Spatial Analysis of the Affecting Factors on Housing Prices in Tehran Metropolis

Subject Areas : Regional Planning

Ahmad Hajiheidari ¹ , Bakhtyar ezatpanah ² , Abolfazl Meshkini ³

1 - Department of Geography and urban planning, Marand Branch, Islamic Azad university, Marand, Iran.
2 - Assistant Professor of Department of Geography and urban planning, Marand branch, Islamic azad university, Marand, Iran.
3 - Associate Professor of Department of Geography and urban planning, University of Tarbiat Modares, Tehran, Iran.

Received: 2020-12-23 Accepted : 2021-04-29 Published : 2022-12-22

Keywords: Supply and Demand, housing, Tehran metropolis, Rent, Economic Fluctuation,

Abstract :

Among the different areas of Tehran, the distinctive and colorful role of several thriving and high-income areas in the north with high volume of construction and sales, the role of price drivers as the first hypothesis of the present study and factors affecting the level of demand and supply. This research is applied in terms of purpose and descriptive-analytical in terms of method. In this research, using spatial statistics technique in Arc GIS environment, the subject was analyzed and studied. To extract the data used in this section from the statistics and information of the Statistics Center of the country and studies of detailed plans of regions (urban land use) as well as reports of the Central Bank of the Islamic Republic of Iran, General Directorate of Economic Statistics (2006-2017), economic and social situation report. The results of the study of construction activities in urban areas of Tehran and the results of statistics on the cost and income of urban households and the authors' calculations and its conversion into cross-sectional data have been used. According to the results of Moran test, the existence of spatial effects on the difference in housing prices in the 22 districts of Tehran metropolis with three factors of distance, degree of concentration and topographic factor is confirmed at a high level of significance. According to the results of the spatial autocorrelation coefficient, the price fluctuation shock in one area has spread to other areas of Tehran metropolis. In other words, in spatial autocorrelation coefficient, among 521556 residential land use units in the neighborhoods and areas of Tehran metropolis, its price fluctuation and amplitude is strongly a function of the topography and stereotype of Balashahr-Paeinshahr in the popular literature of urban economics. So that among the 374 neighborhoods surveyed in the 22 regions of regions 1, 3, 2, 6, 5 and 4, the highest housing prices and regions 12, 15, 18, 11 and 16 have the lowest range of fluctuations and the lowest housing prices in the decade. Experimented 85-95.

References:

• Anamoradnejad, Rahim Bardi. (2015). Evaluation of quantitative and qualitative characteristics of housing in Iran during 1345-1390. Journal of Research and Urban Planning, 6 (20), 35-50. (In Persian)


• Abedin Darkoush, Saeed, and Rahimian, Sara (2009). Analysis of factors affecting housing prices in urban areas of Iran during the period (1370-1385): with emphasis on urban grouping. Housing Economics Quarterly, 46, pp. 37-11. (In Persian)


• Altuzarra, A., & Esteban, M. (2011). Land prices and housing prices: the case of Spain. Journal of Housing and the Built Environment, 26(4), 397.


• Asgari, H., Almasi, I. (2011). Factors affecting the price of housing in urban areas using panel data (during the 1370 to 1385). Economics Research, 11(41), 201-224. (In Persian)


• Awwad, R., & El Khoury, K. (2012). Assessment of sustainable construction in Lebanon. In ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction (Vol. 29, p. 1). IAARC Publications.


• Baltagi, B. H., and G. Bresson (2011), “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”, Journal of Urban Economics, 69(1), 24–42. https: //doi.org/10.1016/j.jue.2010.08.007


• Bazgeer, S., Firoozi, Z., Shamsipour, A., Moghbel, M. (2019). Spatial Analysis of Environmental Conditions for Urban Agriculture in Tehran Metropolis (Case Study: District 5). Geographical Urban Planning Research (GUPR), 7(1), 111-125. (In Persian)


• Chen, K., Long, H., & Qin, C. (2020). The impacts of capital deepening on urban housing prices: Empirical evidence from 285 prefecture-level or above cities in China. Habitat International, 99, 102173.


• Chen, Q., Feng, L., Li, Z., & Lin, C. Y. (2020). Housing prices and trade surpluses in China: An inter-temporal approach. Journal of International Money and Finance, 110, 102284.


• Dunkerley, H. B. (1983). Urban land policy: Issues and opportunities (No. 13338, p. 1). The World Bank.


• Esfandiari, Marzieh (2004). Estimation of Hedanik Housing Price Function in Isfahan between 1992-1977, Journal of the Faculty of Administrative Sciences and Economics, University of Isfahan, Volume 16, Numbers 3 and 4, pp. 121-139. (In Persian)


• Farahmand, Shokoofeh and Foroughi, Ferdows (1390). Spatial Analysis of Factors Affecting Housing Price in Iran Geographical Weight Regression Approach, Third Conference on Urban Planning and Management, Mashhad https: //civilica.com/doc/125037(In Persian)


• fanni, Z., kuzegar, L., samanimajd, A. (2020). Comparative analysis of indicators of sustainable housing and urban renewal in old tissue (Abatik and Punak Neighborhood Study). Uban Planning, 11(42), 137-152. (In Persian)


• Ghaderi J, Eslamloueyan K, Owjimehr S. (2011). Economic Determinants of Housing investment in Iran. QJER; 11 (3): 47-70(In Persian)


• Hatami Nejad, Hossein, Vahedian Beki, Leila and Ziba Pernon (2014). "Assessing the Spatial Distribution Pattern of Urban Services in Tehran's Panj District Using Entropy and Williamson Model", Geographical Research Quarterly, No. 3, pp. 17-28. (In Persian)


• Hjalmarsson, E., & Österholm, P. (2020). Heterogeneity in households’ expectations of housing prices–evidence from micro data. Journal of Housing Economics, 50, 101731.


