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Affordability, Housing Demand and Housing Policy in Urban India

Author

Listed:
  • Piyush Tiwari

    (Housing Development Finance Corporation, Ramon House, 169 Backbay Reclamation, Mumbai 400 020, India, piyush@hdfcindia.com.)

  • Jyoti Parikh

    (Indira Gandhi Institute of Development Research Goregaon(E), Bombay 400 065, India)

Abstract

Designing housing policies and programmes requires a careful estimation of household affordability and demand for housing. The efficiency of housing subsidies would depend on price elasticities of housing demand. Different households have different perceptions of housing demand based on their economic and demographic factors. We estimate the demand function of housing for urban India using step econometric analysis. The first step estimates the hedonic price index for states and in the second step the demand for housing is estimated as a function of economic and household characteristics. The problem of multicollinearity is observed with the data. Ridge regressions are used to correct for multicollinearity and to obtain efficient estimates. The results indicate that the housing demand is inelastic with respect to income and price. The income elasticity is 0.75 while price elasticity is slightly less than — 1. A further analysis to estimate income and price elasticities for different income classes as well as states has also been carried out. We comment on the efficiency of housing subsidies based on our results. The paper concludes with some policy questions.

Suggested Citation

  • Piyush Tiwari & Jyoti Parikh, 1998. "Affordability, Housing Demand and Housing Policy in Urban India," Urban Studies, Urban Studies Journal Limited, vol. 35(11), pages 2111-2129, November.
    • Handle: RePEc:sae:urbstu:v:35:y:1998:i:11:p:2111-2129
    DOI: 10.1080/0042098984033
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    References listed on IDEAS

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    Cited by:

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    2. Ali Osman Solak & Burhan Kabadayi, 2016. "Bounds Testing Approaches to Housing Demand in Turkey: Is There a Real Estate Bubble?," International Journal of Economics and Financial Issues, Econjournals, vol. 6(3), pages 1132-1135.
    3. Ayaz Ahmad & Nasir Iqbal & Rehana Siddiqui, 2018. "Determinants of Housing Demand in Urban Areas of Pakistan: Evidence from the PSLM," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 57(1), pages 1-25.
    4. Saudamini Das & Arup Mitra & Rajnish Kumar, 2017. "Do neighbourhood facilities matter for slum housing? Evidence from Indian slum clusters," Urban Studies, Urban Studies Journal Limited, vol. 54(8), pages 1887-1904, June.
    5. Karmali,Nadeem M. & Aline Weng, 2022. "Housing Demand and Affordability in India : Implications for Housing Policy," Policy Research Working Paper Series 10031, The World Bank.
    6. Hon-Kwong Lui, 2007. "The Redistributive Effect of Public Housing in Hong Kong," Urban Studies, Urban Studies Journal Limited, vol. 44(10), pages 1937-1952, September.
    7. Pritam Ghosh & Asraful Alam & Nilanjana Ghosal & Debodatta Saha, 2021. "A Geospatial Analysis of Temporary Housing Inequality among Socially Marginalized and Privileged Groups in India," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(3), pages 798-819, June.
    8. Yuan, Feng & Wu, Jiawei & Wei, Yehua Dennis & Wang, Lei, 2018. "Policy change, amenity, and spatiotemporal dynamics of housing prices in Nanjing, China," Land Use Policy, Elsevier, vol. 75(C), pages 225-236.
    9. Tan, Teck Hong, 2011. "Measuring the willingness to pay for houses in a sustainable neighborhood," MPRA Paper 30446, University Library of Munich, Germany.
    10. Jingfeng Yuan & Xiaodan Zheng & Jia You & Mirosław J. Skibniewski, 2017. "Identifying Critical Factors Influencing the Rents of Public Rental Housing Delivery by PPPs: The Case of Nanjing," Sustainability, MDPI, vol. 9(3), pages 1-22, February.
    11. Bandyopadhyay, Arindam & Kuvalekar, S V & Basu, Sanjay & Baid, Shilpa & Saha, Asish, 2008. "A Study of Residential Housing Demand in India," MPRA Paper 9339, University Library of Munich, Germany.
    12. Talat Munshi, 2020. "Accessibility, Infrastructure Provision and Residential Land Value: Modelling the Relation Using Geographic Weighted Regression in the City of Rajkot, India," Sustainability, MDPI, vol. 12(20), pages 1-16, October.

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