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Estimating serial cross-correlation in real estate returns


  • Gerald R. Brown

    (Department of Real Estate, National University of Singapore, Singapore)

  • Seow-Eng Ong

    (Department of Real Estate, National University of Singapore, Singapore)


Appraisal smoothing understates the true volatility of real estate returns, and consequently affects asset allocation decisions. The high level of smoothing observed in commercial property index returns can be shown to be largely influenced by the effect of serial cross-correlation. This paper examines this phenomenon by analysing the time series properties of a sample of individual property returns using the generalized autoregressive conditional heteroskedasticity (GARCH) model. The autoregressive conditional heteroskedasticity (ARCH) model, proposed by Engle (1982) and Bollerslev (1986), is used to characterize time series data that exhibits clustering in the residuals. The time-varying conditional variance in ARCH models is often used as a measure of intertemporal risk. We use this property to analyse the cross-correlation coefficients of a sample of properties. Our results suggest that there is positive skewness in the serial cross-correlations. This is consistent with a process that would generate high serial correlation at the index level. We demonstrate that serial cross-correlation can be used as a proxy of the proportion of sticky values in an index. The results indicate that serial cross-correlation is time varying and positively skewed. Copyright © 2001 John Wiley & Sons, Ltd.

Suggested Citation

  • Gerald R. Brown & Seow-Eng Ong, 2001. "Estimating serial cross-correlation in real estate returns," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 22(7), pages 381-387.
  • Handle: RePEc:wly:mgtdec:v:22:y:2001:i:7:p:381-387
    DOI: 10.1002/mde.1027

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    References listed on IDEAS

    1. Carmelo Giaccotto & John Clapp, 1992. "Appraisal-Based Real Estate Returns under Alternative Market Regimes," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 20(1), pages 1-24.
    2. N/A, 1991. "Appraisal," National Institute Economic Review, National Institute of Economic and Social Research, vol. 138(1), pages 3-5, November.
    3. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    4. David Geltner, 1989. "Bias in Appraisal-Based Returns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 17(3), pages 338-352.
    5. Ross, Stephen A & Zisler, Randall C, 1991. "Risk and Return in Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 4(2), pages 175-190, June.
    6. Geltner, David Michael, 1991. "Smoothing in Appraisal-Based Returns," The Journal of Real Estate Finance and Economics, Springer, vol. 4(3), pages 327-345, September.
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    Cited by:

    1. De Santis, Paola & Drago, Carlo, 2014. "Asimmetria del rischio sistematico dei titoli immobiliari americani: nuove evidenze econometriche
      [Systematic Risk Asymmetry of the American Real Estate Securities: Some New Econometric Evidence]
      ," MPRA Paper 59381, University Library of Munich, Germany.

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