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The Bias of the RSR Estimator and the Accuracy of Some Alternatives

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  • William Goetzmann
  • Liang Peng

Abstract

This paper analyzes the implications of cross-sectional hetero- skedasticity in repeat sales regression (RSR). RSR estimators are essentially geometric averages of individual asset returns because of the logarithmic transformation of price relatives. We show that the cross sectional variance of asset returns affects the magnitude of bias in the average return estimate for that period, while reducing the bias for the surrounding periods. It is not easy to use an approximation method to correct the bias problem. We suggest a maximum-likelihood alternative to the RSR that directly estimates index returns that are analogous to the RSR estimators but are arithmetic averages of individual returns. Simulations show that these estimators are robust to time-varying cross-sectional variance and may be more accurate than RSR and some alternative methods of RSR.

Suggested Citation

  • William Goetzmann & Liang Peng, 2001. "The Bias of the RSR Estimator and the Accuracy of Some Alternatives," Yale School of Management Working Papers ysm174, Yale School of Management, revised 01 Mar 2001.
  • Handle: RePEc:ysm:somwrk:ysm174
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    File URL: http://icfpub.som.yale.edu/publications/2592
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    References listed on IDEAS

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    1. Jesse M. Abraham & William S. Schauman, 1991. "New Evidence on Home Prices from Freddie Mac Repeat Sales," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 19(3), pages 333-352.
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    Cited by:

    1. Erdős, Péter & Ormos, Mihály, 2012. "Pricing of collectibles: Baedeker guidebooks," Economic Modelling, Elsevier, vol. 29(5), pages 1968-1978.
    2. Arthur Korteweg & Roman Kräussl & Patrick Verwijmeren, 2016. "Does it Pay to Invest in Art? A Selection-Corrected Returns Perspective," Review of Financial Studies, Society for Financial Studies, vol. 29(4), pages 1007-1038.
    3. repec:eee:regeco:v:66:y:2017:i:c:p:108-118 is not listed on IDEAS
    4. Kathryn Graddy & Jonathan Hamilton & Rachel Pownall, 2012. "Repeat‐Sales Indexes: Estimation without Assuming that Errors in Asset Returns Are Independently Distributed," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 40(1), pages 131-166, March.
    5. Liang Peng, 2012. "Repeat Sales Regression on Heterogeneous Properties," The Journal of Real Estate Finance and Economics, Springer, vol. 45(3), pages 804-827, October.
    6. Rainer Schulz & Martin Wersing & Axel Werwatz, 2014. "Automated valuation modelling: a specification exercise," Journal of Property Research, Taylor & Francis Journals, vol. 31(2), pages 131-153, June.
    7. James Bugden, 2013. "Renovations and the Repeat-Sales House Price Index," Working Papers 2013.08, School of Economics, La Trobe University.
    8. repec:eee:jeborg:v:140:y:2017:i:c:p:120-129 is not listed on IDEAS
    9. Jianping Mei & Michael Moses, 2002. "Art as an Investment and the Underperformance of Masterpieces," American Economic Review, American Economic Association, vol. 92(5), pages 1656-1668, December.
    10. Erdos, Péter & Ormos, Mihály, 2010. "Random walk theory and the weak-form efficiency of the US art auction prices," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 1062-1076, May.
    11. Victor Ginsburgh & Jianping Mei & Michael Moses, 2006. "On the computation of art indices in art," ULB Institutional Repository 2013/7290, ULB -- Universite Libre de Bruxelles.
    12. James Pesando & Pauline Shum, 2007. "The law of one price, noise and “irrational exuberance”: the auction market for Picasso prints," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 31(4), pages 263-277, December.
    13. Deng, Yongheng & McMillen, Daniel P. & Sing, Tien Foo, 2014. "Matching indices for thinly-traded commercial real estate in Singapore," Regional Science and Urban Economics, Elsevier, vol. 47(C), pages 86-98.

    More about this item

    Keywords

    Repeat sales estimators; Real estate index; Simulation;

    JEL classification:

    • R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis

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