Multilevel Impacts of Urban Amenities on Housing Price in Tehran, Iran
Publication: Journal of Urban Planning and Development
Volume 149, Issue 4
Abstract
This study uses a multilevel hedonic model to examine information from official sources including the population census, the land-use map, and the field survey to draw conclusions about the 32,108 Tehran residences that make up the statistical sample. These results show that other factors besides proximity to urban facilities are important in determining the value of a home in Tehran, Iran. The results show that proximity to education, culture, entertainment, tourism, administration, and social service centers has a positive effect on housing prices, while proximity to some urban amenities, such as medical centers, commercial strips, and parks, has a negative effect on housing prices. This gap can be explained in part by the externalities of these facilities, including the creation of through traffic, congestion, and reduced security levels, which discourage home buyers from getting too close to these amenities. Furthermore, the study found that the effect of proximity differs from that of service provision at the neighborhood level. For example, while the presence of a medical/health center at neighborhood level was found to be a positive determinant of house prices, its proximity had a negative effect on house prices. In fact, home buyers prefer to purchase properties in neighborhoods that offer such amenities but are less likely to purchase properties in areas adjacent to such amenities. The higher the ratio of nonresidential to residential uses, the higher the price of housing in those areas. In fact, this shows the advantage of neighborhoods with a variety of uses more than single-use neighborhoods. The data also demonstrate that the variances across neighborhoods in Tehran account for a significant amount of the housing price variation, with 11% and 48% of the total variance attributed to local and regional levels of analysis, respectively. This highlights the nested and hierarchical nature of housing price data and the use of multilevel modeling for estimating home prices in Tehran. The results presented in this work may have theoretical and practical uses for scholars, insurance firms, banks, real estate developers, and others in the field of property economics.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or codes generated or used during the study are proprietary or confidential in nature and may be provided only with restrictions.
Acknowledgments
The authors would like to express their gratitude to the Iranian Ministry of Roads and Urban Development for granting access to the housing transactions data. The authors want to thank the editor and two anonymous reviewers for their insightful feedback.
References
Abdi, M. H., and A. Soltani. 2022. “Which fabric/scale is better for transit-oriented urban design: Case studies in a developing country.” Sustainability 14 (12): 7338. https://doi.org/10.3390/su14127338.
Abdi Daneshpour, Z., and A. Shafiee. 2018. “Analysing spatial inequality in Tehran’s Housing System, via changing prices during 1992–2016.” Geogr. Dev. Iran. J. 16 (52): 267–292.
Allam, Z., S. E. Bibri, D. S. Jones, D. Chabaud, and C. Moreno. 2022. “Unpacking the ‘15-minute city’ via 6G, IoT, and digital twins: Towards a new narrative for increasing urban efficiency, resilience, and sustainability.” Sensors 22 (4): 1369. https://doi.org/10.3390/s22041369.
Allan, A., A. Soltani, M. H. Abdi, and M. Zarei. 2022. “Driving forces behind land use and land cover change: A systematic and bibliometric review.” Land 11 (8): 1222. https://doi.org/10.3390/land11081222.
Aryan, V., H. Majedi, and Z. S. Saeideh Zarabadi. 2019. “The impact of physical-spatial components on residential land value in Zaferanieh Neighborhood, Tehran.” J. Archit. Urban Plann. 11 (22): 19–36.
Bohman, H. 2021. “Same, same but different? Neighbourhood effects of accessibility on housing prices.” Transp. Policy 107: 52–60. https://doi.org/10.1016/j.tranpol.2021.04.016.
Chen, J., Q. Hao, and C. Yoon. 2018. “Measuring the welfare cost of air pollution in Shanghai: Evidence from the housing market.” J. Environ. Plann. Manage. 61 (10): 1744–1757. https://doi.org/10.1080/09640568.2017.1371581.
Conley, K. L., and B. E. Whitacre. 2020. “Home is where the internet is? High-speed internet’s impact on rural housing values.” Int. Reg. Sci. Rev. 43 (5): 501–530. https://doi.org/10.1177/0160017620918652.
Dadashpoor, H., F. Rostami, and B. Alizadeh. 2016. “Is inequality in the distribution of urban facilities inequitable? Exploring a method for identifying spatial inequity in an Iranian city.” Cities 52: 159–172. https://doi.org/10.1016/j.cities.2015.12.007.
Drechsler, I., A. Savov, and P. Schnabl. 2022. “How monetary policy shaped the housing boom.” J. Financ. Econ. 144 (3): 992–1021. https://doi.org/10.1016/j.jfineco.2021.06.039.
