Job training is one of the most important aspects of skill formation and human capital accumulation. In this study we use longitudinal Canadian linked employer-employee data to examine whether white/visible minority immigrants and Canadian-borns experience different opportunities in two...

In a world increasingly globalized, multiple language skills can create more employment opportunities. Several countries include language training programs in active labor market programs for the unemployed. We analyze the effects of a language training program on the re-employment probability...

So far the literature has found that the effect of macroeconomic fluctuations on training decisions is ambiguous. On the one hand, the opportunity cost to train is lower during downturns, and thus training should be counter-cyclical. On the other hand, a positive shock may be related to the...

We study the long-term effects of a randomized intervention targeting children's socio-emotional skills. The classroom-based intervention for primary school children has positive impacts that persist for over a decade. Treated children become more likely to complete academic high school and...

Using a representative sample of European firms, we study whether and to what extent financing constraints affect employers' decision to invest in employee training. We combine survey data on investment activities with administrative data on financial statements to develop an index of financing...

This report looks at employer–provided training in Europe. We start with a brief outline of the economic theory of training. We then look at the recent facts, by combining data from two employer surveys, the European Investment Bank's Investment Survey (EIBIS) and Eurostat's Continuous...

We investigate heterogenous employment effects of Flemish training programmes. Based on administrative individual data, we analyse programme effects at various aggregation levels using Modified Causal Forests (MCF), a causal machine learning estimator for multiple programmes. While all...