Multiple Treatments with Strategic Interaction

Assistant Professor at Department of Economics from University of Texas at Austin, Visiting Assistant Professor at Yale University. Prof. Han earned his PhD in Economics from Yale University, his research interests include Econometric Theory and Applied Econometrics.

Please see Prof. Han's CVfor more information.

We develop an empirical framework in which we identify and estimate the effects of treatments on outcomes of interest when the treatments are results of strategic interaction (e.g., bargaining, oligopolistic entry, decisions in the presence of peer effects). We consider a model where agents play a discrete game with complete information whose equilibrium actions (i.e., binary treatments) determine a post-game outcome in a nonseparable model with endogeneity. Due to the simultaneity in the first stage, the model as a whole is incomplete and the selection process fails to exhibit the conventional monotonicity. Without imposing parametric restrictions or large support assumptions, this poses challenges in recovering treatment parameters. To address these challenges, we first analytically characterize regions that predict equilibria in the ?rst-stage game with possibly more than two players, whereby we ?nd a certain monotonic pattern of these regions. Based on this ?nding, we derive bounds on the average treatment effects (ATE’s) under nonparametric shape restrictions and the existence of excluded variables. We also introduce and point identify a multi-treatment version of local average treatment effects (LATE’s).