Doctoral Seminar in Dynamic Choice Models and Counterfactual Reasoning

4 credits

Introduces models of inter-temporal trade-offs made by consumers and firms. Includes discussion of Markov decision processes, estimation and identification of structural dynamic discrete choice models, offline and online reinforcement learning, and dynamic policy evaluation. Prerequisite: completion of college-level coursework in static discrete choice models; and basic understanding of a programming language.