SPATIOTEMPORAL AUTOREGRESSIVE MODELS OF NEIGHBORHOOD EFFECTS

Using 70,822 observations on housing prices from 1969 to 1991 from Fai rfax County Virginia, this article demonstrates the substantial benefi ts obtained by modeling the spatial as well as the temporal dependence of the data. Specifically, the spatiotemporal autoregression with twe lve variables reduced median absolute error by 37.35% relative to an i ndicator-based model with twenty-six variables. One-step ahead forecas ts also document the improved performance of the proposed spatiotempor al model. In addition, the article illustrates techniques for rapidly computing the estimates and shows how to compute indices for any locat ion.