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Clustered housing cycles

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Author Info

  • Rubén Hernández-Murillo
  • Michael T. Owyang
  • Margarita Rubio

Abstract

Past studies have argued that housing is an important driver of business cycles. Housing markets, however, are highly localized, while business cycles are often measured at the national level. We model a national housing cycle using a panel of cities while also allowing for idiosyncratic departures from the national cycle. These departures occur for clusters of cities that experience simultaneous idiosyncratic housing recessions. We estimate the clustered Markov-switching model proposed in Hamilton and Owyang (2012) using city-level building permits data, a series commonly used at the national level as a business cycle indicator. 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 the average winter temperature and the unemployment rate) appear to be more important determinants of cyclical comovements than similarities in factors affecting the supply for housing (such as housing density and geographic constraints in the availability of developable land).

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Bibliographic Info

Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2013-021.

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Date of creation: 2013
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Handle: RePEc:fip:fedlwp:2013-021

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Keywords: Business cycles ; Housing ; Economic indicators;

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References

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  1. Andra C. Ghent & Michael T. Owyang, 2009. "Is housing the business cycle? evidence from U.S. cities," Working Papers 2009-007, Federal Reserve Bank of St. Louis.
  2. James D. Hamilton & Michael T. Owyang, 2009. "The propagation of regional recessions," Working Papers 2009-013, Federal Reserve Bank of St. Louis.
  3. Matteo Iacoviello, 2002. "House prices, borrowing constraints and monetary policy in the business cycle," Boston College Working Papers in Economics 542, Boston College Department of Economics, revised 06 Dec 2004.
  4. Michael T. Owyang & Jeremy M. Piger & Howard J. Wall & Christopher H. Wheeler, 2007. "The economic performance of cities: a Markov-switching approach," Working Papers 2006-056, Federal Reserve Bank of St. Louis.
  5. Edward E. Leamer, 2007. "Housing IS the Business Cycle," NBER Working Papers 13428, National Bureau of Economic Research, Inc.
  6. Matteo Iacoviello & Stefano Neri, 2008. "Housing market spillovers : evidence from an estimated DSGE model," Working Paper Research 145, National Bank of Belgium.
  7. Frühwirth-Schnatter, Sylvia & Kaufmann, Sylvia, 2004. "Model-based Clustering of Multiple Time Series," CEPR Discussion Papers 4650, C.E.P.R. Discussion Papers.
  8. Michael T. Owyang & Jeremy Piger & Howard J. Wall, 2005. "Business Cycle Phases in U.S. States," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 604-616, November.
  9. Emanuel Moench & Serena Ng, 2011. "A hierarchical factor analysis of U.S. housing market dynamics," Econometrics Journal, Royal Economic Society, vol. 14(1), pages C1-C24, February.
  10. Sylvia Kaufmann, 2010. "Dating and forecasting turning points by Bayesian clustering with dynamic structure: a suggestion with an application to Austrian data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 309-344.
  11. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
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Cited by:
  1. Corradin, Stefano & Fontana, Alessandro, 2013. "House price cycles in Europe," Working Paper Series 1613, European Central Bank.

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