Feng, X., and B. R. Humphreys. 2012. “The impact of professional sports facilities on housing values: Evidence from census block group data.” City Culture Soc. 3 (3): 189–200. https://doi.org/10.1016/j.ccs.2012.06.017.
Feng, Y., and K. Jones. 2015. “Comparing multilevel modelling and artificial neural networks in house price prediction.” In Proc., 2nd IEEE Int. Conf. on Spatial Data Mining and Geographical Knowledge Services, 108–114. New York: IEEE.
Gaglione, F., C. Gargiulo, F. Zucaro, and C. Cottrill. 2022. “Urban accessibility in a 15-minute city: A measure in the city of Naples, Italy.” Transp. Res. Procedia 60: 378–385. https://doi.org/10.1016/j.trpro.2021.12.049.
Ghanbari, R., M. Heidarimozaffar, A. Soltani, and H. Arefi. 2023. “Land surface temperature analysis in densely populated zones from the perspective of spectral indices and urban morphology.” Int. J. Environ. Sci. Technol. 20: 2883–2902. https://doi.org/10.1007/s13762-022-04725-4.
Heroy, S., I. Loaiza, A. Pentland, and N. O’Clery. 2022. “Are neighbourhood amenities associated with more walking and less driving? Yes, but only for the wealthy.” Preprint, submitted January 18, 2022. https://doi.org/10.48550/arXiv.2201.07184.
Hu, M., Z. Lin, and Y. Liu. 2023. “Amenities, housing affordability, and education elites.” J. Real Estate Finance Econ. 66: 141–168.
Huang, Z., R. Chen, D. Xu, and W. Zhou. 2017. “Spatial and hedonic analysis of housing prices in Shanghai.” Habitat Int. 67: 69–78. https://doi.org/10.1016/j.habitatint.2017.07.002.
Hussain, T., J. Abbas, Z. Wei, S. Ahmad, B. Xuehao, and Z. Gaoli. 2021. “Impact of urban village disamenity on neighboring residential properties: Empirical evidence from Nanjing through hedonic pricing model appraisal.” J. Urban Plann. Dev. 147 (1): 04020055. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000645.
Iban, M. C. 2022. “An explainable model for the mass appraisal of residences: The application of tree-based machine learning algorithms and interpretation of value determinants.” Habitat Int. 128: 102660. https://doi.org/10.1016/j.habitatint.2022.102660.
Jang, M., and C.-D. Kang. 2015. “Retail accessibility and proximity effects on housing prices in Seoul, Korea: A retail type and housing submarket approach.” Habitat Int. 49: 516–528. https://doi.org/10.1016/j.habitatint.2015.07.004.
Kang, C.-D. 2019. “Effects of spatial access to neighborhood land-use density on housing prices: Evidence from a multilevel hedonic analysis in Seoul, South Korea.” Environ. Plann. B: Urban Anal. City Sci. 46 (4): 603–625. https://doi.org/10.1177/2399808317721184.
Keskin, B. 2022. “Multilevel approach to the analysis of housing submarkets.” J. Reg. Stud. Reg. Sci. 9 (1): 264–279. https://doi.org/10.1080/21681376.2022.2067005.
Kim, D., and J. Jin. 2019. “The effect of land use on housing price and rent: Empirical evidence of job accessibility and mixed land use.” Sustainability 11 (3): 938. https://doi.org/10.3390/su11030938.
Kok, N., P. Monkkonen, and J. M. Quigley. 2014. “Land use regulations and the value of land and housing: An intra-metropolitan analysis.” J. Urban Econ. 81: 136–148. https://doi.org/10.1016/j.jue.2014.03.004.
Kovacs, K. F. 2012. “Integrating property value and local recreation models to value ecosystem services from regional parks.” Landscape Urban Plann. 108 (2–4): 79–90. https://doi.org/10.1016/j.landurbplan.2012.08.002.
Lan, F., Q. Wu, T. Zhou, and H. Da. 2018. “Spatial effects of public service facilities accessibility on housing prices: A case study of Xi’an, China.” Sustainability 10 (12): 4503. https://doi.org/10.3390/su10124503.
Leishman, C. 2009. “Spatial change and the structure of urban housing sub-markets.” Hous. Stud. 24 (5): 563–585. https://doi.org/10.1080/02673030903082310.
Leishman, C., G. Costello, and S. Rowley. 2013. “The predictive performance of multilevel models of housing submarkets: A comparative analysis.” Urban Stud. 50 (6): 1201–1220. https://doi.org/10.1177/0042098012466603.
Li, H., Y. D. Wei, Y. Wu, and G. Tian. 2019. “Analyzing housing prices in Shanghai with open data: Amenity, accessibility and urban structure.” Cities 91: 165–179.
