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Testing for Bubbles in Housing Markets: A Panel Data Approach

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  • Vyacheslav Mikhed
  • Petr Zemcik

Abstract

We employ recently developed cross-sectionally robust panel data tests for unit roots and cointegration to find whether house prices reflect house-related earnings. We use U.S. data for Metropolitan Statistical Areas, with house price measured by the weighted-repeated-sales index, and cash flows either by market tenant rents or estimates of a fair market rent. In our full sample periods, an error-correction model is not appropriate, i.e. there is a bubble. We then combine overlapping ten-year periods, price-rent ratios, and the panel data tests to construct a bubble indicator. The indicator is high for the late 1980s, early 1990s and since the late 1990s for both panels. Finally, evidence based on panel data Granger causality tests suggests that house price changes are helpful in predicting changes in rents and vice versa.

Suggested Citation

  • Vyacheslav Mikhed & Petr Zemcik, 2007. "Testing for Bubbles in Housing Markets: A Panel Data Approach," CERGE-EI Working Papers wp338, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
  • Handle: RePEc:cer:papers:wp338
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    References listed on IDEAS

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    1. 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.
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    5. Karl E. Case & Robert J. Shiller, 1987. "Prices of single-family homes since 1970: new indexes for four cities," New England Economic Review, Federal Reserve Bank of Boston, issue Sep, pages 45-56.
    6. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    7. Pedroni, Peter, 1999. " Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(0), pages 653-670, Special I.
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    Citations

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    Cited by:

    1. Anundsen, André Kallåk, 2013. "Economic Regime Shifts and the US Subprime Bubble," Memorandum 05/2013, Oslo University, Department of Economics.
    2. Robert A. Jarrow, 2015. "Asset Price Bubbles," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 201-218, December.
    3. John McDonald & Houston Stokes, 2013. "Monetary Policy and the Housing Bubble," The Journal of Real Estate Finance and Economics, Springer, vol. 46(3), pages 437-451, April.
    4. Efthymios Pavlidis & Alisa Yusupova & Ivan Paya & David Peel & Enrique Martínez-García & Adrienne Mack & Valerie Grossman, 2016. "Episodes of Exuberance in Housing Markets: In Search of the Smoking Gun," The Journal of Real Estate Finance and Economics, Springer, vol. 53(4), pages 419-449, November.
    5. Tianhao Zhi & Zhongfei Li & Zhiqiang Jiang & Lijian Wei & Didier Sornette, 2018. "Is there a housing bubble in China," Papers 1801.03678, arXiv.org.
    6. Ogonna Nneji & Chris Brooks & Charles Ward, 2011. "Intrinsic and Rational Speculative Bubbles in the U.S. Housing Market 1960-2009," ICMA Centre Discussion Papers in Finance icma-dp2011-01, Henley Business School, Reading University.
    7. Kholodilin Konstantin A. & Menz Jan-Oliver & Siliverstovs Boriss, 2010. "What Drives Housing Prices Down? Evidence from an International Panel," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 230(1), pages 59-76, February.
    8. Philipp Klotz & Tsoyu Calvin Lin & Shih-Hsun Hsu, 2013. "Property Bubbles and the Driving Forces in the PIGS Countries," ERES eres2013_144, European Real Estate Society (ERES).
    9. Marcelo M. de Oliveira & Alexandre C. L. Almeida, 2014. "Testing for rational speculative bubbles in the Brazilian residential real-estate market," Papers 1401.7615, arXiv.org.
    10. Mikhed, Vyacheslav & Zemcík, Petr, 2009. "Do house prices reflect fundamentals? Aggregate and panel data evidence," Journal of Housing Economics, Elsevier, vol. 18(2), pages 140-149, June.
    11. MeiChi Huang, 2013. "The Role of People’s Expectation in the Recent US Housing Boom and Bust," The Journal of Real Estate Finance and Economics, Springer, vol. 46(3), pages 452-479, April.
    12. Matthew S. Yiu & Lu Jin, 2012. "Detecting Bubbles in the Hong Kong Residential Property Market: An Explosive-Pattern Approach," Working Papers 012012, Hong Kong Institute for Monetary Research.
    13. André K. Anundsen, 2015. "Econometric Regime Shifts and the US Subprime Bubble," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 145-169, January.
    14. Gogas, Periklis & Pragidis, Ioannis, 2010. "Does the Interest Risk Premium Predict Housing Prices?," DUTH Research Papers in Economics 1-2010, Democritus University of Thrace, Department of Economics.
    15. ZEREN, Feyyaz & ERGÜZEL, Oylum Şehvez, 2015. "Testing For Bubbles In The Housing Market: Further Evidence From Turkey," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 19(1), pages 40-52.
    16. Esposti, Roberto, 2008. "Why Should Regional Agricultural Productivity Growth Converge? Evidence from Italian Regions," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 43955, European Association of Agricultural Economists.

    More about this item

    Keywords

    Cointegration; panel data; unit root; bubble; house prices; rents.;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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