In this paper we study the effects on the survival rate in employment of a scheme that facilitates gradual retirement through working time reductions. We use information on the entire labour market career and other observables to control for selection and take dynamic treatment assignment into...

In this paper we study the effects on the survival rate in employment of a scheme that facilitates gradual retirement through working time reductions. We use information on the entire labour market career and other observables to control for selection and take dynamic treatment assignment into...

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...

Based on administrative data of unemployed in Belgium, we estimate the labour market effects of three training programmes at various aggregation levels using Modified Causal Forests, a causal machine learning estimator. While all programmes have positive effects after the lock-in period, we find...

In this paper we study the effects on the survival rate in employment of a scheme that facilitates gradual retirement through working time reductions. We use information on the entire labour market career and other observables to control for selection and take dynamic treatment assignment into...

In this paper we study the effects on the survival rate in employment of a scheme that facilitates gradual retirement through working time reductions. We use information on the entire labour market career and other observables to control for selection and take dynamic treatment assignment into...

Based on administrative data of unemployed in Belgium, we estimate the labour market effects of three training programmes at various aggregation levels using Modified Causal Forests, a causal machine learning estimator. While all programmes have positive effects after the lock-in period, we find...

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...