The Bias of the RSR Estimator and the Accuracy of Some Alternatives
AbstractThis paper analyzes the implications of cross-sectional heteroskedasticity 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.
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Bibliographic InfoPaper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0270.
Date of creation: Apr 2001
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Other versions of this item:
- William N. Goetzmann & Liang Peng, 2002. "The Bias of the RSR Estimator and the Accuracy of Some Alternatives," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 30(1), pages 13-39.
- 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.
- R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis
This paper has been announced in the following NEP Reports:
- NEP-ALL-2001-04-02 (All new papers)
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