Empirical work on regional growth under spatial spillovers uses two workhorse models: the spatial Solow model and Verdoorn's model. This paper contrasts these two views on regional growth processes and demonstrates that in a spatial setting the speed of convergence is heterogenous in both...

The use of hierarchical Bayesian spatial models in the analysis of ecological data is increasingly prevalent. The implementation of these models has been heretofore limited to specifically written software that required extensive programming knowledge to create. The advent of WinBUGS provides...

We use a point-pattern methodology to explore the detailed location patterns of UK manufacturing industries. In particular, we consider the location of entrants and exiters vs. continuing establishments, domestic- vs. foreign-owned, large vs. small, and affiliated vs. independent. We also...

Using a point-patternmethodology, we explore a range of issues regarding the detailed location patterns of UKmanufacturing industries. In particular, we focus on the location of entrants and exiters vs. continuing establishments, domestic- vs. foreign-owned, large vs. small, and affiliated vs....

Applications using quasi-experimental comparison group designs in regional science and geography have increased substantially over the last three decades, inspired by the work of Andrew Isserman and colleagues in the 1980s and 1990s, robust literatures on quasi-experimental design in fields like...

In the last years a central issue in regional economic growth debate is represented by the convergence problem. Many empirical economists have noticed that per-worker GDP of poor regions tend to converge to those of richer regions. However more recently it has been observed that the economic...

We exploit a comprehensive new panel dataset on retailbank branch locations in 233 neighborhoods (local markets) in the metropolitan area of Antwerp to describe (i) how between 1991 and 2006 the patterns of bank presence, entry, exit and choice deeply evolve and (ii) whether and how changes in...

When a large amount of spatial data is available computational and modeling challenges arise and they are often labeled as “big n problem”. In this work we present a brief review of the literature. Then we focus on two approaches, respectively based on stochastic partial differential...