The Bias of the RSR Estimator and the Accuracy of Some Alternatives
William Goetzmann () and
Yale School of Management Working Papers from Yale School of Management
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.
Keywords: Repeat sales estimators; Real estate index; Simulation (search for similar items in EconPapers)
Date: 2001-02-01, Revised 2001-03-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed
Downloads: (external link)
Our link check indicates that this URL is bad, the error code is: 500 Can't connect to icfpub.som.yale.edu:80 (A connection attempt failed because the connected party did not properly respond after a period of time, or established connection failed because connected host has failed to respond.)
Journal Article: The Bias of the RSR Estimator and the Accuracy of Some Alternatives (2002)
Working Paper: The Bias of the RSR Estimator and the Accuracy of Some Alternatives (2001)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ysm:somwrk:ysm174
Access Statistics for this paper
More papers in Yale School of Management Working Papers from Yale School of Management Contact information at EDIRC.
Bibliographic data for series maintained by ().