1# RECORD d66dcd3e24d3aa705a9e17810be910446c18dce32# TITLE: What is the effect of location on rental housing prices in Athens?3# YEAR: 2021.0 VENUE: Review of business Management DOI: 10.7819/rbgn.v23i3.41144# AUTHORS: Jorge Chica-Olmo; Rafael Cano-Guervos; María-Despoina Moschovaki; Ivan Tamires-Turizo5# PAGES: 15 CANDIDATE TABLE PAGES (1-based): [7, 9]6# 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.789===== PAGE 1 (score 4, numeric-paren 0, table-words 0, var-words 4) =====101143912R. Bras. Gest. Neg., São Paulo, v.23, n.3, p.439-453, jul-set 202113REVISTA BRASILEIRA DE GESTÃO DE NEGÓCIOS 14ISSN 1806-489215 e-ISSN 1983-080716© FECAP17RBGN1843919Revista Brasileira de Gestão de 20Negócios21https://doi.org/10.7819/rbgn.v23i3.411422Received on:2308/16/201924Approved on:2512/02/202026Responsible Editor:27Prof. Dr. Joelson Sampaio28Evaluation process:29Double Blind Review30Reviewers:31Fabio Humberto Sepúlveda Murillo; 32Humberto Gallucci Netto33What is the effect of location on rental housing 34prices in Athens?35Jorge Chica-Olmo1 36Rafael Cano-Guervos2 37María-Despoina Moschovaki3 38Ivan Tamaris-Turizo4 39Abstract40Purpose – The aim of this study is to quantify the effect of location on rental 41housing prices in the city of Athens.42Theoretical framework – The right to adequate housing is a fundamental human 43right defended by democratic societies. Therefore, it is of interest to examine 44housing tenures for both owned and rented accommodation.45Design/methodology/approach – Geostatistical methods (regression-kriging) 46were used to obtain the results, which are represented on an isovalue map of 47rental housing prices displaying the minor and major effects of location by zone.48Findings – This study highlights the impact of location on rental housing prices 49by showing how the rent of a standard dwelling in the city of Athens varies 50depending on its location.51Research Practical & Social implications – The main social implications of 52this work is it helps investors determine where to direct investments and it assists 53public authorities in deciding where to focus urban management policies, in order 54to control the undesirable effects of an excessive rise in rents caused by tourism.55Originality/value – The main originality of this paper lies in its isovalue map 56of rental housing prices for standard dwellings, which can also be interpreted as 57a locational isovalue map.58Keywords – rental housing prices, geostatistics, isovalue map, effects of location, 59Athens.601.University of Granada, Department of Quantitative Methods for Economics and 61Business, Granada, Spain.622. University of Granada, Department of Quantitative Methods for Economics and 63Business, Granada, Spain.643. Economic analyst, NGA Human Resources, Granada, Spain.654. International School of Administration and Marketing, Sergio Arboleda University, 66Santa Marta, Colombia.67How to cite:68Chica-Olmo, J., Cano-Guervos, R., Moschovaki, M., Tamaris-Turizo, I. (2021). 69What is the effect of location on rental housing prices in Athens? Revista Brasileira 70de Gestão de Negócios, 23(3), p.439-453.717273===== PAGE 7 (score 31, numeric-paren 1, table-words 7, var-words 13) =====7475 44576R. Bras. Gest. Neg., São Paulo, v.23, n.3, p.439-453, jul-set 202177What is the effect of location on rental housing prices in Athens?78coefficients (multiplied by 100) of the continuous variables 79as the percentage impact of those variables on rental 80housing prices. For the dummy variables, the expression 81082[83*84( )851086]187exp β −88 is used to interpret the percentage impact 89(Halvorsen & Palmquist, 1980).90As indicated, in addition to modeling rental 91housing prices in Athens using the classical OLS method, 92we used RK to run a model with the GLS estimator. 93Table 2 shows the estimates of the model coefficients using 94OLS and RK. Severe multicollinearity was not detected 95in the model given that the highest variance inflation 96factor (VIF) is for the Age variable (7.4326) and does not 97exceed the value of 10. However, the model disturbances 98exhibit spatial autocorrelation given that the Moran’s I 99statistic (I = 0.4242) is significant at the 5% level (p = 1000.000). To consider the spatial autocorrelation in the 101model disturbances, we used an exponential variogram 102model whose parameters are shown in Table 2. The relative 103residual nugget effect (nugget/sill) is 0.33, thus indicating 104clear spatial dependence, which was detected due to the 105significant value of the Moran’s I statistic. The presence 106of spatial dependence in the model disturbances could be 107due to the existence of variables that are not included in 108the model, although they exhibit spatial autocorrelation 109due to the location variables, such as spatial contagion 110and location characteristics. The experimental variogram 111in Figure 3 shows that as the distance between dwellings 112increases, the variability between the residuals also increases. 113Three models (spherical, exponential, and Gaussian) 114were used to select the type of spatial autocorrelation 115structure, all of which yielded very similar results in 116terms of the R-squared of the RK model (Gaussian = 1170.8419, exponential = 0.8434, and spherical = 0.8439). 