Abstract

This paper provides a method for estimating housing indices at the local level. It develops a “distance-weighted repeat-sale” 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 all of the repeated-sales in a metropolitan are 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 through 1994. When distance is defined in terms of socio-economic characteristics, we find that median household income is the salient variable explaining covariance of neighborhood housing returns. Racial composition and educational attainment, while significant, are much less influential. Zip-code level indices often deviate dramatically from the city-wide index, depending upon income levels. This has implications for investors and lenders. Our results indicate that rates of return may vary considerably within a metropolitan area. Thus, simply using broad metropolitan area indices as a proxy for capital appreciation within a specific neighborhood may not be justified.

Key Words: housing returns, distance-weighted repeat-sales, neighborhood substitutability