The Bias of the RSR Estimator and the Accuracy of Some Alternatives
AbstractThis paper analyzes the implications of cross-sectional heteroskedasticity in the 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 the bias in the average return estimate for each 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 an unbiased maximum likelihood alternative to the RSR that directly estimates index returns, which we term MLRSR. The unbiased MLRSR estimators are analogous to the RSR estimators but are arithmetic averages of individual asset returns. Simulations show that these estimators are robust to time-varying cross-sectional variance and that the MLRSR may be more accurate than RSR and some alternative methods. Copyright 2002 by the American Real Estate and Urban Economics Association.
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Bibliographic InfoArticle provided by American Real Estate and Urban Economics Association in its journal Real Estate Economics.
Volume (Year): 30 (2002)
Issue (Month): 1 ()
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Other versions of this item:
- 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.
- William N. Goetzmann & Liang Peng, 2001. "The Bias of the RSR Estimator and the Accuracy of Some Alternatives," NBER Technical Working Papers 0270, National Bureau of Economic Research, Inc.
- R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis
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