The paper attempts to determine regional unemployment rates for NUTS 2 regions based on data available on a regular basis from Eurostat and ILO. In the first part it is shown how the evolution of regional unemployment rates is determined by national unemployment rates by industry and the...

Unemployment is notoriously difficult to predict. In previous studies, once country fixed effects are added to panel estimates, few variables predict changes in unemployment rates. Using panel data for 29 European countries - Austria; Belgium; Bulgaria; Croatia; Cyprus; Czechia; Denmark; Estonia;...

Can economic theory help - forecasting key macroeconomic variables? This article aims to provide some insight into the question by drawing lessons from the literature. The definition of ‘economic theory’ includes a broad range of examples, such as accounting identities, disaggregation and...

In this paper, we compare two popular statistical learning techniques, logistic regression and random forest, with respect to their ability to classify jobseekers by their likelihood to become long-term unemployed. We study the performance of the two methods before the COVID-19 pandemic as well...

This paper studies the predictability of long-term unemployment (LTU) and analyzes its main determinants using rich administrative data in Sweden. Compared to using standard socio-demographic variables, the predictive power more than doubles when leveraging the rich data environment. The largest...

Unemployment is notoriously difficult to predict. In previous studies, once country and year fixed effects are added to panel estimates, few variables predict changes in unemployment rates. Using panel data for 29 European countries collected by the European Commission over 444 months between...

In an era characterized by population aging and economic challenges in welfare states across the world, sustaining these welfare systems requires a large workforce. Many individuals outside the labor market aspire to work but encounter a labyrinth of obstacles. While Public Employment Services...

Factor models can cope with many variables without running into scarce degrees of freedom problems often faced in a regression-based analysis. In this article we review recent work on dynamic factor models that have become popular in macroeconomic policy analysis and forecasting. By means of an...

This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range...

We consider the problem of ex-ante forecasting conditional correlation patterns using ultra high frequency data. Flexible semiparametric predictors referring to the class of dynamic panel and dynamic factor models are adopted for daily forecasts. The parsimonious set up of our approach allows to...