactual prediction unrealistically preclude time variation in the hedonic values of housing attributes, thereby exacerbating specification error and reducing the accuracy of point estimates. We show how time-varying hedonic regression (TVHR) can overcome this deficiency by allowing hedonic values to change over time. Applying the method to a dataset of residential transactions from Auckland, New Zealand, that spans 2009 to 2018, we find that loss aversion significantly inflates transaction prices. However, by comparison, existing methods yield imprecise estimates of this premium that are implausibly large and sensitive to the sample period selected. Our findings suggest that THVR is an attractive alternative to conventional approaches to quantifying loss aversion.",10.0,438doi_10_1080_0042098032000116103,10.1080/0042098032000116103,Estimating the Effect of Land Leases on Prices of Inner-city Apartment Buildings,2003,Urban Studies,Christian T. L. Janssen,"The effect of land leases as opposed to freehold tenure on selling price is investigated for income property in proximity to the city centre. Hedonic estimation with multiplicative and additive models in a cross-section analysis is used to estimate the relationship between property characteristics on the one hand and selling price on the other. If land leases are valued by the market as the present value of the lease payments independent of other property features, an additive lease component should be appropriate. If, on the other hand, the valuation of the land lease aspect is not independent of other property features, a multiplicative lease component should be appropriate. Theoretical arguments can be advanced for either point of view, making it interesting to study the issue empirically. A sub-issue of interest is the effect on value of distance to the city centre. The sample consists of major apartment buildings centrally located in downtown Stockholm sold during a selected three-year period.",10.0,439doi_10_1080_00343404_2010_521147,10.1080/00343404.2010.521147,Spatial Transferability of Hedonic House Price Functions,2012,Regional Studies,David Philip McArthur; Liv Osland; Inge Thorsen,,10.0,440893b48b4e888469d4d32c1607b8a338cdc3fed8b,10.24136/oc.2018.003,Estimating repeat sales residential price indices for Krakow,2018,,Michał Głuszak; Jarosław Czerski; Robert Zygmunt,"Research background: There are several methods to construct a price index for infrequently traded real estate assets (mainly residential, but also office and land). The main concern to construct a valid and unbiased price index is to address the problem of heterogeneity of real estate or put differently to control for both observable and unobservable quality attributes. The one most frequently used is probably the hedonic regression methodology (classic, but recently also spatial and quantile regression). An alternative approach to control for unobservable differences in assets’ quality is provided by repeat sales methodology, where price changes are tracked based on differences in prices of given asset sold twice (or multiple times) within the study period. The latter approach is applied in renown S&P CoreLogic Case-Shiller house price indices. Purpose of the article: The goal of the paper is to assess the applicability of repeat sales methodology for a major housing market in Poland. Previous studies used the hedonic methodology or mix adjustment techniques, and applied for major metropolitan areas. The most widely known example is the set of quarterly house price indices constru",9.0,http://economic-research.pl/Journals/index.php/oc/article/download/715/680441537410dc265890e0a0cb2e251a597ed701caec93,10.1108/ijhma-10-2018-0080,Empirical analysis of residential submarket conceptualisation in Ghana,2019,International Journal of Housing Markets and Analysis,E. Gavu; Anthony Owusu-Ansah,"442Purpose443The purpose of this paper is to empirically test for submarket existence based on an understanding of the residential rental housing market in Ghana.444445446Design/methodology/approach447Based on extant literature and market observations, the authors provide key concepts and an overview of the residential rental market dynamics in Ghana. Reseachers appreciate that submarkets may exist in the Ghanaian rental market but have ignored the empirical testing for submarket existence due to data asymmetries. Based on real estate experts and stakeholder consultations, a priori delineation of submarkets are constructed based on spatial, structural and a nested approach. Submarket existence is tested using the Kruskal–Wallis H test and Hedonic modelling techniques.448449450Findings451By using fieldwork data from Accra rental market, the analysis provides credence to the conceptualisation of submarkets and how to empirically test for same. It is argued that researchers should use alternative methods to compare results to make far-reaching conclusions.452453454Research limitations/implications455Examining the hypothesis that differential rental values exists for submarkets has implications for policy decisio",9.0,https://www.emeraldinsight.com/doi/pdfplus/10.1108/IJHMA-10-2018-00804567ce0acbaf9b9d681b526f8a687010f697e1ba8f3,10.17632/75285sbbp6.1,The effects of the BP Deepwater Horizon oil spill on housing markets,2018,Journal of Housing Economics,Javier Cano-Urbina; Christopher M. Clapp; Kevin Willardsen,"Abstract When the Deepwater Horizon oil rig exploded in 2010, it resulted in the largest off-shore oil spill in United States history. Economic theory dictates that the oil damage and restitution payments that resulted from the spill should be capitalized into property values. To measure the extent of this capitalization, we create a novel dataset by linking surveys of the location and severity of oil observed along over 4,300 miles of the Gulf Coast to measures of local housing market outcomes. We then perform hedonic-style analysis to determine the net effects of the spill on affected real estate markets. In doing so, we provide the first plausibly causal estimates of the effect of the spill on affected housing markets throughout the Gulf region. Identification comes from a triple-difference framework that exploits the random nature of both the spill and the spatial distribution of oil that affected coastal communities, as well as controls for the confounding effects of the housing market crash. Results suggest that on net, the BP oil spill caused a significant decline in home prices of between 4% and 8% that persisted until at least 2015. This implies housing markets capitalized",9.0,https://doi.org/10.2139/ssrn.311503345708341acc11b43555d0c090a83bb0b921b5f1a523,10.3390/land13101686,Nature’s Neighborhood: The Housing Premium of Urban Parks in Dense Cities,2024,Land,Si-Qi Feng; Y. Zhuo; Zhong-Guo Xu; Yang Chen; Guan Li; Xue-Qi Wang,"Urban parks, a core component of urban landscapes, play a crucial role in mitigating the negative effects of rapid urbanization and achieving sustainable urban development. In densely populated urban environments, providing urban parks fairly and efficiently, taking social preferences into account, is an important challenge. In this regard, we take Hangzhou, China, as an example and use a hedonic pricing model with a difference-in-differences estimator to test the effect of different types of urban parks on housing prices, quantify their respective economic values, and reflect homebuyers’ preferences. The findings indicate that the construction of new urban parks leads to an overall increase in the value of the surrounding real estate to some extent. Specifically, the construction of comprehensive parks and large parks significantly enhances the value of nearby housing, while proximity to new medium-sized parks also results in a housing price premium, albeit to a lesser extent. In contrast, community parks and specialized parks have a less significant impact on housing prices. These findings provide valuable insights for equitable urban development and planning, optimizing the allo",9.0,https://doi.org/10.3390/land131016864580a4917c7f444817b4974629ac2f7d58ef2f99321,10.13106/jafeb.2020.vol7.no6.517,"The Hedonic Method in Evaluating Apartment Price: A Case of Ho Chi Minh City, Vietnam",2020,,H. Nguyen; H. Phan; T. Van Tran; Thang Kiem Viet Tran,"The study examines factors affecting apartment prices in the real estate market of Ho Chi Minh City, Vietnam. The study uses primary data based on surveys of customers who have traded successfully, and collects transaction data from real estate trading companies that are the top investors in Ho Chi Minh City real estate market. The collected data include 384 observations in a total of 24 districts, detailing that each district surveyed on a minimum of four projects, each project carried out a survey on a minimum of four apartments. The survey collected 339 valid questionnaires for analysis and model testing. This study employs multivariate regression with the data of 339 observations. The research results reveal that five significant factors affect positively the price of apartments in Ho Chi Minh City – apartment area, toilet and bedroom, apartment floor, reference price, and apartment interior. Besides, there are three significant factors affecting negatively the price of apartments – next price trend, distance to city center, and potential building. From the results, the research proposes solutions in the pricing of apartments in the real estate market in Ho Chi Minh City – bett",9.0,https://doi.org/10.13106/jafeb.2020.vol7.no6.517459e6c58cb070edd6cfaff8b1bababd256016f5ed90,10.1007/s43071-023-00039-w,Hedonic real estate price estimation with the spatiotemporal geostatistical model,2023,Journal of Spatial Econometrics,Sachio Muto; Shonosuke Sugasawa; Masatomo Suzuki,"This study argues that the spatiotemporal geostatistical model for real estate prices, which accounts for and incorporates spatial autocorrelation, can be estimated successfully using the Bayesian Markov Chain Monte Carlo (MCMC) estimation. While this procedure often encounters difficulty in calculating probabilistic densities in the Metropolis–Hastings (MH) algorithm, this study introduces a feasible and practical estimation method, providing useful estimated parameters for the model. Using single-family house transaction data, we show that ordinary estimations of real estate prices, with respect to certain explanatory variables, may lead to the underestimation of standard errors of coefficients for explanatory variables with spatial effects unless spatial autocorrelation is controlled for. Our model also makes it possible to obtain accurate in-sample predictions and moderately improved out-of-sample predictions for real estate prices. This study further estimates a “decay rate:” a diminishing correlation between real estate prices and increasing distance, showing that geographical proximities are likely to have an important impact on real estate prices, especially at a range unde",9.0,https://link.springer.com/content/pdf/10.1007/s43071-023-00039-w.pdf4609cec02be2fce93fd71880c26336b985983dff14c,10.3390/su13010292,Valuation Models for Holiday Rentals’ Daily Rates: Price Composition Based on Booking.com,2020,Sustainability,Jose Antonio C. Santos; M. A. Fernández-Gámez; M. Solano-Sánchez; F. Rey-Carmona; L. C. L. D. del Río,"In recent years, the number of sharing economy accommodations has grown exponentially due to the Internet and peer-to-peer networks, which has made researchers increasingly interested in analysing this new type of lodging. This study sought to develop models that determine the significant variables for the daily price of staying in holiday rentals based on data extracted from Booking.com and other sources. The hedonic pricing method (HPM) was selected to conduct the research as this methodology has been widely used in real estate valuation and hotel daily rate determination; however, the HPM is still rarely used for holiday rentals. The study focused on the city of Seville, where a notable increase in holiday rentals has been observed in recent years. Variables related to the accommodation typology, including location, size and equipment, as well as seasonality, are the most influential factors in the proposed models. These results are of interest to both owners and users of holiday rentals and can help these individuals to determine if the price of a stay is what would commonly be offered in the market under normal circumstances.",9.0,https://www.mdpi.com/2071-1050/13/1/292/pdf4618bd308f78fb4466f73af2035a6682d0f84ccee3e,10.3390/su13073612,Residential Property Behavior Forecasting in the Metropolitan City of Milan: Socio-Economic Characteristics as Drivers of Residential Market Value Trends,2021,Sustainability,Marzia Morena; G. Cia; L. Baiardi; Juan Sebastián Rodríguez Rojas,"The phenomenon of urbanization of cities has been the subject of numerous studies and evaluation protocols proposing to analyze the degree of economic and social sustainability of development projects. Through careful research and synthesis of the theoretical framework regarding residential properties’ performance measurement and forecasting, this paper goes deeper into the proposition of property development as an asset class that represents the biggest share of the Italian property market and yet is avoided by the big portfolios. The analysis model was applied to the city of Milan and its Metropolitan Area. The method is based on the development of correlation indices to evaluate different behaviors, through time and a Geographic Information System (GIS) based on the Hedonic Price Method (HPM). Results from a hedonic model estimated for several recent years suggest that, depending on the particular view, the relation between the rent/price performance and the different external and intrinsic variables can represent a useful parameter for evaluating the feasibility of different real estate investments.",9.0,https://www.mdpi.com/2071-1050/13/7/3612/pdf?version=1616757840462387c90bd781ef3cca43b776a1fe3e4d7c98fb2e6,10.2478/remav-2013-0030,Differentiation of Local Housing Markets in the Poznań Suburban Area,2013,,Justyna Tanas,"Abstract In recent years, there has been a strong interest in land intended for single-family housing in the suburban zones of big cities. This is strongly related to the suburbanization process. In the present study, the author endeavored to present the differentiation of local markets of undeveloped real estate intended for single-family housing in the suburban zones of Poznań. Notary deeds related to sales transactions in the segment of undeveloped land plots were the basic source of information used in the article. The article shortly discusses the specifics of the land market in the suburban zone, presents the research method (the nature of the real estate prices index) and then, creates a regression function of plot prices and indicates hedonic prices for undeveloped plots intended for single-family housing in particular communes. Finally, it seeks to define the similarities and differences within the local undeveloped property market in the Poznań agglomeration.",9.0,https://www.sciendo.com/pdf/10.2478/remav-2013-0030463085abe23b2c58d10b976dc43e934590d1cc7f8b5,10.1080/21681376.2024.2305951,The fibre broadband housing premium across three US States,2024,"Regional Studies, Regional Science",Brian E. Whitacre,"ABSTRACT This paper meshes 1.7 million housing transactions across three US states (Iowa, Minnesota and Texas) between 2015 and 2021 with data on broadband infrastructure to evaluate the impact of fibre broadband availability on home prices. This was a period of dramatic fibre growth in these states: prior to 2019, fibre was only available to roughly 24% of the houses sold but rose to 54% in later years. A traditional hedonic pricing model that includes a wide array of housing characteristics and census block group-level fixed effects estimates the fibre premium at around 1% in all three states for the full 2105–2021 period. The fibre premium was higher in the earlier part of this period, likely reflecting its novelty during that time. A more rigorous instrumental variable approach estimates the fibre premium at 2% in Minnesota and 9% in Texas. A conservative national estimate of the increase in housing value from deploying ubiquitous fibre is $36 billion.",9.0,https://doi.org/10.1080/21681376.2024.2305951464321664826269788c8435ead0315a2539fb9837f3,10.21837/pm.v19i17.1003,ENHANCING THE ACCURACY OF MALAYSIAN HOUSE PRICE FORECASTING: A COMPARATIVE ANALYSIS ON THE FORECASTING PERFORMANCE BETWEEN THE HEDONIC PRICE MODEL AND ARTIFICIAL NEURAL NETWORK MODEL,2021,PLANNING MALAYSIA,Nurul Fazira Sa’at; N. H. Adi Maimun; N. H. Idris,"The Hedonic Price Model (HPM), a prominent model used in real estate appraisal and economics, has been argued to be marred with nonlinearity, multicollinearity and heteroscedasticity problems that affect the accuracy of price predictions. An alternative method called Artificial Neural Network Model (ANN) was identified as capable of addressing the shortcomings of HPM and produces superior predictive performance. Hence, this study aims to evaluate the forecasting performance between HPM and ANN using Malaysian housing transaction data from the period between 2009 to 2018, sourced from the Valuation and Property Service Department, Johor Bahru. The models’ performance was evaluated and compared based on their statistical and predictive performance. Results showed that ANN outperformed HPM in both statistical and predictive performance. This study benefits the expansion of academic and practical knowledge in enhancing the accuracy of house price forecasting.",9.0,https://www.planningmalaysia.org/index.php/pmj/article/download/1003/699465https://openalex.org/W2911438300,10.1080/09599916.2018.1562490,Analysis of spatial variance clustering in the hedonic modeling of housing prices,2019,Journal of Property Research,Sören Gröbel,"This paper examines the spatial dependency exhibited by the error term variance of hedonic modeling based on German housing price data. To this end, it applies the spatial autoregressive conditional heteroscedasticity (SARCH) model previously discussed in housing literature, which allows for the consideration of spatial dependency when modeling the error variance of hedonic pricing. This model represents a spatialized version of the well-known ARCH-model used in time series analysis. Consistent with previous findings, this paper confirms the existence of spatial conditional heteroscedasticity, i.e. dependency in the error variance. However, this spatial dependency is not a global phenomenon, but can be ascribed to spatial concentrations of apartments with a relatively high variance in a small number of the same neighborhoods. The analysis of spatial heteroscedasticity helps to improve the estimation efficiency and prediction accuracy. In addition, spatial differences can be used to account for idiosyncratic risk when conducting mass appraisal.",9.0,466a2ea97ac51efa95bc0afe5e21b1890bf2fae22b7,10.5539/jsd.v4n3p199,The Impact of Jacuzzi Bathtubs on House Prices,2011,,A. Otegbulu; Olusola Johnson,"The study examines the impact of Jacuzzi bathtubs on house prices. Jacuzzi bathtubs have health related benefits. This study empirically tests a hedonic house pricing model using a sample of 138 houses in high income residential sub-market of Lekki phase one in Lagos metropolis. Forty-six duplexes have Jacuzzi bathtubs installed in their homes while Ninety-two do not. The study results show that that having Jacuzzi bathtubs increases home value by N2, 167,615. 1. Background of Study A house is a heterogeneous good. Its value depends on a number of characteristics such as size, age, and location. Rosen (1974) hedonic pricing model hypothesized that a housing market can be viewed as the interaction of implicit markets for these characteristics. As a result, regression analysis can be utilized to derive the implicit price of each housing attribute and the contribution of each attribute to the overall house price. The housing attributes used are generally classified into: structural attributes, such as age and floor area; location-related attributes, such as proximity to the CBD, floor level, and view; and neighbourhood attributes such as the provision of social facilities (Mok, Chan a",8.0,https://ccsenet.org/journal/index.php/jsd/article/download/10892/7756467207221def10a8ad1d4b5869ab5582235019678fe,10.1108/ijhma-01-2021-0003,Comparing predictive performance of general regression neural network (GRNN) and hedonic regression model for factors affecting housing prices in “Pune-India”,2021,,A. Abhyankar; H. Singla,"468Purpose469The purpose of this study is to compare the predictive performance of the hedonic multivariate regression model with the probabilistic neural network (PNN)-based general regression neural network (GRNN) model of housing prices in “Pune-India.”470471472Design/methodology/approach473Data on 211 properties across “Pune city-India” is collected. The price per square feet is considered as a dependent variable whereas distances from important landmarks such as railway station, fort, university, airport, hospital, temple, parks, solid waste site and stadium are considered as independent variables along with a dummy for amenities. The data is analyzed using a hedonic type multivariate regression model and GRNN. The GRNN divides the entire data set into two sets, namely, training set and testing set and establishes a functional relationship between the dependent and target variables based on the probability density function of the training data (Alomair and Garrouch, 2016).474475476Findings477While comparing the performance of the hedonic multivariate regression model and PNN-based GRNN, the study finds that the output variable (i.e. price) has been accurately predicted by the GRNN model. All the ",8.0,478https://openalex.org/W3141713414,10.35808/ijeba/526,The Hedonic Pricing Model Applied to the Housing Market,2020,International Journal of Economics and Business Administration,My-Linh,"Purpose: The article applies the hedonic pricing model to estimate house price in the housing market of Vietnam, which is a country with a fledgeling housing market, so the study is expected to bring interesting findings.Design/Methodology/Approach: By applying the hedonic pricing model, most of the previous studies have reported that house price is significantly influenced by the characteristics of the house itself, its location and surrounding facilities.Based on this, the article adopts the Ordinary Least Squares (OLS) regression in combination with robustness statistics in the model estimation, so the estimated results on house price are reliable and able to be widely applied.Data are collected through the survey into housing projects in Ho Chi Minh and Ha Noi city, which are the two largest cities in Vietnam.Findings: The findings reveal that the hedonic pricing model can be applied to estimate house price in Vietnam's housing market.This can be said to be a big success in giving first empirical evidence in Vietnam on this matter.Specifically, house price is negatively affected by its proximity to the city center.Also, factors including house size, house type, house structure,",8.0,https://www.ijeba.com/journal/526/download479207e168cf66b36df6b290a7e34c4057a1c2438cf,10.1007/s10901-023-10102-5,"Hedonic price effects of homeworking under the COVID-19: evidence from housing markets in Guangzhou, China",2024,Journal of Housing and the Built Environment,Bo Wang; Xin Feng; Becky P. Y. Loo; Desheng Xue; Ji-Xiang Liu; Siyao Tong,"The COVID-19 pandemic has prompted homeworking to become a ‘new normal’. Consequently, the effects of various homeworking-related housing attributes on housing prices may be changed. However, few studies have explicitly examined if and how the practice of homeworking changes the associations between these particular housing attributes and housing prices. In light of this, based on a database of 2-year property transaction records in Guangzhou, China, this study develops several multilevel hedonic price models and multilevel difference-in-differences (DID) hedonic price models to delve into the COVID-19-induced variations in such housing attributes-housing prices associations. Our findings are as follows. (1) The practice of homeworking seems not to have fundamentally changed the effects of homeworking-related housing attributes on housing prices (suggested by the unchanged coefficient directions between pre- and post-COVID models); (2) Significant differences do exist in magnitudes of the effects of homeworking-related housing attributes on housing prices between pre- and post-COVID periods; (3) Those attributes (associated with homeworking space, convenient commute between workpla",8.0,https://hub.hku.hk/handle/10722/344691480649664b7d83d315457a2a548f911f1657b4faaae,10.1177/00420980211024156,"The effect of film production studios on housing prices in Atlanta, the Hollywood of the South",2021,Urban studies,Velma Zahirovic-Herbert; K. Gibler,"Governments compete to attract film productions to their communities, expecting them to provide economic benefits directly through local purchases and employment and indirectly through publicity and image building. Atlanta, Georgia, has become a large film production hub, partially because of a state tax credit programme. As a result, permanent production facilities have been established that may influence surrounding real estate prices. Convenience and a desire to live among other creatives may encourage actors, technical workers and support staff to live nearby, and the film industry cachet may attract additional residents, increasing house prices. However, if the facilities are perceived to be similar to other industrial operations, they may negatively affect surrounding house prices. We investigate film production studios’ effect on residential property values using housing sales data and information on film production studios’ location, size and year established. To mitigate bias from the potential endogeneity of studios’ location choices, we augment the standard hedonic pricing framework to incorporate proximity to a film production studio and construct treatment and comparis",8.0,48106400ee6d5319f64a8f6daf26a289c6acbc8e9b8,10.3989/ic.15.053,Redes neuronales (RN) aplicadas a la valoración de locales comerciales,2017,,J. N. Núñez Tabales; F. R. Rey Carmona; J. C. Y. Ocerín,"Several agents, such as buyers and sellers, or local or tax authorities need to estimate the value of properties. There are different approaches to obtain the market price of a dwelling. Many papers have been produced in the academic literature for such purposes, but, these are, almost always, oriented to estimate hedonic prices of residential properties, such as houses or apartments. Here these methodologies are used in the field of estimate market price of commercial premises, using AI techniques. A case study is developed in Cordova —city in the South of Spain—. Neural Networks are an attractive alternative to the traditional hedonic modelling approaches, as they are better adapted to non-linearities of causal relationships and they also produce smaller valuation errors. It is also possible, from the NN model, to obtain implicit prices associated to the main attributes that can explain the variability of the market price of commercial properties.",8.0,https://doi.org/10.3989/ic.15.053482doi_10_1111_j_1465_7287_2009_00190_x,10.1111/j.1465-7287.2009.00190.x,THE ECONOMIC VALUE OF PROTECTING INVENTORIED ROADLESS AREAS: A SPATIAL HEDONIC PRICE STUDY IN NEW MEXICO,2010,Contemporary Economic Policy,GERMÁN M. IZÓN; MICHAEL S. HAND; MATIAS FONTENLA; ROBERT P. BERRENS,"The objective of this paper is to examine the off‐site benefits, as capitalized into housing values, of protecting 1.6 million acres of Inventoried Roadless Areas (IRAs) in the state of New Mexico, United States. In light of petitions filed by various U.S. states to maintain the status of IRAs as roadless lands, spatial hedonic price models are estimated and used to calculate the implicit value of IRAs in New Mexico. Findings show that a two‐stage least squares (2‐SLS), robust spatial‐lag model is the most appropriate econometric representation of the hedonic price function, and that IRA lands are a significant and positive determinant of house value. After controlling for the presence of Wilderness Areas (WAs) and other characteristics, results indicate that, on average, there is a 5.6% gain in the property value of a house from being located in, or adjacent to, a Census tract with IRAs. In the aggregate, this gain represents 3.5% of the value of all owner‐occupied units in New Mexico ($1.9 billion in capitalized value, or an annualized value in perpetuity of $95 million, assuming a 5% interest rate). ( JEL R22, H40, Q51, C21)",8.0,483doi_10_1108_01443589710156907,10.1108/01443589710156907,Measuring Irish housing quality,1997,Journal of Economic Studies,Edward Shinnick,"Reviews the development of Irish housing policy from the eighteenth century to the present. Emphasizes the importance of measuring quality in housing, where housing may be described by a vector of measured characteristics. Undertakes a detailed price determination of these various characteristics using a hedonic model. Explains observed house prices in terms of the various housing characteristics using a hedonic model, from which a set of implicit or “hedonic” prices emerges. Reviews the theoretical basis of such an approach and develops a model specifically for aggregated data, as other studies in this area used