Spatio-Temporal Autoregressive Models of Neighborhood Effects

Using 70,822 observations on housing prices during 1969-91 from Fairfax County Virginia, this manuscript demonstrates the substantial benefits obtained by modeling the spatial as well as the temporal dependence of the data. Specifically, the spatio temporal autoregression with 12 variables reduced median absolute error by 37.35% relative to an indicator-based model with 26 variables. One-step ahead forecasts also document the improved performance of the proposed spatio-temporal model. In addition, the manuscript illustrates techniques for rapidly computing the estimates and shows how to compute indices for any location