The geographical distribution and persistence of regional/local unemployment rates in heterogeneous economies (such as Germany) have been, in recent years, the subject of various theoretical and empirical studies. Several researchers have shown an interest in analysing the dynamic adjustment...

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...

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...

Regions, independent of their geographic level of aggregation, are known to be interrelated partly due to their relative locations. Similar economic performance among regions can be attributed to proximity. Consequently, a proper understanding, and accounting, of spatial liaisons is needed in...

Using representative and consistent microdata from the German Socio-Economic Panel Study (SOEP) from 1985-2007, we illustrate that capital income (CI = return on financial investments) and imputed rent (IR = return on investments in owner-occupied housing) have become increasingly important...

This paper analyses the contribution of capital income to income inequality in a cross-national comparison. Using micro-data from the Cross-National Equivalent File (CNEF) for three prominent panel studies, namely the BHPS for Great Britain, the SOEP for West Germany, and the PSID for the USA, a...

Using representative and consistent microdata from the German Socio-Economic Panel Study (SOEP) from 1985-2007, we illustrate that capital income (CI = return on financial investments) and imputed rent (IR = return on investments in owner-occupied housing) have become increasingly important...