disaggregated models. Obtains quantitative estimates of the qualitative and quantitative characteristics of the housing bundle before and after a series of model transformations. The results indicate the premium associated with certain housing characteristics. They emphasize, in particular, the importance of floor area and location in determining new Irish estate house prices.",8.0,48492bac0fedc2b2c76c61a818b86c082653958bed3,10.2139/ssrn.1392402,"Valuing Proximity to Lake and Ski Recreation Amenities: Hedonic Prices for Vacation Rental Houses at Deep Creek Lake, Maryland",2009,,Jon P. Nelson,,8.0,https://doi.org/10.2139/ssrn.13924024851a1bb3e008862bd1c0992dabbda8d9c30a372253,10.1007/s41685-023-00290-x,"Spatial heterogeneity of marginal willingness to pay for air quality in PM2.5: analysis of buyers’ housing price in Beijing through hedonic price, spatial regression, and quantile regression models",2023,Asia-Pacific Journal of Regional Science,Chao Zhang; Mimi Xiong; Xuehui Wei; Zongmin Lan,,8.0,48620616066b27a2540fa1941814b92faa4e9515493,10.3406/estat.2013.10200,Les risques industriels et le prix des logements,2013,,Céline Grislain-Letrémy; Arthur Katossky,"[spa] Los riesgos industriales y los precios de la vivienda. . El precio de la vivienda puede disminuir por encontrarse a proximidad de instalaciones industriales. Este efecto depende de la percepcion del riesgo por parte de los vecinos y puede verse potencialmente modificado por ciertos elementos, como los planes de prevencion de riesgos tecnologicos en Francia. El impacto de estos planes es dificil de estimar puesto que los planes implantados en zonas urbanizadas son recientes. Sin embargo, el analisis de otros eventos que tambien inciden en la percepcion del riesgo permite aportar unos primeros elementos de respuesta. Las tres zonas urbanizadas estudiadas se encuentran cerca de instalaciones industriales en las aglomeraciones francesas de Burdeos, Dunkerque y Rouen. El metodo de los precios hedonicos permite estimar el efecto de la proximidad de fabricas en el precio de la . vivienda. Los resultados sugieren que las diferencias de precio no se ven modificadas ni por los incidentes locales . ni por la catastrofe de AZF en Toulouse, ni por los dispositivos de informacion, ni por la instauracion de . un regimen de seguro contra catastrofes tecnologicas. [ger] Mietpreise konnen aufg",7.0,https://insee.hal.science/hal-05540505v1/document48703bfeba917085bc65a0ab641e5a03916b687b20f,10.1088/2634-4505/abfe05,Economic feasibility of wood-based structures—Improving urban carbon neutrality strategies,2021,,I. Talvitie; J. Vimpari; S. Junnila,"Countries and cities alike have set carbon neutrality goals to the near future. Urban areas are experiencing an increased demand for new housing developments, and buildings are responsible for one third of all greenhouse gas emissions. The relative share of construction emissions is increasing as energy production is de-carbonizing. Wooden structures have showcased potential in substantially decreasing these emissions. However, for the construction industry to utilize environmentally friendly products, the cost efficiency needs to be determined. Prior research does not present conclusive results regarding the construction costs or value of wooden buildings. This study aims to determine the economic feasibility of wood-based structures in housing. We approach this by estimating the effect of wood on Finnish dwelling prices through hedonic regression analyses. Dwelling prices are analysed with transaction data from the Helsinki metropolitan area. It is provided by the Central Federation of Finnish Real Estate Agencies. The data represents occurred transactions between 1999 and 2018. The study discovers that a wooden structure has a positive price effect in the Helsinki metropolitan r",7.0,https://iopscience.iop.org/article/10.1088/2634-4505/abfe05/pdf488d18ef170fa3d168124ca1dd169fff80ecaadfcd5,10.3390/land12030626,Effects of Multifaceted Street Art on Price Premium of Pre War Commercial Buildings: The Case of Georgetown UNESCO World Heritage Site,2023,Land,Chin-Tiong Cheng; G. Ling; H. Chin; Pau-Chung Leng,"Street art is promoted in most countries to intensify the cultural elements of the cityscape. Although street art provides cultural and social values, its impact on the prices of prewar historic property is still unknown. Therefore, an empirical study that examines the relationship between prewar shophouse prices and street art is needed to improve real estate professionals’ understanding of the historic preservation market. Using pre- and post-models for the years 2009 to 2019, this study systematically determined the actual location of 119 street art objects (in the form of sculptures and murals) and the 852 prewar shophouses sold in George Town, Penang. The price change of prewar shophouses correlates with the number of street art objects within 100 m, 500 m, and 1000 m of the properties. Due to the heterogeneous characteristics of the properties, six primary hedonic models were developed to extract the price premium of street art. This study has shown the impact of street art on a prewar commercial building, where an additional unit of sculpture could increase its price by 8.32%, 1.62%, and 0.74%, based on radii of 100 m, 500 m, and 1000 m, respectively, in the post-model (afte",7.0,https://www.mdpi.com/2073-445X/12/3/626/pdf?version=1678780560489e2aec14baa7ef3008564e4685e54665957939139,10.14246/irspsd.10.1_167,"Determinants of Luxurious Condominium Prices in Bangkok CBD: A Case study of Encouraging Housing Affordability in Bangkok, Thailand",2022,International Review for Spatial Planning and Sustainable Development,Pornraht Pongprasert,": This study aims to find the factors influencing prices of luxurious condominiums within 1-km radius of urban rail transit stations in Bangkok CBD, where the property value rapidly increases since last decade. According to recorded data, the average price of condominiums in CBD is higher, nearly 28% during 2016-2019. Besides, the growth of luxurious condominium in these areas grows higher sharply. 52% of new condominiums are above Luxury class while housing affordability of Bangkok’s largest population is too low. Also, urban policy cannot control the unpredictable price of condominiums in CBD. As a tool for urban planners, post-windfall gain tax would be collected from real estate developers who get uplift property values as result of public infrastructure planning. It would be used to fund infrastructure such as transit, affordable housing. This paper can recommend urban policy planners which factors influencing unpredictable price of luxurious condominium in CBD should be considered in condition of windfall profit taxation. In addition, results suggest developers to set more reasonable price of new luxurious condominiums near rail station in CBD. In this study, 55 luxurious con",7.0,https://www.jstage.jst.go.jp/article/irspsd/10/1/10_167/_pdf4901b06d5abfe32d650517ed54e21f8d196f135c666,10.1108/ijhma-03-2021-0033,"Impact of light rail line on residential property values – a case of Sydney, Australia",2021,International Journal of Housing Markets and Analysis,R. Abidoye; Felice Fam; O. Oshodi; A. Oyetunji,"491Purpose492The construction of new transportation infrastructure tends to affect the adjoining properties, economy and environment. In particular, studies have investigated the change in the value of properties due to increased access to transportation facilities. The purpose of this paper is to examine the impact of the recently completed light rail on residential property values in Sydney, Australia.493494495Design/methodology/approach496Sales data of residential properties was extracted from the CoreLogic’s RP database. The hedonic pricing model was used to assess the effect of proximity to the light rail stops. Two models were developed for the announcement and construction phases of the light rail project.497498499Findings500It was found that during the announcement phase, properties located within the 400 m radius from the station were 3.3% more expensive than those within the 400–800 radius. At the construction stage, the properties within the 0–400 m radius from the stops sold at 3.1% more than those within the 400–800 m radius. This study concludes that a positive relationship exists between the values of residential property and proximity to light rail stations.501502503Practical implications504Th",7.0,https://eprints.lancs.ac.uk/id/eprint/157495/1/PDF_Proof_IJHMA.PDF50520af8282e8223ab05308dc9a73159f03ea6d7362,10.3390/su16114453,"Investigating the Correlation between Air Pollution and Housing Prices in Seoul, South Korea: Application of Explainable Artificial Intelligence in Random Forest Machine Learning",2024,Sustainability,Dongwon Ko; Seunghoon Park,"South Korea’s Particulate Matter (PM) concentration is among the highest among Organization for Economic Cooperation and Development (OECD) member countries. However, many studies in South Korea primarily focus on housing characteristics and the physical built environment when estimating apartment prices, often neglecting environmental factors. This study investigated factors influencing apartment prices using transaction data for Seoul apartments provided by the Ministry of Land, Infrastructure, and Transport (MOLIT) in 2019. For this purpose, the study compared and analyzed a traditional hedonic price model with a machine learning-based random forest model. The main findings are as follows: First, the evaluation results of the traditional hedonic price model and the machine learning-based random forest model indicated that the random forest model was found to be more suitable for predicting apartment prices. Second, an importance analysis using Explainable Artificial Intelligence (XAI) showed that PM is more important in determining apartment prices than access to education and bus stops, which were considered in this study. Finally, the study found that areas with higher concent",7.0,https://doi.org/10.3390/su16114453506a7fe404df2e413395450e192cebe2f68aa921579,10.3846/ijspm.2022.18004,IMPACT OF ACCESS TO SUNLIGHT ON RESIDENTIAL PROPERTY VALUES: AN EMPIRICAL ANALYSIS OF THE HOUSING MARKET IN SHANGHAI,2022,International Journal of Strategic Property Management,Y. Zhong; Jia-Jun Lu; Zhe-Han Li,"As an important environmental amenity, sunlight brings us a large number of benefits and improves the quality of our daily lives, and its welfare measurement depends on concrete living conditions. The purpose of this article is to empirically document the non-marketed value of sunlight in light of the view orientation of an apartment in the context of the housing market. Using a hedonic pricing model estimated with the real estate transaction data over 40,000 housing units in 2019–2021 in Shanghai, it is found that: (1) homeowners, on average, are willing to pay an extra 7.2% to choose the apartments with a high level of sunshine (facing south), relative to those with no direct access to sunlight (facing north); (2) the value of sunlight shrinks with pollution and becomes larger if living in a higher apartment; (3) residents living in higher units have a larger willingness to pay for the sunlight and environmental quality improvement. These empirical findings shed light on the welfare measurement of sunlight and have profound implications for the capitalization of environmental amenities reflected in housing prices.",7.0,https://journals.vilniustech.lt/index.php/IJSPM/article/download/18004/11472507a2f3aa1231044ada5d057e2ff6e2432ec15655b5,10.1080/00036846.2022.2118223,The anticipated legacies of mega sporting events: An econometric analysis of Olympic announcement effect on the real estate market in small communities,2022,Applied Economics,Changsoo Hur; Kihan Kim,"ABSTRACT In this study, we examine the influence of the successful Olympic bid announcement on real estate prices for properties in host districts of the 2018 PyeongChang Olympic Winter Games. We perform a series of simple mean comparisons and hedonic spatial difference-in-differences analyses on a total of 198,048 apartment sales records for 1,059 apartment complexes collected from 2008 to 2017—3 years prior to winning the Olympic bid to 6 years after. The sales prices of the apartment complexes in the three Olympic host districts were 6.6% higher than the nonhost districts after eliminating the difference that had already existed before the announcement. Further analyses indicate a price premium for the apartments located near the main Olympic stadium. This study extends the research on the effects of Olympic bid announcements on real estate prices for small host cities with little international awareness.",7.0,https://doi.org/10.1080/00036846.2022.211822350876a0c1254f7c6017ddaba2614f2618c5679059ea,10.1080/07352166.2022.2147077,Past structural racism and present home prices,2023,Journal of Urban Affairs,Robert W. Wassmer,"ABSTRACT The widely acknowledged rating system of the Federal Homeowners’ Loan Corporation (HOLC) was a relative measure of pre-1940 racist practices in residential real estate activities in large United States central cities. It was not an assessment that guided HOLC or later Federal Housing Administration (FHA) mortgage lending practices. The research question examined here is whether a similar home in different HOLC-rated neighborhoods in the City of Sacramento (California) sold for a different price eight decades after receiving its HOLC grade. A hedonic regression result shows that homes in the two forms of lower-rated neighborhoods sold for about 13% less than those in the two forms of higher-rated neighborhoods. A Blinder-Oaxaca decomposition breaks down the average selling price difference of $195,000 between a home sold in HOLC green/blue compared to yellow/red rated neighborhoods. A third of this difference in home prices, which is not due to home characteristics, represents a starting measure of the legacy of discriminatory housing practices. The remaining two-thirds of the difference could be due to variations in current home characteristics also influenced by Pre-1940s",7.0,509a719a56ff10dbde96aa64c738fede432288b47fc,10.1080/08965803.2024.2346413,The Value of Sustainable Property Management in Real Estate: Evidence From Hong Kong,2024,Journal of Real Estate Research,Jianfu Shen; Kwok-Yuen Fan; E. Hui; Sik-Man Ho,": This study investigates whether sustainability in property management is valued by property buyers. Using a sample of 365,201 property transactions in Hong Kong from 2007 to 2021 and based on a hedonic pricing model, we find that the environmental, social and governance (ESG) performance of property management companies is positively associated with housing price; and housing price drops if property management companies incur ESG related risk incidents. The results are robust if the sample is restricted to transactions with repeated sales and a location-based matching approach is used. Further analysis suggests that housing prices increase with social and governance performance but not environmental performance of property management companies. The negative effect of ESG accidents on property prices is exaggerated if the accidents are reported by high reach media. Home buyers and non-local buyers are more willing to pay a premium for sustainability in property management than housing speculators and local buyers. Additional evidence suggests that ESG practices play a more significant role in determining property value through lower risk rather than higher rents. Taken together, t",7.0,510011148667cf42b65807b050b2dc9f527a19d50ea,10.11606/1413-8050/ea147474,Urban amenities and Real State Value: An Empirical Analysis for Recife City,2016,,Deborah Maria da Silva Seabra; Raul da Mota Silveira; T. D. de Menezes,"This study provides estimates of the amenities’ influence on the value of residential property in Recife, a city particularly marked by the presence of beaches and rivers. Therefore, a model of hedonic prices with correction for different types of spatial dependence was considered and a rich database provided by the City Hall was used, which includes information about sold properties and urban amenities. The evidence indicates that “ocean view” and proximity to the river are the most valued amenities in the city, while the value of real estate tends to be negatively affected by proximity to ZEIS, subways and violent places",7.0,http://www.revistas.usp.br/ecoa/article/download/111684/1098575115e29c89db542c6c2eac7f27b138b14759c353a92,10.1080/20421338.2020.1830542,Waste Disposal Sites and Residential Rental Values Nexus: An Appraisal of Agogo Asante Akyem Dumps,2021,,Peres Ofori,"The study, using regression and ANOVA, assessed the extent to which waste disposal sites impact residential rental values. The research collected data from both secondary and primary sources using a mixed method cross sectional survey. The linear hedonic price model was adopted to suit the research objectives. A questionnaire survey, expert interviews and a field investigation were used to gather raw data. The study revealed that all the residential properties that were far away from the waste disposal sites had higher rental values between (GH¢1200–1680) than those that were close (GH¢600–720). Construction of an engineered landfill by the district assembly for the town was recommended. Also, real estate developers in the town should be more circumspect about the siting of their residential properties since most of the people were not willing to pay higher rent if buildings are close to a filthy area like a dump site, irrespective of the architectural designs.",7.0,5122c777d53a0356c060ec452c1ee17fe4f762d5e7b,10.1007/978-3-642-37896-6_5,Spatial Hedonic Modeling of Housing Prices Using Auxiliary Maps,2018,,B. Bajat; M. Kilibarda; Milutin Pejović; Mileva Samardžić Petrović,,7.0,513784bd147866d1ec15bbfa3c42d3c2fc6a9ac3192,10.48264/vvsiev-20233402,The economic value of sustainability. Real estate market and energy performance of homes,2023,Valori e Valutazioni,Ezio Micelli; Giulia Gilberto; Eleonora Righetto; G. Tafuri,"The energy transition and decarbonisation require a major transformation of the housing stock. Responsible for around 40% of fossil fuel consumption and 30% of CO2 emissions, the built heritage must be upgraded in terms of energy performance. The issue is particularly sensitive for Italy, where seven out of ten homes are in the worst energy classes according to the classification introduced by the EU. The research aimed at investigating whether, and to what extent, energy-efficient homes command a premium price on the market compared to less efficient homes. The study focused on three medium-sized cities in northern Italy and developed three hedonic models based on more than 900 ask prices. The results confirm the stratification of the market in terms of energy efficiency levels. Estimates converge in absolute and relative terms between different cities. Particularly significant is the average gap found between properties in the highest efficiency class (Class A) and those in the lowest efficiency class (Class G), with values of around thirty percentage points, while the gap is around fourteen percentage points if we consider properties in Class D compared to Class G. The conclusio",6.0,https://siev.org/wp-content/uploads/2024/01/02_MICELLI-ET-AL-1.pdf5147eadd470dbd0528a230b0d82610a65f8d5102be7,10.3390/jrfm16060291,Delineating Housing Submarkets Using Space–Time House Sales Data: Spatially Constrained Data-Driven Approaches,2023,Journal of Risk and Financial Management,Meifang Chen; Y. Chun; D. Griffith,"With the increasing availability of large volumes of space–time house data, delineating space–time housing submarkets is of interest to real estate agents, homebuyers, urban policymakers, and spatial researchers, among others. Appropriately delineated housing submarkets can help nurture submarket monitoring and housing policy developments. Although submarkets are often expected to represent areas with similar houses, neighborhoods, and amenities characteristics, delineating spatially contiguous areas with virtually no fragmented small areas remains challenging. Furthermore, housing submarkets can potentially change over time along with concomitant urban transformations, such as urban sprawl, gentrification, and infrastructure improvements, even in large metropolitan areas, which can complicate delineating submarkets with data for lengthy time periods. This study proposes a new method for integrating a random effects model with spatially constrained data-driven approaches in order to identify stable and reliable space–time housing submarkets, instead of their dynamic changes. This random effects model specification is expected to capture time-invariant spatial patterns, which can he",6.0,https://www.mdpi.com/1911-8074/16/6/291/pdf?version=1685703681515c49249533069d801725af6064afc1523fa876dc1,10.5198/jtlu.2023.2297,Access-based land value appreciation for assessing project benefits,2023,Journal of Transport and Land Use,Yadi Wang; D. Levinson,"The traditional mobility-oriented travel-time saving benefit assessment method has been repeatedly questioned for numerous intrinsic flaws, motivating the search for alternative benefit assessment approaches. Although a wealth of literature confirms the capitalization effect of access benefits induced by transport improvements to land or real estate value, the access-based land value uplift method hasn’t yet been widely recognized and employed as an official tool assisting transport decision-making. The present paper collects 136 empirical studies and aims to disentangle the obstacles hindering the promotion of the access-based assessment method by systematically reviewing methodological design, the access metrics used, and the target real estate sub-markets or land use types upon which access benefits are quantified. First, it was found that almost half of the sampled studies just investigated the general effects of transport operation on real estate prices without incorporating sufficient temporal and locational considerations, thereby failing to isolate project-specific incremental impacts. Second, while the hedonic pricing model remains the most popular model, a trend towards e",6.0,https://jtlu.org/index.php/jtlu/article/download/2297/1709516527c17fa11ad1ccaff05d13eaeb2dfa2ff940bdd,10.3390/w13172401,Geospatial Heterogeneity in Monetary Value of Proximity to Waterfront Ecosystem Services in the Gulf of Mexico,2021,Water,Ram P. Dahal; R. Grala; J. Gordon; I. Munn; D. Petrolia,"Open spaces, including waterfront areas, are critical to coastal communities and provide many benefits, including recreation opportunities, economic development, ecological benefits, and other ecosystem services. However, it is not clear how values of waterfront ecosystem services vary across geographical areas which prevents development and adoption of site-specific natural resource conservation plans and suitable long-term land management strategies. This study estimated the monetary value of distance to different waterfront types in coastal counties of Mississippi and Alabama (U.S.) using a geographically weighted regression (GWR) approach as an extension to a traditional hedonic pricing method (HPM). In addition, the study utilized publicly available data from the U.S. Census Bureau instead of certified rolls of county property assessors and Multiple Listing Service (MLS) data which can be costly and difficult to obtain. Residents valued most waterfront types which was reflected in greater assessed prices for houses in proximity to these waterfronts. However, the value of ecosystem services associated with waterfronts differed geospatially. The marginal implicit prices ranged f",6.0,https://www.mdpi.com/2073-4441/13/17/2401/pdf?version=1631177184517433778217c0b45ad4ea3ea67a7a55879a3671224,10.1016/j.jenvman.2025.125312,Indoor and outdoor health factors in the pricing of commercial real estate: A hedonic analysis of U.S. office buildings.,2025,Journal of Environmental Management,Katharina Minkow; F. Fuerst,"Research on the connection between occupant health and the financial performance of commercial buildings is scarce. This study tests the willingness to pay for health-promoting features and estimates the relative contribution of indoor and outdoor features. For this purpose, a hedonic framework is applied to assess the effect of different attributes on prices. Based on a proprietary, assembled dataset of physical and financial characteristics, a sample of health-certified U.S. office buildings is compared to a large sample of non-certified buildings in the same markets. Potential biases are mitigated by statistical methods such as panel data estimation and propensity score matching. Health-certified offices are found to achieve a rental premium of 4-6 % on average, across model specifications. In addition, proximity to health services and an encouraging environment for active transport modes of commuting tend to increase office rents while outdoor air quality and hospital quality ratings yield mixed results. Comparing the individual price effects of indoor and outdoor health-related features shows that higher active commuting scores or walkability have the strongest positive associ",6.0,https://doi.org/10.1016/j.jenvman.2025.1253125184890340e533c9bfd3821e785c5ef400b1b35eca9,10.1080/12265934.2019.1651669,Assessing the impact of the intensifying UK minimum energy efficiency standards (MEES) on regional office rental values,2020,International Journal of Urban Sciences,Yasmin Booker,"ABSTRACT Since the introduction of the UK Minimum Energy Efficiency Standards (MEES) in April 2018, commercial buildings with a substandard Energy Performance Certificate (EPC) rating may be deemed untenable, depreciate in value and become obsolete. This paper aims to establish the value of the EPC in UK commercial buildings utilizing the hedonic pricing model and how the intensifying MEES might affect these values. The findings can then inform investors and developers in the Real Estate Development (RED) industry of the risks associated with low energy-performing assets. The missing link between environmental performance and property value is the consideration of the local market’s response to sustainability. Subsequently, this paper focusses on market location and environmental performance as the key regression variables. Data has been collated on 5444 commercial office buildings across the 12 UK regions, sourced from CoStar UK and the Ministry of Housing, Communities and Local Government Non-Domestic Energy Performance Register. The regression results indicate the first statistically significant findings relating to the EPC and office rental values. Interaction variables between",6.0,51932fba603276bf3ee4d3e883dcf58dcd8f483d562,10.3390/buildings15122088,Unveiling the Value of Green Amenities: A Mixed-Methods Analysis of Urban Greenspace Impact on Residential Property Prices Across Riyadh Neighborhoods,2025,Buildings,Tahar Ledraa; Sami Abdullah Aldubikhi,"The literature shows greenspaces generally increase nearby property values, but in Riyadh, this relationship is complex and understudied. Existing studies lack sector-specific analyses across Riyadh’s neighborhoods, overlook the impact of the Green Riyadh Project launched in 2019, and fail to address negative externalities associated with large greenspaces in an arid, privacy-conscious context. Such paradoxical impact of larger greenspaces bordering major roads at the neighborhood edge, unexpectedly reduce property values by 2–4% due to petty crime, congestion, poor upkeep, and privacy concerns, contrasting with 10–18% premiums for properties abutting greenspaces with restricted access in affluent neighborhoods. Global studies typically report positive greenspace effects, so negative impacts in specific Riyadh sectors are surprising. This highlights the city’s unique arid, cultural, and urban dynamics in addressing this research gap. The research uses purposive quota sampling of Riyadh neighborhood greenspaces and a mixed-methods approach of quantitative hedonic pricing analysis combined with qualitative semi-structured interviews with real estate agents. Findings underscore the ne",6.0,https://www.mdpi.com/2075-5309/15/12/2088/pdf?version=17501568315208bb2d90259ecee2da847f548a2527133a00ef0f5,10.1108/ijhma-06-2018-0042,Understanding real estate investments through big data goggles,2019,International Journal of Housing Markets and Analysis,Marcelo Cajias,"521Purpose522This paper aims to develop a conceptual understanding and a methodological approach for calculating residential net initial yields for both a buy-to-hold and rental investment strategy from hedonic models.523524525Design/methodology/approach526The markets modelled comprehend of dwellings for rent and sell in Germany. For each of them, two regression models are estimated to extract implicit prices and rents for an artificial identical dwelling and estimate the willingness to pay for the same asset from both a buy-to-hold and rental investment strategy.527528529Findings530The 3,381 estimated net initial yields in the 161 German markets showed a spatial pattern with the biggest and most attractive cities showing the lowest yields and a self-adjusting process in the markets surrounding the top cities. The net initial yields over time show that prices have increased stronger than rents, leading to rock bottom yields for residential assets and a significant premium in comparison to government bond yields. The approach responds to the spatial hierarchy of markets in Germany, meaning that the level of the estimated yields is accurate and achievable from an investment perspective.531532533Practical impl",6.0,534581b08355bf0171fcd8fbc78ce3131f0b8ed8e92,10.1108/ijhma-12-2023-0173,Does the market value energy efficiency within EPC-labels? An analysis of the residential real estate market in Flanders,2024,International Journal of Housing Markets and Analysis,Alesia Gerassimenko; L. De Moor; Laurens Defau,"535Purpose536The current literature has not investigated the perceived value of energy efficiency by households, regardless of financial benefits. Furthermore, there is a severe lack of research that investigates the effectiveness of the current format of EPC-labels. Therefore, the purpose of this paper is twofold: to study how households value energy efficiency in the housing market, regardless of price effects.537538539Design/methodology/approach540This study uses multiple hedonic regression models to analyse 706,778 Flemish properties for sale or rent between 2019 and 2023. The data is provided by Immoweb – the largest online real estate platform in Belgium. Given that the selling market is driven by different mechanisms than the rental market, the data set was divided in sold (522,164 listings) and rented properties (184,614 listings).541542543Findings544The ambiguous results of the A-label in the selling market indicate that the “class evaluation effect” found in related markets which use labels (e.g. household appliances) is also present in the housing market. However, the results of the other (lower) labels clearly show that owners do value energy improvements within labels, and this effect bec",6.0,5453284b13d3d2589a5886f884f24420e24a883d1c3,10.1007/978-3-032-06118-8_12,On the Performance of LLMs for Real Estate Appraisal,2025,ECML/PKDD,Margot Geerts; Manon Reusens; B. Baesens; S. V. 