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Geographic Heterogeneity in Housing. Evidence from Spain

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  • Raquel ArÈvalo TomÈ
  • JosÈ MarÌa Chamorro Rivas

Abstract

This article offers an empirical analysis of geographical differences in the characteristics of housing in the different provinces of Spain. The study employs multiple correspondence analysis to derive a housing index, in line with ArÈvalo (1999). While ArÈvalo used only structural variables, this research also includes proxy variables for access to services derived from the location of the living unit. A readily interpretable index is thus created, which measures the level of internal and external services that a living unit (house or apartment) provides for its occupiers. The results confirm that characteristics derived from location are complementary to structural characteristics of the living unit itself (housing services). Moreover, with the addition of location variables, the new housing index shows: (i) increased correlation with observed rental and house prices, and (ii) a more realistic view of geographical differences in the level of services of Spanish housing. The study contributes new housing indicators that are easily applicable, for example, in studies on household quality of life, social exclusion, and poverty.

Suggested Citation

  • Raquel ArÈvalo TomÈ & JosÈ MarÌa Chamorro Rivas, "undated". "Geographic Heterogeneity in Housing. Evidence from Spain," Studies on the Spanish Economy 203, FEDEA.
  • Handle: RePEc:fda:fdaeee:203
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    1. W. Erwin Diewert & Saeed Heravi & Mick Silver, 2009. "Hedonic Imputation versus Time Dummy Hedonic Indexes," NBER Chapters,in: Price Index Concepts and Measurement, pages 161-196 National Bureau of Economic Research, Inc.
    2. Raquel Arévalo-Tomé, 1999. "Construcción de un índice de calidad de la vivienda," Investigaciones Economicas, Fundación SEPI, vol. 23(2), pages 267-280, May.
    3. Michael Greenacre, 2008. "Correspondence analysis of raw data," Economics Working Papers 1112, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2009.
    4. Michel Tenenhaus & Forrest Young, 1985. "An analysis and synthesis of multiple correspondence analysis, optimal scaling, dual scaling, homogeneity analysis and other methods for quantifying categorical multivariate data," Psychometrika, Springer;The Psychometric Society, vol. 50(1), pages 91-119, March.
    5. W. Erwin Diewert, 2003. "Hedonic Regressions. A Consumer Theory Approach," NBER Chapters,in: Scanner Data and Price Indexes, pages 317-348 National Bureau of Economic Research, Inc.
    6. Silver, Mick & Heravi, Saeed, 2007. "The Difference Between Hedonic Imputation Indexes and Time Dummy Hedonic Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 239-246, April.
    7. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    8. Hubert, Franz, 1995. "Contracting with costly tenants," Regional Science and Urban Economics, Elsevier, vol. 25(5), pages 631-654, October.
    9. Edward Shinnick, 1997. "Measuring Irish housing quality," Journal of Economic Studies, Emerald Group Publishing, vol. 24(1/2), pages 95-119, January.
    10. Arévalo, Raquel & Ruiz-Castillo, Javier, 2004. "The rental equivalence approach to nonrental housing in the consumer price index. evidence from Spain," UC3M Working papers. Economics we041704, Universidad Carlos III de Madrid. Departamento de Economía.
    11. Marvin L. Wolverton & Jimmy Senteza, 2000. "Hedonic Estimates of Regional Constant Quality House Prices," Journal of Real Estate Research, American Real Estate Society, vol. 19(3), pages 235-253.
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