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...

Spatial interaction models of the gravity type are widely used to describe origin-destination flows. They draw attention to three types of variables to explain variation in spatial interactions across geographic space: variables that characterize the origin region of interaction, variables that...

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...