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",6.0,https://arxiv.org/pdf/2506.11812546973124ea687da38bfcb0d526fb28745dae9e1e90,10.1016/j.spasta.2017.07.010,MCMC Bayesian spatial filtering for hedonic models in real estate markets,2017,,P. Gargallo; Jesus Miguel; M. Salvador,"Abstract The traditional hedonic model postulates that housing prices depend on their characteristics and their location. However, this model assumes a constant relationship between the dependent and the independent variables. This assumption is unrealistic because empirical studies have shown that the regression coefficients depend on the housing location. For this reason, it is necessary to use models with spatially varying coefficients. The approaches proposed in the literature used to estimate this type of models do not incorporate the uncertainty associated with the estimation and selection of models and/or are computationally expensive. To improve these aspects, this paper proposes spatial filtering techniques to parsimoniously model the spatial dependencies of the hedonic coefficients and an adaptive MCMC Bayesian algorithm to select the most appropriate filters. The method is illustrated through an application to the real estate market of Zaragoza, and a comparison with alternative procedures is conducted. Our results show that our valuation methodology has better goodness of fit and predictive performance properties than alternative methods. Although our proposal assumes n",6.0,http://zaguan.unizar.es/record/7119054738179b5c7e3f351be7bae8fd62cdf31516c1ef88,10.1108/ijhma-08-2022-0112,"The impacts of pandemic on urban housing prices: evidence from the outbreak of COVID-19 in Beijing, 2020",2023,International Journal of Housing Markets and Analysis,B. Qin; Yan-Yan Peng; Lu Feng,"548Purpose549The COVID-19 pandemic has significantly raised economic risk and uncertainty worldwide. How does COVID-19 affect urban housing markets? Is there any difference when different areas encounter COVID-19? This study aims to investigate the impacts of the pandemic on housing prices by using Beijing’s housing markets data in 2020.550551552Design/methodology/approach553The authors use transaction-level data from April to September in 2020 to conduct a hedonic price analysis of the housing markets in Beijing. The data included 70,843 transactions scraped from a real estate agent’s website. The authors use the difference-in-differences approach to evaluate the impacts of the COVID-19 outbreak from the Beijing Xinfadi market (the largest and most important food wholesale market in Beijing) in 2020.554555556Findings557This outbreak of COVID-19 caused a 6.3% drop in housing prices in Beijing from April to September in 2020. However, the impacts of COVID-19 on housing prices in different urban neighbourhoods were spatially heterogeneous. Housing prices in neighbourhoods with industries that rely on face-to-face communication were more affected by the pandemic, while those that can work remotely were l",6.0,558https://openalex.org/W2526936923,10.1080/02664763.2016.1238053,A varying coefficient approach to estimating hedonic housing price functions and their quantiles,2016,Journal of Applied Statistics,Alan T. K. Wan; Shangyu Xie; Yong Zhou,"The varying coefficient (VC) model introduced by Hastie and Tibshirani [26 T. Hastie and R. Tibshirani, Varying-coefficient models, J. R. Statist. Soc. (Ser. B) 55 (1993), pp. 757–796.[Web of Science ®] , [Google Scholar]] is arguably one of the most remarkable recent developments in nonparametric regression theory. The VC model is an extension of the ordinary regression model where the coefficients are allowed to vary as smooth functions of an effect modifier possibly different from the regressors. The VC model reduces the modelling bias with its unique structure while also avoiding the ‘curse of dimensionality’ problem. While the VC model has been applied widely in a variety of disciplines, its application in economics has been minimal. The central goal of this paper is to apply VC modelling to the estimation of a hedonic house price function using data from Hong Kong, one of the world's most buoyant real estate markets. We demonstrate the advantages of the VC approach over traditional parametric and semi-parametric regressions in the face of a large number of regressors. We further combine VC modelling with quantile regression to examine the heterogeneity of the marginal effects",6.0,https://www.cb.cityu.edu.hk/ef/doc/GRU/WPS/GRU%232016-003%20Alan%20W.pdf5591cfe837df0de5fbf9301d42a68087ac61222c173,10.1590/2175-3369.014.e20210447,"The real estate market and public transportation systems in developing countries: the case of Medellín, Colombia",2022,Urbe : Revista Brasileira de Gestão Urbana,H. D. Villada-Medina,"Abstract The objective of this study was to measure the effect of the distance between homes and the stations of the integrated public transportation system in Medellín on home prices. The hedonic models used here were calculated using ordinary least squares (OLS) and two spatial econometric models: the spatial autoregressive (SAR) model and the spatial error model (SEM). The results obtained indicate that the stations of this transportation system have an impact on home prices depending on the income level of the district where they are located. On the one hand, the price of a home in a low- or middle-income district can increase (17.1% or 15%) if it is “near” a station (1.5-2.0 km and 1.0-1.5 km, respectively), but it is not affected if the housing unit is “too close” (up to 1.0 km). On the other hand, if the housing unit is located in a high-income district, the nearer it is to a station, the lower its price (-15% between 0 and 1.0 km, and -12% between 0.5 and 1.0 km). These results are relevant for all the agents involved in real estate and public policy makers interested in executing transportation infrastructure projects in cities in developing countries.",6.0,https://www.scielo.br/j/urbe/a/7YVRZWspXMGTvQ9Hnm9gKBm/?lang=en&format=pdf56005c8066a4f1ebf0565508520c4002c90671161c4,10.2478/remav-2025-0003,Algorithm-Driven Hedonic Real Estate Pricing – An Explainable AI Approach,2024,Real Estate Management and Valuation,S. Tarasov; Bartłomiej Dessoulavy-Śliwiński,"Abstract Data-driven machine learning algorithms triggered a fundamental change in hedonic real estate pricing. However, their adaptive nonparametric structure makes inference and out-ofsample prediction challenging. This study introduces an explainable approach to interpreting machine learning predictions, which has not been done before in the local market context. Specifically, Random Forest and Extreme Gradient Boosting models are developed for residential real estate price prediction in Warsaw in 2021 on 10,827 property transactions. Model-agnostic Explainable Artificial Intelligence (XAI) methods are then used to investigate the black box decision making. The results show the practicability of applying XAI frameworks in the real estate market context to decode the rationale behind data-driven algorithms. Information about the relationships between input variables is extracted in greater detail. Accurate, reliable and transparent real estate valuation support tools can offer substantial advantages to participants in the real estate market, including banks, insurers, pension and sovereign wealth funds, as well public authorities and private individuals.",6.0,https://sciendo.com/pdf/10.2478/remav-2025-000356188ad98a57373aa3b16881de2e01f9dd1700559b2,10.1109/icspcre62303.2024.10675142,Real Estate Price Prediction Using PySpark MLlib,2024,2024 IEEE International Conference on Smart Power Control and Renewable Energy (ICSPCRE),Kadam Prajwal Dharmaraj; Pradeep Kumar Gupta; K. Ajith; Mahi Kolli; Sangita Khare; Niharika Panda,"Prices of real estates in metropolitan landscapes harbour immense importance in steering the complexities of dynamic city environments. In India, the real estate sector contributes around 6–7% to India's GDP. Therefore, accurate forecasting of real estate prices is a factor in making informed decisions, affecting various stakeholders. Many techniques were used for this in past several years, like Hedonic models, Repeat-Sales models, Rule-Based Systems and Heuristics, etc. This study leverages the power of machine learning and big data to develop a robust framework for predicting housing prices in metropolitan landscapes. We employ PySpark, a powerful big data processing framework with built-in MLlib library (machine learning library), to analyse large-scale housing data encompassing various cities in India & to predict the prices for the same. By implementing a comparative analysis of prominent regression models - Random Forest, Linear Regression, Decision Tree, and Gradient-Boosted Tree - our approach identifies the most effective algorithms for real estate price prediction using MLlib library. Also, this study highlights the need for scalable solutions to manage an increasing num",6.0,562doi_10_1108_17538271111137930,10.1108/17538271111137930,Insight into apartment attributes and location with factors and principal components,2011,International Journal of Housing Markets and Analysis,Alain Bonnafous; Marko Kryvobokov,"Purpose The purpose of this paper is to better understand the spatial structure of the Lyon urban area focusing on real estate. For this, two aims are formulated. The first aim is to identify and geographically analyse latent structure underlying apartment variables and location. The second aim is to decrease a number of explanatory variables in a hedonic model of real estate prices applying latent constructs. Design/methodology/approach For the first aim of a parsimonious representation among measured variables, exploratory factor analysis is applied. For the second aim of data reduction, principal component analysis (PCA) is used. The exploited regression methodologies are global and geographically weighted ordinary least squares. Findings Four factors are extracted, of which two represent apartment attributes and other two – location attributes. Principal components provide better insight into location attributes dividing the service employment centres into two geographical groups. The inclusion of principal components in hedonic price equation instead of initial location variables decreases goodness of fit, but does not gradually change non‐location estimates and other paramete",6.0,5631f11a1b17c740b828b9aa879b13637b6be55eaba,10.1111/gean.12377,What's a School Worth to a Neighborhood? A Spatial Hedonic Analysis of Property Prices in the Context of Accommodation Reviews in Ontario,2023,Geographical Analysis,John Merrall; Christopher D Higgins; Antonio Páez,"Due to a change in capital funding formula, many school boards across the Province of Ontario engaged in Accommodation Reviews to rationalize the supply of school capacity. This process led to numerous school closures and raised important policy questions regarding the economic value of a school in terms of its capitalization into property values and, by extension, how the closure of a school might affect local neighborhoods. To explore these questions, this research uses spatial hedonic methods to estimate the implicit value of accessibility to schools in the City of Hamilton, Ontario. Spatial Durbin model results provide evidence of a significant negative correlation between distance to schools and housing prices in the Canadian context. This suggests that accessibility to schools is capitalized into property values and that the closure of a neighborhood school may result in potentially significant losses of economic value in communities.",6.0,https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/gean.1237756403c7319d6d03a3326e49bd775951ee9918110cee,10.1016/j.seps.2020.100914,Does my house have a premium or discount in relation to my neighbors? A regression-kriging approach,2020,,Jorge Chica-Olmo; Rafael Cano-Guervos,"Abstract In the real estate literature, numerous studies have applied hedonic models to estimate the implicit value of the characteristics that influence housing prices. However, few studies have quantified the weight of location in the price of residential properties, and still fewer have quantified the premium or discount used to weigh the price of a home. In this paper, the regression-kriging method is applied to address the two previous objectives in the city of Granada, Spain. This method is also adapted, interpreted and made accessible to real estate appraisers with a view to providing these professionals with an objective, sophisticated and powerful tool in accordance with their know-how. This method can also be useful for investors, urban planners, public administrators and revenue departments, among others, as it can determine the value distribution of the location.",6.0,https://hdl.handle.net/10481/1090905650ecf3823469a3d4458d89fbf3c8d844873f2dc90,10.3390/land10121330,"Heterogeneity Analysis of Urban Rail Transit on Housing with Different Price Levels: A Case Study of Chengdu, China",2021,Land,Peng-Yu Ren; Zhaoji Li; Weiguang Cai; Lina Ran; Lei Gan,"The impact of urban rail transit on housing prices has attracted the extensive attention of scholars, but few studies have explored the heterogeneous impact of rail transit on housing prices with different price levels. To solve this problem, we adopted the hedonic price model based on ordinary least squares regression as a supplementary method of quantile regression to study the heterogeneous impact of the Chengdu Metro system on low-, middle-, and high-priced housing. The result shows that the housing price rises first, then falls with the distance from the housing to the nearest subway station. Besides, the influence of transportation accessibility on low-, middle-, and high-priced housing decreases progressively. This research can provide a reference for the government’s transportation planning and decision-making.",6.0,https://www.mdpi.com/2073-445X/10/12/1330/pdf?version=163886740456622d1760a5d45a527fd2cb56e6e71b48788d6dd76,10.1080/09640568.2022.2079079,Traffic noise and property values: an instrumental variable strategy for hedonic valuation,2022,Journal of Environmental Planning and Management,Luis Bravo-Moncayo; Roberto Mosquera; Virginia Puyana-Romero; M. Romero; José F. Lucio-Naranjo; E. Suárez,"Noise pollution is a consequence of socioeconomic development processes and urbanization. Noise action plans, urban planning, and traffic management are costly, and their undertaking raises the issue of the value of noise reduction to households. We use hedonic pricing to estimate the value of traffic noise for urban residents in Quito, Ecuador. Results were obtained using instrumental variables in order to control the possible omitted variables due to any spatial effect. Considering a large dataset of property attributes and noise exposure, properties inside the mixed land use were compared to those right behind them in a 20-meter buffer, which was characterized by similar structural attributes but different noise exposure levels.",6.0,https://figshare.com/articles/journal_contribution/Traffic_noise_and_property_values_an_instrumental_variable_strategy_for_hedonic_valuation/23766584567doi_10_1108_02637470710723263,10.1108/02637470710723263,Pricing inter‐neighbourhood variation,2007,Property Management,Sherif Roubi; Ashraf Ghazaly,"Purpose The purpose of this paper is to focus on inter‐neighbourhood variation in the rental apartment market in Greater Cairo, Egypt, and its potential influence on property prices and performance of hedonic pricing models. Design/methodology/approach The paper delves into the issue of whether comparables from different neighbourhoods are homogeneous enough to be aggregated in hedonic pricing models. This paper extends the research on rental‐property market segmentation by investigating the existence of apartment submarkets determined by neighbourhoods. Findings Results show that parameters are unstable across neighbourhoods and Chow test provides further support for utilising spatial hedonic pricing models. Originality/value This paper provides further support for spatial hedonic pricing models using empirical evidence from Greater Cairo, Egypt. The paper finds that explanatory and predictive powers of hedonic pricing models are improved when separate hedonic equations are estimated for each neighbourhood in Greater Cairo. The paper does not provide an elaborate solution for implementing spatial models in Greater Cairo but rather supports the notion that one has to be developed.",6.0,568https://openalex.org/W2325155093,10.1080/14445921.2002.11104123,An Hedonic Price Model of New Housing in Indonesia,2002,Pacific Rim Property Research Journal,Supardi Samapatti; Linda Tay,"This study investigates the prices of new housing in the Greater Jakarta Metropolitan Area, Indonesia. Based on the average sale prices of 149 new housing projects launched between January and June 1997, the ANOVA statistical tool is used to test whether different sizes of development adopt the same hedonic pricing model. Following this, multiple regression analyses are conducted to identify the hedonic factors and their impacts on the new house prices in small, medium and large developments. The study concludes that small, medium, and large-sized developments do not adopt the same hedonic pricing model. With the exception of small-sized developments hedonic model in which structural, locational and neighborhood characteristics are important determinants of prices, the medium and large-sized development hedonic models showed that only locational attributes have significant impact on house prices.",6.0,569https://openalex.org/W2138716974,10.1109/icmse.2010.5720005,Empirical analysis on the housing price in Harbin City based on hedonic model,2010,International Conference on Management Science and Engineering (ICMSE),Wang Wei; Tong Guang-ji; Hongrui Zhang,"This paper selects 9 housing characteristics as the independent variables for the market supply-demand equilibrium model to construct a housing hedonic model in a multiple linear functional form, and tests the model using sample data collected from more than 400 multi-storey housing buildings in Harbin City. Conclusion shows that the model can be used to analyze and explain the influence of housing characteristics on housing prices. It is found that the 9 housing characteristics have differing impacts on housing prices. Moreover, the paper also classifies and sorts different levels of influence of housing characteristics on the basis of hedonic prices.",6.0,570https://openalex.org/W3092430233,10.15301/jepa.2020.28.3.213,Estimating Values of Urban Green Space in Seoul: Application of Hierarchical Linear Regression Model on Hedonic Housing Price Analysis,2020,환경정책,Hye Kyung Jung; Seong Do Yun; Tae-kyun Kim; Seung Gyu Kim,"도시민의 도시녹지 생태서비스에 대한 수요가 늘어남에 따라 이들에 대한 접근성이나 경관에 대한 가치 추정 또한 꾸준히 이어지고 있다. 본 연구는 서울의 이질적 자연 환경 즉, 한강, 일반산림, 북한산에 대한 가치를 추정하기 위하여 서울의 대표적 주거 형태인 아파트에 대한 실거래가격을 취득하여 주택특성가격분석을 시행하였다. 과정에서 집합건물의 특성상 동일한 위치 정보와 동일한 주택특성을 가진 다수의 거래자료로 인하여 거래가격에는 공간종속성, 설명변수에는 위계적 구조가 발생하였다. 이의 해결을 위해 공간시차 변수 추가, 동일 주택 특성별 데이터 그룹화, 위계선형모형의 적용이 고려되었고, 주택 특성별 그룹화 거래자료에 2수준 임의절편 선형모형을 적용할 때 주택특성가격모형 오차항의 공간종속성이 통계적으로 존재하지 않는 수준으로 감소함을 확인하였다. 따라서 집합주택 거래자료를 이용한 주택특성가격 모형의 추정에서 대용량 거래건수로 인해 공간계량모형의 적용이 불가할 경우 대안적으로 고려할 가치가 있는 것으로 보인다. 추정결과를 살펴보면 북한산 조망에 대해서는 양의 경관가치가 추정되었지만 일반 산림에 대해서는 나타나지 않았다. 한강에 대해서는 다른 도시녹지에 비해 상대적으로 큰 조망가치가 계측되었다.",6.0,571https://openalex.org/W2605276908,10.47672/aje.148,RESIDENTIAL HOUSING DEMAND IN NAIROBI; A HEDONIC PRICING APPROACH,2017,American Journal of Economics,Mongare G. Kemunto; Wilfred Nyangena,"Purpose: The purpose of this study was to asses the residential housing demand in Nairobi using a hedonic pricing approach.Methodology: The study used an OLS regression model to link House rent to various determinants. For the purpose of analysis the population o be sampled was based in Nairobi. The researcher focused on the Nairobi up market residential areas and the Nairobi lower market residential areas. The sampling frame consisted of residential housing facilities in both the up market and lower market Nairobi area. The sample size was specifically fifty five up market and lower market residents in Nairobi. Short and simple questionnaires were the main data collection method used to obtain the primary data of the information.Results: Results revealed that that the HSESIZE (number of bedrooms) were positively and significantly correlated to the VALUE (house rent). This implies that the higher the pollution number of bedrooms, the higher the rent. The results also indicate that EXPLEVEL (exposure level to pollution) was negatively and significantly correlated to VALUE (House rent). This implies that the higher the pollution exposure, the lower the rent. The results also indicate",5.0,https://ajpojournals.org/journals/AJE/article/download/148/265572d7bafcfe00c8c1481a4adcfc99e041cbc2706a38,10.1108/pm-03-2022-0023,"Modelling apartments values in the Nairobi metropolitan area, Kenya",2022,Property Management,E. K. Museleku,"PurposeThe purpose of this paper is to determine the most significant factors influencing apartment values in Nairobi Metropolitan Area (NMA), Kenya and develop a valuation model using the identified variables. The paper is thus promoting the adoption of advanced, more reliable and accurate valuation methods in developing economies such as Kenya. Therefore, the paper demonstrates the potential of the hedonic pricing method (HPM) in property valuation by making objective adjustments to comparable sales data.Design/methodology/approachThe paper utilizes a case study design by analysing recent (January 2020 to December 2021) apartment sales and apartment attributes in NMA. A sample size of 264 transactions was analysed using the HPM.FindingsThe study identified six significant factors affecting apartment values in the study area: apartment size, location, floor finishes, provision of shopping facilities, swimming pool and gym. A valuation model has been developed using the six variables.Research limitations/implicationsThe paper is contributing to the ongoing global debate on the accuracy, reliability and validity of property valuations with particular emphasis on the developing econo",5.0,5730e568775e77ac2d90b96f6f8ecad954135ed43b0,10.4102/jef.v12i1.204,Listing price estimation of apartments: A generalised linear model,2019,Journal of Economic and Financial Sciences,Dane Bax; Mihalis Chasomeris,"Orientation: Residential property is an important segment of the property market in South Africa. Residential property transactions are typically infrequent and relate to a highly differentiated set of items making measurement techniques complex and difficult. Research purpose: The aim of this research was to develop a statistical model to estimate listing prices of apartments in KwaZulu-Natal, South Africa, and build a software application to disseminate the results thereof. Motivation for the study: This study presents a novel alternative to the log linear (ordinary least squares) method of deriving a hedonic price function for residential property where the arithmetic mean is computed as the expected value and not the geometric mean. Research design, approach and method: Using a data set of 1314 residential apartments provided by Private Property (Pty) Ltd, this research derives a hedonic price function for residential property using a generalised linear model based on the gamma distribution and log-link function. Main findings: The results showed that floor area, number of bedrooms, number of bathrooms and a dummy variable for suburb (location) were statistically significa",5.0,https://jefjournal.org.za/index.php/jef/article/download/204/670574abfbaa44b12551b6f57b5817d678cf6d56a7a872,10.1108/ijhma-09-2023-0121,Housing price determinants in Ecuador: a spatial hedonic analysis,2024,International Journal of Housing Markets and Analysis,Felipe Miguel Valdez Gómez de la Torre; Xu-Wei Chen,"575Purpose576This paper aims to compare the efficiency of spatial and nonspatial hedonic price models in capturing housing submarkets dynamics for cities in developing countries. This study expects to contribute to a better understanding of the housing price determinants from both nonspatial and spatial perspectives. In addition, this paper fills a gap in the literature on the study of housing prices from a spatial perspective in Latin American cities.577578579Design/methodology/approach580This study uses a comparative analysis between an ordinary least squares regression and a geographical weighted regression, GWR. The study also assesses the performance of two distinct data sources: the city’s cadastral records and a real estate sales web portal.581582583Findings584The results suggest that compared to the traditional regression model, the spatial regression models are more effective at capturing housing market variations on a fine scale. Moreover, they reveal interesting findings on the spatial varying, sometimes contradictory effects of some housing attributes on housing prices in different areas of the city, suggesting the potential impact from segregation.585586587Research limitations/implications588The ",5.0,589c0719dfc2e99247adf55e3df25480bbce55099dd,10.1108/ijhma-05-2022-0071,Modelling coastal externalities effects on residential housing values,2022,International Journal of Housing Markets and Analysis,A. B. Ayoola; A. Oladapo; B. Ojo; A. Oyetunji,"590Purpose591This paper aims to examine the impact of coastline on the rental value of residential property in proximity to the coastline, using the hedonic pricing model from two perspectives. First, Model 1A–C accounted for estimating the influence of coastal amenities while controlling for other housing attributes influencing rent. Second, Model 2A–C accounted for the interaction between coastal amenities/disamenities and other housing attributes influencing rent.592593594Design/methodology/approach595A survey approach was adopted for the data collection process. For both models, property values were measured in proximity to coastline using 0–250 m, 251–500 m and 0–500 m.596597598Findings599Findings revealed that property rental value increases as we move away from the coastline when disamenities are not controlled. The results suggested that for a mean-priced home (N2,941,029 or $8,170) at the mean distance from the coastline (301.83 m), a 1% increase in distance from the coastline would result in a 0.001% or N9.77 ($0.03) increase in rental value.600601602Practical implications603The implication to real estate valuers is that varying premiums should be considered when valuing a property depending on the ",5.0,https://eprints.lancs.ac.uk/id/eprint/174737/1/IJHMA_acceptance.PDF60421a28b66973ad1e7bfe57d006d009de881a0e4af,10.3390/buildings13102571,"Co-Living at Its Best—An Empirical Study of Economies of Scale, Building Age, and Amenities of Housing Estates in Hong Kong",2023,Buildings,Zhankun Chen; Ka-Shing Cheung; Desmond Tsang; Chung Yim Edward Yiu,"Co-living is commonly considered as an arrangement for rental housing. However, co-living in housing estates by sharing common amenities among co-owners has been practiced for many years in high-density cities. Yet, there have been very few empirical studies on the estate premium and the economies/diseconomies of scale effect on house prices, probably due to the lack of data. This study is a novel attempt to examine the economies/diseconomies of scale effect using the hedonic price model to estimate the impact of the number of housing units in a housing estate on house prices, ceteris paribus, using Hong Kong housing transaction data. The results confirm the hypothesis of estate premium and the economies of scale effect of co-living in housing estates. Economies of scale