Ricerc@Sapienza

In economics causal analysis is a fundamental instrument to study the effect of a policy or, more in general, the effects of a treatment on an outcome of interest (TE). But, in last decades, researchers put their attention not only on the TEs, but also on causal mechanisms through which this treatment transmits the effects to the outcome. In this case, the researchers want to disentangle the total treatment effect into a direct effect of the treatment on the outcome and into an indirect effect, that operates through one or more intermediate variables, called mediators, that lie in the causal pathway between treatment and outcome. Even in presence of a double randomization of treatment and mediator, these effects are not identified. To tackle this issue, a regression discontinuity approach (RD) is proposed for the identification: in particular, this procedure permits to control for the structural endogeneity of the mediator. A simulation study gives an intuition of these results.