This paper provides an evaluation of a training programme for graduates entitled "Work Experience for Graduates" (WELL - Work Experience Laureati and Laureate) that was recently implemented in Italy. The aim of the programme was to increase the career prospects of unemployed graduates in the...

We provide a novel evidence about the innovation-employment nexus by decomposing it by R&D intensity in a continuous setup and relaxing the linearity assumption. Using a large international firm-level panel data set for OECD countries and employing a flexible semi-parametric method – the...

This paper suggests a causal framework for disentangling individual level treatment effects and interference effects, i.e., general equilibrium, spillover, or interaction effects related to treatment distribution. Thus, the framework allows for a relaxation of the Stable Unit Treatment Value...

This paper estimates the causal effects of the 2003 reform of the Italian apprenticeship contract which aimed at introducing the "dual system" in Italy by allowing on-the-job training. The reform also increased the age eligibility of the apprenticeship contract and introduced a minimum floor to...

Contract farming is often seen as a panacea to many of the challenges faced by agricultural production in developing countries. Given the large heterogeneity of contract farming arrangements, it is debatable whether all kinds of contract farming arrangements offer benefits to participating...

We place young professionals into established firms to shadow middle managers. Using random assignment into program participation, we find positive average effects on wage employment, but no average effect on the likelihood of self-employment. We match individuals to firms using a...

Estimation of the causal effect of a binary treatment on outcomes often requires conditioning on covariates to address selection on observed variables. This is not straightforward when one or more of the covariates are measured with error. Here, we present a new semi-parametric estimator that...

This paper builds on the Empirical Monte Carlo simulation approach developed by Huber et al. (2013) to study the estimation of Timing-of-Events (ToE) models. We exploit rich Swedish data of unemployed job-seekers with information on participation in a training program to simulate placebo...

Estimation of the causal effect of a binary treatment on outcomes often requires conditioning on covariates to address selection concerning observed variables. This is not straightforward when one or more of the covariates are measured with error. Here, we present a new semi-parametric estimator...

Multidimensional heterogeneity and endogeneity are important features of models with multiple treatments. We consider a heterogeneous coefficients model where the outcome is a linear combination of dummy treatment variables, with each variable representing a different kind of treatment. We use...