This article provides a method for estimating housing indices at the local level. It develops a ““distance-weighted repeat-sales”” procedure to exploit the factor structure of the error-covariance matrix in the repeat-sales model. A distance function defined in characteristic and geographical space provides weights for the generalized least-squares model, and allows the use of all of the repeated sales in a metropolitan area to measure returns for the specific neighborhood of interest. We use distance-weighted repeat sales to estimate return indices for all zip codes in the San Francisco Bay area over the period 1980--1994.
The Journal of Real Estate Finance and Economics – Springer Journals
Published: Sep 30, 2004
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