The Accuracy Of Real Estimate Indices: Repeat Sale Estimators
AbstractSimulation techniques allow the author to examine the behavior and accuracy of several repeat sales regression estimators used to construct real estate return indices. He shows that the generalized least squares (GLS) method is the maximum likelihood estimator, and he shows how estimation accuracy can be significantly improved through a Bayesian approach. In addition, he introduces a biased estimation procedure based upon the James and Stein method to address the problems of multicollinearity common to the procedure. Copyright 1992 by Kluwer Academic Publishers
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Bibliographic InfoPaper provided by Columbia - Graduate School of Business in its series Papers with number fb-_90-17.
Length: 42 pages
Date of creation: 1990
Date of revision:
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Postal: U.S.A.; COLUMBIA UNIVERSITY, GRADUATE SCHOOL OF BUSINESS, PAINE WEBBER , New York, NY 10027 U.S.A
Phone: (212) 854-5553
Web page: http://www.columbia.edu/cu/business/
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regression analysis ; estimator ; maximum likelihood;
Other versions of this item:
- Goetzmann, William Nelson, 1992. "The Accuracy of Real Estate Indices: Repeat Sale Estimators," The Journal of Real Estate Finance and Economics, Springer, vol. 5(1), pages 5-53, March.
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