# RECORD d66dcd3e24d3aa705a9e17810be910446c18dce3 # TITLE: What is the effect of location on rental housing prices in Athens? # YEAR: 2021.0 VENUE: Review of business Management DOI: 10.7819/rbgn.v23i3.4114 # AUTHORS: Jorge Chica-Olmo; Rafael Cano-Guervos; María-Despoina Moschovaki; Ivan Tamires-Turizo # PAGES: 15 CANDIDATE TABLE PAGES (1-based): [7, 9] # ABSTRACT: Abstract Purpose: The aim of this study is to quantify the effect of location on rental housing prices in the city of Athens. Theoretical framework: The right to adequate housing is a fundamental human right defended by democratic societies. Therefore, it is of interest to examine housing tenures for both owned and rented accommodation. Design/methodology/approach: Geostatistical methods (regression-kriging) were used to obtain the results, which are represented on an isovalue map of rental housing prices displaying the minor and major effects of location by zone. Findings: This study highlights the impact of location on rental housing prices by showing how the rent of a standard dwelling in the city of Athens varies depending on its location. Research Practical & Social implications: The main social implications of this work is it helps investors determine where to direct investments and it assists public authorities in deciding where to focus urban management policies, in order to control the undesirable effects of an excessive rise in rents caused by tourism. Originality/value: The main originality of this paper lies in its isovalue map of rental housing prices for standard dwellings, which can also be interpreted as a locational isovalue map. ===== PAGE 1 (score 4, numeric-paren 0, table-words 0, var-words 4) ===== 439 R. Bras. Gest. Neg., São Paulo, v.23, n.3, p.439-453, jul-set 2021 REVISTA BRASILEIRA DE GESTÃO DE NEGÓCIOS ISSN 1806-4892 e-ISSN 1983-0807 © FECAP RBGN 439 Revista Brasileira de Gestão de Negócios https://doi.org/10.7819/rbgn.v23i3.4114 Received on: 08/16/2019 Approved on: 12/02/2020 Responsible Editor: Prof. Dr. Joelson Sampaio Evaluation process: Double Blind Review Reviewers: Fabio Humberto Sepúlveda Murillo; Humberto Gallucci Netto What is the effect of location on rental housing prices in Athens? Jorge Chica-Olmo1  Rafael Cano-Guervos2  María-Despoina Moschovaki3  Ivan Tamaris-Turizo4  Abstract Purpose – The aim of this study is to quantify the effect of location on rental housing prices in the city of Athens. Theoretical framework – The right to adequate housing is a fundamental human right defended by democratic societies. Therefore, it is of interest to examine housing tenures for both owned and rented accommodation. Design/methodology/approach – Geostatistical methods (regression-kriging) were used to obtain the results, which are represented on an isovalue map of rental housing prices displaying the minor and major effects of location by zone. Findings – This study highlights the impact of location on rental housing prices by showing how the rent of a standard dwelling in the city of Athens varies depending on its location. Research Practical & Social implications – The main social implications of this work is it helps investors determine where to direct investments and it assists public authorities in deciding where to focus urban management policies, in order to control the undesirable effects of an excessive rise in rents caused by tourism. Originality/value – The main originality of this paper lies in its isovalue map of rental housing prices for standard dwellings, which can also be interpreted as a locational isovalue map. Keywords – rental housing prices, geostatistics, isovalue map, effects of location, Athens. 1.University of Granada, Department of Quantitative Methods for Economics and Business, Granada, Spain. 2. University of Granada, Department of Quantitative Methods for Economics and Business, Granada, Spain. 3. Economic analyst, NGA Human Resources, Granada, Spain. 