Set identification of panel data models with interactive effects via quantile restrictions

•We provide set identification results for panel data models with interactive effects via conditional quantile restrictions.•The identification results are compared with Rosen (2012) who considers panel data models with only individual effects.•Numerical examples are used to illustrate the nature of the identified sets.

In this paper we study the identification via conditional quantile restrictions of panel data models where the individual and time effects enter the model interactively. It is shown that the parameters are set identified under a weak conditional independence assumption on the error terms and a support restriction on the time effects, while the distributions of the individual effects are unrestricted.