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Spatial Market Inefficiency in Housing Market: A Spatial Quantile Regression Approach

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  • Jiyoung Chae

    (Federal Reserve Bank of Richmond)

  • Anil K. Bera

    (University of Illinois at Urbana-Champaign)

Abstract

This paper empirically tests housing market efficiency in the spatial dimension by using the spatial autoregressive conditional heteroskedastic (ARCH) and spatial quantile regression models. The tests were conducted in terms of both housing returns and squared returns (volatility). The sale price data used is from Cook County residential MLS for the years 2010–2016. The main findings are that housing returns are not spatially correlated but squared returns are spatially correlated, and the spatial dependence of squared returns seems to be stronger for higher squared return quantiles.

Suggested Citation

  • Jiyoung Chae & Anil K. Bera, 2024. "Spatial Market Inefficiency in Housing Market: A Spatial Quantile Regression Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 69(1), pages 70-99, July.
    • Handle: RePEc:kap:jrefec:v:69:y:2024:i:1:d:10.1007_s11146-022-09923-y
    DOI: 10.1007/s11146-022-09923-y
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    More about this item

    Keywords

    Housing market; Market efficiency; Spatial dependence; Spatial volatility clustering; Spatial quantile regression;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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