House Price Growth Interdependencies and Comovement

Jeffrey Cohen, Cletus Coughlin and Daniel Soques

No 2019-028, Working Papers from Federal Reserve Bank of St. Louis

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.

Keywords: housing price cycles; Markov-switching; cluster analysis; comovement; spatial dependence (search for similar items in EconPapers)
JEL-codes: C3 R30 (search for similar items in EconPapers)
Pages: 35 pages
Date: 2019-09-25, Revised 2021-01-11
New Economics Papers: this item is included in nep-ore and nep-ure
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DOI: 10.20955/wp.2019.028

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