DP12470 Identification of Counterfactuals in Dynamic Discrete Choice Models
Dynamic discrete choice models (DDC) are not identified nonparametrically. However, the non-identification of DDC models does not necessarily imply non-identification of coun- terfactuals of interest. Using a novel approach that can accommodate both nonparametric and restricted payoff functions, we provide necessary and sufficient conditions for the iden- tification of counterfactual behavior and welfare for a broad class of counterfactuals. The conditions are simple to check and can be applied to virtually all counterfactuals in the DDC literature. To explore the robustness of counterfactual results to model restrictions in practice, we consider a numerical example of a monopolist’s entry problem, as well as an empirical model of agricultural land use. In each case, we provide examples of both identified and non-identified counterfactuals of interest.