Identifying direct and indirect effects in economics

The identification of the causal effect of an explanatory variable on an outcome is a central task in economics. However, the (total) causal effect does usually not reveal the underlying causal mechanisms through which it operates. E.g., an active labor market policy might increase the labor market success (such as placement into employment) of participants directly by increasing the human capital, or indirectly through increasing job search effort, which is itself an intermediate outcome of the labor market policy. Though the identification of direct and indirect effects is crucial for understanding the causal mechanisms that characterize an economic problem, convincing identification strategies are rare. In particular the ubiquitous issues of endogeneity (of (i) the explanatory variable, (ii) the intermediate outcome, or (iii) both with the outcome of interest) and non-random outcome attrition (when the outcome is only observed for a selective subpopulation) have been widely ignored. This research project aims at developing credible non- and semiparametric methods for the identification of direct and indirect effects under endogeneity and/or outcome attrition. Both instrumental variable strategies for point identification and partial identification (i.e., the derivation of bounds on the effects in the absence of an instrument) will be used depending on the economic problem. Furthermore, the methods will be applied to empirical labor and health data. The project is to be realized in the course of a full year research visit to Prof. Guido W. Imbens, Ph.D., at Harvard University, one of the world's leading micro-econometricians.