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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, September.
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    Cited by:

    1. 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.
    2. Arthur Korteweg & Roman Kräussl & Patrick Verwijmeren, 2016. "Does it Pay to Invest in Art? A Selection-Corrected Returns Perspective," The Review of Financial Studies, Society for Financial Studies, vol. 29(4), pages 1007-1038.
    3. David Chambers & Elroy Dimson & Christophe Spaenjers, 0. "Art as an Asset: Evidence from Keynes the Collector," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(3), pages 490-520.
    4. 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.
    5. Bernard Thion & Tatiana Bouzdine Chameeva, 2001. "Comparative Analysis of Several Models of Price Indices in Real Estate Transactions," ERES eres2001_285, European Real Estate Society (ERES).
    6. 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.
    7. 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.
    8. James Bugden, 2013. "Renovations and the Repeat-Sales House Price Index," Working Papers 2013.08, School of Economics, La Trobe University.
    9. Jarl G. Kallberg & Crocker H. Liu & Paolo Pasquariello, 2014. "On the Price Comovement of U.S. Residential Real Estate Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 42(1), pages 71-108, March.
    10. 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.
    11. Liang Peng, 2020. "Benchmarking Local Commercial Real Estate Returns: Statistics Meets Economics," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 48(4), pages 1004-1029, December.
    12. Erdős, Péter & Ormos, Mihály, 2012. "Pricing of collectibles: Baedeker guidebooks," Economic Modelling, Elsevier, vol. 29(5), pages 1968-1978.
    13. Melser, Daniel, 2017. "Disaggregated property price appreciation: The mixed repeat sales model," Regional Science and Urban Economics, Elsevier, vol. 66(C), pages 108-118.
    14. Claudio Borio & Øyvind Eitrheim & Marc Flandreau & Clemens Jobst & Jan F Qvigstad & Ryland Thomas, 2022. "Historical monetary and financial statistics for policymakers: towards a unified framework," BIS Papers, Bank for International Settlements, number 127.
    15. Jianhua Gang & Liang Peng & Jinfan Zhang, 2021. "Are Pricier Houses Less Risky? Evidence from China," The Journal of Real Estate Finance and Economics, Springer, vol. 63(4), pages 662-677, November.
    16. Liang Peng & Thomas G. Thibodeau, 2020. "Interest Rates and Investment: Evidence from Commercial Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 60(4), pages 554-586, May.
    17. Vecco, Marilena & Zanola, Roberto, 2017. "Don’t let the easy be the enemy of the good. Returns from art investments: What is wrong with it?," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 120-129.
    18. 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.
    19. 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.
    20. 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.

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    More about this item

    Keywords

    Repeat sales estimators; Real estate index; Simulation;
    All these keywords.

    JEL classification:

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

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