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 effects parameters modeled using a connectivity structure between regions that can reflect...

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...

Changes in land use patterns impact significantly environmental conditions as well as economic and social welfare. These changes are influenced by socio-economic as well as pedo-climatic factors. A good understanding of how these factors influence land use patterns would provide new dimensions...

This paper examines Africa's and Middle East's growth performance for the period 1990- 2005. It employs a Bayesian Model Averaging method that constructs estimates as a weighted average of Spatial Autoregressive estimates for every possible combination of included variables. One of the results...

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...

According to New Economic Geography models, the limited diffusion of knowledge through space is a key determinant of the location decision of innovative activities. Following the dynamic externality approach presented by Glaeser et al. (1992), many recent econometric studies attempt to evaluate...

This paper examines Africa’s and Middle East’s growth performance for the period 1990- 2005. It employs a Bayesian Model Averaging method that constructs estimates as a weighted average of Spatial Autoregressive estimates for every possible combination of included variables. One of the...

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 travel...

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...

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...