Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions

In any economic analysis, regions or municipalities should not be regarded as isolated spatial units, but rather as highly interrelated small open economies. These spatial interrelations must be considered also when the aim is to forecast economic variables. For example, policy makers need accurate forecasts of the unemployment evolution in order to design short- or long-run local welfare policies. These predictions should then consider the spatial interrelations and dynamics of regional unemployment. In addition, a number of papers have demonstrated the improvement in the reliability of long-run forecasts when spatial dependence is accounted for. We estimate a heterogeneouscoefficients dynamic panel model employing a spatial filter in order to account for spatial heterogeneity and/or spatial autocorrelation in both the levels and the dynamics of unemployment, as well as a spatial vector-autoregressive (SVAR) model. We compare the short-run forecasting performance of these methods, and in particular, we carry out a sensitivity analysis in order to investigate if different number and size of the administrative regions influence their relative forecasting performance. We compute short-run unemployment forecasts in two countries with different administrative territorial divisions and data frequency: Switzerland (26 regions, monthly data for 34 years) and Spain (47 regions, quarterly data for 32 years)

Regional age structure, human capital and innovation - is demographic ageing increasing regional disparities?

Demographic change is expected to affect labour markets in very different ways on a regional scale. The objective of this paper is to explore the spatio-temporal patterns of recent distributional changes in the workers age structure, innovation output and skill composition for German regions by conducting an Exploratory Space-Time Data Analysis (ESTDA). Beside commonly used tools, we apply newly developed approaches which allow investigating the space-time dynamics of the spatial distributions. We include an analysis of the joint distributional dynamics of the patenting variable with the remaining interest variables. Overall, we find strong clustering tendencies for the demographic variables and innovation that constitute a great divide across German regions. The detected clusters partly evolve over time and suggest a demographic polarization trend among regions that may further reinforce the observed innovation divide in the future