Towards a Hedonic Pricing Method for the Bucharest Private Housing Market
DOI:
https://doi.org/10.47743/saeb-2019-0031Keywords:
hedonic regression, OLS, quantiles, structural attributesAbstract
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.
JEL Codes - C21; R30
References
Baranzini, A., and Schaerer, C., 2011. A sight for sore eyes: Assessing the value of view and land use in the housing market. Journal of Housing Economics, 20(3), 191-199. http://dx.doi.org/10.1016/j.jhe.2011.06.001
Benson, E. D., Hansen, J. L., Schwartz, A. L., and Smersh, G. T., 1998. Pricing residential amenities: The value of a view. The Journal of Real Estate Finance and Economics, 16(1), 55-73. http://dx.doi.org/10.1023/A:1007785315925
Brecard, D., Boennec, R. L., and Salladarre, F., 2018. Accessibility, local pollution and housing prices. Evidence fromNantes Metropole, France. Economie et Statistique. Economie & Statistique(500-502), 97-115. http://dx.doi.org/10.24187/ecostat.2018.500t.1952
Camins-Esakov, J., and Vandegrift, D., 2018. Impact of a light rail extension on residential property values. Research in Transportation Economics, 67, 11-18. http://dx.doi.org/10.1016/j.retrec.2017.04.004
Chen, W. Y., and Jim, C. Y., 2010. Amenities and disamenities: A hedonic analysis of the heterogeneous urban landscape in Shenzhen (China). The Geographical Journal, 176, 227-240. http://dx.doi.org/10.1111/j.1475-4959.2010.00358.x
Conroy, S., and Milosch, J. L., 2011. An Estimation of the Coastal Premium for Residential Housing Prices in San Diego County. The Journal of Real Estate Finance and Economics, 42(2), 211-228. http://dx.doi.org/10.1007/s11146-009-9195-x
Conroy, S., Narwold, A., and Sandy, J., 2013. The value of a floor: Valuing floor level in high-rise condominiums in San Diego. International Journal of Housing Markets and Analysis, 6(2), 197-208. http://dx.doi.org/10.1108/IJHMA-01-2012-0003
Cordera, R., Coppola, P., dell'Olio, L., and Ibeas, A., 2019. The impact of accessibility by public transport on real estate values: A comparison between the cities of Rome and Santander. Transportation Research Part A, Policy and Practice, 125, 308-319. http://dx.doi.org/10.1016/j.tra.2018.07.015
Czembrowski, P., and Kronenberg, J., 2016. Hedonic pricing and different urban green space types and sizes: Insights into the discussion on valuing ecosystem services. Landscape and Urban Planning, 146, 11-19. http://dx.doi.org/10.1016/j.landurbplan.2015.10.005
D'Acci, L., 2019. Quality of urban area, distance from city centre, and housing value. Case study on real estate values in Turin. Cities (London, England), 91, 71-92. http://dx.doi.org/10.1016/j.cities.2018.11.008
Dahal, R. P., Grala, R. K., Gordon, J. S., Munn, I. A., Petrolia, D. R., and Cummings, J. R., 2019. A hedonic pricing method to estimate the value of waterfronts in the Gulf of Mexico. Urban Forestry & Urban Greening, 41, 185-194. http://dx.doi.org/10.1016/j.ufug.2019.04.004
Damigos, D., and Anyfantis, F., 2011. The value of view through the eyes of real estate experts: A Fuzzy Delphi Approach. Landscape and Urban Planning, 101(2), 171-178. http://dx.doi.org/10.1016/j.landurbplan.2011.02.009
Efthymiou, D., and Antoniou, C., 2013. How do transport infrastructure and policies affect house prices and rents? Evidence from Athens, Greece. Transportation Research Part A, Policy and Practice, 52, 1-22. http://dx.doi.org/10.1016/j.tra.2013.04.002
Feng, H., and Lu, M., 2013. School quality and housing prices: Empirical evidence from a natural experiment in Shanghai, China. Journal of Housing Economics, 22(4), 291-307. http://dx.doi.org/10.1016/j.jhe.2013.10.003
Fernandez, M. A., and Bucaram, S., 2019. The changing face of environmental amenities: Heterogeneity across housing submarkets and time. Land Use Policy, 83, 449-460. http://dx.doi.org/10.1016/j.landusepol.2019.02.024
Huang, D. J., Leung, C. K., and Qu, B. Z., 2015. Do bank loans and local amenities explain Chinese urban house prices? China Economic Review, 34, 19-38. http://dx.doi.org/10.1016/j.chieco.2015.03.002
Huang, Z. Z., Chen, R. S., Xu, D., and Zhou, W., 2017. Spatial and hedonic analysis of housing prices in Shanghai. Habitat International, 67, 69-78. http://dx.doi.org/10.1016/j.habitatint.2017.07.002