4. International School of Administration and Marketing, Sergio Arboleda University, Santa Marta, Colombia. How to cite: Chica-Olmo, J., Cano-Guervos, R., Moschovaki, M., Tamaris-Turizo, I. (2021). What is the effect of location on rental housing prices in Athens? Revista Brasileira de Gestão de Negócios, 23(3), p.439-453. ===== PAGE 7 (score 31, numeric-paren 1, table-words 7, var-words 13) ===== 445 R. Bras. Gest. Neg., São Paulo, v.23, n.3, p.439-453, jul-set 2021 What is the effect of location on rental housing prices in Athens? coefficients (multiplied by 100) of the continuous variables as the percentage impact of those variables on rental housing prices. For the dummy variables, the expression 0 [ * ( ) 10 ]1 exp β − is used to interpret the percentage impact (Halvorsen & Palmquist, 1980). As indicated, in addition to modeling rental housing prices in Athens using the classical OLS method, we used RK to run a model with the GLS estimator. Table 2 shows the estimates of the model coefficients using OLS and RK. Severe multicollinearity was not detected in the model given that the highest variance inflation factor (VIF) is for the Age variable (7.4326) and does not exceed the value of 10. However, the model disturbances exhibit spatial autocorrelation given that the Moran’s I statistic (I = 0.4242) is significant at the 5% level (p = 0.000). To consider the spatial autocorrelation in the model disturbances, we used an exponential variogram model whose parameters are shown in Table 2. The relative residual nugget effect (nugget/sill) is 0.33, thus indicating clear spatial dependence, which was detected due to the significant value of the Moran’s I statistic. The presence of spatial dependence in the model disturbances could be due to the existence of variables that are not included in the model, although they exhibit spatial autocorrelation due to the location variables, such as spatial contagion and location characteristics. The experimental variogram in Figure 3 shows that as the distance between dwellings increases, the variability between the residuals also increases. Three models (spherical, exponential, and Gaussian) were used to select the type of spatial autocorrelation structure, all of which yielded very similar results in terms of the R-squared of the RK model (Gaussian = 0.8419, exponential = 0.8434, and spherical = 0.8439). Ultimately, the exponential model was chosen as it is the most frequently used model in the literature (Webster & Oliver, 2007). The figure also shows the adjusted variogram model, whose effective range is equal to 2,635.818 meters (3*878.606). This distance indicates the area of influence of local variables on rental housing prices in Athens. As can be seen in Table 2, the variables that are significant at the 5% and 10% levels have the expected signs in both models. As regards the goodness-of-fit of the model, it can be observed that the RK model is more suitable than the OLS one, since the R-squared has increased and the root-mean-square prediction error (RMSE) has decreased. From the point of view of the housing market, it is clearly of interest to determine housing prices at any given location and thus obtain isovalue maps (Clapp, 2004; Yue, Liu, & Fan, 2010). To do so, it is first necessary to estimate the price of housing at any point on the map. However, given that it is impossible to know the structural characteristics for all points on the map, we defined a standard dwelling. A standard dwelling was obtained by assigning the numerical value of the sample mean if the variable was continuous or the mode if the variable was binary. Figure 4 shows the estimated values for a standard dwelling in Athens. As can be observed, the highest prices are found in the center of the city, around the Acropolis. Table 1. Descriptive statistics of the variables Mean Mode SD Min Max Dependent variable Rental housing prices 817.713 800 673.819 120 6,000 Explanatory variables Age 23.460 44 17.227 0 114 Surface 127.974 100 82.566 25 600 Bedrooms 2.336 2 1.081 0 6 WC 0.526 1 0.569 0 3 Storage room 0.472 0 0.500 0 1 Air conditioned 0.361 0 0.481 0 1 View 0.421 0 0.494 0 1 Fireplace 0.462 0 0.499 0 1 Heat 0.966 1 0.182 0 1 Elevator 