A space–time filter is set forth for spatial panel data situations that include random effects. We propose a general spatial dynamic specification that encompasses several spatiotemporal models previously used in the panel data literature. We apply the model to the case of highway induced...

The location of new homes defines the urban-rural fringe and determines many facets of the urban-rural interaction set in motion by construction of new homes in previously rural areas. Home, neighborhood and school district characteristics play a crucial role in determining the spatial location...

We use a spatial econometric extension of the traditional regression-based gravity model introduced in LeSage and Pace (2005) to model commodity flows between 35 regions in Austria. Our focus is on a formal methodology for incorporating information regarding the highway network into the spatial...

In this study, we consider R&D collaboration networks as a mechanism that modifies knowledge flows in space, and hence as another source of interaction among regional innovation processes. Our objective is to understand the relative role of spatial neighbors and network neighbors on patenting...

County-level estimates of employment, unemployment, and the unemployment rate are not produced directly from a sample survey; rather, they are developed through models that use information on the labor force from a number of statistical programs such as the CPS (Current Population Survey), CES...

This study investigates the pattern of knowledge spillovers arising from patent activity between European regions. A Bayesian hierarchical model is developed that specifies region-specific latent factors modeled using a connectivity structure between regions that can reflect geographical as well...

We extend the literature on Bayesian model comparison for ordinary least-squares regression models to include spatial autoregressive and spatial error models. Our focus is on comparing models that consist of different matrices of explanatory variables. A Markov Chain Monte Carlo model...

A space-time filter structure is introduced that can be used to accommodate dependence across space and time in the error components of panel data models that contain random effects. This general specification encompasses several more specific space-time structures that have been used recently...

This study suggests a two-step approach to identifying and interpreting regional convergence clubs in Europe. The first step involves identifying the number and composition of clubs using a space-time panel data model for annual income growth rates in conjunction with Bayesian model comparison...

There is near universal agreement that estimates and inferences from spatial regression models are sensitive to particular specifications used for the spatial weight structure in these models. We find little theoretical basis for this commonly held belief, if estimates and inferences are based...