This paper provides conditions for identification and estimation of the conditional or unconditional average effect of a binary treatment or policy on a scalar outcome in models where treatment may be misclassified. Misclassification probabilities and the true probability of treatment are also...

When selection bias can purely be attributed to observables, several estimators have been discussed in the literature to estimate the average effect of a binary treatment or policy on a scalar outcome. Identification typically exploits the unconfoundedness of the treatment, which is verified if...

One of the lessons of the treatment effects literature is the lack of consensus about the ability of statistical and econometric methods to replicate experimental estimates. In this paper, we provide new evidence using an unusual unemployment insurance experiment that allows the identification...

Even tough child labor is a wide spread phenomena in Bolivia, little is known about its main determinants. By using a bivariate probit model in order to take into account the joint nature of the decisions between labor and schooling, this paper investigates which are the key factors that...

This paper offers a theoretical and empirical analysis of child labor, schooling, and `idleness' (neither work nor school), with particular emphasis on the roles of child ability and credit constraints in determining these decisions. We show theoretically that `idleness' may be chosen optimally...

This paper provides evidence on the the impact of child labor on child schooling.The limited evidence that does exist on this issue makes little or no attempt to control for the endogeneity of child labour hours in the estimation.Such endogeneity can arise because of the reverse causation of...