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Use of a Gini index to examine housing price heterogeneity: A quantile approach

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  • Villar, Jaume García
  • Raya, Josep Maria

Abstract

This paper contributes to the existing literature that deals with the full distribution of house prices and its decomposition (primarily McMillen, 2008) by conducting a deeper analysis of housing price heterogeneity. Our approach differs from McMillen’s insofar as our goal is to explain the variation in housing prices at a point in time rather than over a period of time. The basic statistic used to summarise house price distribution is the Gini index, which compares the actual distribution of the price per square metre (PPSM) with a uniform distribution. We decompose the Gini index into what can be explained for by the explanatory variables (which can also be easily decomposed into the contribution of each explanatory variable) and what remained unexplained. With a data set that includes appraisal values for 9297 dwellings in Barcelona in 1998–2001, the part explained by the standard OLS slopes (up to 60%) suggests a high degree of homogeneity in the linkage between PPSM and the explanatory variables. In any event, when heterogeneity is introduced using a quantile approach, that part of the Gini index explained for by the regressors falls. Finally, the variable that produces the most heterogeneity is area.

Suggested Citation

  • Villar, Jaume García & Raya, Josep Maria, 2015. "Use of a Gini index to examine housing price heterogeneity: A quantile approach," Journal of Housing Economics, Elsevier, vol. 29(C), pages 59-71.
    • Handle: RePEc:eee:jhouse:v:29:y:2015:i:c:p:59-71
    DOI: 10.1016/j.jhe.2015.06.001
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    References listed on IDEAS

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    Cited by:

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    2. Jiansheng Wu & Junhao Zhou & Wen Zhang, 2020. "A Framework to Classify Environmental Inequity in Absolute and Relative Terms, and Its Application in Beijing," Sustainability, MDPI, vol. 12(11), pages 1-16, June.
    3. Anthony Orlando, 2018. "Asset Markets, Credit Markets, and Inequality: Distributional Changes in Housing, 1970-2016," ERES eres2018_182, European Real Estate Society (ERES).
    4. Jose Torres-Pruñonosa & Pablo García-Estévez & Josep Maria Raya & Camilo Prado-Román, 2022. "How on Earth Did Spanish Banking Sell the Housing Stock?," SAGE Open, , vol. 12(1), pages 21582440221, March.
    5. Jose Torres-Pruñonosa & Pablo García-Estévez & Camilo Prado-Román, 2021. "Artificial Neural Network, Quantile and Semi-Log Regression Modelling of Mass Appraisal in Housing," Mathematics, MDPI, vol. 9(7), pages 1-16, April.

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    More about this item

    Keywords

    Quantile regressions; Housing prices; Hedonic models; Gini index; Heterogeneity in housing prices;
    All these keywords.

    JEL classification:

    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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