Hui, E. C. M., Zhong, J. W., and Yu, K. H., 2012. The impact of landscape views and storey levels on property prices. Landscape and Urban Planning, 105(1-2), 86-93. http://dx.doi.org/10.1016/j.landurbplan.2011.12.002
Ibeas, A., Cordera, R., dell'Olio, L., Coppola, P., and Dominguez, A., 2012. Modelling transport and real-estate values interactions in urban systems. Journal of Transport Geography, 24, 370-382. http://dx.doi.org/10.1016/j.jtrangeo.2012.04.012
Jim, C. Y., and Chen, W. Y., 2009. Value of scenic views: Hedonic assessment of private housing in Hong Kong. Landscape and Urban Planning, 91(4), 226-234. http://dx.doi.org/10.1016/j.landurbplan.2009.01.009
Keskin, B., 2008. Hedonic Analysis of Price in the Istanbul Housing Market. International Journal of Strategic Property Management, 12(2), 125-138. http://dx.doi.org/10.3846/1648-715X.2008.12.125-138
Kim, H., Park, S. W., Lee, S., and Xue, X. Q., 2015. Determinants of house prices in Seoul: A quantile regression approach. Pacific Rim Property Research Journal, 21(2), 91-113. http://dx.doi.org/10.1080/14445921.2015.1058031
Lancaster, K. J., 1966. A New Approach to Consumer Theory. Journal of Political Economy, 74(2), 132-157. http://dx.doi.org/10.1086/259131
Larsen, J. E., and Blair, J. P., 2014. Price effects of surface street traffic on residential property. International Journal of Housing Markets and Analysis, 7(2), 189-203. http://dx.doi.org/10.1108/IJHMA-12-2012-0062
Laszkiewicz, E., Czembrowski, P., and Kronenberg, J., 2019. Can proximity to urban green spaces be considered a luxury? Classifying a non-tradable good with the use of hedonic pricing method. Ecological Economics, 161, 237-247. http://dx.doi.org/10.1016/j.ecolecon.2019.03.025
Li, H., Wei, Y. D., Wu, Y., and Tian, G., 2019. Analyzing housing prices in Shanghai with open data: Amenity, accessibility and urban structure. Cities (London, England), 91, 165-179. http://dx.doi.org/10.1016/j.cities.2018.11.016
Liang, X. J., Liu, Y. L., Qiu, T. Q., Jing, Y., and Fang, F. G., 2018. The effects of locational factors on the housing prices of residential communities: The case of Ningbo, China. Habitat International, 81, 1-11. http://dx.doi.org/10.1016/j.habitatint.2018.09.004
Liao, W. C., and Wang, X. Z., 2012. Hedonic house prices and spatial quantile regression. Journal of Housing Economics, 21(1), 16-27. http://dx.doi.org/10.1016/j.jhe.2011.11.001
Ligus, M., and Peternek, P., 2016. Measuring structural, location and environmental effects: A hedonic analysis of housing market in Wroclaw, Poland. Procedia: Social and Behavioral Sciences, 220, 251-260. http://dx.doi.org/10.1016/j.sbspro.2016.05.497
Lin, J. J., and Yang, S. H., 2019. Proximity to metro stations and commercial gentrification. Transport Policy, 77, 79-89. http://dx.doi.org/10.1016/j.tranpol.2019.03.003
Lu, J. J., 2018. The value of a south-facing orientation: A hedonic pricing analysis of the Shanghai housing market. Habitat International, 81, 24-32. http://dx.doi.org/10.1016/j.habitatint.2018.09.002
McCord, M. J., Davis, P. T., Bidanset, P., McCluskey, W., McCord, J., Haran, M., and MacIntyre, S., 2018. House prices and neighbourhood amenities: Beyond the norm? International Journal of Housing Markets and Analysis, 11(2), 263-289. http://dx.doi.org/10.1108/IJHMA-04-2017-0043
Mulley, C., Ma, L., Clifton, G., Yen, B., and Burke, M., 2016. Residential property value impacts of proximity to transport infrastructure: An investigation of bus rapid transit and heavy rail networks in Brisbane, Australia. Journal of Transport Geography, 54, 41-52. http://dx.doi.org/10.1016/j.jtrangeo.2016.05.010
Mulley, C., Tsai, C. H. P., and Ma, L., 2018. Does residential property price benefit from light rail in Sydney? Research in Transportation Economics, 67, 3-10. http://dx.doi.org/10.1016/j.retrec.2016.11.002
Ooi, J. T. L., Le, T. T. T., and Lee, N. J., 2014. The impact of construction quality on house prices. Journal of Housing Economics, 26, 126-138. http://dx.doi.org/10.1016/j.jhe.2014.10.001
Rosen, S., 1974. Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition. Journal of Political Economy, 82(1), 34-55. http://dx.doi.org/10.1086/260169
Selim, H., 2009. Determinants of house prices in Turkey: Hedonic regression versus artificial neural network. Expert Systems with Applications, 36(2), 2843-2852. http://dx.doi.org/10.1016/j.eswa.2008.01.044
