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...

Commuting shapes countless everyday-lives around the world, with dynamics varying from city to regional and cross regional level. Taking as reference the free-movement EU-28 area (plus Switzerland and Norway), the analysis considers a total sample of 195 NUTS2 regions over the decade 2007-2017...

Flow data across regions can be modeled by spatial econometric models, see LeSage and Pace (2009). Recently, regional studies became interested in the aggregation and disaggregation of flow models, because trade data cannot be obtained at a disaggregated level but data are published on an...

Spatial interaction models of the gravity type are used in conjunction with sample data on flows between origin and destination locations to analyse international and interregional trade, commodity, migration and commuting patterns. The focus is on the classical log-normal model version and...

This paper analyzes the role of regional demographic, socioeconomic and political factors on changes in mobility during the COVID-19 pandemic. It provides new empirical evidence for the regional differentiation of lockdown measures and indicates a possible reorganization of spatial economic and...

We describe econometric techniques to treat spatial autocorrelation in multiequation cross-section models. The cross-section approaches discussed here are heavily based on the spatial GMM procedure, proposed by Conley (1999). An extension for fullinformation instrumental variable models is...