In this paper we investigate whether peers’ behavior influences the choice of college major. Using a unique dataset of students at Bocconi University and exploiting the organization of teaching at this institution, we are able to identify the endogenous effect of peers on such decision through...

In this paper we introduce the Random Recursive Partitioning (RRP) method. This method generates a proximity matrix which can be used in applications like average treatment effect estimation in observational studies. RRP is a Monte Carlo method that randomly generates non-empty recursive...

Experiments offer more reliable evidence on causation than observational studies, which is not to gainsay the contribution to knowledge from observation. Experiments should be analyzed as experiments, not as observational studies. A simple comparison of rates might be just the right tool, with...

Regressions can be weighted by propensity scores in order to reduce bias. However, weighting is likely to increase random error in the estimates, and to bias the estimated standard errors downward, even when selection mechanisms are well understood. Moreover, in some cases, weighting will...

Causal effects are usually estimated under the assumption of no interference between individuals. This assumption means that the potential outcomes for one individual are unaffected by the treatments received by other individuals. In many situations, this is not reasonable to assume. Moreover,...

The conventional Wilcoxon/Mann-Whitney test can be invalid for comparing treatment effects in the presence of missing values or in observational studies. This is because the missingness of the outcomes or the participation in the treatments may depend on certain pre-treatment variables. We...

This paper provides a survey of six widely used non-experimental methods for estimating the impact of programmes in the context of developing economies (instrumental variables, regression discontinuity, direct matching, propensity score matching, linear r

Semi-competing risks data frequently arise in biomedical studies when time to a disease landmark event is subject to dependent censoring by death, the observation of which however is not precluded by the occurrence of the landmark event. In observational studies, the analysis of such data can be...

A new matching method is proposed for the estimation of the average treatment effect of social policy interventions (e.g., training programs or health care measures. Given an outcome variable, a treatment and a set of pre-treatment covariates, the method is based on the examination of random...

Since interventions by the public sector generally commit substantial societal resources, the evaluation of effects and costs of policy interventions is imperative. This paper outlines why program evaluation should follow well-respected scientific standards and why it should be performed by...