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US Disposable Personal Income and Housing Price Index: A Fractional Integration Analysis

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  • Guglielmo Maria Caporale
  • Luis A. Gil-Alana

Abstract

This paper examines the relationship between US disposable personal income (DPI) and house price index (HPI) during the last twenty years applying fractional integration and long-range dependence techniques to monthly data from January 1991 to July 2010. The empirical findings indicate that the stochastic properties of the two series are such that cointegration cannot hold between them, as mean reversion occurs in the case of DPI but not of HPI. Also, recursive analysis shows that the estimated fractional parameter is relatively stable over time for DPI whilst it increases throughout the sample for HPI. Interestingly, the estimates tend to converge toward the unit root case after 2008 once the bubble had burst. The implications for explaining the recent financial crisis and choosing appropriate policy actions are discussed.

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File URL: http://www.diw.de/documents/publikationen/73/diw_01.c.362681.de/dp1070.pdf
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Bibliographic Info

Paper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 1070.

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Length: 19 p.
Date of creation: 2010
Date of revision:
Handle: RePEc:diw:diwwpp:dp1070

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Keywords: Personal Disposable Income; House Price Index; Fractional Integration;

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  1. Francis X. Diebold & Glenn D. Rudebusch, 1988. "Long memory and persistence in aggregate output," Finance and Economics Discussion Series 7, Board of Governors of the Federal Reserve System (U.S.).
  2. Lobato, Ignacio N & Savin, N E, 1998. "Real and Spurious Long-Memory Properties of Stock-Market Data: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 280-83, July.
  3. 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.
  4. Meen, Geoffrey, 2002. "The Time-Series Behavior of House Prices: A Transatlantic Divide?," Journal of Housing Economics, Elsevier, vol. 11(1), pages 1-23, March.
  5. I.N. Lobato & N.E. Savin, 1996. "Real and Spurious Long Memory Properties of Stock Market Data," Econometrics 9605004, EconWPA, revised 26 Sep 1996.
  6. Katsumi Shimotsu & Peter C.B. Phillips, 2000. "Local Whittle Estimation in Nonstationary and Unit Root Cases," Cowles Foundation Discussion Papers 1266, Cowles Foundation for Research in Economics, Yale University, revised Sep 2003.
  7. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
  8. Carstensen, Kai, 2006. "Stock Market Downswing and the Stability of European Monetary Union Money Demand," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 395-402, October.
  9. Gil-Alana, L. A. & Robinson, P. M., 1997. "Testing of unit root and other nonstationary hypotheses in macroeconomic time series," Journal of Econometrics, Elsevier, vol. 80(2), pages 241-268, October.
  10. Jonathan McCarthy & Richard W. Peach, 2004. "Are home prices the next "bubble"?," Economic Policy Review, Federal Reserve Bank of New York, issue Dec, pages 1-17.
  11. Katsumi Shimotsu & Peter C.B. Phillips, 2002. "Exact Local Whittle Estimation of Fractional Integration," Cowles Foundation Discussion Papers 1367, Cowles Foundation for Research in Economics, Yale University, revised Jul 2004.
  12. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
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