Because of heterogeneity across regions, economic policy measures are increasingly targeted at the regional level. As a result, the need for economic forecasts at a sub-national level is rapidly increasing. The data available to compute regional forecasts is usually based on a pseudo-panel that...

There is an increasing awareness of the potential of nonlinear modeling in regional science, which can partly be explained by the recognition of the limitations of conventional equilibrium models in complex situations and partly by the easy availability and accessibility of sophisticated...

Unemployment rates appear to vary widely at a subregional (e.g., local or provincial) level. Using spatial econometric models for spatial autocorrelation, this paper focuses attention on the spatial structure of regional unemployment disparities of Italian provinces. On the basis of findings...

In this paper, a set of neural network (NN) models is developed to compute short-term forecasts of regional employment patterns in Germany. NNs are modern statistical tools based on learning algorithms that are able to process large amounts of data. NNs are enjoying increasing interest in...

This paper investigates patterns of manufacturing location in the context of increased economic integration in Central and East European countries. Using regional data for the period 1990-1999, we identify and compare patterns and determinants of manufacturing location in five European Union...