Nonparametric identification of dynamic treatment effects in competing risks models

We introduce a dynamic treatment to the mixed proportional hazard competing risks model and allow for selection on unobservables. Our model can e.g. be used to evaluate the effect of benefit sanctions on the transition rate out of unemployment when more than one exit risk is of interest. Imposing a benefit sanction will influence the transition rate to employment. However, the sanction can also affect the decision of an individual to exit the labor force. The latter effect is often ignored in empirical work. In this paper we present a general model which allows to identify different effects of a treatment such as a sanction on several competing exit risks such as 'finding work' vs. 'exit the labor force'. Our approach exploits the timing at which the individual enters into treatment by adding the hazard rate of the duration to treatment as an additional equation to the competing risks model. We present a new identification result of this model for single-spell duration data. Furthermore, we intend to include an empirical application in this paper to illustrate the estimation procedure.