are observed, with larger estates commanding a premium of up to 5031 units, beyond which the effect declines, hinting at potential diseconomies. Building age moderates this effect, as we observe a larger scale effect in especially younger estates with lower maintenance costs. Additional tests confirm the positive correlation between amenities and prices, with an optimal amenity number enhancing prices, while excess",5.0,https://www.mdpi.com/2075-5309/13/10/2571/pdf?version=169709912760519e11c4e4e4a1ee1339b548065653ee715260536,10.3390/buildings14071982,Exploring the Spatially Heterogeneous Effects of Street-Level Perceived Qualities on Listed Real Estate Prices Using Geographically Weighted Regression (GWR) Modeling,2024,Buildings,Rui Wang; Guo-Qin Zhang; Yu Zhang; Yanzhe Lan,"The listed price of real estate is a subjective reflection of its value by sellers, usually related to structural, neighborhood, and environmental attributes. Although previous studies have proposed the hedonic pricing model, factors related to perception are rarely seen in explanatory variables. This study aims to explore the impact of street-level perceived qualities on the listed price per square meter of plot set by the seller of the real estate using the Geographically Weighted Regression (GWR)-based hedonic pricing model and analyzes the spatially heterogeneous effects of the coefficients. In the city of Eindhoven, the Netherlands, Google Street View photos collected at 200 m intervals were employed to calculate representative variables of perceptual quality via a validated convolutional neural network, alongside structural and neighborhood attributes. The final model includes eight explanatory variables, and the results indicate that, apart from the plot area and the number of rooms, the influencing mechanisms of other factors are different. The impact of perceived beautiful quality on listed real estate prices demonstrates obvious distinctions between the north and the sout",5.0,https://www.mdpi.com/2075-5309/14/7/1982/pdf?version=171982343960605133875334147dc5ac7d37a0479720642327db6,10.3386/w25701,"Market Frictions, Arbitrage, and the Capitalization of Amenities",2019,,Amine Ouazad; Romain G. Ranciere,"The price-amenity arbitrage is a cornerstone of spatial economics, as the response of land and house prices to shifts in the quality of local amenities and public goods is typically used to reveal households' willingness to pay for amenities. With informational, time, and cash constraints, households' ability to arbitrage across locations with different amenities (demographics, crime, education, housing) depends on their ability to compare locations and to finance the swap of houses. Arbitrageurs with deep pockets and better search and matching technology can take advantage of price dispersions and unexploited trade opportunities. We develop a disaggregated search and matching model of the housing market with endogenously bargained prices, identified on transaction-level data from the universe of deeds for 6,400+ neighborhoods of the Chicago metropolitan area, matched with school-level test scores and geocoded criminal offenses. Price-amenity gradients reflect preferences and the capitalization of trading opportunities, which are arbitraged away in the frictionless limit. Thus the time-variation in hedonic pricing coefficients partly reflects the time variation in search and credit",5.0,http://www.nber.org/papers/w25701.pdf6070fe82e8b18cc371498773e34654f4904c5d797a9,10.3390/jrfm15040159,Homebuyer Purchase Decisions: Are They Anchoring to Appraisal Values or Market Prices?,2022,Journal of Risk and Financial Management,Ka-Shing Cheung; Chung Yim Edward Yiu; Yihan Guan,"Price discovery is an important research topic in real estate due to the heterogeneous nature of housing attributes and relatively thin trading activities compared to other assets. In Commonwealth countries, including New Zealand, governments usually conduct periodic appraisals for the purpose of collecting rates and levies. Such official appraisal values of properties, also known as capital values (CVs), are considered a price anchor for market participants in their negotiation processes. Real estate agents often use these appraisal values to advertise their listings and negotiate transaction prices. In this study, we aim to make an initial attempt to study the influence of CV on market prices using Granger causality tests and a hedonic pricing model. To test the lead-lag relationships, three million housing transactions from 1990 to 2020 in New Zealand are used to construct the capital values (CVs) and transacted prices (TPs) indices in both primary and secondary housing markets. The Granger causality test suggests that the indices of TPs and CVs have a bi-directional lead-lag relationship in the secondary housing market, whereas the relationship does not follow in the primary ma",5.0,https://www.mdpi.com/1911-8074/15/4/159/pdf?version=16489033316086a582c18a0b55c4939a0e4812ae293fd34b678de,10.4236/chnstd.2018.74025,Capitalization of Public School Quality into Housing Prices: An Empirical Analysis Based on School District Housing for Public Primary Schools in Shanghai,2018,,Tiancheng Zhou,"This paper examines the capitalization of public school quality into housing prices in the specific context of China’s compulsory education system and “district correspondence enrollment” policy, which stipulates a strict correspondence between residential estates and enrollment into public primary schools. Taking 344 neighborhoods in 7 main districts of Shanghai, China as its sample, this paper carries out detailed descriptive analysis of the data. It also employs the traditional Hedonic Price Model and 2SLS regression method to quantitatively calculate the exact capitalization rates while isolating eight non-school attributes affecting housing prices. It yields the conclusion that for every one-rank improvement in the quality of the corresponding public primary school, the average housing price of a neighborhood is projected to increase by 3.1%, 2.8%, and 1.9%, on the citywide, urban, and suburban scale, respectively. The capitalization effect of public school quality in housing prices is statistically significant, so the status-quo of the distribution of public educational resources in Shanghai is still considerably unequal. In the final section of this paper, the significance o",5.0,http://www.scirp.org/journal/PaperDownload.aspx?paperID=884166091cdacbd24ebfbf2ed0522dfc87265e5bfeb1da60,10.3390/ijgi13050159,Total Least Squares Estimation in Hedonic House Price Models,2024,ISPRS Int. J. Geo Inf.,Wen-Xi Zhan; Yu Hu; Wenxian Zeng; Xing Fang; Xiong Kang; Dawei Li,"In real estate valuation using the Hedonic Price Model (HPM) estimated via Ordinary Least Squares (OLS) regression, subjectivity and measurement errors in the independent variables violate the Gauss–Markov theorem assumption of a non-random coefficient matrix, leading to biased parameter estimates and incorrect precision assessments. In this contribution, the Errors-in-Variables model equipped with Total Least Squares (TLS) estimation is proposed to address these issues. It fully considers random errors in both dependent and independent variables. An iterative algorithm is provided, and posterior accuracy estimates are provided to validate its effectiveness. Monte Carlo simulations demonstrate that TLS provides more accurate solutions than OLS, significantly improving the root mean square error by over 70%. Empirical experiments on datasets from Boston and Wuhan further confirm the superior performance of TLS, which consistently yields a higher coefficient of determination and a lower posterior variance factor, which shows its more substantial explanatory power for the data. Moreover, TLS shows comparable or slightly superior performance in terms of prediction accuracy. These resul",5.0,https://doi.org/10.3390/ijgi13050159610https://openalex.org/W4411991185,10.1016/j.mlwa.2025.100707,Explaining drivers of housing prices with nonlinear hedonic regressions,2025,Machine Learning with Applications,Heng Wan; Pranab K. Roy Chowdhury; Jim Yoon; Parin Bhaduri; Vivek Srikrishnan; David R. Judi; Brent Daniel,"Housing markets play a critical role in shaping the spatial and demographic evolution of urban areas. Simulating housing price dynamics can enhance projections of future urban development outcomes. However, traditional hedonic regressions for housing prices, which neglect nonlinear interactions among explanatory variables, often exhibit limited predictive performance. While machine learning (ML) methods can provide a more flexible representation of the relationships between predictors, they are often regarded as “black boxes” due to their complexity and lack of transparency. Interpretable ML techniques provide a promising route by combining the flexibility of ML methods with approaches to analyze the relationships between inputs and outputs. In this study, we employ interpretable ML to analyze the patterns driving the housing market in Baltimore, Maryland, USA. We train an Artificial Neural Network (ANN) to predict Baltimore housing prices based on structural characteristics (e.g., home size, number of stories) and locational attributes (e.g., distance to the city center). We then conduct sensitivity and Partial Dependence Plot (PDP) analyses to interpret the fitted ANN model. We f",5.0,6110122a631e41bf9758c29784cc01333d32c8da9c7,10.3390/su132011489,Computational Valuation Model of Housing Price Using Pseudo Self Comparison Method,2021,Sustainability,S. Choi; Mun Yong Yi,"Hedonic pricing method (HPM), which is commonly used for estimating real estate property values, considers the property’s internal and external characteristics for its valuation. Despite its popularity, however, the method lacks the mechanism that directly reflects the target property’s price fluctuation and the real estate market’s volatility over time. To overcome these limitations, we propose Pseudo Self Comparison Method (PSCM), which reduces the real estate valuation problem to finding a pseudo self, which is defined as a housing property that can most closely approximate the characteristics of the target housing property, and adjusting its previous transaction price to be in sync with the real estate market change. The proposed PSCM is tested for two scenarios in which the volatility of the real estate market varies greatly, using the transaction data compiled from Seoul, the capital of South Korea, and its surrounding region, Gyeonggi. The study results show almost five times lower estimation errors when predicting housing transaction prices using the PSCM compared to the HPM in both scenarios and in both areas. The proposed method is particularly useful for mass valuation o",5.0,https://www.mdpi.com/2071-1050/13/20/11489/pdf?version=16348811516120c37515c387a1abe60322f69a10c6d7ceebf6b00,10.3390/land10121321,"Residents’ Demands for Urban Retail: Heterogeneity in Housing Structure Characteristics, Price Quantile, and Space",2021,Land,Peng-Yu Ren; Yuan-Li Li; Kai-Rui You,"A thorough understanding of residents’ demands plays an important role in realizing the rational distribution of urban retail (UR) and promoting the habitability of cities. Unfortunately, these demands for UR are currently under-researched. To solve this problem, this study aims to quantify the capitalization effect of UR on housing prices and explores the impact of heterogeneity in housing structure characteristics, price quantile, and space on the residents’ demands for UR according to the hedonic price model, quantile regression, and geographically weighted regression in Chengdu. The results of these models show the following: (1) good property management and building sound insulation can reduce the negative influence of UR on residents’ lives; (2) only the owners of low-price houses are willing to pay a premium for UR; and (3) residents’ demands for UR increase from the central area to the peripheral area of Chengdu, and an inverted U-shaped relationship was found between housing prices and the UR level. A comprehensive analysis of the heterogeneity of residents’ demands for UR can provide a reference for planning departments, real-estate developers, and UR owners and promote t",5.0,https://www.mdpi.com/2073-445X/10/12/1321/pdf?version=1638409490613e45573dfee5ae9713a92fc2b8504ea00c4b447c0,10.1177/1471082x231157205,A multilevel analysis of real estate valuation using distributional and quantile regression,2023,Statistical Modelling,Alexander Razen; Wolfgang A. Brunauer; Nadja Klein; T. Kneib; S. Lang; Nikolaus Umlauf,"Real estate valuation is typically based on hedonic regression models where the expected price of a property is explained in dependence of its attributes. However, investors in the housing market are equally interested in the distribution of real estate market values (including price variation), that is, determining the impact of attributes of a property on the entire conditional distribution. We therefore consider Bayesian structured additive distributional and quantile regression models for real estate valuation. In the first approach, each parameter of a potentially complex parametric response distribution is related to a structured additive predictor. In contrast, the second approach proceeds differently and models arbitrary quantiles of the response distribution directly and nonparametrically. Both models presented are based on a multilevel version of structured additive regression thereby utilizing the typical hierarchical structure of real estate data. We demonstrate the proposed methodology within a detailed case study based on more than 3 000 owner-occupied single family homes in Austria, discuss interpretation of the resulting effect estimates, and compare models based on",5.0,https://journals.sagepub.com/doi/pdf/10.1177/1471082X231157205614cdc2c570d488b25e40ea567da8068ca1ff68558c,10.1111/1540-6229.70030,Explainable spatial machine learning for hedonic real estate modeling,2026,Real Estate Economics,Tim Gyger; Simona Hauri; Simon Bühlmann; Manuel Lehner; Jaron Schlesinger; Fabio Sigrist,"Accurately modeling rents and prices is a key challenge in real estate analysis. Traditional linear models may fail to capture complex non‐linear relationships, and spatial dependencies are often ignored in existing machine‐learning approaches. This article introduces a novel hybrid statistical machine‐learning model for modeling real estate rents and prices. The proposed approach combines a spatial Gaussian process with tree boosting. In so doing, spatial correlations are explicitly accounted for, and the tree‐boosting part can handle complex non‐linear relationships and interactions. We compare the proposed model against established benchmarks using a large‐scale dataset consisting of more than 1.5 million rental apartment listings across Germany and also a smaller condominium price listings dataset. Our findings demonstrate that the proposed model yields superior prediction accuracy due to accounting for both nonlinear patterns and spatial dependencies. We further use machine‐learning explainability techniques to better understand the nonlinear relationships present among rents and predictor variables, and we conduct a detailed analysis of the impact of locational characteristic",5.0,https://doi.org/10.1111/1540-6229.700306150a59d5d819d469e24a6d9d4cb8216c6ffdf3de2d,10.1108/ijhma-04-2021-0041,Distance in geographic and characteristics space for real estate pricing,2021,International Journal of Housing Markets and Analysis,E. Ozhegov; A. Ozhegova,"616PurposeA common approach to predicting the price of residential properties uses the hedonic price model and its spatial extensions. Within the hedonic approach, real estate prices are decomposed into internal characteristics of an apartment, apartment characteristics and external characteristics. To account for the unobserved quality of the surrounding environment, price models include spatial price correlation factors, where the distance is usually measured as the distance in geographic space. In determining the price, a seller focuses not only on the observed and unobserved factors of the apartment and its environment but also on the prices of similar marketed objects that can be selected both by geographic proximity and by characteristics similarity. The purpose of this study is to show the latter point empirically.617618619Design/methodology/approachThis study uses an ensemble clustering approach to measure objects' proximity and test whether the proximity of objects in the property characteristics space along with spatial correlation explain the significant variation in prices.620621622FindingsIn this paper, the pricing behaviour of sellers in a reselling market in Perm, Russia is studie",5.0,6231daf1d20ba429ff68e39043313dece9a679c8c5d,10.1007/s10182-023-00476-w,A spatial semiparametric M-quantile regression for hedonic price modelling,2023,AStA Advances in Statistical Analysis,Francesco Schirripa Spagnolo; R. Borgoni; A. Carcagnì; A. Michelangeli; N. Salvati,"This paper proposes an M-quantile regression approach to address the heterogeneity of the housing market in a modern European city. We show how M-quantile modelling is a rich and flexible tool for empirical market price data analysis, allowing us to obtain a robust estimation of the hedonic price function whilst accounting for different sources of heterogeneity in market prices. The suggested methodology can generally be used to analyse nonlinear interactions between prices and predictors. In particular, we develop a spatial semiparametric M-quantile model to capture both the potential nonlinear effects of the cultural environment on pricing and spatial trends. In both cases, nonlinearity is introduced into the model using appropriate bases functions. We show how the implicit price associated with the variable that measures cultural amenities can be determined in this semiparametric framework. Our findings show that the effect of several housing attributes and urban amenities differs significantly across the response distribution, suggesting that buyers of lower-priced properties behave differently than buyers of higher-priced properties.",5.0,https://link.springer.com/content/pdf/10.1007/s10182-023-00476-w.pdf6245963388754babe6d31f55353775ebbc3931ecfb3,10.24187/ecostat.2018.500t.1952,Does information to buyers affect the sales price of a property? Mandatory disclosure and the hedonic price model – A test on French data,2018,Economie et Statistique / Economics and Statistics,A. Mauroux,"[eng] Under the assumption of complete and perfect information, hedonic prices can be interpreted as marginal willingness to pay. This assumption may appear strong, especially in cases of exposure to natural risks. This assumption is tested for the French real estate market: we assess the impact of an informational shock – the implementation of the obligation to inform buyers and tenants (IAL) on 1st June 2006 – on real estate prices. If the information available to buyers was perfect, there should not be any impact. A hedonic price model is estimated in difference-in-differences, using notarial data spatially matched with maps of regulated zones covered by flood risk prevention plans. The results do not show an impact of the introduction of the IAL on the average price of the houses concerned. However, for certain categories of properties (ground floor apartments) and certain municipalities (where the housing market is the least tense, such as the so-called “recentred” Robien zone C), the estimated impact is negative and significant, a sign that not all buyers were initially in a situation of complete and perfect information.",5.0,https://doi.org/10.24187/ecostat.2018.500t.19526255170d50eab56ddf40c03eaf3e11552023cf9142d,10.1515/apjri-2017-0003,House Price Models for Banking and Insurance Applications: The Impact of Property Characteristics,2017,,Adam W. Shao; Katja Hanewald; M. Sherris,"Abstract House price indices are needed to assess house price risk in households’ portfolio allocation decisions and in many housing-related financial products such as reverse mortgages, mortgage insurance and real estate derivatives. This paper first introduces nine widely-used house price models to the insurance, risk management and actuarial literature and provides new evidence on the relative performance of these models. We then show how portfolio-level house price indices for properties with specific physical and locational characteristics can be constructed for these different models. All analyses are based on a large dataset of individual property transactions in Sydney, Australia, for the period 1971-2011. The unrestricted hedonic model and a hybrid hedonic repeat-sales model provide a good model fit and reliable portfolio-level house price indices. Our results are important for banks, insurers and investors that have exposure to house price risks.",5.0,https://unsworks.unsw.edu.au/bitstreams/0956de8a-e407-442a-9c07-a63275a047c3/download6267eac765766a4833adcc8dbfc5ac301a2170ac93f,10.1109/wids-psu54548.2022.00015,Analysis of the Dimensionality Issues in House Price Forecasting Modeling,2022,2022 Fifth International Conference of Women in Data Science at Prince Sultan University (WiDS PSU),S. Sakri; Zaiton Ali,"House price fluctuations in the real estate market occur due to the effects of other variables that are correlated to housing prices. Some prices cannot be controlled or it is not known when they will increase or decrease. These fluctuations accord with the hedonic pricing theory, which suggests that house pricing depends on the composite features. Our study explores this econometric concept using machine learning algorithms in the effort to accurately forecast house prices. To build the forecasted models, we use the Ames housing dataset, which include 82 explanatory features and 2930 entries on housing sales in Ames, Iowa, USA. We use particle swarm optimization feature selection to address the dataset dimensionality issues for both classification-based models and regression-based models. With dimension reduction, the experimental results demonstrate that the house price prediction accuracy increased from 81.4% to 84.4% for classification-based models, and the price prediction error decreased from 13.3% to 6.9% for regression-based models. The experimental results demonstrate that there is a substantial difference between using and not using feature selection in terms of the perfo",5.0,6271b2d27fe76aef4a9ca8a0dbcbfe7ec076f98fe39,10.1017/s1068280500002835,Spatially Delineated Public Goods and Spatially Located Public Bads: A Hedonic Approach to Measuring Urban Revitalization,2011,Agricultural and Resource Economics Review,John E. M. Brown; J. Geoghegan,"A regression discontinuity approach is used to measure the impact of public-goods creating programs in a declining inner city neighborhood of Worcester Massachusetts. Using GIS data, we develop a hedonic model of residential sales, using a parcel-level GIS tax assessment and land use database linked to property sales data for the years 1988 through 2007, to test the effect of the creation of a new high-performing public school, as well as other locational amenities and disamenities on neighborhood housing prices, by comparing properties adjacent to either side of the school catchment area boundary.",5.0,http://ageconsearch.umn.edu/record/120683628doi_10_1007_s13147_017_0485_0,10.1007/s13147-017-0485-0,Der Einfluss städtischer Grünflächen auf die Immobilienpreise: Eine hedonische Analyse für die Stadt Berlin,2017,Raumforschung und Raumordnung | Spatial Research and Planning,Henry Wüstemann; Jens Kolbe,"Urban green space represents a key aspect for the sustainable development of urban areas. The benefit of urban green space can also be reflected in higher property and land prices. Although a high number of international studies prove the impact of urban green on real estate prices, the empirical basis in Germany is still very limited. The overall purpose of this study is to investigate the impact of urban green space on real estate prices in Germany. The data set contains transaction data for single family homes (1996-2012) provided by the Committee of Valuation Experts (GAA, Gutachterausschuss für Grundstückswerte) for the city of Berlin and cross section geo-coded data for urban green drawn from the European Urban Atlas (EUA) of the European Environment Agency. In order to control for additional open space categories we further incorporated geo-coded data on water bodies, forest, farmland and fallow land. The analysis shows a positive impact of urban green on real estate prices. The results provide helpful information on the capitalization of urban green space in real estate prices.",5.0,62978c8565dad17d0909801fbca0086a58af83c2ab3,10.1109/icwr.2019.8765250,Using Web Mining in the Analysis of Housing Prices: A Case study of Tehran,2019,2019 5th International Conference on Web Research (ICWR),R. Annamoradnejad; Issa Annamoradnejad; T. Safarrad; J. Habibi,"There have been many previous works to determine the determinants of housing prices. All of these works relied on a relatively small set of data, mostly collected with the help of real estate agencies. In this work, we used web mining methods to generate a big, organized dataset from a popular national brokerage website. The dataset contains structural characteristics of more than 139,000 apartments, alongside their location and price. We provided our full dataset for the article, so that other researchers can reproduce our results or conduct further analyses. Using this dataset, we analyzed housing prices of Tehran in order to identify its major determinants. To this aim, we examine the dynamics of housing prices at the district levels of Tehran using Hedonic Price model. Our results highlight a number of points, including: Base area of an apartment is positively correlated with price per square meter (r=0.89), showing a two-folded impact on the overall price. Air quality is in a positive, and floor level is in negative correlation with housing prices.",5.0,630doi_10_1080_00420988520080761,10.1080/00420988520080761,Resident Age and Housing Search: Evidence From Hedonic Residuals,1985,Urban Studies,Larry DeBoer,"Elderly people are likely to have higher housing market search costs than the population as a whole. Costly search increases the price paid by older persons for housing relative to its characteristics, and also increases the range of prices paid. To test this latter hypothesis, hedonic equations are estimated for six SMSAs using data from the Annual Housing Survey. The residuals of these hedonics represent variation in prices not explained by housing characteristics. It is found that the absolute variation of these residuals is positively related to resident age, which is evidence supporting the hypothesis that the elderly pay higher housing prices due to higher search costs. A possible policy response to this problem is to create a housing market information service directed at reducing the search costs of the elderly.",5.0,631https://openalex.org/W1993389335,10.2747/0272-3638.18.4.347,SPATIOTEMPORAL CONTROLS IN HEDONIC HOUSING PRICE MODELS,1997,Urban Geography,Kyoun-Sup Chung; Paul A. Waddell; Brian J. L. Berry,An interactive spatiotemporal fixed-effect hedonic housing price model estimated by weighted least squares will control for most forms of spatial and ecological autocorrelation and produce efficient housing price estimates.,5.0,63214d90baab3d6b08e6abbc686c43df7491db35636,10.1142/s2010007821500032,ESTIMATING DEMAND FOR GOOD CLIMATE AND AIR QUALITY IN TAIWAN,2021,,D. Shaw; JU-CHIN Huang; CHUAN-YAO Lin; Tingting Hsu; Ming-Hugh Tsai,"We measure the amenity values of climate and air quality in Taiwan using the two-step hedonic price method (HPM). Separate hedonic housing price equations, one for each of three metropolitan areas ...",5.0,63350b6c4240b68f75afb455037cdf3bca4b8d7fab0,10.3390/land13030311,Exploring the Impact of Multimodal Access on Property and Land Economies in Shanghai’s Inner Ring Districts: Leveraging Advanced Spatial Analysis Techniques,2024,Land,Wei He; Ruqing Zhao; Shu Gao,"This study explores the impact of accessibility on property pricing and land economies by advanced spatial analysis techniques, focusing on Shanghai as a representative metropolis. Despite the impact of metro systems on residential property values, which has been frequently assessed, a research gap exists in understanding this phenomenon in Asian, particularly Chinese, urban contexts. Addressing this gap is crucial for shaping effective urban land use policy and improving the land economy rationally in China and similar settings facing urban challenges. To assess the impact of metro station accessibility on property prices in Shanghai, with extensive rail transit, and to deeply explore the overall impact of land value varieties driven by metro on urban development, we conducted a comprehensive analysis, with discussion about future aspirations for land planning and management along with landscape and facility design, and measures to improve land economy. The procedures involved creating neighborhood centroids to represent accessibility and using the Euclidean distance analysis to determine the shortest paths to metro stations. Our evaluation incorporated a hedonic pricing model, co",4.0,https://www.mdpi.com/2073-445X/13/3/311/pdf?version=1709220851634384ca1593b9f09c264ffdb7a6a7790b41c3a1523,10.1108/jpif-01-2018-0004,Are corporate office buildings priced differently?,2018,Journal of Property Investment & Finance,Odilon Costa; F. Fuerst; Wesley