Tian, G., Wei, Y. D., and Li, H., 2017. Effects of accessibility and environmental health risk on housing prices: A case of Salt Lake County, Utah. Applied Geography (Sevenoaks, England), 89, 12-21. http://dx.doi.org/10.1016/j.apgeog.2017.09.010
Wang, Y., Wang, S. J., Li, G. D., Zhang, H. O., Jin, L. X., Su, Y. X., and Wu, K. M., 2017. Identifying the determinants of housing prices in China using spatial regression and the geographical detector technique. Applied Geography (Sevenoaks, England), 79, 26-36. http://dx.doi.org/10.1016/j.apgeog.2016.12.003
Wen, H. Z., Xiao, Y., and Hui, E. C. M., 2019. Quantile effect of educational facilities on housing price: Do homebuyers of higher-priced housing pay more for educational resources? Cities (London, England), 90, 100-112. http://dx.doi.org/10.1016/j.cities.2019.01.019
Wen, H. Z., Xiao, Y., Hui, E. C. M., and Zhang, L., 2018. Education quality, accessibility, and housing price: Does spatial heterogeneity exist in education capitalization? Habitat International, 78, 68-82. http://dx.doi.org/10.1016/j.habitatint.2018.05.012
Wen, H. Z., Xiao, Y., and Zhang, L., 2017a. School district, education quality, and housing price: Evidence from a natural experiment in Hangzhou, China. Cities (London, England), 66, 72-80. http://dx.doi.org/10.1016/j.cities.2017.03.008
Wen, H. Z., Xiao, Y., and Zhang, L., 2017b. Spatial effect of river landscape on housing price: An empirical study on the Grand Canal in Hangzhou, China. Habitat International, 63, 34-44. http://dx.doi.org/10.1016/j.habitatint.2017.03.007
Wen, H. Z., Zhang, Y., and Zhang, L., 2014. Do educational facilities affect housing price? An empirical study in Hangzhou, China. Habitat International, 42, 155-163. http://dx.doi.org/10.1016/j.habitatint.2013.12.004
Wen, H. Z., Zhang, Y., and Zhang, L., 2015. Assessing amenity effects of urban landscapes on housing price in Hangzhou, China. Urban Forestry & Urban Greening, 14(4), 1017-1026. http://dx.doi.org/10.1016/j.ufug.2015.09.013
Wilhelmsson, M., 2002. Spatial Models in Real Estate Economics Housing. Theory and Society, 19(2), 92-101. http://dx.doi.org/10.1080/140360902760385646
Wu, C., Ye, X. Y., Du, Q. Y., and Luo, P., 2017. Spatial effects of accessibility to parks on housing prices in Shenzhen, China. Habitat International, 63, 45-54. http://dx.doi.org/10.1016/j.habitatint.2017.03.010
Xiao, Y., Hui, E. C. M., and Wen, H. Z., 2019. Effects of floor level and landscape proximity on housing price: A hedonic analysis in Hangzhou, China. Habitat International, 87, 11-26. http://dx.doi.org/10.1016/j.habitatint.2019.03.008
Yang, L. C., Zhou, J. P., Shyr, O. F., and Huo, D., 2019. Does bus accessibility affect property prices? Cities (London, England), 84, 56-65. http://dx.doi.org/10.1016/j.cities.2018.07.005
Yuan, F., Wu, J. W., Wei, Y. D., and Wang, L., 2018. Policy change, amenity, and spatiotemporal dynamics of housing prices in Nanjing, China. Land Use Policy, 75, 225-236. http://dx.doi.org/10.1016/j.landusepol.2018.03.045
Zhang, L., and Leonard, T., 2014. Neighborhood impact of foreclosure: A quantile regression approach. Regional Science and Urban Economics, 48, 133-143. http://dx.doi.org/10.1016/j.regsciurbeco.2014.06.004
Zhang, L., and Yi, Y. M., 2017. Quantile house price indices in Beijing. Regional Science and Urban Economics, 63, 85-96. http://dx.doi.org/10.1016/j.regsciurbeco.2017.01.002
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2019 SCIENTIFIC ANNALS OF ECONOMICS AND BUSINESS
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
All accepted papers are published on an Open Access basis.
The Open Access License is based on the Creative Commons license.
The non-commercial use of the article will be governed by the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License as currently displayed on https://creativecommons.org/licenses/by-nc-nd/4.0
Under the Creative Commons Attribution-NonCommercial-NoDerivatives license, the author(s) and users are free to share (copy, distribute and transmit the contribution) under the following conditions:
1. they must attribute the contribution in the manner specified by the author or licensor,
2. they may not use this contribution for commercial purposes,
3. they may not alter, transform, or build upon this work.
This work is licenced under a 