0.627 1 0.487 0 2 Furnished 0.292 0 0.455 0 1 Garage 0.472 0 0.500 0 1 ===== PAGE 8 (score 0, numeric-paren 0, table-words 0, var-words 0) ===== 446 R. Bras. Gest. Neg., São Paulo, v.23, n.3, p.439-453, jul-set 2021 Jorge Chica-Olmo / Rafael Cano-Guervos / María-Despoina Moschovaki / Ivan Tamaris-Turizo Figure 2. Location of the housing in the sample ===== PAGE 9 (score 63, numeric-paren 28, table-words 3, var-words 23) ===== 447 R. Bras. Gest. Neg., São Paulo, v.23, n.3, p.439-453, jul-set 2021 What is the effect of location on rental housing prices in Athens? There are several reasons for this. The main one is that the central business district and the most important monuments (Syntagma Square, the Cathedral, the Hellenic Parliament, most of the ministries, and almost all the embassies) are located in this area. This is also the central point where most of the shops, bars, restaurants, designer boutiques, museums, and other amenities and leisure facilities are located. In addition, there are a large number of hotels, banks, post offices, as well as subway, bus, and tram lines that provide easy access to the area. However, the center is not the only area where high rental prices can be found. The prices in the southern coastal zone (Glyfada) are similar to in the central area. This is due to the proximity of the housing to the sea and the Port of Piraeus, which is the chief port in Greece and one of the most important in Europe. The presence of numerous hotels, the proximity to the city center, and the good transport links enable residents from these areas to enjoy the beaches while they can continue to work close to the main hub. In addition, there are numerous nautical companies, which are paramount to the country’s economy. Another high-priced area is located in the north (Kifissia), which is characterized by relatively new and exclusive housing owned by people with high purchasing power. This area is far enough from the center to escape the noise and hustle and bustle of the city and is surrounded by many green spaces and forests. The transport links to the center are good and there is quick access to the motorway out of Athens. Lastly, the area between Galatsi and Agia Paraskevi is also characterized by its high housing prices. Table 2. Model estimated using OLS and RK. Dependent variable: Rental housing price Explanatory variables OLS RK Const. 5.214 (0.000) 5.4425 (0.000) Age -0.0055 (0.006) -0.0084 (0.000) Age-squared 0.0001 (0.000) 0.0001 (0.000) Surface 0.0038 (0.000) 0.0038 (0.000) Bedrooms 0.0596 (0.009) 0.0719 (0.000) WC 0.1348 (0.000) 0.0768 (0.001) Storage room 0.0811 (0.008) 0.0314 (0.020) Air conditioned 0.0789 (0.005) 0.0298 (0.019) View 0.0963 (0.000) 0.0679 (0.003) Fireplace 0.2052 (0.000) 0.1107 (0.000) Heat 0.1758 (0.015) 0.0984 (0.080) Elevator 0.0761 (0.005) 0.0734 (0.002) Furnished 0.1493 (0.000) 0.1279 (0.000) Garage 0.1867 (0.000) 0.1775 (0.000) Variogram Exponential Nugget -- 0.0432 Partial sill 0.0848 Range 878.606 Model fit R-squared 0.7504 0.8434 RMSE 0.3490 0.2768 Note: N = 757; p-values in parenthesis. Figure 3. Experimental variogram and adjust­ ed exponential model ===== PAGE 10 (score 6, numeric-paren 0, table-words 0, var-words 6) ===== 448 R. Bras. Gest. Neg., São Paulo, v.23, n.3, p.439-453, jul-set 2021 Jorge Chica-Olmo / Rafael Cano-Guervos / María-Despoina Moschovaki / Ivan Tamaris-Turizo This is due to the numerous squares, parks, avenues, and green areas surrounding both districts. The extension of the subway into these areas has also increased rental prices. In contrast, one of the areas with the lowest prices in the city due to socio-economic problems is located between Aigaleo, Galatsi, and Peristeri. Lastly, the eastern zone also has low prices because it is far from the urban center and has poor transport links. The results show the areas where the rents for residential properties are higher due to their cultural and environmental attractions, among other location characteristics. These same attractions are also highly Figure 4. Rental price of standard dwellings