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...

This paper develops a flexible multi-dimensional assessment method for the comparison of different statistical-econometric techniques based on learning mechanisms, with a view to analysing and forecasting regional labour markets. The aim of this paper is twofold. A first major objective is to...

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...

The emergence of the COVID-19 pandemic led state and local governments throughout New England and much of the nation to issue ordinances restricting activity that might otherwise contribute to the spread of the disease. Individuals also freely adjusted their behavior, hoping to reduce the...

Population changes are decisive for growth performances. This has been shown in a number of country studies, using time series data. The analysis is here extended in two dimensions: 1) the importance of demographics for growth is taking in to account a regional dimension allowing for spatial...