118Ultimately, the exponential model was chosen as it is the 119most frequently used model in the literature (Webster & 120Oliver, 2007). The figure also shows the adjusted variogram 121model, whose effective range is equal to 2,635.818 meters 122(3*878.606). This distance indicates the area of influence 123of local variables on rental housing prices in Athens.124As can be seen in Table 2, the variables that are 125significant at the 5% and 10% levels have the expected 126signs in both models. As regards the goodness-of-fit 127of the model, it can be observed that the RK model is 128more suitable than the OLS one, since the R-squared 129has increased and the root-mean-square prediction error 130(RMSE) has decreased.131From the point of view of the housing market, 132it is clearly of interest to determine housing prices at any 133given location and thus obtain isovalue maps (Clapp, 1342004; Yue, Liu, & Fan, 2010). To do so, it is first necessary 135to estimate the price of housing at any point on the 136map. However, given that it is impossible to know the 137structural characteristics for all points on the map, we 138defined a standard dwelling. A standard dwelling was 139obtained by assigning the numerical value of the sample 140mean if the variable was continuous or the mode if the 141variable was binary.142Figure 4 shows the estimated values for a standard 143dwelling in Athens. As can be observed, the highest prices 144are found in the center of the city, around the Acropolis. 145Table 1.146Descriptive statistics of the variables147Mean148Mode149SD150Min151Max152Dependent variable153Rental housing prices154817.713155800156673.8191571201586,000159Explanatory variables160Age16123.4601624416317.2271640165114166Surface167127.97416810016982.56617025171600172Bedrooms1732.33617421751.08117601776178WC1790.52618011810.56918201833184Storage room1850.47218601870.50018801891190Air conditioned1910.36119201930.48119401951196View1970.42119801990.49420002011202Fireplace2030.46220402050.49920602071208Heat2090.96621012110.18221202131214Elevator2150.62721612170.48721802192220Furnished2210.29222202230.45522402251226Garage2270.47222802290.50023002311232233234===== PAGE 8 (score 0, numeric-paren 0, table-words 0, var-words 0) =====235236446237R. Bras. Gest. Neg., São Paulo, v.23, n.3, p.439-453, jul-set 2021238Jorge Chica-Olmo / Rafael Cano-Guervos / María-Despoina Moschovaki / Ivan Tamaris-Turizo239Figure 2. Location of the housing in the sample240241242===== PAGE 9 (score 63, numeric-paren 28, table-words 3, var-words 23) =====243244 447245R. Bras. Gest. Neg., São Paulo, v.23, n.3, p.439-453, jul-set 2021246What is the effect of location on rental housing prices in Athens?247There are several reasons for this. The main one is that 248the central business district and the most important 249monuments (Syntagma Square, the Cathedral, the 250Hellenic Parliament, most of the ministries, and almost 251all the embassies) are located in this area. This is also the 252central point where most of the shops, bars, restaurants, 253designer boutiques, museums, and other amenities and 254leisure facilities are located. In addition, there are a large 255number of hotels, banks, post offices, as well as subway, 256bus, and tram lines that provide easy access to the area.257However, the center is not the only area where 258high rental prices can be found. The prices in the southern 259coastal zone (Glyfada) are similar to in the central area. 260This is due to the proximity of the housing to the sea and 261the Port of Piraeus, which is the chief port in Greece and 262one of the most important in Europe. The presence of 263numerous hotels, the proximity to the city center, and the 264good transport links enable residents from these areas to 265enjoy the beaches while they can continue to work close 266to the main hub. In addition, there are numerous nautical 267companies, which are paramount to the country’s economy.268Another high-priced area is located in the north 269(Kifissia), which is characterized by relatively new and 270exclusive housing owned by people with high purchasing 271power. This area is far enough from the center to escape the 272noise and hustle and bustle of the city and is surrounded by 273many green spaces and forests. The transport links to the 274center are good and there is quick access to the motorway 275out of Athens. Lastly, the area between Galatsi and Agia 276Paraskevi is also characterized by its high housing prices. 277Table 2.278Model estimated using OLS and RK. Dependent variable: Rental housing price279Explanatory variables280OLS281RK282Const.2835.214 (0.000)2845.4425 (0.000)285Age286-0.0055 (0.006)287-0.0084 (0.000)288Age-squared2890.0001 (0.000)2900.0001 (0.000)291Surface2920.0038 (0.000)2930.0038 (0.000)294Bedrooms2950.0596 (0.009)2960.0719 (0.000)297WC2980.1348 (0.000)2990.0768 (0.001)300Storage room3010.0811 (0.008)3020.0314 (0.020)303Air conditioned3040.0789 (0.005)3050.0298 (0.019)306View3070.0963 (0.000)3080.0679 (0.003)309Fireplace3100.2052 (0.000)3110.1107 (0.000)312Heat3130.1758 (0.015)3140.0984 (0.080)315Elevator3160.0761 (0.005)3170.0734 (0.002)318Furnished3190.1493 (0.000)3200.1279 (0.000)321Garage3220.1867 (0.000)3230.1775 (0.000)324Variogram325Exponential326Nugget327--3280.0432329Partial sill3300.0848331Range332878.606333Model fit334R-squared3350.75043360.8434337RMSE3380.34903390.2768340Note: N = 757; p-values in parenthesis.341Figure 3. Experimental variogram and adjust342ed exponential model343344345===== PAGE 10 (score 6, numeric-paren 0, table-words 0, var-words 6) =====346347448348R. Bras. Gest. Neg., São Paulo, v.23, n.3, p.439-453, jul-set 2021349Jorge Chica-Olmo / Rafael Cano-Guervos / María-Despoina Moschovaki / Ivan Tamaris-Turizo350This is due to the numerous squares, parks, avenues, and 351green areas surrounding both districts. The extension of 352the subway into these areas has also increased rental prices.353In contrast, one of the areas with the lowest prices 354in the city due to socio-economic problems is located 355between Aigaleo, Galatsi, and Peristeri. Lastly, the eastern 356zone also has low prices because it is far from the urban 357center and has poor transport links.358The results show the areas where the rents for 359residential properties are higher due to their cultural 360and environmental attractions, among other location 361characteristics. These same attractions are also highly 362Figure 4. Rental price of standard dwellings363