Mendes-da-Silva,"635Purpose636While broader property-type categories of real estate markets have been scrutinized at microeconomic level in some segments – namely, residential, retail, industrial and hospitality, there is limited evidence showing that local office markets can be viewed as monolithic and economically integrated entities. The purpose of this paper is to investigate how occupiers differ in their willingness to pay for principal office rent determinants in the corporate and non-corporate sectors.637638639Design/methodology/approach640A sample of properties located in the largest office market in Latin America is partitioned based on the average size of leasable units. This approach captures interactions between different groups of investors and occupiers, and is commonly adopted by local market practitioners due to lack of detailed information on market participants. The pricing schedules for these two groups of buildings are then empirically compared through hedonic regression analysis and parameter stability tests.641642643Findings644The regressions show that corporate and smaller occupier properties form distinct spatial and non-spatial submarkets, but that their temporal patterns are quite similar. Th",4.0,https://www.repository.cam.ac.uk/handle/1810/2804356454d2cf36586abe5a8dcb4cd171a95a31095559520,10.15201/hungeobull.73.3.3,The influence of urban green and recreational areas on the price of housing in Zagreb,2024,Hungarian Geographical Bulletin,Mirela Turk Cerovečki; Zoran Stiperski,"Urban green and recreational spaces are important for residents and one of the foundations for the functioningof cities. They offer numerous benefits, including the influence on the price of real estate as an economic benefit.In this paper, the influence of green and recreational areas in Zagreb on the price of apartments in residential buildings is analysed using the hedonic pricing model. The data for the study was processed and analysed using a geographic information system. A local hedonic price model was developed. The results show that some of the observed green and recreational areas increase the price of housing due to their proximity, while others decrease it. Some areas have no influence on the price of housing. The influence of the observed areas on housing prices was heterogeneous. Spatial differences were also found in the influence of the observed areas on housing prices. The most attractive factors when choosing a place to live are Jarun and the parks in the city centre. The price of apartments that near the Jarun increases by 41 EUR/m2 if the apartment is 100 m closer to the Jarun. The price of the apartment increases by 91 EUR/m2 the closer the apartment is to the ",4.0,https://ojs3.mtak.hu/index.php/hungeobull/article/download/15650/142176467409c1d2d6de0d63dfd17da30463090cc23beeee,10.15641/jarer.v9i2.1457,"Property Supply, Economic Factors and House Prices in Nairobi Kenya",2024,Journal of African Real Estate Research,D. Chirchir; Mirie Mwangi; Cyrus Iraya,"Residential real estate is an important asset class for both institutional and individual investors. The housing bubble in the US led to a global financial crisis in 2007 – 2008. As such, understanding the factors that influence property prices is central to the investment process and portfolio management. The objective of the paper was to first construct a Nairobi house price index and then determine the relationship among economic factors, property supply, and house prices. The study period was ten years (2011Q1 to 2020Q4). Autoregressive Distributed Lag (ARDL) model was adopted to estimate long run and short run relationships. The Nairobi real estate price index was developed using hedonic model based on the data collected on actual selling price and characteristics of a sample of houses in Nairobi spanning ten years. The paper finds that GDP and inflation have significant positive long run effect on house prices. Property supply has a significant negative long run effect on real estate prices. However, interest rates do not have significant effect on house prices. In the short run however, GDP had a significant negative effect on prices. The speed of adjustments towards equilib",4.0,https://journals.uct.ac.za/index.php/JARER/article/download/1457/1082647d2bd48101813a415410f72a9cc4ee814b25eca80,10.3897/oneeco.7.e89705,Setting priorities for greening cities with monetary accounting values for amenity services of urban green,2022,One Ecosystem,Beyhan Ekinci; K. Grunewald; Sophie Meier; Steffen Schwarz; Burkhard Schweppe-Kraft; R. Syrbe,"Life Satisfaction Analyses in Germany reveal a significant positive correlation between the amount of green space within 1 km of residence and well-being. The comparison of the effects of green space and income on well-being allows the derivation of a monetary demand function for green spaces close to the place of home. This demand function was used together with land-use and population data to estimate the monetary value of green space close to home for every 2 km × 2 km grid cell in Germany.648 The results can be used in environmental economic accounting as a proxy for the (visual) amenity services of green spaces close to residences and provide urban planners with additional information on the strength and spatial distribution of demand for green spaces in residential areas.649 The study shows that, especially in densely populated areas where more than 30 per cent of the German population lives, the (simulated) exchange value of green spaces (price per additional hectare derived from the demand function) multiplied by the number of households that would pay this price, is higher than the price per ha that can be achieved on the real estate market.650 A comparison with the results of a",4.0,https://doi.org/10.3897/oneeco.7.e89705651d536c9af6b0a1a741a0b9a7b2e9651cf70a61fdf,10.1108/pm-09-2022-0070,"Urban property markets and security risk: explaining how neighborhood security shapes housing rental prices in Ojo Lagos, Nigeria",2023,Property Management,I. R. Aliu,"PurposeWhile the declining rate of urban security and its potential effects have been globally acknowledged, the ways urban neighborhood security shapes real estate markets in African cities remain largely unexplained. The purpose of this paper therefore is to present the findings from a study of the nexus between urban neighborhood security and home rental prices in Lagos, Nigeria.Design/methodology/approachThis paper is based on the hedonic price theory, an objectively derived urban neighborhood security index (UNSI) and property rental price data in Ojo, Lagos, Nigeria. This is a quantitative cross-sectional study that employs multistage sampling survey procedure. Data are analyzed using descriptive statistics, nonparametric correlation and hedonic price function with ordinary least squares (OLS).FindingsResults show that nearly 50% of the study area is prone to insecurity and average rental values in Ojo, Lagos range from N151329.41 ($302.66) to N167333.33 ($334.67) per annum. Correlation analysis shows that home rental prices have high, positive and significant correlations (rs = 0.725 and p < 0) with UNSI. After controlling for neighborhood and structural factors, it is found",4.0,6520ccbd4aca038e0326541c122572d5f1253922e23,10.1016/j.ijforecast.2021.04.008,Reducing revisions in hedonic house price indices by the use of nowcasts,2021,International Journal of Forecasting,Doron Sayag; Dano Ben-Hur; D. Pfeffermann,"Abstract National Statistical Institutes (NSIs) must balance between timeliness and accuracy of the indicators they publish. Because some of the house sales transactions are reported several months after they occur, many countries that include Israel, publish provisional house price indices (HPIs) that are subject to large revisions as further transactions are reported. This happens because the late-reported transactions behave differently from the transactions reported on time. In this paper, we propose a novel methodology to minimize the size of the revisions, with illustrations from Israel, but the method can be applied to other countries with appropriate modifications. The proposed methodology consists of nowcasting three types of variables at a subdistrict level and adding them as input data to an extended hedonic model used for the computation of the HPI: (1) the average characteristics of the late-reported transactions such as the average number of rooms and the area size of the sold apartments; (2) the average price of the late-reported transactions; and (3) the number of late-reported transactions. The three variables are nowcasted based on models fitted to data from previ",4.0,https://eprints.soton.ac.uk/448832/1/International_Journal_of_Forecasting.docx6531a7546cc50601a1a7fda80e5d3256d1ec84d567a,10.3390/land14010182,Valuation of Urban Parks Under the Three-Level Park System in Shenzhen: A Hedonic Analysis,2025,Land,Xun Li; Qing-Yun He; Wen-Wen Huang; Siu-Tai Tsim; Jian-Wen Qiu,"Urban parks play a pivotal role in fostering ecologically advanced cities in China, contributing significantly to enhancing urban environments and the overall quality of life for residents. However, their value is often hard to quantify by urban planners due to the absence of a clear market price. Using the hedonic price method, this study delves into the distinct impacts of different types of urban parks (community parks, city parks, country parks) on housing prices under the three-level park system in Shenzhen. The outcomes reveal that owning a view of both city parks and country parks from the apartment has significant positive influence on housing prices, with a premium of 14.8916% (RMB 920,396.73) and 30.7299% (RMB 1,899,309.15), respectively. Regarding accessibility, shortening walking distance by 100 m to the nearest community park and city park can attach a premium to the housing price by 0.3269% (RMB 20,203.55) and 0.6130% value gain (RMB 37,889.53), respectively. The results drawn from distinctive park types are expected to give insights to urban planners in formulating strategies for ecological civilization construction, with an emphasis on prioritizing visible and acces",4.0,https://www.mdpi.com/2073-445X/14/1/182/pdf?version=17370813056542344ebd24eeebb31c33011f3e72a12383c3c1e88,10.11114/ijsss.v5i9.2510,"Hedonic Price Modeling of New Residential Property Values in Xi’an City, China",2015,,Kai Liu; T. Ichinose,"This study analyzed new residential property values of Xi’an City in March, 2014. Results show that accessibility indices, such as distance to CBD, have been well capitalized into the residential property values. Particularly, a within-zone housing unit is sold 9.4% more than if it was outside the attendance zone of a Key Primary School, i.e. home buyers have how much willingness-to-pay for the high-quality educational resource. Another corollary is got that the accessibility to subway stations has not significantly been capitalized, only with a low premium reflecting in the real estate market of Xi’an City. Considered that spatial local singularities caused by unobserved variables or estimation bias can be associated with multi-regression errors, this study herein has explored an unconventional viewpoint to residual problem, which combines the regional differences (coming from real world) and the spatial distributions of singularities (feedback from data). Furthermore, whole samples are classified into 5 agglomerations for revealing the underlying reasons about the future trend and variation of real estate market within each region. It is effective to provide scientific basis of d",4.0,http://redfame.com/journal/index.php/ijsss/article/download/2510/27816552580ac3af513b0ee5f2e19ed10bd991f2a8c8015,10.1177/23998083231213894,Extracting real estate values of rental apartment floor plans using graph convolutional networks,2023,Environment and Planning B Urban Analytics and City Science,A. 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. 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.",4.0,https://arxiv.org/pdf/2303.135686569b5602b5f63471ae059cd36c45480c83e988d6f5,10.1093/acrefore/9780190625979.013.583,Willingness to Pay in Hedonic Pricing Models,2021,Oxford Research Encyclopedia of Economics and Finance,David Wolf; H. Klaiber,"The value of a differentiated product is simply the sum of its parts. This concept is easily observed in housing markets where the price of a home is determined by the underlying bundle of attributes that define it and by the price households are willing to pay for each attribute. These prices are referred to as implicit prices because their value is indirectly revealed through the price of another product (typically a home) and are of interest as they reveal the value of goods, such as nearby public amenities, that would otherwise remain unknown.657 This concept was first formalized into a tractable theoretical framework by Rosen, and is known as the hedonic pricing method. The two-stage hedonic method requires the researcher to map housing attributes into housing price using an equilibrium price function. Information recovered from the first stage is then used to recover inverse demand functions for nonmarket goods in the second stage, which are required for nonmarginal welfare evaluation. Researchers have rarely implemented the second stage, however, due to limited data availability, specification concerns, and the inability to correct for simultaneity bias between price and quali",4.0,6581aa52b387c00d728ed5f6e7b8aeacbd09246f0d3,10.5539/ijef.v3n4p14,Property Tax Capitalization within a National Historic District versus Property Tax Capitalization outside that National Historic District: Another Application of the Tiebout Hypothesis,2010,,Richard J. Cebula; M. Foley; R. Houmes,"This study has two objectives. First, it seeks to apply a hedonic pricing model to determine whether property taxes have been capitalized into the prices of single family homes located within in the Savannah Historic Landmark District in Savannah, Georgia. A total of 593 home sales over the 2000-2005 period are considered, with the housing prices and the property tax expressed in 2005 dollars. Second, this study seeks to apply that very same model to prices of some 1908 single family homes within the metropolitan Savannah area but outside the Savannah Historic Landmark District. Estimating the model in semi-log form, after allowing for a variety of housing characteristics, reveals that the natural log of the real sales price of single-family houses within the Savannah Historic Landmark District as well as those outside the Savannah Historic Landmark District were in fact negatively affected by the city and county property tax level.",4.0,https://ccsenet.org/journal/index.php/ijef/article/download/11802/830365913a61953f01e5f8f119d4fa1872eb72503252526,10.31235/osf.io/2psk5,The Reflection of Income Segregation and Accessibility Cleavages in Sydney's House Prices,2021,ISPRS Int. J. Geo Inf.,M. Ng; J. Roper; C. Lee; C. Pettit,"This paper explores the relationships between accessibility, income segregation, and house prices in the Greater Sydney Area. Sydney is found to have reasonably even employment accessibility, reflecting the increasingly polycentric nature of the modern city; however, it also shows considerable income segregation and variance in property prices between different parts of the city. Entropy is used to examine the diversity and mixing of different income groups. Finally, hedonic price models using ordinary least square and geographically-weighted regression techniques to show the differing effects of employment accessibility on house prices in different parts of the city. The results show that accessibility has small to negative effects on prices in the most valuable areas, suggesting that other effects such as recreational access and employment type/quality may be important to investigate further in this context.",4.0,https://unsworks.unsw.edu.au/bitstreams/3f99bf9c-f521-4d1b-80c3-344f0d58ddb9/download660c15ba8a0a6017224eaf4694459bf962179074662,10.30785/mbud.1284843,A Study of the Metro and Housing Value Interaction with Hedonic Price Model: Comparison of Ankara Batıkent and Koru Metro Stations,2023,Mimarlık Bilimleri ve Uygulamaları Dergisi (MBUD),Fatma Erdoğanaras; Kübra Cihangir Çamur; Gülsel Satoğlu,"The effects of urban rail systems on the real estate market were studied by analysing housing prices around Ankara Koru and Batıkent Metro Stations using the Hedonic Price Model. Quantitative data on residential sales were used. The findings reveal that sale values of residences are more elastic in term of metro effect in Batıkent, where middle-lower income groups live, compared to Koru Metro Station, where middle-upper income groups live. As the distance to the metro station decreases in Batıkent, prices increase. These results suggest that subways can help reduce polarization between income groups in cities while increasing accessibility. Providing access to neighbourhoods with both low and high-income individuals by metro increases housing prices more in favour of low-income groups and reduces income polarization between income groups.",4.0,https://dergipark.org.tr/en/download/article-file/3090963661doi_10_1111_j_1538_4632_1995_tb00339_x,10.1111/j.1538-4632.1995.tb00339.x,Place‐to‐Place Rent Comparisons among Canadian Cities,1995,Geographical Analysis,John R. Miron,"This paper estimates average monthly gross rents for comparable rented private‐sector accommodation in Census Metropolitan Areas across Canada. By “gross rent” is meant the typical monthly payment in a CMA for a principal residence by a tenant of given traits under the conditions of a standard lease to a for‐profit landlord in competitive market equilibrium for premises used exclusively for accommodation, in an arm's length transaction, and includes heating and utility expenses where paid separately by the tenant. A single average gross rent is estimated for each city for dwellings and households, each with specified characteristics. This paper reviews the application of hedonic price models for this purpose, identifies shortcomings of current research in the field, and suggests a new form for such models. This new model is estimated using microlevel data from a sample of renter households taken across the twenty‐three largest urban areas in Canada. A classical version of the model is fitted first to renter data for individual cities, and its limitations assessed. A measure of “relative supply” is introduced to help explain city to city variations in the hedonic prices. Then an all",4.0,662dbd28c092fc069f6d3654ffe2e3088e3d8de25c9,10.1515/remav-2017-0027,Repeat Assessed Values Model for Housing Price Index,2017,,M. Carini; M. Ciuna; Manuela De Ruggiero; F. Salvo; M. Simonotti,"Abstract This study proposes an innovative methodology, named Repeat Appraised Price Model (RAV), useful for determining the price index numbers for real estate markets and the corresponding index numbers of hedonic prices of main real estate characteristics in the case of a lack of data. The methodological approach proposed in this paper aims to appraise the time series of price index numbers. It integrates the principles of the method of repeat sales with the peculiarities of the Hedonic Price Method, overcoming the problem of an almost total absence of repeat sales for the same property in a given time range; on the other hand, the technique aims to overcome the limitation of the repeat sales technique concerning the inability to take into account the characteristics of individual properties.",4.0,https://content.sciendo.com/downloadpdf/journals/remav/25/4/article-p25.pdf6630d896ad4da506c7ad6d29f952bc02cbf2078422f,10.1108/ijhma-02-2021-0016,The influence of privately initiated rezoning on housing prices,2021,,J. Robert; Velma Zahirovic-Herbert,"664Purpose665The purpose of this paper is to evaluate the parcel-level impacts of the zoning change.666667668Design/methodology/approach669Using hedonic regression and propensity score matching econometric techniques, this paper analyses single-family housing prices within Fulton County Georgia. This paper combines data on the parcel-level zoning changes with nearby housing sales transactions to study the potential externality effects because of rezoning induced by private parties.670671672Findings673The paper finds evidence of heterogeneous rezoning effects, depending upon the type of rezoning conducted. At a distance within 0.75 miles, housing prices appreciate by 8.31% when nearby privately initiated rezoning maintains the residential character of a neighbourhood. However, housing prices decline by 21.26% when residential housing zones are converted to non-residential housing zones. The negative influences of rezoning residential use to non-residential uses decline as distance increases.674675676Originality/value677The analysis provides quantitative information on the impact of rezoning on residential property prices. Planning officials and developers can use these results to assuage homeowner fears of pot",4.0,678957b7ae41dcaefe03a6f1c97347d060b63c91fe2,10.3329/jbip.v5i1.76959,"Stuctural, Spatial and Other Attibutes of House Price: The Case of Bangladesh",2012,Journal of Bangladesh Institute of Planners,T. Bashar,"This paper examines the significance of structural and spatial characterstics of house contributing to the property value. Longitudinal data on property value over the last ten years and cross sectional data on house rent have been analysed using Hedonic Regressions Function to derive a house price index for the current housing market in Bangladesh. The trend of house price is increasing more rapidly with the demand driven housing market in Bangladesh. Real estate attracts a great deal of speculative investment, but there is no indication of the relative importance of various factors in this process. This paper hopes to make an initial dent into this problem.679Journal of Bangladesh Institute of Planners, Vol. 5, Dec 2012, pp. 13-24",4.0,https://www.banglajol.info/index.php/JBIP/article/download/76959/5079568018be2c2cbd8cba146ad89528e652ddbafc384355,10.1080/09599916.2021.1888774,Appraising residential property using hierarchical generalised additive models,2021,,Dane Bax; Temesgen T. Zewotir; D. North,"ABSTRACT Log linear hedonic models are ubiquitous in econometric real estate research even though functional form assumptions are often not satisfied and the nested structure of homes in suburbs is not captured adequately. This study focuses on appraising different residential property types located throughout South Africa, investigating a flexible approach which does not assume some explicit functional form. The objective of this paper was to fit and compare two hierarchical generalised additive models to 412 500 property listings from 2013 to 2017. A gamma hierarchical model with random intercepts for the suburb provided the best fit and generalisability, while accounting for the spatial dependency in the data. The results show that hierarchical generalised additive models capture complex shapes between listing prices and structural property characteristics, and further reveal that partial pooling is useful to capture between suburb variability.",4.0,681doi_10_1017_s1355770x0300202,10.1017/s1355770x0300202,Hedonic pricing in Windhoek townships,2003,Environment and Development Economics,Michael Nokokure Humavindu; Jesper Stage,"This study applies the hedonic pricing model to property sales in the township areas in Windhoek, the capital city of Namibia, where municipal authorities have pursued a programme of selling plots of land to settlers in order to encourage them into a formalized economic situation. We find that, apart from house quality, access to the central business district, access to marketplaces and access to transportation, environmental quality also has a large impact on property prices. Properties located close to a garbage dump sell at considerable discounts, while properties located close to a combined conservation and recreation area sell at premium prices. The results thus suggest that the hedonic pricing method can be useful for studying townships in developing countries, and that this can help to clarify the importance of environmental factors which are otherwise frequently neglected in town planning for township settlements.",4.0,682d77c6f67d0521f20e3fb61913dc38e5348ef0f70,10.1080/00330124.2022.2048866,Spatial Hedonic Regression Analysis of the Impact of Cell Towers on Las Vegas Real Estate Market,2022,Professional Geographer,Awanti Acharya; S. Basu; Dean M. Hanink,"Cell towers are considered a disamenity due to apprehensions about health issues and visual pollution. This study examines the impact of cell towers on house prices in Las Vegas (2014–2017) using three spatial hedonic regression models. The distance-based model shows that house prices appreciate by approximately 2.02 percent with a 1-km increase in distance from the tower. The inverse distance–based model is used to determine the nonlinear effect of distance from a tower on house prices. Finally, the impact of visibility on house prices is considered but is not statistically significant. A negative impact of tower height on house prices is also observed. Furthermore, it is identified that camouflaged tree towers have a relatively less negative impact on house prices compared to conventional cell towers.",4.0,683ac3ac03b9b7b5a1369098534befd900449d1ea14,10.3368/le.95.4.515,The Implicit Price of Food Access in an Urban Area: Evidence from Milwaukee Property Markets,2019,Land Economics,Phillip Warsaw; D. Phaneuf,"An ongoing debate in the food security literature focuses on a definition of food security that is operational and generalizable. In this paper, we suggest that food security is related to the implicit prices paid by households in urban residential markets for food access. Using the hedonic property value model, we examine the distribution of implicit prices across socioeconomic characteristics for access to local food sources. Using land use and residential transaction data from Milwaukee, Wisconsin, we find evidence of higher implicit access prices in neighborhoods with a larger proportion of African American and Latino American households. (JEL Q18, R21)",4.0,684df82821de51ea5db43e76c5cff0d2647c8370a74,10.1108/ijhma-03-2025-0054,Air pollution and housing market valuation: a spatial hedonic pricing approach to welfare loss estimation,2025,International Journal of Housing Markets and Analysis,Warawut Ruankham,"685Purpose686This study aims to explore three key questions: How does air pollution affect real estate prices across markets, considering income, demographics and urban density? How do spatial econometrics improve air pollution impact estimation compared to traditional hedonic pricing models (HPM)? What are the welfare implications of air pollution, particularly in terms of compensating surplus (CS), and how can a multistage HPM framework enhance economic loss assessment? By addressing these, the research aims to refine property valuation, inform urban policy and support sustainable housing and environmental regulations.687688689Design/methodology/approach690This study uses a multistage HPM combined with spatial econometric techniques (Spatial Lag Model [SLM] and Spatial Error Model [SEM]) to estimate the impact of air pollution on housing prices in Thailand. To address endogeneity, a two-stage least squares (2SLS) approach is implemented using distance to factory and rainfall as instrumental variables. The marginal implicit price (MIP) and CS are derived to quantify economic losses. The Hausman and Hansen J-Tests validate model robustness. This integrated framework provides a spatially aware ",3.0,6919f8dfc9dffccb44488f89953a9acc675f8791ab7,10.15396/eres2019_347,Spatial pattern of housing prices in polycentric cities,2019,26th Annual European Real Estate Society Conference,Aurélien Décamps; Frédéric Gaschet; G. Pouyanne; S. Virol,"This article analyses the formation of urban and suburban employment centralities and their impact on local housing values. Urban sprawl combined with the formation of suburban employment poles have produced complex spatial patterns, characterized by polycentric cities. This paper assumes that these changes in urban forms have influenced residential dynamics and have thus influenced housing prices. Suburban centralities are expected to improve local attractiveness and thus to be capitalized in housing prices.We use hedonic regressions to estimate the impact of the polycentric structure of the city on housing values, among other traditional factors. These estimations are completed by semi-parametric regressions in order to analyse sharply the form of the price gradients in a polycentric city. Data on residential transactions come from the PERVAL database recorded by French notary offices. The precise geolocation of transactions is used, in addition to a rich set of intrinsic characteristics of the buildings, to estimation sharply the spatial pattern of real estate prices. It is completed by a rich set of locational attributes coming from several data sources recorded at a fine spati",3.0,https://eres.architexturez.net/system/files/P_20190801140926_8851.pdf6925bed224cb10ce261eda55857ae903598b9f96697,10.2495/tdi-v3-n4-295-305,"Investigation of the impact of railways on housing values; the case of Istanbul, Turkey",2019,International Journal of Transport Development and Integration,E. Cengiz; H. Çelik,"Housing units located near transportation facilities tend to have a higher market value than those that are at a greater distance to transport