Li, J., and H. Huang. 2020. “Effects of transit-oriented development (TOD) on housing prices: A case study in Wuhan, China.” Res. Transp. Econ. 80: 100813. https://doi.org/10.1016/j.retrec.2020.100813.
Liu, T., W. Hu, Y. Song, and A. Zhang. 2020. “Exploring spillover effects of ecological lands: A spatial multilevel hedonic price model of the housing market in Wuhan, China.” Ecol. Econ. 170: 106568. https://doi.org/10.1016/j.ecolecon.2019.106568.
Louati, A., R. Lahyani, A. Aldaej, A. Aldumaykhi, and S. Otai. 2022. “Price forecasting for real estate using machine learning: A case study on Riyadh city.” Concurrency Comput. Pract. Exper. 34 (6): e6748. https://doi.org/10.1002/cpe.6748.
Lux, M., and P. Sunega. 2022. “Pragmatic socioeconomics: A way towards new findings on sources of (housing) market instability.” Hous. Theory Soc. 39 (2): 129–146. https://doi.org/10.1080/14036096.2020.1853226.
Moghadam, A. S., A. Soltani, B. Parolin, and M. Alidadi. 2018. “Analysing the space-time dynamics of urban structure change using employment density and distribution data.” Cities 81: 203–213. https://doi.org/10.1016/j.cities.2018.04.009.
Moreno, C., Z. Allam, D. Chabaud, C. Gall, and F. Pratlong. 2021. “Introducing the ‘15-Minute City’: Sustainability, resilience and place identity in future post-pandemic cities.” Smart Cities 4 (1): 93–111. https://doi.org/10.3390/smartcities4010006.
MRUD (Ministry-of-Roads-and-Urban-Development). 2015. Comprehensive housing plan, consolidation document: Understanding the current situation, future perspective, strategic and executive document. Tehran, Iran: MRUD.
Naddafi, K., M. S. Hassanvand, M. Yunesian, F. Momeniha, R. Nabizadeh, S. Faridi, and A. Gholampour. 2012. “Health impact assessment of air pollution in megacity of Tehran, Iran.” Iran. J. Environ. Health Sci. Eng. 9 (1): 1–7. https://doi.org/10.1186/1735-2746-9-28.
Nasehi, S., A. Yavari, E. Salehi, and R. Emmanuel. 2022. “Role of local climate zone and space syntax on land surface temperature (case study: Tehran).” Urban Clim. 45: 101245. https://doi.org/10.1016/j.uclim.2022.101245.
Nazmfar, H., S. Alavi, B. Feizizadeh, R. Masodifar, and A. Eshghei. 2020. “Spatial analysis of security and insecurity in urban parks: A case study of Tehran, Iran.” Prof. Geogr. 72 (3): 383–397. https://doi.org/10.1080/00330124.2019.1696686.
Nicoletti, L., M. Sirenko, and T. Verma. 2022. “Disadvantaged communities have lower access to urban infrastructure.” Preprint, submitted March 25, 2022. https://doi.org/10.48550/arXiv.2203.13784.
Osland, L., J. Östh, and V. Nordvik. 2022. “House price valuation of environmental amenities: An application of GIS-derived data.” Reg. Sci. Policy Pract. 14 (4): 939–959.
Qadikolaei, M. R., N. Zali, and A. Soltani. 2022. “Spatiotemporal investigation of the digital divide, the case study of Iranian Provinces.” Environ. Dev. Sustainability. 22 (3): 70–86. https://doi.org/10.1007/s10668-022-02738-0.
Rosen, S. 1974. “Hedonic prices and implicit markets: Product differentiation in pure competition.” J. Polit. Econ. 82: 34–55. https://doi.org/10.1086/260169.
SCI (Statistical Center of Iran). 2021. Accessed November 18, 2022. www.amar.org.ir.
Soltani, A., M. Heydari, F. Aghaei, and C. J. Pettit. 2022. “Housing price prediction incorporating spatio-temporal dependency into machine learning algorithms.” Cities 131: 103941. https://doi.org/10.1016/j.cities.2022.103941.
Soltani, A., M. Hosseinpour, and A. Hajizadeh. 2017. “Urban sprawl in Iranian medium-sized cities; investigating the role of masterplans.” J. Sustainable Dev. 10: 122–131. https://doi.org/10.5539/jsd.v10n1p122.
Soltani, A., C. J. Pettit, M. Heydari, and F. Aghaei. 2021. “Housing price variations using spatio-temporal data mining techniques.” J. Hous. Built Environ. 36: 1199–1227.
