IDEAS home Printed from https://ideas.repec.org/a/ire/issued/v03n012000p65-92.html
   My bibliography  Save this article

Housing Demand in Tokyo

Author

Abstract

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, Global Social Science Institute, vol. 3(1), pages 65-92.
  • Handle: RePEc:ire:issued:v:03:n:01:2000:p:65-92
    as

    Download full text from publisher

    File URL: https://www.gssinst.org/irer/wp-content/uploads/2020/10/2000-Vol-3-No-1-Housing-Demand.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alla Koblyakova & Larisa Fleishman & Orly Furman, 2022. "Accuracy of Households’ Dwelling Valuations, Housing Demand and Mortgage Decisions: Israeli Case," The Journal of Real Estate Finance and Economics, Springer, vol. 65(1), pages 48-74, July.
    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. Tan, Teck Hong, 2011. "Measuring the willingness to pay for houses in a sustainable neighborhood," MPRA Paper 30446, University Library of Munich, Germany.
    4. Yuta Kanno & Takayuki Shiohama, 2022. "Land price polarization and dispersion in Tokyo: a spatial model approach," Asia-Pacific Journal of Regional Science, Springer, vol. 6(2), pages 807-835, June.
    5. 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.
    6. 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.
    7. 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

    Keywords

    Housing demand; Discrete choice model; Nested Multinomial Logit Model;
    All these keywords.

    JEL classification:

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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ire:issued:v:03:n:01:2000:p:65-92. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: IRER Graduate Assistant/Webmaster (email available below). General contact details of provider: https://www.gssinst.org/gssinst/index.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.