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National, regional and metro-specific factors of the U.S. housing market

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  • Dong Fu

Abstract

We build a dynamic latent factor model to decompose housing prices in major U.S. metropolitan areas into national, regional, and metro-specific idiosyncratic factors, in order to distinguish the different dynamics behind housing price movements. We find that there is a distinctive national factor that has contributed about one-fourth of the individual metropolitan's housing price volatility. The regional factor accounts for another one-fourth and the idiosyncratic factor explains about half of housing price fluctuations. However, at the regional level, the factors' contributions vary across a fairly wide range. Although it only has modest explanatory power of housing price volatility, the national factor seems to account for much of the price increase in the current housing boom. Interestingly, the regional factor exerts negative influence on housing prices in a fairly large number of metros lately, only to be outweighed by the national factor's positive contribution. We also explore the possible forces influencing the national factor of housing price movements, including monetary policy, population growth, real economic activity, general inflation and other asset prices.

Suggested Citation

  • Dong Fu, 2007. "National, regional and metro-specific factors of the U.S. housing market," Working Papers 0707, Federal Reserve Bank of Dallas.
  • Handle: RePEc:fip:feddwp:0707
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    1. Ben S. Bernanke & Mark Gertler, 2001. "Should Central Banks Respond to Movements in Asset Prices?," American Economic Review, American Economic Association, vol. 91(2), pages 253-257, May.
    2. Refet S. Gürkaynak, 2008. "Econometric Tests Of Asset Price Bubbles: Taking Stock," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 166-186, February.
    3. Case Karl E. & Quigley John M. & Shiller Robert J., 2005. "Comparing Wealth Effects: The Stock Market versus the Housing Market," The B.E. Journal of Macroeconomics, De Gruyter, vol. 5(1), pages 1-34, May.
    4. Morris A. Davis, 2010. "housing and the business cycle," The New Palgrave Dictionary of Economics,, Palgrave Macmillan.
    5. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    6. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    7. Richard J. Rosen, 2005. "Explaining recent changes in home prices," Chicago Fed Letter, Federal Reserve Bank of Chicago, issue Jul.
    8. Nathan S. Balke & Mark E. Wohar, 2002. "Low-Frequency Movements in Stock Prices: A State-Space Decomposition," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 649-667, November.
    9. Ben S. Bernanke & Mark Gertler, 1999. "Monetary policy and asset price volatility," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 77-128.
    10. Marco Del Negro & Christopher Otrok, 2005. "Monetary policy and the house price boom across U.S. states," FRB Atlanta Working Paper 2005-24, Federal Reserve Bank of Atlanta.
    11. Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999. "Statistical algorithms for models in state space using SsfPack 2.2," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 107-160.
    12. Aoki, Kosuke & Proudman, James & Vlieghe, Gertjan, 2004. "House prices, consumption, and monetary policy: a financial accelerator approach," Journal of Financial Intermediation, Elsevier, vol. 13(4), pages 414-435, October.
    13. John V. Duca, 2005. "Making sense of elevated housing prices," Southwest Economy, Federal Reserve Bank of Dallas, issue Sep, pages 1,7-13.
    14. Jonathan McCarthy & Richard Peach, 2004. "Are home prices the next \\"bubble\\"?," Economic Policy Review, Federal Reserve Bank of New York, issue Dec, pages 1-17.
    15. James H. Stock & Mark W. Watson, 1998. "Diffusion Indexes," NBER Working Papers 6702, National Bureau of Economic Research, Inc.
    16. M. Ayhan Kose & Christopher Otrok & Charles H. Whiteman, 2003. "International Business Cycles: World, Region, and Country-Specific Factors," American Economic Review, American Economic Association, vol. 93(4), pages 1216-1239, September.
    17. Davis, Morris A. & Heathcote, Jonathan, 2007. "The price and quantity of residential land in the United States," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2595-2620, November.
    18. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    19. Charles Himmelberg & Christopher Mayer & Todd Sinai, 2005. "Assessing High House Prices: Bubbles, Fundamentals and Misperceptions," Journal of Economic Perspectives, American Economic Association, vol. 19(4), pages 67-92, Fall.
    20. Olivier J. Blanchard & Mark W. Watson, 1982. "Bubbles, Rational Expectations and Financial Markets," NBER Working Papers 0945, National Bureau of Economic Research, Inc.
    21. Ben R. Craig & Joseph G. Haubrich, 2005. "Too much risk?," Economic Commentary, Federal Reserve Bank of Cleveland, issue Mar.
    22. James H. Stock & Mark W. Watson, 1993. "Business Cycles, Indicators, and Forecasting," NBER Books, National Bureau of Economic Research, Inc, number stoc93-1, May.
    23. Stock, James H. & Watson, Mark W. (ed.), 1993. "Business Cycles, Indicators, and Forecasting," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226774886, December.
    24. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers 55, Federal Reserve Bank of Minneapolis.
    25. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    26. Bradford Case & Susan Wachter, 2005. "Residential real estate price indices as financial soundness indicators: methodological issues," BIS Papers chapters, in: Bank for International Settlements (ed.), Real estate indicators and financial stability, volume 21, pages 197-211, Bank for International Settlements.
    27. James H. Stock & Mark W. Watson, 1993. "A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 95-156, National Bureau of Economic Research, Inc.
    28. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
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