Federal Reserve Bank of St. Louis
Clustered housing cycles
Using a panel of U.S. city-level building permits data, we estimate a Markov-switching model of housing cycles that allows cities to systematically deviate from the national housing cycle. These deviations occur for clusters of cities that experience simultaneous housing contractions. We find that cities do not form housing regions in the traditional geographic sense. Instead, similarities in factors affecting the demand for housing (such as population growth or availability of credit) appear to be more important determinants of cyclical co-movements than similarities in factors affecting the supply for land (such as the availability of developable land or the elasticity of land supply).
Cite this item
Rubén Hernández-Murillo & Michael T. Owyang & Margarita Rubio, Clustered housing cycles, Federal Reserve Bank of St. Louis, Working Papers 2013-021, 2013, revised 10 May 2017.
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
Keywords: Business cycles; Housing; Economic indicators
This item with handle RePEc:fip:fedlwp:2013-021
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