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Housing Demand in Tokyo



Housing policy formulation should be informed by a careful understanding of the behaviour of the housing market, as reflected by housing demand. Such basic information is important, not only for improved project design but also for the development of better sector-wide policies. Housing is a complex outcome of cultural, economic and regulatory environment. Consistent estimates of price and income elasticity of housing demand are prerequisites for effective policy design. Results, from earlier studies on Japanese housing markets, are inconclusive and the estimates of price and income elasticity of housing demand vary over a wide range. It may be argued that measuring the volume of housing services as housing expenditure, as is done in previous research, essentially ignores the heterogeneity, and for large number of policy purposes like impact of tax on tenure choice, choice between owning and renting etc., the distribution of housing consumption into qualitatively different categories is of more interest than an aggregate qualitative measure of housing expenditure alone. This paper analyzes the demand for housing in Tokyo using a discrete choice model. Three dimensions of choice, tenure, dwelling size (as number of rooms) and structure type (as type of unit) determine demand for housing which are modeled simultaneously. The income elasticity of market share of ownership house is positive and ranges between 0.16 to 0.34. However, income elasticity for rental houses is negative ranging between -0.17 to -0.57. The own price elasticities vary over a large range from -0.03 to -5.1 with smaller in magnitude for ownership houses and larger for rental houses.

Suggested Citation

  • Piyush Tiwari, 2000. "Housing Demand in Tokyo," International Real Estate Review, Asian Real Estate Society, vol. 3(1), pages 65-92.
  • Handle: RePEc:ire:issued:v:03:n:01:2000:p:65-92

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    References listed on IDEAS

    1. Garber, Peter M, 1990. "Famous First Bubbles," Journal of Economic Perspectives, American Economic Association, vol. 4(2), pages 35-54, Spring.
    2. Manuel Gottlieb, 1976. "Long Swings in Urban Development," NBER Books, National Bureau of Economic Research, Inc, number gott76-1, January.
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    4. Clapp John M. & Giaccotto Carmelo, 1994. "The Influence of Economic Variables on Local House Price Dynamics," Journal of Urban Economics, Elsevier, vol. 36(2), pages 161-183, September.
    5. Smith, Lawrence B. & Ho, Michael H. C., 1996. "The Relative Price Differential between Higher and Lower Priced Homes," Journal of Housing Economics, Elsevier, vol. 5(1), pages 1-17, March.
    6. Karl E. Case & Robert J. Shiller, 1990. "Forecasting Prices and Excess Returns in the Housing Market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 18(3), pages 253-273.
    7. Hali J. Edison & Pongsak Luangaram & Marcus Miller, 1998. "Asset bubbles, domino effects and 'lifeboats': elements of the East Asian crisis," International Finance Discussion Papers 606, Board of Governors of the Federal Reserve System (U.S.).
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    Cited by:

    1. 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.
    2. Tan, Teck Hong, 2011. "Measuring the willingness to pay for houses in a sustainable neighborhood," MPRA Paper 30446, University Library of Munich, Germany.
    3. Berry Blijie, 2005. "The impact of accessibility on residential choice - empirical results of a discrete choice model," ERSA conference papers ersa05p626, European Regional Science Association.
    4. Deutsch, Edwin & Tiwari, Piyush & Moriizumi, Yoko, 2006. "The slowdown in the timing of housing purchases in Japan in the 1990s," Journal of Housing Economics, Elsevier, vol. 15(3), pages 230-256, September.
    5. 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.

    More about this item


    Housing demand; Discrete choice model; Nested Multinomial Logit Model;

    JEL classification:

    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services


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