Applying recent developments in time series econometrics to the spatial domain

This paper sur?:cys some recent developments in time series econometrics an d examines to what degree they might have useful analogs in spatial econome trics. Spatial analogs of stationary vector autoregression models might be useful in modeling groups of spatial series, but the literature on non-stat ionarity and cointegration does not have a useful purely spatial analog. Wi th the exception of some special cases, pure spatial series cannot be integ rated processes. However, cointegration might apply to space-time processes . Space-time cointegration and Granger causality methods are developed and applied to explaining reductions in sulfur emissions in Europe.