• Khajeh Shahkoohi, Alireza and Mahdavi, Shahram (2012). Analysis of effective factors in increasing land prices in urban areas (Case study: Kashan). Journal of New Attitudes in Human Geography, 4 (4), 153-169. (In Persian)


• Khakpour, D., Samadi, R. (2014). Analysis and Evaluation of Factors Affecting Land and Housing Prices in District No. 3 of Mashhad City. Geography and Territorial Spatial Arrangement, 4(13), 21-38. (In Persian)


• Khalili Iraqi, Seyed Mansour; Mehrara, Mohsen and Azimi, Seyed Reza (2012). Investigating the Factors Affecting Housing Price in Iran Using Combined Data. Quarterly Journal of Economic Research and Policy, 63, pp. 50-33. (In Persian)


• Khandan, M., Jahanshahloo, L., Zabihi, H. (2019). Analyze the factors affecting the increase of urban land rent in district one in Tehran metropolitan. Geography (Regional Planning), 9(2), 255-239. (In Persian)


• Mehregan, Nader, and Tartar, Mohsen (2014). Short-term and long-term effects of costs on housing prices in Tehran. Housing Economics, 50, pp. 68-45. (In Persian)


• Mohamadzadeh, P., Panahi, H., Aleemran, S. (2016). The Relationship between Land Prices and Housing Prices in Iran. Quarterly Journal of Applied Theories of Economics, 3(1), 89-114. (In Persian)


• Moameri, E., Farrokhzad, M., Sayyad Salar, Y. (2020). Measuring physical indicators of urban housing (Case Study: Gorgan). Urban Panning, 10(39), 135-144. (In Persian)


• Motavasseli M, Mohammadi S, Doroudeyan H. (2010). Diffusion of House Price Dynamics in Tehran: Using Spatial Autoregressive and Vector Error-Correction Models. QJER.; 10 (1), pp. 55-83. (In Persian)


• Motavasseli M, Mohammadi S, Doroudeyan H. (2010). Diffusion of House Price Dynamics in Tehran: Using Spatial Autoregressive and Vector Error-Correction Models. QJER; 10 (1), pp. 118-138. (In Persian)


• Pourmohammadi, M., Ghorbani, R., Taghipour, A. (2014). The Estimation of Hedonic Price Model for Tabriz City. Geographical Planning of Space, 3(9), 83-105. (In Persian)


• Rahnama, Mohammad Rahim, Asadi, Amir, and Rousta, Mojtaba (2013). Analysis of spatial distribution of land prices in Mashhad. Zagros Landscape Geography and Urban Planning Quarterly, 18, pp. 106-87. (In Persian)


• Rennie short, J. 2006. Urban Theory a Critical Assessment, Rutledge.


• Shojaei, Reyhaneh Sadat (2010). Investigating the relationship between land prices and urban land use in Tehran (three neighborhoods of Jamalabad, Yousefabad, Yakhchiabad), Journal of Housing Economics, 46, pp. (In Persian)


• Soheili K, Fattahi S, Ovaisi B. (2014). A Survey of Factors Affecting Fluctuations of Housing Prices in Kermanshah. QJER; 14 (2): 41-67 (In Persian)


• Statistical Yearbook of Tehran (2017). Tehran Municipality Information and Communication Technology Organization www.tehran.ir (In Persian)


• Statistics Center of Iran (2000-2013). Results of statistics on the expenditure and income of urban households. (In Persian)


• Taleblou, R., Mohammadi, T., Pirdayeh, H. (2017). Analysis of Spatial Diffusion of Housing Price Changes in Iranian Provinces; Spatial Econometrics Approach. Economics Research, 17(66), 55-95. (In Persian)


• Vassaf, Esmaeil (2008). "Study of urban space price system: Hadanik price function approach (Case study: Mashhad city)", Master Thesis in Economics, Faculty of Economics, Allameh Tabatabai University. (In Persian)


• Yang, Z., & Pan, Y. (2020). Human capital, housing prices, and regional economic development: Will “vying for talent” through policy succeed? Cities, 98, 102577.


• Yazdani Borujeni, Fardin (1996) Estimation of demand function for housing characteristics in urban areas, application of Hadanik price model Case: Shahrekord, Chaharmahal and Bakhtiari province, Master Thesis in Economic Systems Planning, Shiraz University. (In Persian)


• Zhang, J., Li, H., Lin, J., Zheng, W., Li, H., & Chen, Z. (2020). Meta-analysis of the relationship between high quality basic education resources and housing prices. Land Use Policy, 99, 104843.


• Ziari, Yousef Ali (2013). Investigating the effect of land price on the city's spatial organization (Case study: District 5 of District 1 of Tehran during 1995-2004). City Identity, 14, pp. 60-49. (In Persian).