This paper assesses the impact of the first wave of the pandemic on the local economies of one of the hardest-hit countries, Italy. We combine quarterly local labor market data with the new machine learning control method for counterfactual building. Our results document that the economic...

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...

We systematically investigate the effect heterogeneity of job search programmes for unemployed workers. To investigate possibly heterogeneous employment effects, we combine non-experimental causal empirical models with Lasso-type estimators. The empirical analyses are based on rich...

Inequality is a dynamic phenomenon, and the relative and absolute positions of individuals are subject to frequent shocks. It is important to know if preventive interventions mitigate adverse inequality effects of labor market shocks. We consider individuals up to three months before the...

Empirical evaluations of national minimum wages, such as in Germany or the UK, rely on bite measures that capture treatment variation; measured from the incidence (or intensity) of employees paid below the threshold before the minimum wage was introduced or raised. Bite-dependent estimations...