A SPATIAL MODEL OF HOUSING RETURNS AND NEIGHBORHOOD SUBSTITUTABILITY

This article provides a method for estimating housing indices at the l ocal 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 metropoli tan 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. When distance is defined in terms of socioeconomic characteristics, w e find that median household income is the salient variable explaining covariance of neighborhood housing returns. Racial composition and ed ucational attainment, while significant, are much less influential. Zi p-code level indices often deviate dramatically from the citywide inde x, depending upon income levels. This has implications for investors a nd lenders. Our results indicate that rates of return may vary conside rably within a metropolitan area. Thus, simply using broad metropolita n area indices as a proxy for capital appreciation within a specific n eighborhood may not be justified.