Matching has become a popular approach to estimate average treatment effects. It is based on the conditional independence or unconfoundedness assumption. Checking the sensitivity of the estimated results with respect to deviations from this identifying assumption has become an increasingly...

An important goal when analyzing the causal effect of a treatment on an outcome is to understand the mechanisms through which the treatment causally works. We define a causal mechanism effect of a treatment and the causal effect net of that mechanism using the potential outcomes framework. These...

We evaluate the effect of the size of deductibles in the basic health insurance in Switzerland on the probability of a doctor visit. We employ nonparametric bounding techniques to minimise statistical assumptions. In order to tighten the bounds we consider three further assumptions: mean...

Recent empirical evidence has found that employment services and small-business assistance programmes are often successful at getting the unemployed back to work. One important concern of policy makers is to decide which of these two programmes is more effective and for whom. Using unusually...

We consider an artificial population of forward looking heterogeneous agents making decisions between schooling, employment, employment with training and household production, according to a behavioral model calibrated to a large set of stylized facts. Some of these agents are subject to policy...

We analyze the impact on schooling outcomes of growing up in a family headed by a single mother. Growing up in a non-intact family in Germany is associated with worse outcomes in models that do not control for possible correlations between common unobserved determinants of family structure and...

While providing the most reliable method of evaluating social programs, randomized experiments in developing and developed countries alike are accompanied by political risks and ethical issues that jeopardize the chances of adopting them. In this paper we use a unique data set from rural Mexico...

This paper examines whether the chances of job placements improve if unemployed persons are counselled by caseworkers who belong to the same social group, defined by gender, age, education, and nationality. Based on an unusually informative dataset, which links Swiss unemployed to their...

This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that the duration framework in discrete time provides a fertile ground for effect evaluations. We suggest easy-to-use nonparametric survival function...

We characterize the bias of propensity score based estimators of common average treatment effect parameters in the case of selection on unobservables. We then propose a new minimum biased estimator of the average treatment effect. We assess the finite sample performance of our estimator using...