facilities but have similar characteristics. Provision of public infrastructure has a great impact on urban areas, especially on urban development patterns, spatial distribution of urban land use and real estate values. Mass transit systems are one of the most important public infrastructures in cities. Mass transit operations have a significant effect on property values, since they increase accessibility in urban areas. Railway projects are long-lasting investments and by their nature are extremely expensive when compared to other land transportation modes. It is not always possible or reasonable for many countries to fund these high-price projects only with their national budget generated by taxes collected from all citizens. Literature suggests that property values tend to rise in parallel to land values after any kind of public infrastructure investment. Nowadays transportation, especially railway system investments, is regarded as the most important public infrastructure in urban areas impacting land values maximally. Railway investment",3.0,https://doi.org/10.2495/tdi-v3-n4-295-3056936663c2076db87ffe9baf2162abc65f7ffa450ab0,10.1016/j.dadr.2024.100242,"Evaluating the effects of supervised consumption sites on housing prices in Montreal, Canada using interrupted time series and hedonic price models",2024,Drug and Alcohol Dependence Reports,M. Schaefer; D. Panagiotoglou,"Background In 2017, three brick and mortar supervised consumption sites (SCS) opened in Montreal, Canada. Opponents argued the sites would attract people who use drugs and reduce local real estate prices. Methods We used interrupted time series and hedonic price models to evaluate the effects of Montreal’s SCS on local real estate prices. We linked the Quebec Professional Association of Real Estate Brokers’ housing sales data provided by Centris Inc. with census tract data and gentrification scores. Homes sold within 200 m of the SCS locations between 1 January 2014 and 31 December 2021 were included. We adjusted for internal (e.g., number of bed/bathrooms, unit size) and external attributes (e.g., neighbourhood demographics), and included a spatio-temporal lag to account for correlation between sales. For sensitivity analysis we used site-specific dummy variables to better account for unmeasured neighbourhood differences, and repeated analyses using 500 m and 1000 m radii. Results We observed a price shock after the opening of the first two SCS in June 2017 (level effect: −10.5%, 95% CI: −19.1%, −1.1%) but prices rose faster month-to-month (trend effect: 1.1%, 95% CI: 0.7%, 1.6%) ",3.0,https://doi.org/10.1016/j.dadr.2024.10024269437e8b014df3e5f26ac93ad70c5f3f3c607c04c26,10.5198/jtlu.2025.2593,"Estimation of the anticipation effects of the metro project on real estate dynamics in Bogotá, Colombia",2025,Journal of Transport and Land Use,C. Vergel-Tovar; Juan Sebastián García; J. P. Álvarez; S. Mesa; Ingrid Lorena Molano; Leonardo Cañón-Rubiano; Laura M. Correa-Garzón,"Studies of the impacts of rail-based mass transit systems on land values and real estate prices are scarce in the Colombian context. Most studies have focused on estimating the impacts of bus rapid transit systems (BRT), mainly in Bogotá. There is an emerging literature on rail-based systems impacts on urban development and land values in Medellín, Colombia, while there is also an emerging interest regarding the effects of the announcements of the two metro projects of Bogotá in the city’s urban spatial structure. This paper develops a quasi-experimental research design looking at the anticipatory effects of the two lines of the Bogota Metro program on real estate market dynamics between 2007 and 2023. We used databases generated by the private sector with new housing developments including housing unit attributes and we estimated spatial variables and urban attributes associated with the location of each real estate development project. Through hedonic price models with control variables that incorporate attributes at different scales, our study estimates the effects of the Bogota Metro Line 1 project (in construction since 2021) on prices per square meter of real estate developme",3.0,https://jtlu.org/index.php/jtlu/article/download/2593/17966959c6a703a8764eedd5681875d0f03390b30c734cd,10.4314/etsj.v13i2.2,Assessment of the Contribution of Environmental Attributes to Residential Property Rental Value in Abuja,2023,Environmental Technology and Science Journal,O. F. Ayeni; O. Kemiki; N. Popoola; H. Musa,"The contribution of environmental attributes in residential price determination is premised on the issue relating to inefficient attributes pricing. The study analysed three environmental attributes such as structural, neighbourhood and natural attributes of the environment with a view to determining its hedonic value upon which residential property price is derived. In order to achieve the aim of the study, a sample size of 2401 was drawn out of 104166 properties using estimation method; 50% estimation rate and precision range of ±4 were adopted in estimating the sample size. The study administered two set of structured questionnaires; one to Estate Surveyor and Valuer firms to collect data on rental values (2008-2019) and second questionnaires were administered on the respondents to collect information on condition of environmental attributes using the census and simple random sampling method technique. Hedonic regression was employed to analyse the data. Environmental attributes were scored based on current condition and ratio scale was used alongside the average property value. The result revealed that neighbourhood attributes contributed between 60.3% -71.6%, natural attribute",3.0,https://www.ajol.info/index.php/etsj/article/download/242337/229153696942f0ff361a49b68c1333c31381f78c02a3d0937,10.1088/1757-899x/603/4/042015,How different are dwellings whose energy efficiency impacts price formation?,2019,IOP Conference Series: Materials Science and Engineering,Ai Chen; Carlos Marmolejo-Duarte,"Housing energy-efficiency has become a relevant issue since it is mandatory to exhibit an Energy Performance Certificate (EPC) when transacting real estate in the European Union. A number of studies have focused on energy-efficiency marginal prices using hedonic models from cross-sectional and longitudinal perspectives. Some of them have found that the increase of relevance of EPC ranks (i.e. marginal prices) is not the same for all the A-G classes. This study aims to explore the differences in terms of architectonic and location attributes between the apartments depicting an increase of EPC ranking marginal prices regarding those where energy efficiency seems not to play a role in price formation. In doing so, a pooled spatial error hedonic model is done using selling information for multifamily housing in Barcelona for the years of 2014 and 2016. Furthermore, it is shown which EPC ranks do exhibit an increase in terms of marginal prices in the period studied. Finally, we compare the architectonic and locative attributes for the set of homes where the energy efficiency has increased in terms of price importance to the set of homes where it has not increased. The results suggest th",3.0,https://iopscience.iop.org/article/10.1088/1757-899X/603/4/042015/pdf6974c087c7aa1e58aacc5fbc3b82a5ed35b84f7b9d6,10.1002/ldr.4270,Sustainability transitions of contaminated sites: A global meta‐analysis on economic effects of remediation behaviour,2022,Land Degradation & Development,Xiao-Nuo Li; Shi-Yi Yi; A. Cundy; Wei-Ping Chen,"The worldwide diversity of contaminated sites, coupled with a scarcity of available land presents a challenge for urban spatial planning and, has led to an increasing political significance for brownfield conservation and reuse to achieve land resource sustainability. In this study, economic or the so‐called ‘rebound effects’ of land regeneration are studied via a global meta‐analysis on value fluctuation of surrounding property. To this end, a total of 91 observations from 28 HPM (hedonic pricing model) studies were synthesized to conduct a meta‐analysis following a conditional random effects procedure. The empirical results indicate that, in line with expectations, the conservation and recycling of land resource indeed generate significant rebound in the implicit price of residential houses, especially for those located within 2 km of contaminated sites. Before land remediation and reuse, dwellings closest in distance to contaminated sites experience the greatest value loss. On average, the depreciation in property values within the first 1 km distance from a contaminated site is about 8.18%, significantly at the 1% level, while the corresponding adverse impact from 1 to 2 km dis",3.0,https://www.authorea.com/doi/pdf/10.22541/au.164394739.92744323/v1698fdf3432efb95e96e6e45a3ba105603f17a38d366,10.20885/ejem.v4i2.3318,HEDONIC VALUATION OF MARGINAL WILLINGNESS TO PAY FOR AIR QUALITY IMPROVEMENT,2012,,Endah Saptutyningsih; A. Basuki,"Abstract This study aims to identify the highest air pollution areas and to estimate household marginal willingness to pay for air quality improvement. The result of Kriging technique indicates that six sub districts in Yogyakarta City and one sub district in Gunungkidul have highest concentration of particle pollution (PM10). The result of hedonic price method conclude that by adopting a two-stage estimation procedure an 1% increase in the level of PM10 reduced property prices in the study area by 0.32%. Marginal implicit price for reducing PM10 is Rp 957,900.00. The households are willing to pay an additional amount of 1.34 percent for a reduction in PM10 by 1%. Keywords: Air pollution, marginal willingness to pay, hedonic price, implicit price JEL classification numbers: D12, Q53 Abstrak Penelitian ini bertujuan mengidentifikasi daerah polusi udara tertinggi dan untuk memperkirakan kesediaan marginal rumah tangga untuk membayar untuk perbaikan kualitas udara. Dengan menggunakan teknik Kriging, hasil penelitian menunjukkan bahwa enam kecamatan di Kota Yogyakarta dan satu kecamatan di Gunungkidul memiliki konsentrasi tertinggi partikel polusi (PM10). Sementara itu, dengan metode h",3.0,https://doi.org/10.20885/ejem.v4i2.33186990893ce95f4ec80e891e9cf83dfb029d633e4a22d,10.21837/pm.v20i21.1114,HEDONIC REGRESSION ANALYSIS IN DETERMINING THE EFFECT OF GREEN ON HIGH RISE RESIDENTIAL,2022,PLANNING MALAYSIA,Lizawati Abdullah; T. Mohd,"In predicting house price, there are many influential variables, and each variable is identified as a price determinant. Theoretically, variables are divided into categories, namely locational and neighbourhood attribute, structural attribute, time attribute, and environment attribute. Green element is one of the attributes as describe under environment category. The attribute is important as other variables which significantly explained how people willing to pay intangible variable. The relationship between property price and attribute needs to be examined to understand the influence of the green element on property price. Thus, this research attempts to demonstrate the independent variables correlated to the house price, including the green variable, by using hedonic regression analysis. Hedonic regression analysis is a well-known approach in determining the relationship between two or more variables. Green element represents the green-rated obtained by the housing scheme as evidence that the building possesses sustainable characteristics. The cost of green is relatively high than a conventional building. A dataset of 934 house price transactions with 14 variables was analysed. F",3.0,https://www.planningmalaysia.org/index.php/pmj/article/download/1114/8027001e904244e524160b9e63bc29b60aefb773acae55,10.1108/jpif-11-2018-0088,Income capitalisation method and hedonic model: an integrated approach,2019,Journal of Property Investment & Finance,G. Lisi,"701Purpose702The purpose of this paper is to provide an integrated approach that combines the two methods usually used in the real estate appraisals, namely, the income capitalisation method and the hedonic model.703704705Design/methodology/approach706In order to pull out the link between the income capitalisation approach and the hedonic model, the standard hedonic price function is introduced into the basic model of income capitalisation instead of the house market value. It follows that, from the partial derivative, a direct relation between hedonic prices and discount rate can be obtained. Finally, by using the close relationship between income capitalisation and direct capitalisation, a mathematical relation between hedonic prices and capitalisation rate is also obtained.707708709Findings710The developed method allows to estimate the capitalisation rate using only hedonic prices. Indeed, selling and hedonic prices incorporate all of the information required to correctly estimate the capitalisation rate. Furthermore, given the close relation among going-in and going-out capitalisation rates and discount rate, the proposed method could also be useful for determining both the going-out capitalisatio",3.0,7112d57316014c82828e51c8e462be7a1a743a99ce8,10.1108/pm-10-2020-0070,Pricing office rents in Sydney CBD: testing the water on automated rent reviews,2021,Property Management,O. Filippova; Jeremy Gabe; Michael Rehm,"PurposeAutomated valuation models (AVMs) are statistical asset pricing models omnipresent in residential real estate markets, where they inform property tax assessment, mortgage underwriting and marketing. Use of these asset pricing models outside of residential real estate is rare. The purpose of the paper is to explore key characteristics of commercial office lease contracts and test an application in estimating office market rental prices using an AVM.Design/methodology/approachThe authors apply a semi-log ordinary least squares hedonic regression approach to estimate either contract rent or the total costs of occupancy (TOC) (“grossed up” rent). Furthermore, the authors adopt a training/test split in the observed leasing data to evaluate the accuracy of using these pricing models for prediction. In the study, 80% of the samples are randomly selected to train the AVM and 20% was held back to test accuracy out of sample. A naive prediction model is used to establish accuracy prediction benchmarks for the AVM using the out-of-sample test data. To evaluate the performance of the AVM, the authors use a Monte Carlo simulation to run the selection process 100 times and calculate the t",3.0,712b34f2af5cff586af9757e0b66b7191bb692373e4,10.55463/hkjss.issn.1021-3619.64.29,"Determinants of New Condominium Prices near MRT Orange Line Stations: Case study of Estimating Housing Affordability in Bangkok, Thailand",2025,Hong Kong Journal of Social Sciences,Pornraht Pongprasert,"This research aims to analyze the factors influencing the pricing of condominium projects along the Mass Rapid Transit (MRT) Orange Line, an electric train expected to start operations in 2025. As the main heavy rail line connecting the Eastern Bangkok suburbs with the city’s New Central Business District (New CBD), the Orange Line has significant implications for urban development. To promote land development opportunities, Bangkok’s city plan has undergone changes along the Orange Line corridor, particularly on the Ramkhamhaeng Road, which is anticipated to drive up land prices.This study examines how condominium prices may fluctuate when various factors are considered, such as proximity to MRT stations, main roads, expressway access points, private facilities, operator reliability, and the cost of common areas. The research equips real estate developers with a comprehensive understanding of these determinants to guide project development and pricing strategies aligned with market conditions. Condominium buyers can leverage accurate pricing information to make informed decisions, while real estate investors can incorporate these insights into their investment strategies. Addition",3.0,71389394c4d5debd11bf6857ba2849b1991929a224a,10.3390/su13010113,The Urban Blight Costs in Taiwan,2020,Sustainability,Chich-Ping Hu; Tai-Shan Hu; P. Fan; Hai-Ping Lin,"Urban blight is not only an eyesore for city residents, but also a threat to health, psychological well-being, and safety. It not only represents substantial economic decline, but also spreads through urban space. As well as the loss of personal property value, urban blight also harms public interests in the public domain. This study finds that danger and age are the two main factors of urban blight. Ignoring these two factors causes housing prices to fall. The decline in population due to long-term economic stagnation and the exodus of residents and industries, coupled with the long-term decline in income and spending on maintenance of old houses, has led to major visual and physical economic blight. This investigation adopts the hedonic model to analyze the correspondence of house prices with urban blight, based on real estate prices and related township variables announced by the government in Taiwan in 2017, and applies the spatial regression model to investigate the direct and indirect effects of real estate prices. The following conclusions can be drawn from the analytical results. 1. The spatial lag model finds that urban blight has a spatial spillover effect. 2. The governm",3.0,https://www.mdpi.com/2071-1050/13/1/113/pdf?version=1608869833714https://openalex.org/W2001190078,10.1109/icmse.2006.314131,"Impacts of Land Supply Factors on Housing Price: An Hedonic Price Model on Chengdu, China",2006,,Zheng Li; Bing Yu,"The relationship between housing price and land price is one of most important issues in Mainland of China, which is concerned by developers, consumers and government. However, this issue is often discussed on the theoretical level. This paper suggests an alternative and meaningful model on testing the relationship between housing price and land supply factors. The study is based on land parcels' information and relevant housing developments information of Chengdu, the capital of Sicuan Province, from 1999 to 2004. This paper choose an basic angle to study the relationship between housing price and land factors that are included in parcel area, land lease mode, land price etc. The Hedonic price model is applied in this paper to measure the implicit price of different factors of land. The empirical results present that: (1) If other factors keep stable, the elasticity of land price to housing price is very small. This means that housing price is not impacted by land cost very much; (2) Land supply mode has very significant impact on housing price. Paper compares three kinds of mode. They are agreement supply (mode 1), ownership transfer mode (mode 2) and public auction (mode 3). Ave",3.0,715e7abd4cac2e48be9258309ca620790be22771fe9,10.20965/jaciii.2018.p0809,Hedonic Price Ripple Effect and Consumer Choice: Evidence from New Homes,2018,Journal of Advanced Computational Intelligence and Intelligent Informatics,Guang-Tong Gu,"This study uses the hedonic price model to examine the determinants of house prices. It employs kernel density to estimate the spatial weight matrix and conducts spatial econometrics and instrumental variables quantile regression analysis. Taking a new building in Shanghai city as an example, this micro-perspective study shows that hedonic prices of houses are derived from consumer hedonic preferences and their changes in terms of inertia and spatial ripple effects. However, there are large differences in the drivers of the same hedonic attribute across quantile degrees. With house prices gradually decreasing from the city center to the surrounding areas, the ripple effect is significant in determining residents’ preferred consumption characteristics and presents several inverted U-shaped and inverted U-shaped relationships. Residents’ preference for housing consumption is mainly reflected in the average area of the house, property fee, location of the administrative area, and so on. Regional real estate price changes are mainly reflected in hedonic house prices, and real consumer demand for housing is mainly derived from hedonic preference. Therefore, government regulation and con",3.0,https://doi.org/10.20965/jaciii.2018.p080971646f7725ea3bf9cd15d25ff88070bfd2b25833b52,10.3390/ijgi14110436,How Does Built Environment Influence Housing Prices in Large-Scale Areas? An Interpretable Machine Learning Method by Considering Multi-Dimensional Accessibility,2025,ISPRS Int. J. Geo Inf.,Ziyi Wang; Yu Wang; Xinyu Xia; Shaozhu Chen; Wei Jiang,"The housing prices are crucial to the sustainable development of the real estate market. Nowadays, few academic attempts have focused on the impact of multi-dimensional accessibility on housing prices in a large-scale area. This study utilized machine learning methods to extract indicators of the visual environment from street view images. The indicators were combined with multiple sources of spatiotemporal geographic big data, such as second-hand housing data and online map POIs, to quantify the factors of housing prices. Both the hedonic price model and random forest were constructed, with Shapley additive explanations applied to interpret the results. Our work took Shanghai as a case study, and the results indicate that the random forest exhibits superior performance compared to the hedonic price model. The location accessibility (e.g., distance to the CBD) is paramount, and functional accessibility (e.g., to subways and finance facilities) exhibits nonlinear thresholds. We further uncovered the characteristics of the nonlinear relationship between visual environmental factors and housing prices. Our findings can deepen the understanding of housing price variation in the spatial",3.0,https://www.mdpi.com/2220-9964/14/11/436/pdf71748eac7bf57c93dd9c75ad616d67bde640db7b527,10.1080/16184742.2025.2494829,A monetary valuation of hosting a sport mega-event via residential real estate markets in small host communities: evidence from post-event analysis,2025,European Sport Management Quarterly,Chan Hyeon Hur; Nicholas M. Watanabe,"ABSTRACT Research question This study explores the monetary value of non-market goods, such as hosting a sport mega-event, by analyzing housing prices in small host communities, particularly those influenced by the PyeongChang 2018 Olympics. The research anticipates that small communities might experience unique effects from social overhead capital, including new rail lines and sport facilities upgraded for the Games. Research methods The study analyzes apartment sales data before and after the Games. It employs Two-Way Fixed Effects (TWFE) regressions, grounded in the hedonic pricing (HP) model and propensity score matching (PSM), to estimate housing price changes in host regions and determine if these changes correlate with the Olympics. Geographic Information System (GIS) network analysis assesses realistic proximity effects, measuring driving time to sport facilities. Results and findings Results indicate the Games had no significant influence on housing prices in host communities during or immediately after the event. However, about a year later, an effect on prices emerged, suggesting a delayed influence. Although GIS analysis suggests potential influences within a 20-minute ",3.0,71800a2fd8a3af8f6e0e127c590fbea4879d95d7c78,10.25295/fsecon.895779,Analysis of Determinants of House Prices Using Hedonic Price Model: The Case of TR 71 Region,2021,,Arif İğdeli,"Bu arastirmanin amaci TR71 bolgesinde konut fiyatlarinin belirleyicilerini hedonik model yardimiyla analiz etmektir. Yari logaritmik form uzerine kurulan hedonik konut fiyat modelinin analizinde en kucuk kareler tahmincisi kullanilmistir. Analiz bulgusuna gore konutun genisligi, oda sayisi, konutun bulundugu kat, binanin kat sayisi ve banyo sayisi konut fiyatlarini pozitif yonde etkilerken, konutun bulundugu binanin yasi konut fiyatlarini negatif yonde etkilemektedir. Ayrica analiz bulgusunda konutun sahibi yerine emlakci tarafindan satilmasinin konut fiyatlari uzerindeki negatif yonlu etkisi gorulmektedir. Bununla birlikte analiz bulgulari Nigde sehir merkezi temel alindiginda konutun Aksaray, Kirsehir ve Nevsehir illerinde bulunmasinin konut fiyatlari uzerindeki pozitif yonlu etkisine isaret etmektedir. Analiz bulgulari konut fiyatlari uzerinde konutun fiziksel ozelliklerine gore mekânsal faktorlerin etkisinin daha belirgin oldugunu gostermektedir. Analiz bulgularinda konutun isitma sistemleri acisindan kombi, kalorifer, soba ve yerden isinma sisteminin konut fiyatlari uzerinde anlamli bir etkisine rastlanmamaktadir. Son olarak analiz bulgulari konutun site icerisinde yer almasin",3.0,https://dergipark.org.tr/en/download/article-file/16344407190d7a1f874f9358489f6f5882b5a4900f21774211,10.18070/erciyesiibd.1122568,SPATIAL HETEROGENEITY IN HOUSING MARKET: ANKARA METROPOLITAN AREA,2022,Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi,Tuğba Güneş; A. Apaydın,"Advanced statistical models have been widely used in real estate valuations for various purposes over the last fifty years, and hedonic approaches with their simple and easy interpretable features are still the most popular among these models. However, spatial heterogeneity and spatial autocorrelation are the two major features of the housing markets, and traditional regression cannot reflect these locational effects into the model sufficiently. This study employs a Geographically Weighted Regression (GWR) model to explore the spatial heterogeneity in the metropolitan area housing market in the city of Ankara. By applying a Gaussian kernel weighting function with adaptive bandwidth based on cross-validation approach on a house listing dataset, it is found that the GWR fit the data better than the traditional ordinary least squares regression which mostly ignore the spatial effects, and there is spatial heterogeneity in the housing market. Explanatory power of the GWR model and parameter estimations are non-stationary over the geographical area. The variations in the coefficients of the variables are depicted on the map and is supported with the spatial correlations between the hous",3.0,https://doi.org/10.18070/erciyesiibd.1122568720009443a37464c7bfc0c1892b4c485e939d19af7c,10.13060/23362839.2023.10.2.558,Testing Housing Price Drivers in Santiago de Chile: A Hedonic Price Approach,2023,Critical Housing Analysis,Francisco Vergara-Perucich,"Hedonic modelling is an empirical analysis technique that is widely used to review the housing market and unpack the main determinants of price. A correct determination of housing price drivers allows a weighted prediction of the value of each dwelling for sale or rent. This paper reviews the fundamental determinants of housing prices that have been published in the literature to see which ones have a better predictive fit for the case of the housing market in the city of Santiago, Chile. From a record of 456,000 property transactions, a dataset composed of 11 explanatory variables is elaborated. Through a semi-logarithmic regression, 4 variables that contribute to explaining the formation of housing prices in Santiago, Chile, are identified. The results indicate that the socioeconomic characterisation of urban areas where housing is traded, the price of copper on the London Metal Exchange, the mortgage interest rate, the age of residential buildings are the main drivers for the main drivers of prices in Santiago. Given the crisis of access to housing in Chile, the article provides relevant information for decision-makers in housing policy.",3.0,https://www.housing-critical.com/data/USR_057_DEFAULT/04_Testing_Housing_Price_Drivers_in_Santiago_de_Chile_A_Hedonic_Price_Approach.pdf7214893a26c61882e42b9e52026edcc8d0f508a9e8b,10.3390/buildings14030728,"Hedonic Approach to Vertical Residential Rentals in the Brazilian Amazon: The Case of Belém, Pará",2024,Buildings,Yan Gabriel Pereira Magalhães de Freitas; Frederico Guilherme Pamplona Moreira; Alexander Hierro Ferreira de Souza; Victor Igor Monteiro dos Santos,"This study set out to identify and analyze the factors that influence the formation of rental prices for residential apartments in the city of Belém. The approach adopted was based on the hedonic price theory, which considers that the rental price of an apartment reflects the implicit prices of its attributes—structural, locational, and neighborhood quality. The sample used consisted of 259 observations, corresponding to the rental advertisements of the representative apartments in each building. The ordinary least squares (OLS), spatial lag model (SLM), and geographically weighted regression (GWR) techniques were used in the statistical analysis in this study. The results of the OLS model showed statistical significance between the attributes analyzed and the rental price of the apartments. In turn, the SLM indicated that the structural attributes have an impact on the rental prices of neighboring apartments, configuring a contagion effect in the real estate market. The GWR model showed that there was no spatial heterogeneity in the effects of the determinants on apartment rental prices throughout the sample.",3.0,https://www.mdpi.com/2075-5309/14/3/728/pdf?version=170986562672265a1056b073b3f3445fae0a823c7193e36c8db97,10.22158/wjssr.v5n1p89,"Temporal and Spatial Effects of Urban Center on Housing Price — A Case Study on Hangzhou, China",2018,,Luhong Chu; Hai-Zhen Wen,"With the acceleration of urbanization and the rapid development of real estate, people pay more and more attention to the change of urban housing prices. Over time, the change of city center will inevitably