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House Price Growth Interdependencies and Comovement

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Abstract

This paper examines house price comovement across U.S. metropolitan areas (MSAs). We develop a Markov-switching framework that includes a spatial similarity element based on distances between MSAs. Our approach allows for house price comovements that occur due to similar timing of downturns across groups or clusters of MSAs. The inclusion of the spatial element improves the model fit compared to a standard endogenous clustering model. We find seven clusters of MSAs, where each cluster experiences idiosyncratic house price downturns, plus one distinct national house price cycle. Notably, only the housing downturn associated with the Great Recession spread across all the MSAs in our sample; all other house price downturns remained contained to a single cluster. We also identify MSA economic and geographic characteristics that correlate with cluster membership. In addition, while prior research has found housing and business cycles to be related closely at the national level, we find very different house price comovement and employment comovement across clusters and across MSAs.

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  • Jeffrey P. Cohen & Cletus C. Coughlin & Daniel Soques, 2019. "House Price Growth Interdependencies and Comovement," Working Papers 2019-028, Federal Reserve Bank of St. Louis, revised 11 Jan 2021.
    • Handle: RePEc:fip:fedlwp:2019-028
    DOI: 10.20955/wp.2019.028
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    More about this item

    Keywords

    housing price cycles; Markov-switching; cluster analysis; comovement; spatial dependence;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General

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