A1519
Title: Robust network targeting with multiple Nash equilibria
Authors: Guanyi Wang - Washington University in St Louis (United States) [presenting]
Abstract: Many policy problems involve designing individualized treatment allocation rules to maximize the equilibrium social welfare of interacting agents. Focusing on large-scale simultaneous decision games with strategic complementarities, an optimal treatment allocation mechanism is developed that is robust to the presence of multiple equilibria. The approach remains agnostic about changes in the equilibrium selection mechanism under counterfactual policies, and a closed-form expression for the boundary of the set-identified equilibrium outcomes is provided. To address the incompleteness that arises when an equilibrium selection mechanism is not specified, the maximin welfare criterion is used to select a policy, which is implemented using a greedy algorithm. A performance guarantee for the method is established by deriving a welfare regret bound, which accounts for sampling uncertainty and the use of the greedy algorithm. The method is demonstrated with an application to a microfinance dataset.