affect the urban land or housing prices, which is reflected in the spatial distribution of urban land or housing prices. Therefore, this article attempts to explore the impact of urban center on housing prices from the perspective of multi-center city and study separately from two aspects of time and space. This paper takes the six main urban districts of Hangzhou as the research scope. At the time level, we select the residential data from 2007 to 2015 to construct models respectively based on the hedonic price theory and find that the influence of different urban center on housing price shows a certain change with time. On the spatial level, this paper choses the residential data in 2012 to construct geographic weighted regression model and the result shows that the impact of three centers on housing prices shows a certain degree of spatial heterogeneity.",3.0,http://www.scholink.org/ojs/index.php/wjssr/article/download/1269/1429723bd743a3f41d84dd0f683bba87dd78264f1d19462,10.1016/j.jenvman.2023.118064,"Capitalisation of multiple ecosystems on property prices in Auckland, New Zealand.",2023,Journal of Environmental Management,M. Fernandez,"Ecosystems and their associated services have become essential in policymaking as they often have implications for the welfare of those who live nearby. Coupled with the shift toward integrating green infrastructure, ecosystem services, and nature-based solutions in urban and environmental planning, ecosystems may capitalise on property prices. But a potential phenomenon in applications of hedonic prices models is the offsetting between amenities and disamenities values, which may result in insignificant marginal effects. Some strategies to mitigate this phenomenon involve introducing a greater categorisation of open spaces and housing submarkets typology. Hence, this paper explores the capitalisation patterns of 14 terrestrial and aquatic ecosystems across the housing market segments of Auckland, New Zealand's largest city. We used a dataset of 274 thousand sales transactions between January 2011 and December 2019. Models are estimated via OLS and unconditional quantile regressions (UQR) to account for heterogeneity, outliers and heavy-tailed distributions. UQR produce more accurate estimates of the implicit prices and lead to more effective policy recommendations. We find multipl",3.0,7242792b4c943809eb914728ff2391864089ea9f685,10.11118/actaun201866040991,Determinants of Real Estate Prices in the Statutory City of Brno,2018,Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis,Vlastimil Reichel; Petr Zimcik,"The real estate market demand for both houses and flats has been growing recently. This trend is one of the factors, which are able to influence the price of real estate. Our paper introduces determinants of housing price and their influence on actual real estate prices in the statutory city of Brno. The aim of this paper is to present key determinants of house price and find the hedonic price model, which describes, how determinants affect house price best. Realized prices were analyzed for housing units located in different districts of Brno. Key determinants in this research are a year of sale, an area of flat in square meters, number of rooms, location in districts of Brno, type of masonry and reconstruction. The dataset covers the time period between years 2012 and 2015. Hedonic price model is estimated by the method of ordinary least square. Besides main aim, four assumptions were verified, which should determine the influence on the price of individual determinants in the statutory city of Brno.",3.0,http://acta.mendelu.cz/doi/10.11118/actaun201866040991.pdf725f3e8139a9bae31412c774a650463040f4089489c,10.48128/pisg/2022-67.4-01,"A study of metro’s influence on the primary housing market in Warsaw, Poland",2023,Prace i Studia Geograficzne,Jakub Kuśmierz; M. Dąbski; Magdalena Fuhrmann,"Residential real estate prices vary significantly, being susceptible to numerous components. One of the most contributing factors is thought to be the proximity of an underground train (metro) station. Classically, the relationship between housing prices and distance to a metro station is measured by a hedonic model. This paper presents a new method to study such a relationship, and it is a new composite index - Metro Station Proximity Effect Estimator (MSPEE), which allows looking at differences between not only metro stations but also the city districts. The MSPEE index was calculated as a mean of a set of sub-indicators, assembled as variables determining the final value of the composite indicator. Through the MSPEE index as well as more traditional methods, the paper suggests and illustrates a generally strong negative correlation between the proximity of Metro and apartment prices. Moreover, the study lists and describes exceptions to the trend around Warsaw.",3.0,https://wgsr.uw.edu.pl/pisg/wp-content/uploads/2023/02/PiSG_67.4-01.pdf72621bee0327e4c09063343cc6edfc40534e6b3b2ad,10.1080/17512549.2024.2411263,An investigation of the impact of energy performance certificate (EPC) ratings on residential property prices in Oxfordshire: a hedonic study,2024,Advances in Building Energy Research,H. Perez; O. Amoudi; F. Famuyiwa; J. Tah,"ABSTRACT This paper investigates whether energy performance ratings measured by Energy Efficiency Certificates (EPCs) affect the sales prices of residential properties in Oxfordshire, UK. The study makes use of 186,913 sales transactions that took place between 1995 and 2023. Using a hedonic regression estimation, a nonlinear pattern between energy efficiency levels and the sales prices of dwellings, are observed. The results also show that there is evidence of a significant positive relationship between EPC ratings and detached, semi-detached, terraced houses and flats. In the second part of this study, we examine the effects of age, county and type of dwelling on price premiums. To the best of the authors’ knowledge, this study is the only study, using the most comprehensive literature; and the largest, most up to date available data in analysing the Oxfordshire real-estate market, in terms of energy efficiency and price premiums.",3.0,https://doi.org/10.1080/17512549.2024.24112637271a982c52a3a695b67a2c28687558f3b538f90e8d,10.3989/ic.68059,La influencia de las características de las viviendas de segunda mano en sus precios de venta: evidencias en el mercado alicantino,2020,,V. Pérez-Sánchez; R. Mora-García; J. C. Pérez-Sánchez; M. F. Céspedes-López,"This paper estimates the impact that the characteristics of second-hand homes in Alicante have on the asking price. In order to carry out this research, information has been used from real estate portals, which offer information such as the characteristics of dwellings, the building, their geographical location and asking prices. The analysis is developed in the province of Alicante geographic context. A hedonic regression is estimated in which the dwellings characteristics and location act as independent variables, and the asking price as a dependent value. The results show significant differences in the dwelling asking price depending on its characteristics and location, suggesting higher prices for dwellings: located in the coastal regions of the north of Alicante, that have a swimming pool, garden or parking space. However, dwellings with lower asking prices are: those located in southern and inland regions of the province.",3.0,http://informesdelaconstruccion.revistas.csic.es/index.php/informesdelaconstruccion/article/download/6009/730372863a890a7132ee313630fc8340765e1e2fab9adb4,10.3390/jrfm13050105,Estimating Bargaining Power in Real Estate Pricing Models: Conceptual and Empirical Issues,2020,Journal of Risk and Financial Management,S. B. Caudill; F. Mixon,"The relative bargaining power of the buyer and seller is a key feature of real estate pricing models. Classic real estate studies have sought to address bargaining effects in hedonic regression models. Prior research proposes a procedure to estimate bargaining effects in hedonic regression models that depends critically on a substitution to eliminate omitted variables bias. This study shows that the proposed solution that is often cited in the real estate economics literature does not solve the omitted variables problem given that both models are merely different parameterizations of the same model, and thus produces biased estimates of bargaining power when certain property characteristics are omitted. A classic hedonic regression model of real estate prices using Corsican apartment data supports our contention, even when the assumption of bargaining power symmetry is relaxed.",3.0,https://www.mdpi.com/1911-8074/13/5/105/pdf?version=1590549120729https://openalex.org/W1863902336,10.13128/aestimum-3274,Mixed environmental quality indexes for hedonic housing price models: an alternative with area-to-point kriging with external drift,2009,Aestimum,José María Bové Montero; Gema Fernández‐Avilés,"(a) When environmental variables are included in hedonic house price models, the locations where a property transaction has been taken place are more than those equipped with an environmental monitoring station. (b) When environmental variables are numerous, an environmental quality index (EQI) is needed. The solution is to interpolate (kriging) environmental variables and, subsequently, elaborate an EQI, because of the lower prediction variance. (c) Environmental informations can be both objective and subjective. The potential mismatch between the spatial support for both the objective informations and the subjective ones is solved by using a kriging strategy (area-to-point kriging) that forces scarce objective environmental informations to be coherent with dense subjective ones. These options for elaborating EQIs are compared in Madrid City (Spain).",3.0,https://oaj.fupress.net/index.php/ceset/article/download/5561/55617300666574c1bdbecf9c16ca5e04db0681e571940f1,10.1108/jerer-11-2024-0087,Reflections on hedonic price modeling,2025,Journal of European Real Estate Research,Steven C. Bourassa; Martin Hoesli; Michael Mayer; Nicola Stalder,"PurposeThis paper provides a critical history of residential hedonic price modeling, highlighting key issues and advances. It is based on the keynote address presented by the first author at the European Real Estate Society Annual Conference in Sopot (Gdańsk), Poland, in June 2024.Design/methodology/approachThe core of the paper is a high-level review of the methodological literature, focusing on three issues: model specification, multicollinearity and functional form. This review is framed by an early example of hedonic price modeling and a current application. These examples demonstrate key issues and advances in hedonic price modeling.FindingsHedonic price research has expanded dramatically with the advent of personal computing. Increased availability of data has enabled better model specification. At the same time, the development of interpretable machine learning techniques has allowed much more flexible modeling of functional form. However, multicollinearity continues to be, by definition, an intractable problem.Originality/valueThis paper presents a review of residential hedonic price modeling intended to provide researchers with a useful high-level perspective on the topic.",3.0,731b23321cc4ed934fd7892a99edc64415a9b2d4d98,10.1080/03610918.2019.1704418,A non–stationary non–Gaussian hedonic spatial model for house selling prices,2019,Communications in statistics. Simulation and computation,V. D. de Oliveira; M. Ecker,"Abstract This work proposes a hedonic random field model to describe house selling prices from 2000 to 2005 in Cedar Falls, Iowa. This real estate market presents two distinctive features that are not well described by traditional stationary Gaussian random field models: (a) the city has, on its periphery, a hoglot that acts as an externality, affecting both the mean and variance of the selling prices, and (b) the distribution of house selling prices display heavy tails, even after the distance to the hoglot and house–specific covariates are accounted for in the mean structure of the model. A non–stationary and non–Gaussian random field model is constructed by multiplying two independent Gaussian random fields tailored to model the probabilistic features displayed by the Cedar Falls dataset. A Markov chain Monte Carlo algorithm that uses data augmentation is employed to fit the proposed model.",3.0,732https://openalex.org/W2020614446,10.1109/icmss.2010.5577066,Hedonic Price Study on Urban Housing: The Case of Shijiazhuang City,2010,International Conference on Management and Service Science (MASS),Zhao Yan; Xiaojun Liu,"Housing is a kind of heterogeneous product; every housing unit includes different characteristic aggregation. Hedonic price theory is an effective method to study the quantitative relation between housing characteristic and price. This paper applies hedonic price theory to the housing market in Shijiazhuang. After collecting and trimming 2075 housing price and characteristic samples in Shijiazhuang city, the paper selects housing structure, location and neighborhood characteristics as explanatory variables, and implements OLS regression to estimate the parameters of the model, then analysises main characteristics that affect residential housing price and attempts to explain the quantitative relationship between housing price and housing characteristics. Based on that, we establish the hedonic model of Shijiazhuang housing market and validate the applicability of hedonic price model.",3.0,7339ce8cb298438ae064be6a168a446ca4827b9cfb4,10.1007/978-3-319-11469-9_5,Hedonic House Price Modeling Based on Multilevel Structured Additive Regression,2015,,Alexander Razen; Wolfgang A. Brunauer; Nadja Klein; S. Lang; Nikolaus Umlauf,,3.0,7343bbf88ea5271189e3329337f57932674d7aa341e,10.59490/abe.2017.4.1747,The Spatial Dimension of House Prices,2017,Architecture and the Built Environment,Yun-Long Gong,"The economic reform in China, launched in the late 1970s, gradually promotes the free mobility of capital and labour between rural and urban areas, and between cities. The following housing market reform in the late 1990s thoroughly terminates the socialist allocation of housing and introduces market forces into the housing sector. Such institutional shifts have profound effects on the evolution of the Chinese interurban housing market. Yet, little is known about the spatial behaviour of house prices across cities in the post-reform era. How do the housing markets of different cities organise across space? What is the relationship between the house price dynamics of different cities? To answer these questions, this research performs economic and econometric analysis of the spatial dimension of the Chinese interurban housing market. In addition, this research also concerns the construction of a reliable house price index in the presence of spatial heterogeneity and dependence in the urban housing market of China. A reliable house price index is essential to the analysis of house price dynamic behaviour. However, owing to the data problem, this part is conducted based on the housing mar",2.0,https://journals.open.tudelft.nl/abe/article/download/1747/177173515d1d5c8aefe2b6d20676707fa88061b380c1f1a,10.1108/ijhma-09-2025-0213,Understanding the determinants of house prices in Moroccan cities,2025,International Journal of Housing Markets and Analysis,Onur Ozsoy; C. Ozsoy; C. Ozsoy,"736 737 This study aims to analyze the main factors affecting house prices in various major Moroccan cities. This study uses a hedonic pricing model with robust standard errors to figure out the relationship between the structural, amenity and locational characteristics and house prices. This study draws on data from Avito.ma, a leading Moroccan online real estate platform, filling a major gap in understanding housing markets across Morocco and the wider MENA region while providing valuable insights for policymakers, developers and investors.738 739 740 741 This study uses an Ordinary Least Squares model with robust standard errors. The dependent variable is the natural logarithm of housing prices. The analysis is based on 1,088 verified housing listings collected from Avito.ma between February and May 2025. The independent variables consist of property size, floor level and a range of amenities, including parking, air conditioning, sports facilities and security. To capture regional differences, city fixed effects were added to the model. This approach makes it possible to eliminate local price dynamics and account for unobserved spatial variations. A Chow-type test was conducted to establish",2.0,742ac5df38ff1193e29bc1ed35d6ad8cf4f1c037be5,10.5821/ctv.7988,Rentabilidad inmobiliaria & calidad de zona,2014,"9° Congresso Città e Territorio Virtuale, Roma, 2, 3 e 4 ottobre 2013",Jesús Quintana; Josep Roca; A. Ojeda,"El presente trabajo tiene el propósito de estimar la influencia de los elementos de calidad de 743zona, en la rentabilidad inmobiliaria; entendiendo por zona, al espacio urbano diferenciado 744dentro de la ciudad denominado barrio; y por calidad de zona, aquellos elementos por los 745cuales los compradores de vivienda están dispuestos a incrementar su disposición a pagar. La 746tasa de rentabilidad inmobiliaria, como la capacidad del bien inmueble para generar renta; la 747medida de esta capacidad se estima a partir del Método de Capitalización Directa, el cual se 748fundamenta en el conocimiento del valor del inmueble y los ingresos periódicos que genera. La 749calidad de zona, se estimada con base en indicadores relativos a: la accesibilidad, el entorno 750urbano, la edificación y la jerarquía social. Esta calidad se integra con la maximización de la 751presencia de las características de calidad en la zona, bajo el supuesto de igualdad de 752importancia, para lo cual se utiliza un indicador sintético que contempla las variaciones de los 753elementos observados. El indicador sintético de calidad de zona, parte de la recolección de 754información asociada a la calidad de barrio, donde la recogida de esta",2.0,https://upcommons.upc.edu/bitstream/2099/16467/1/1503_1526%20POLIT%20URB%20PROC%20TERRIT%20CIUDAD.pdf7555d2222f07c45ca2157e7255f3655020551f0f7ef,10.1108/jerer-02-2021-0009,"Location, location, location!*: a quality-adjusted rent index for the Oslo office market",2021,Journal of European Real Estate Research,A. K. Anundsen; Christian Bjørland; Marius Hagen,"PurposeCommonly used rent indices are based on average developments or expert opinions. Such indices often suffer from compositional biases or low data coverage. The purpose of this paper is to overcome these challenges using the authors' approach.Design/methodology/approachThe authors construct a quality-adjusted rent index for the office market in Oslo using detailed data from 14,171 rental contracts.FindingsThe authors show that compositional biases can have a large impact on rental price developments. By adding building-fixed effects to a standard hedonic regression model, the authors show that the explanatory power increases considerably. Furthermore, indices excluding location-specific information, or which include less granular location controls than at the building level, portray quite a different picture of rent developments than indices that do take this into account. The authors also exploit information on contract signature date and find that a more timely detection of turning points can be achieved by using the signature date instead of the more typically used start date of the lease.Research limitations/implicationsThe study is confined to Norwegian data, and an avenu",2.0,756a7a83b631f85316bae926a6c965b325fb26c01c4,10.4102/jef.v12i1.476,A gamma generalised linear model as an alternative to log linear real estate price functions,2019,,Dane Bax; T. Zewotir; D. North,"Orientation: Residential property markets play an important role in economies, informing policy development and decision-making. However, measuring quality-adjusted growth is difficult because of the heterogeneity of properties. Hedonic regression is frequently used in real estate econometric studies as a quality-adjusted technique to estimate residential property prices for the development of price indices. Log linear models are typically used to derive these hedonic price functions. Research purpose: This article develops hedonic pricing functions using generalised linear models for South African residential property listings over a 5-year period. Motivation for the study: A parametric alternative to the log linear model is investigated to address the limited studies conducted in South Africa. An important feature of this study is the inclusion of different property types and the geographic scope. Research approach/design and method: The data set consisted of 415 200 residential properties from all over South Africa. The data spanned a period from January 2013 to August 2017. Several generalised linear models were developed and compared. Main findings: The gamma generalised linea",2.0,https://jefjournal.org.za/index.php/jef/article/download/476/8077578a99113b012c7dc5288863734eba9456a85fd906,10.3389/frsc.2025.1511761,"Investigating the impact of property characteristics, cost of living, and environmental factors on rental prices in Baidoa’s climate-affected real estate market: a hybrid approach using hedonic regression and neural networks",2025,Frontiers in Sustainable Cities,Mohamed Ibrahim Nor; Buba Audu; A. Mohamed,"Understanding the determinants of residential rental prices is crucial for policymakers, investors, and real estate practitioners. This study investigates the influence of property value, property characteristics, cost of living, political stability, essential services, and environmental factors on rental prices in Baidoa city. Additionally, the research compares different modeling approaches to enhance rental price forecasting.A dual-method approach was employed, integrating hedonic regression analysis and artificial neural network (ANN) models to analyze rental values. The dataset includes key variables such as the number of bedrooms, essential services, cost of living, and environmental conditions. The predictive performance and interpretability of both models were assessed to determine their effectiveness in rental price estimation.The findings reveal that rental prices are significantly influenced by the number of bedrooms, essential services (e.g., electricity), cost of living, and environmental conditions. However, political stability and displacement did not exhibit significant effects. While hedonic regression provided clear, interpretable insights into direct predictors, ",2.0,https://doi.org/10.3389/frsc.2025.1511761758739f198de19a4f1181fc95d47e57a9488a23580b,10.1108/jerer-11-2021-0051,Identifying how the time on the market affects the selling price: a case study of residential properties in Paphos (Cyprus) urban area,2022,Journal of European Real Estate Research,Philippos Nikiforou; T. Dimopoulos; P. Sivitanides,"PurposeThe purpose of this study is to investigate how the degree of overpricing (DOP) and other variables are associated with the time on the market (TOM) and the final selling price (SP) for residential properties in the Paphos urban area.Design/methodology/approachThe hedonic pricing model was used to examine the association of TOM and SP with various factors. The association of the independent variable of DOP and other independent variables with the two dependent variables of TOM and SP were investigated via ordinary least squares (OLS) regression models. In the first set of models the dependent variable was TOM and in the second set of models the dependent variable was SP. A sample of N = 538 completed transactions from Q1 2008 to Q2 2019 was used to estimate the optimum DOP that a seller must apply on the current market value of a property in order to achieve highest SP price in the shortest TOM.FindingsThe results of this study also suggest that the degree of overpricing in thin and less transparent markets is higher than that in transparent markets with high property transaction volumes. In mature markets like the USA and the UK where the actual sold prices are published, t",2.0,https://www.emerald.com/insight/content/doi/10.1108/JERER-11-2021-0051/full/pdf?title=identifying-how-the-time-on-the-market-affects-the-selling-price-a-case-study-of-residential-properties-in-paphos-cyprus-urban-area7593b820e938ca4b455736f08f285e1b5bb43f7674a,10.11648/j.ijber.20241303.11,Determinants of Residential Real Estate Property Prices in Ethiopia: The Case of Bahir Dar City,2024,International Journal of Business and Economics Research,Tamirat Mekuria; Seid Yimam; Yohans Negashi,"The Ethiopian real estate industry has grown in the previous two decades, especially in the capital city of the country and regional capitals, including Bahir Dar. Real estate prices have doubled and even tripled in a few years because of different factors. Thus, the purpose of this study is to analyse the factors affecting residential real estate prices in Ethiopia, particularly in Bahir Dar City. For this purpose, the study used both purposive and stratified random sampling techniques. Descriptive and inferential statistics were used to analyze the data, and the ordinary least squares method was used to identify the factors that influence residential real estate prices. The hedonic regression model result reveals that R<sup>2</sup> statistics (0.880) indicate that 88% of the variation in residential real estate prices can be explained by variation in the independent variables. Hedonic regression model results revealed that plot size, floor area, number of rooms, age of the house, external wall finishing material, ceiling finishing material, the direction of the house, distance of the property from the main road, and involvement of brokers in the transaction process, were major mi",2.0,https://article.sciencepg.com/pdf/j.ijber.20241303.11760549587ac03dcb9d550c7fe68da027277dd876b12,10.1007/s10479-025-06889-x,A divide-and-conquer approach for spatio-temporal analysis of large house price data from Greater London,2024,Annals of Operations Research,Kapil Gupta; Soudeep Deb,"Recent statistical research in real estate markets focuses on the spatio-temporal dynamics of house prices. Bayesian methods are common but often slow for a large dataset in that regard. We propose a divide-and-conquer (D&C) approach, partitioning the data into subsets and applying Gaussian process models in parallel. The results are combined using the Wasserstein barycenter technique to obtain global parameters. This method allows for multiple observations per spatial and time unit. As a real-life application, we analyze house price data of more than 0.6 million transactions from 983 middle layer super output areas in London over a period of eight years. A couple of our major findings is that different types of property command different levels of premiums across the region; and that lower carbon emissions correlate positively with house prices, though the magnitude of this premium has diminished over recent years. Overall, our proposed model offers a better fit than competing approaches, attaining the highest \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgr",2.0,https://arxiv.org/pdf/2407.159057613b1d616e363428d106cc01163013d33b70a53708,10.1108/jerer-09-2021-0048,Does size matter? Is there an optimal size for tenant–owner associations?,2022,Journal of European Real Estate Research,Peter Karpestam; Peter Palm,"PurposeThe authors investigate how prices of condominiums are affected by the size of the tenant-owner associations that they belong to.Design/methodology/approachThe authors use data of sold apartments in the Swedish municipality Malmö 2013–2018 and estimate hedonic price regressions. The authors also perform semi-structured interviews with three senior professionals in real estate companies.FindingsThe authors find significantly negative relationships between the prices of condominiums and the size of tenant-owner associations. Also, regression results indicate that associations should be no smaller than 6–10 apartments. The interviews support that associations should not be too small or too big. The lower and upper limit was suggested by the respondents to 40–50 and 80–150 apartments, respectively. In these ranges, economies of scale can be achieved, and residents will not lose the sense of community and responsibility.Research limitations/implicationsThe authors do not prove causality. Smaller associations may have relatively exclusive common amenities, about which we lack data. The same relationships may not exist in different market conditions.Originality/valueThe authors are",2.0,https://www.emerald.com/insight/content/doi/10.1108/JERER-09-2021-0048/full/pdf?title=does-size-matter-is-there-an-optimal-size-for-tenant-owner-associations7627f206890031d1d54ba82515e526e51ef8c34c412,10.17713/ajs.v54i2.1904,A Parsimonious Hedonic Distributional Regression Model for Large Data with Heterogeneous Covariate Effects,2025,Austrian Journal of Statistics,Julian Granna; Wolfgang A. Brunauer; Stefan Lang; Nikolaus Umlauf,"Modeling real estate prices in the context of hedonic models often involves fitting a Generalized Additive Model, where only the mean of a (lognormal) distribution is regressed on a set of variables without taking other parameters of the distribution into account. Thus far, the application of regression models that model the full conditional distribution of the prices, has been infeasible for large data sets, even on powerful machines. Moreover, accounting