Sotomayor, L., D. Tarhan, M. Vieta, S. McCartney, and A. Mas. 2022. “When students are house-poor: Urban universities, student marginality, and the hidden curriculum of student housing.” Cities 124: 103572. https://doi.org/10.1016/j.cities.2022.103572.
Tan, R., Q. He, K. Zhou, Y. Song, and H. Xu. 2019. “Administrative hierarchy, housing market inequality, and multilevel determinants: A cross-level analysis of housing prices in China.” J. Hous. Built Environ. 34 (3): 845–868. https://doi.org/10.1007/s10901-019-09690-y.
Tehran Municipality. 2021. “Housing statistics.” Accessed December 9, 2022. https://data.tehran.ir.
Tian, G., Y. D. Wei, and H. Li. 2017. “Effects of accessibility and environmental health risk on housing prices: A case of Salt Lake County, Utah.” Appl. Geogr. 89: 12–21. https://doi.org/10.1016/j.apgeog.2017.09.010.
Treg, C. 2010. “A multilevel property hedonic approach to valuing parks and open space.” Thesis, Dept. of Economics, Univ. of Vermont.
Wen, H., Y. Zhang, and L. Zhang. 2014. “Do educational facilities affect housing price? An empirical study in Hangzhou, China.” Habitat Int. 42: 155–163. https://doi.org/10.1016/j.habitatint.2013.12.004.
Wu, C., X. Ye, Q. Du, and P. Luo. 2017. “Spatial effects of accessibility to parks on housing prices in Shenzhen, China.” Habitat Int. 63: 45–54. https://doi.org/10.1016/j.habitatint.2017.03.010.
Wu, J., M. Wang, W. Li, J. Peng, and L. Huang. 2015. “Impact of urban green space on residential housing prices: Case study in Shenzhen.” J. Urban Plann. Dev. 141 (4): 05014023. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000241.
Yang, J., Y. Bao, Y. Zhang, X. Li, and Q. Ge. 2018. “Impact of accessibility on housing prices in Dalian city of China based on a geographically weighted regression model.” Chin. Geogr. Sci. 28 (3): 505–515. https://doi.org/10.1007/s11769-018-0954-6.
Yang, L., K. Chau, W. Szeto, X. Cui, and X. Wang. 2020. “Accessibility to transit, by transit, and property prices: Spatially varying relationships.” Transp. Res. Part D: Transp. Environ. 85: 102387. https://doi.org/10.1016/j.trd.2020.102387.
Yousefi, S., and I. Farahani. 2022. “Spatial inequality in Tehran, a structural explanation.” Urban Res. Pract. 15 (1): 25–46. https://doi.org/10.1080/17535069.2019.1699596.
Yuan, F., Y. D. Wei, and J. Wu. 2020. “Amenity effects of urban facilities on housing prices in China: Accessibility, scarcity, and urban spaces.” Cities 96: 102433. https://doi.org/10.1016/j.cities.2019.102433.
Zali, N., F. H. Ghal’ejough, and Y. Esmailzadeh. 2016. “Analyzing urban sprawl of Tehran metropolis in Iran (during 1956–2011).” Anu. do Inst. de Geociênc. 39 (3): 55–62. https://doi.org/10.11137/2016_3_55_62.
Zali, N., A. Tajiik, and M. Gholipour. 2014. “An application of AHP for physical sustainability assessment on New Town of Andisheh, Tehran-Iran.” Raega-O Espaço Geográfico em Análise 31: 69–90. https://doi.org/10.5380/raega.v31i0.31449.
Zhang, L., T. Zhou, and C. Mao. 2019. “Does the difference in urban public facility allocation cause spatial inequality in housing prices? Evidence from Chongqing, China.” Sustainability 11 (21): 6096. https://doi.org/10.3390/su11216096.
Zhang, T., and P. J. Burke. 2022. ‘“The effect of gasoline prices on suburban housing values in China.”’ China Econ. Rev. 72: 101762. https://doi.org/10.1016/j.chieco.2022.101762.
Information & Authors
Information
Published In
Journal of Urban Planning and Development
Volume 149 • Issue 4 • December 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Nov 16, 2022
Accepted: Apr 5, 2023
Published online: Jul 17, 2023
Published in print: Dec 1, 2023
Discussion open until: Dec 17, 2023
ASCE Technical Topics:
- Buildings
- Business management
- Contracts and subcontracts
- Developing countries
- Engineering fundamentals
- Field tests
- Housing
- Infrastructure
- Practice and Profession
- Pricing
- Residential buildings
- Residential location
- Structural engineering
- Structures (by type)
- Tests (by type)
- Traffic congestion
- Traffic engineering
- Traffic management
- Transportation engineering
- Urban and regional development
- Urban areas
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.