Measuring the diffusion of housing prices across space and over time

Abstract

How fast and how long (and to what magnitude) does a change in housing prices in one region affect its neighbors? In this paper, I apply a time series technique for measuring impulse response functions from linear projections to a spatial autoregressive model of housing prices. For a dynamic panel of California counties, the data reveal that spatial autocorrelation between regional housing prices is highly persistent over time, lasting up to two and half years. This result, and the econometric techniques employed, should be of interest to not only housing and regional economists, but to a variety of applied econometricians as well.