for heterogeneity of effects regarding time and locale, is often achieved by naive stratification of the data rather than on a model basis. A novel batchwise backfitting algorithm is applied in the context of a structured additive distributional regression model, which enables us to efficiently model all distributional parameters of the price distribution. Using a large German dataset of apartment asking prices with over one million observations, we employ a model-based clustering algorithm to capture the heterogeneity of covariate effects on the parameters with respect to dwelling locale. We thus identify clusters that are homogeneous with respect to the influence of dwelling locale on price. A boosting type algorithm of the bat",2.0,https://www.ajs.or.at/index.php/ajs/article/download/1904/869763568c30e468c5223b6ac2efcd49c1c392f1a241ae,10.3390/land14051099,The Economic Performance of Urban Sponge Parks Uncovered by an Integrated Evaluation Approach,2025,Land,Xiao Peng; Shipeng Wen,"Climate change and extreme rainfall events pose great pressures on a city’s resilience to flooding and waterlogging. Designed as a kind of green infrastructure to manage stormwater, urban sponge parks (USPs) in China have been demonstrated to have ecological and societal benefits, while their landscape economic values lack evaluation. Taking the real-estate choices surrounding six USPs in China as an example, an evaluation framework integrating text mining with housing introduction documents and hedonic price model (HPM) regression with housing prices was constructed to combine the stated preferences and revealed preferences of citizens when purchasing properties. The main findings include the following: (1) USPs do contribute to property appreciation, especially in newer urban areas, although they are not as strong as location and property characteristic factors; (2) the extent of the influence of USPs on houses decreases as the distance increases, with a maximum radius of 3 km; (3) a USP’s effects vary according to the urban and environmental context, as HPM with GWR (R2 ranges from 0.203 to 0.679) outperforms the OLS method (R2 ranges from 0.149 to 0.491), which evokes the need ",2.0,https://www.mdpi.com/2073-445X/14/5/1099/pdf?version=17475660527640e8221fad5dffd447b52c9be164621765eb67679,10.1108/jerer-02-2025-0033,From peaks to prices: the economic impact of natural amenities on alpine real estate values,2025,Journal of European Real Estate Research,Carolina Bonardi Pellizzari; Luisa Eusse-Villa; C. Franceschinis; T. Tempesta; Mara Thiene; D. Vecchiato,"765 766 This study aims to analyse the effects of environmental and climate (dis)amenities on house prices in the Italian Alps.767 768 769 770 Drawing on a dataset containing 447 sales contracts, this research adopted two modelling approaches: the classical hedonic model, estimated via ordinary least squares and a spatial model. Combining hedonic models with spatial models offers insights into studying property prices in alpine areas by capturing spatial dependencies of neighbouring areas, thus avoiding biased estimates and improving model accuracy.771 772 773 774 We show that higher winter temperatures significantly decrease property prices, reflecting preferences for higher altitudes with reliable winter sports conditions. Increased forest cover also negatively impacts prices, suggesting a preference for traditional alpine landscapes with panoramic views. Energy-efficient dwellings, however, command higher prices, indicating their value in the market.775 776 777 778 We contribute to the literature by (1) exploring the relationship between house prices and natural amenities in the European Alps; (2) using transaction data instead of property listings in Italy to provide more accurate estimates and (3) accoun",2.0,https://doi.org/10.1108/jerer-02-2025-003377912092f283369285b82ea77ca6ce1b199b74a5826,10.47836/pjssh.32.4.13,Swiftlet Farming Industry—A White Gold in the Malaysian Housing Market?,2024,Pertanika Journal of Social Sciences and Humanities,N. H. Adi Maimun; Yeong Ka Choon,"The swiftlet farming industry is fast-growing and contributes to Malaysia’s economic growth. Nonetheless, dirty and noisy surroundings caused by bird droppings and audio systems are unattractive and may adversely impact the housing market. Hence, this study seeks to ascertain the price impacts of the swiftlet farming industry. The first objective defines the hedonic model by reviewing its definition, theoretical framework, methodological process, and house price applications. The second objective explores factors influencing house prices, including the animal farming industry, through a literature review. The third objective evaluates the impact of the swiftlet farming industry on house prices. Ten-year house transaction data and spatial data provided by the Valuation and Property Services Department and Municipal District of Bentong are used to construct the Hedonic model. The result is evaluated based on its logical, statistical and predictive performance. The study found that swiftlet farming in Bentong has a negative impact on house prices, with an inverse price impact that increases with distance from the farming area. Buyers are reluctant to pay for houses near farming due to",2.0,http://www.pertanika.upm.edu.my/resources/files/Pertanika PAPERS/JSSH Vol. 32 (4) Dec. 2024/13 JSSH-8986-2023.pdf7806902792e014ff34816d6a002095db91af18cc0ab,10.6008/cbpc2179-6858.2020.006.0008,"Urban green areas and real estate prices in Curitiba, Brazil",2020,,Alessandro Panasolo; F. Galvão; H. Higachi; E. D. de Oliveira; Fernando C. De Oliveira; Carlos Wroblewski; T. Gadda; C. Balbinot,"We attempted to identify to which extent the implicit ecosystem service values of urban green areas impact real estate values in the city of Curitiba, Brazil. The study is based on spatial econometrics techniques and hedonic price theory applied to 43 urban green areas, highlighting three units: the Airumã Private Natural Heritage Reserve, the Teresa Urban Ecological Station, and the President Getulio Vargas Refinery. Information was obtained on the structural characteristics of more than 5,300 apartments and houses. The results of exploratory spatial data analysis (ESDA) and estimates from hedonic regression model parameters show that the presence of urban green areas contribute to the final property prices. The effects of proximity to urban green areas on the price of urban residential property are not homogeneous and stationary throughout urban spaces and can generate distinct spatial clusters of real estate prices: high-high and low-low. The used methodology proved to be efficient to assess the value of urban green areas with regard to the use of information, processing, data analysis, and results generated. Furthermore, it measured the impact of these areas on property prices ",2.0,http://www.sustenere.co/index.php/rica/article/download/CBPC2179-6858.2020.006.0008/2279781224c36dfebe2a43e9622127820f9c95208d028fa,10.52324/001c.8019,Searching for Isard’s Regional Essence,2017,,Douglas P. Woodward,"At the inception of the Southern Regional Science Association in the early 1960s, Walter Isard maintained that areal regions are fundamental units of observation and analysis. To this day, understanding the special significance of regions motivates much of our empirical research. In my address, I argue that regional fixed effects estimates from regression analysis can help us comprehend the distinctive character of areal units. This paper offers two examples from my research. First, I present the results of a regression model that explains regional knowledge spillovers in U.S. counties. Santa Clara County (the Silicon Valley) has by far the largest fixed effect estimate of any U.S. county. Overall, the county level fixed effects for knowledge spillovers follow a pattern of rapid exponential decay. Next, I inspect neighborhood fixed effects taken from a hedonic housing price model of the Charleston, South Carolina region. The results suggest a clear preference for coastal proximity as reflected in housing prices. For neighborhoods away from the coast, the fixed effects estimates exhibit a steep decline toward zero. Like the Silicon Valley’s regional advantage in knowledge, beachfron",2.0,https://doi.org/10.52324/001c.8019782cd14452210a9587708ebe096b26fdf0b86a75455,10.3390/su16093874,Impact of New Energy Vehicle Charging Point Subsidy Policy on Subway Demand: Evidence from Beijing’s Real Estate Market,2024,Sustainability,Yilin Bi; Jiangwei Liu; Zhu Liu; Suhao Wei,"New energy vehicles (NEVs) offer a sustainable private transportation alternative. Charging points are the source of power for NEVs; thus, their construction can significantly lower the costs associated with their use, thereby encouraging their adoption. This could potentially impact the subway demand, which is reflected by the relationship between housing prices and subway proximity in this paper, leading to a decrease in the premium for properties near subway stations. Utilizing a comprehensive data set of 599,916 housing transactions in Beijing and a difference-in-differences approach based on the hedonic price model, we found that China’s NEV charging point subsidy policy significantly decreases the subway premium of housing prices and mitigates housing price disparities. Furthermore, we explored the spatial heterogeneity of this impact, finding that the policy has less influence on residents living near the city center. Our findings indicate that the policy has resulted in a considerable decrease in the subway premium, ranging from ¥19,217 to ¥55,936 ($2745 to $7991) per transaction, which is equivalent to the annual income for an average individual at the time of the policy. ",2.0,https://doi.org/10.3390/su1609387478384a6e8ef31bf481e52cb738679f636c9a2fcc69f,10.35762/aer.2016.38.3.1,Loss of Value in House Properties due to Air Pollution in Map Ta Phut Industrial Area of Thailand,2016,,Nararuk Boonyanam,"Air pollution in the Map Ta Phut Industrial Estate in Thailand, has caused increasing risk of death, injury and health problems for local residents. Existing control measures are ineffective due to weak law enforcement. Although the problem has drawn a lot of attention, the monetary value of the impacts of air pollution in Map Ta Phut is not known. The objective of this paper was to estimate the economic cost of air pollution damage in Map Ta Phut using the Hedonic Pricing Method, with 192 house samples. The results showed that the marginal willingness to pay (MWTP) for a one unit reduction of AQI level was THB 2,815 or around USD 80, or each unit increase in air pollution would result in an estimated loss of THB 2,815 or around USD 80 in house price. The total value of losses to housing from one unit of air pollution in Map Ta Phut which is comprise of 38 communities was THB 119.3 million (about USD 3.4 million). Detection of the loss of value has implications for local residents, housing development investors, factories, and government and environmental institutions to manage air pollution as their top priority as well as to evaluate the efficiency of existing measures and budget",2.0,https://www.tci-thaijo.org/index.php/aer/article/download/69142/56253784f39f30c9ffb95cc4f228cb1c0702c1b497d41175,10.46923/ijets.v1i1.13,"The Impact Of Prison Displacement On Apartment Sale Price (A Case Study For Yeongdengpo Old Prison, Seoul)",2019,"International Journal of Engineering, Technology and Natural Sciences",Chul Sohn; Jeki Trimarstuti,"Locally unwanted land uses (LULUs) impact differently over time. Prison is one of the LULUs that may influence nearby real estate prices. Yeongdengpo Old Prison is located at the center of Seoul, the capital city of South Korea. After the fast urbanization of Seoul, nowadays that area is covered by apartments with more than 10 stories. Therefore, city planners of Seoul designed a new prison location outside the Seoul city. We assessed the apartment prices before the rumor of prison relocation, during the rumor stage, after the public announcement and after the relocation happens. We used average price of apartment sale in 2000, constant price of apartment sales from 2006 to 2012 and the nominal price and transaction prices of apartments from April 2013 to June 2013 for GIS analysis to determine distance effect of the prison within 500m. We used hedonic regression model to test the effects of area, age, unit, and distance from prison of apartments to its prices. The effect of relocation was not big enough compare to the first announcement of the relocation. Therefore, the distance premium mostly effected by the first public announcement of the relocation and the effect gradually dim",2.0,https://doi.org/10.46923/ijets.v1i1.1378509606caa4e89fef20f2121017b11527b39cb349b,10.1177/23998083241301846,Valuing the ‘new normal’? Housing markets under COVID-19: Insights from a hybrid hedonic repeat sales model,2025,,Stephen Hincks; Chris Leishman; Hung N. Pham; Jenny Preece,"This study considers the impact of the COVID-19 pandemic on sub-national housing markets in Wales, focusing on the contribution of environmental and productivity attributes on house price change. Using a hybrid hedonic/repeat sales framework, we examine trends before, during, and after the pandemic. Initially, higher-quality environmental and productivity attributes were associated with a positive premium in price growth, while lower quality attributes were associated with a negative premium. However, during the pandemic’s second phase, these effects reversed but positive premiums for higher-quality attributes did not fully unwind during the transition to less acute phases of the pandemic. When we disaggregate the analysis for the urban-rural gradient, we find that both contexts placed a premium on high quality environmental housing, but lower quality productivity attributes negatively affected urban areas. The contribution of the study lies in revealing the complex, evolving and unequal relationship between the COVID-19 pandemic, housing preferences, and prices that, in our study context, have been subject to much conjecture but with little empirical investigation.",2.0,https://journals.sagepub.com/history/c93e3f37-49a4-438f-bcc5-cbaed7c97308/23998083241301846.17907678.pdf786f61b328070efeea37eed3a7e0b623eae1f073c37,10.1108/ijhma-12-2023-0167,"Impact of proximity to cell phone tower base stations on residential property prices in the City of Johannesburg, South Africa",2024,International Journal of Housing Markets and Analysis,Koech Cheruiyot; Nosipho Mavundla; Mncedisi J. Siteleki; Ezekiel Lengaram,"Purpose787With revolutions in the telecommunication sector having led to wide unprecedented consequences in all facets of human life, this paper aims to examine the relationship between cell phone tower base stations (CPTBSs) and residential property prices within the City of Johannesburg (CoJ), South Africa.788789Design/methodology/approach790The authors align their work with global literature and assess how the impact of CPTBSs influences residential property values in South Africa. The authors use a semi-log hedonic pricing model to test the hypothesis that proximity of CPTBSs to residential properties does not account for any variation in residential property prices.791792Findings793The results show a significant impact that proximity of CPTBS has on residential property sale prices. However, the impact of CTPBSs’ proximity on residential property prices depends on their distance from the residential properties. The closer a residential property is to the CTPBS, the greater the impact that the CTPBS will have on the selling price of the residential property.794795Originality/value796With international studies offering mixed findings on the impact of CPTBSs on residential property values, there is ",2.0,7970aed4606387835599541d79050eabb05449e0442,10.1080/00036846.2022.2159008,The effect of Movida on residential property prices: up or down?,2023,Applied Economics,E. Ottoz; P. Pavese; L. Sella,"ABSTRACT Hedonic regression technique has often been used to study the effect of road, railway and airport noise on property prices. However, European cities are experiencing a particular type of noise pollution originated by night-time recreational activities mainly located in the city centres, the so-called ‘Movida’, which has not been properly investigated yet. The aim of this paper is to examine the effect of recreational noise on residential property prices. We used an original highly detailed housing transactions dataset from the City of Turin covering the period 2017 to 2018 and built an indicator of recreational noise based on the proximity of dwellings to the night recreational activities. The results obtained employing hedonic modelling show that the adverse environment for an apartment located in a ‘Movida’ district will result in a lower market value as compared to an apartment with similar characteristics, except for recreational noise. This occurs because potential buyers reduce their demand, as they discount the present value of the costs of annoyance, loss of tranquillity and health effects due to sleep deprivation.",2.0,https://hdl.handle.net/2318/1885000798d555b7523f1b2210b768288f3d94d621ed191fb4,10.34096/rtt.i20.6394,Inversión pública y plusvalías urbanas. Análisis espacial y efectos no lineales de la proximidad de la red de subterráneos sobre los precios de la vivienda en Buenos Aires,2019,Revista transporte y territorio,S. Rosanovich; Ana Paula Di Giovambattista,"As regards the capture and recovery of urban capital gains, one of the requirements for the design of public policy is the identification not only of the measure of the effect but also of the universe of affected properties as a result of urban development. In this article, the selling offers of apartments in Buenos Aires are analyzed in relation to its localization and distance to the subway network. Furthermore, for the first time a non-linear hedonic price model with spatial dependence is implemented in order to show the impact over real-estate market using a new dataset of selling prices. The presence of a non-linear effect of the price per square meter based on the distance to the subway stations is verified, negative for the range between 0 and 200 meters (-5%) and positive for the range of 300 to 600 meters (+3,6%). In addition, a detailed description of the current heterogeneities between subway lines is included, stressing the differences in the spatial distribution of house prices, partially determined by the attributes (v.g. vigilance, swimming pool, gym) of the buildings in the different neighborhoods of the city.",2.0,http://revistascientificas.filo.uba.ar/index.php/rtt/article/download/6394/56467990726a6cc581fee39cc268e4d32d8292b296bebc9,10.26740/jram.v8n2.p94-104,THE COMPARISON OF HEDONIC REGRESSION AND ARTIFICIAL NEURAL NETWORK IN THE DEVELOPMENT OF MASS APPRAISAL MODEL,2024,Jurnal Riset dan Aplikasi Matematika (JRAM),Mukti Ratna Dewi; B. S. S. Ulama; D. Susilaningrum,"The appraisal of land and building tax objects in Surabaya City has been carried out manually, so it is prone to bias, human error, and inefficiency in terms of time and energy. Therefore, it is necessary to develop a mass appraisal system based on a property price prediction model in accordance with the real estate market structure. The traditional approach to mass appraisal is based on multiple regression analysis, which, despite having a long history in the appraisal world, cannot address interactions between variables such as nonlinearity. This deficiency was then overcome by introducing an Artificial Intelligence approach based on an artificial neural network (ANN), which has the ability to learn on its own and generalize solutions. Specifically, this study aims to build a mass appraisal model for residential property using (i) multiple regression analysis and (ii) artificial neural network, as well as (iii) determining the best mass appraisal model. The result of the study shows that ANN performs better than multiple regression analysis in predicting the value of residential property in Surabaya City.",2.0,https://journal.unesa.ac.id/index.php/jram/article/download/34980/12295800827a4ee174ffcf0cbe7d753591b176f3892eacba,10.1590/s0103-65131995000100004,Estimativa de modelos de preços hedônicos para locação residencial em Porto Alegre,1995,,M. A. I. González; C. Formoso,"This research work aim at investigating the behavior of the real estate market of the city of Porto Alegre, through the use of multiple variable statistical models, which explain the value formation of housing rents. The models developed were based on a sample of 504 apartments, from several different areas of the city, offered in the market during July 1992. The universe is all properties offered in that period. The models developed were based on a sample of 504 apartments, extracted of the total of 1819. In that apartments, a number of variables had their influence in the value of rent investigated, like building condition and proximity conditions, completed by information of public institutions. The data were tested by factor and regression analysis, with the compilation of econometric models (hedonic). in various aggregation levels. The analysis demonstrated what the market can to be explicated by this models, what present significative differences, according to data collection, but permit the obtainment of models for all dwellings and a best understanding of working of real estate market",2.0,https://www.scielo.br/j/prod/a/FNWKQHWTh9t7QFPyk6TrRxp/?lang=pt&format=pdf801doi_10_1108_14635781111138109,10.1108/14635781111138109,Seasonal and spatial hedonic price indices,2011,Journal of Property Investment & Finance,Anastassios N. Karaganis,"Purpose This paper aims to deal with the construction of seasonal price indices for the housing market, based on Rosen's hedonic equations and using spatial econometric autoregression (SAR) techniques. Design/methodology/approach More precisely, the hedonic equations are estimated using disaggregated data, and the extracted indices are averaged over zip code areas. Then the seasonality, which is considered deterministic, is extracted after eliminating the spatial effects. The data set used consists of 8,685 valuations of dwellings, detached dwellings and detached houses that took place in Attica on behalf of a commercial bank during the period 2000‐2009. Findings The paper concludes that evidence exists to support the hypothesis that property prices are affected by seasonal and spatial effects beyond structural effects and the effects of the general economic situation. Property valuations are strongly connected with deterministic exogenous variables, such as the size, age and location of the property, the general economic situation, and to a lesser effect the spatial system and the season during which the valuation took place. The estimated spatial effect is positive and quite larg",2.0,8022799534456858542797f23b6cf17bd1f12439819,10.47743/saeb-2019-0031,Towards a Hedonic Pricing Method for the Bucharest Private Housing Market,2019,Scientific Annals of Economics and Business,Ion Radu Zilișteanu; R. Muntean; Ș. Gherghina; G. Vintilă; T. Barbu,"This paper aims at exploring the drivers of dwellings’sale prices in Bucharest, Romania, over the period 2014-2018. Several housing structural attributes are covered, such as the number of rooms, useful and constructed surface, type of comfort, floor, the number of bathrooms, balconies and parking, the seniority from construction, as well as from renovation, structure type, height regime, and the duration until completion of the real estate transaction. By estimating a standard hedonic price model via OLS regression for a sample of 765 transactions, we notice that all the selected variables, except the floor level and seniority from construction, positively influence the property prices. However, in case of useful and constructed surface, nonlinear relationships with property prices were acknowledged. Robustness checks in form of quantile regressions reinforce the empirical findings.",2.0,https://doi.org/10.47743/saeb-2019-00318032aa7fd38898d91520a1e835f9c23698e9be3c219,10.1108/ijhma-06-2024-0079,Unveiling housing preferences amidst flood risks: an empirical study in an emerging market,2024,International Journal of Housing Markets and Analysis,H. Nguyen; H. Truong,"804Purpose805This study investigates the interplay between flood risk, financial constraints and buyer behavior in the housing market. It aims to discern how flood experience influences housing choices, particularly among financially constrained buyers.806807808Design/methodology/approach809Using hedonic pricing models and probit analysis, this research examines the implicit prices of house characteristics and evaluates the determinants of housing choices, considering factors such as flood risk, financial status and past flood experience.810811812Findings813The study underscores that lower house prices incentivize buyers to opt for homes in flood-prone areas, thereby increasing their vulnerability to flood risks. Consequently, financial constraints exacerbate this situation, compelling low-income buyers to accept higher flood risks. However, flood experience fosters risk awareness among buyers, encouraging them to steer clear of flood-prone areas, albeit with lesser efficacy among financially constrained individuals.814815816Originality/value817This research contributes to the understanding of how flood risk and financial limitations shape housing decisions. It highlights the role of flood experience in influ",2.0,818d2575f46b52ad2b5d7618aa3376e1105c299c6dc,10.1142/9789813277618_0008,Pricing Characteristics: An Application of Shephard’s Dual Lemma,2015,World Scientific-Now Publishers Series in Business,R. Färe; S. Grosskopf; R. Sickles; Chenjun Shang,"The recent housing bubble has provided impetus for revisiting indicators of housing price inflation and property characteristics. Diewert (2011, Alternative Approaches to Measuring Housing Price Inflation, paper presented at the Economic Measurement Group Workshop, 2011, UNSW, Australia) for example has provided a comparison of various methods of constructing property price indices using index number and hedonic regression methods, which he illustrates using data from a small Dutch town over a number of quarters. We provide an alternative approach based on Shephard's dual lemma and apply it to the same data used by Diewert. This method avoids the multicollinearity problem associated with traditional hedonic regression, and the resulting prices of property characteristics show smoother trends than Diewert's results. We also revisit the Diewert and Shimizu (2013) study that employed hedonic regressions to decompose the price of residential property in Tokyo into land and structure components and that constructed constant quality indexes for land and structure prices respectively. We use three models from Diewert and Shimizu (2013) to fit our real estate data from town ""A"" in Netherla",2.0,819022728fa0357108d860d58d647affccbd10a0292,10.37256/redr.122020260,Measuring the Effect of Location on House Prices in Italy,2020,Regional Economic Development Research,G. Lisi; Mauro Iacobini,"The Italian housing market is characterised by both a strong heterogeneity of real estate assets and a reduced number of property sales. These features, indeed, hamper the use of the hedonic price method, namely, the method that is mostly used for assessing the house prices and for estimating the monetary value of housing characteristics. In this paper, therefore, a hedonic model with dummy variables that identify housing submarkets is used to achieve two important results: enabling greater use of multiple regression analysis in the study of the Italian real estate market, and catching, in the simplest possible manner, the effect of location on house price. Indeed, the house's location is, together with the area in square metres, the housing characteristic that most influences the house price.",2.0,https://doi.org/10.37256/redr.1220202608203ea725c94fee00d743a2424653d254a479f75657,10.1109/wids-psu61003.2024.00038,Assessment of the Hybrid Deep Learning Models and Hedonic Pricing Model for House Price Prediction,2024,2024 Seventh International Women in Data Science Conference at Prince Sultan University (WiDS PSU),S. Sakri; Zaiton Ali; Nurul Halimatul Asmak Ismail,"Modeling the pricing process or estimating a property’s fair market value in an objective manner is highly complicated. Several variables, including geographical and temporal ones, can heighten this intricacy. Researchers and real estate appraisers have been attempting to simulate the process for ages. Prior until recently, real estate appraisal and data evaluation were both improved by computer-aided valuation systems. However, they are not very efficient, accurate, or transparent and require continuous improvements. In this study, we investigate how hybrid deep learning (DL) algorithms can improve economic activity by making better predictions of house prices. The research employs the DL algorithms and the hedonic regression modeling for the house price prediction. DL and hedonic pricing models were trained using the Ames housing dataset containing 82 variables and 2,930 samples. The research contributes to the feasibility of employing hybrid DL algorithms to predict home values. Finally, the prediction model’s goodness of fit is reported, with CNN+LSTM+FCL (the proposed hybrid DL model) achieving the highest R-squared score of 96.15%, while the hedonic regression model acquired ",2.0,821