IDEAS home Printed from https://ideas.repec.org/p/ecm/ausm04/266.html
   My bibliography  Save this paper

Spatial Clustering of Housing Construction in the Tokyo Metropolitan Area: An Application of Spatially Clustered Fixed-Effects and Spatially Correlated Random-Effects Models

Author

Listed:
  • Atsushi Yoshida
  • Tatsuhiro Shichijo

Abstract

We proposed two types of econometric models, a spatially clustered fixed-effects model (SCFEM) and a spatially correlated random-effects model (SCREM), to examine area-based panel data. We investigate what factors influence housing construction in the Tokyo Metropolitan Area, incorporating unobservable factors, local regulatory differences in housing development and spillovers of local public or private goods, which may cause spatial clustering or correlation of housing construction. The SCFEM is a type of fixed-effects model where a cluster has the same effects, so that we have to find which areas constitute a cluster. The issue of finding clusters can be regarded as a problem of model selection from too many possible models. We adopt an aggregate prediction error as a model selection criterion, which is estimated by a resampling method, namely leave-one-out cross-validation. We showed by simulations that the estimated parameters of concern are more efficient than the within estimates. The SCREM is a model where the random-effects are spatially correlated. We use the concentrated maximum likelihood method for the estimation. The unobservable area-effects are large in the east, west and north areas of the TMA but small in the south, where regulations against development are more severe than in the other areas. Clusters are found in huge cities

Suggested Citation

  • Atsushi Yoshida & Tatsuhiro Shichijo, 2004. "Spatial Clustering of Housing Construction in the Tokyo Metropolitan Area: An Application of Spatially Clustered Fixed-Effects and Spatially Correlated Random-Effects Models," Econometric Society 2004 Australasian Meetings 266, Econometric Society.
  • Handle: RePEc:ecm:ausm04:266
    as

    Download full text from publisher

    File URL: http://repec.org/esAUSM04/up.20796.1077874247.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Topel, Robert H & Rosen, Sherwin, 1988. "Housing Investment in the United States," Journal of Political Economy, University of Chicago Press, vol. 96(4), pages 718-740, August.
    2. Mayer, Christopher J. & Somerville, C. Tsuriel, 2000. "Residential Construction: Using the Urban Growth Model to Estimate Housing Supply," Journal of Urban Economics, Elsevier, vol. 48(1), pages 85-109, July.
    3. Pinkse, Joris & Slade, Margaret E., 1998. "Contracting in space: An application of spatial statistics to discrete-choice models," Journal of Econometrics, Elsevier, vol. 85(1), pages 125-154, July.
    4. DiPasquale Denise & Wheaton William C., 1994. "Housing Market Dynamics and the Future of Housing Prices," Journal of Urban Economics, Elsevier, vol. 35(1), pages 1-27, January.
    5. Gramlich, Edward M & Rubinfeld, Daniel L, 1982. "Micro Estimates of Public Spending Demand Functions and Tests of the Tiebout and Median-Voter Hypotheses," Journal of Political Economy, University of Chicago Press, vol. 90(3), pages 536-560, June.
    6. Janet S. Netz & Beck A. Taylor, 2002. "Maximum Or Minimum Differentiation? Location Patterns Of Retail Outlets," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 162-175, February.
    7. Aaronson, Daniel, 2001. "Neighborhood Dynamics," Journal of Urban Economics, Elsevier, vol. 49(1), pages 1-31, January.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    cluster-effects model; housing construction; area-based panel data; spatial correlation; spillover effects;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ecm:ausm04:266. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum). General contact details of provider: http://edirc.repec.org/data/essssea.html .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.