<title>Abstract</title> Spatial filtering in various forms has become a popular way to address spatial dependence in statistical models (Griffith, 2003; Tiefelsdorf & Griffith, 2007). However, spatial filtering faces computational challenges for large <italic>n</italic> as the current method requires order of n-super-3 operations....

<title>Abstract</title> First introduced in the field of economics of innovation by Anselin, Varga and Acs (1997), spatial econometric tools are increasingly used to study the geography of innovation. By taking spatial autocorrelation and spatial heterogeneity of regional innovation into account, this paper...

Abstract We use a spatial econometric extension of the traditional regression-based gravity model to model commodity flows, focusing on a formal methodology for incorporating information regarding the highway network into the spatial connectivity structure of the spatial autoregressive...

Abstract We attempt to clarify a number of points regarding use of spatial regression models for regional growth analysis. We show that as in the case of non-spatial growth regressions, the effect of initial regional income levels wears off over time. Unlike the non-spatial case, long-run...