Policy Learning under Endogeneity Using Instrumental Variables

2022/06/20 by Yan Liu, Liu, Yan · 1 citation
Economics, Econometrics and Finance · #Econometrics (econ.EM) #Economic Policies and Impacts #FOS: Economics and business

paper · pdf · doi:10.48550/arxiv.2206.09883

openalex publication_date 2022/06/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

I propose a framework for learning individualized policy rules in observational data settings characterized by endogenous treatment selection and the availability of an instrumental variable. I introduce encouragement rules that manipulate the instrument. By incorporating the marginal treatment effect (MTE) as a policy invariant parameter, I establish the identification of the social welfare criterion for the optimal encouragement rule. Focusing on binary encouragement rules, I propose to estimate the optimal encouragement rule via the Empirical Welfare Maximization (EWM) method and derive the welfare loss convergence rate. I apply my method to advise on the optimal tuition subsidy assignment in Indonesia.

Cited by

• Policy Learning under Unobserved Confounding: A Robust and Efficient Approach

Related

• Policy Learning with New Treatments
• Personalized Subsidy Rules
• Welfare Analysis via Marginal Treatment Effects
• Policy Learning With Observational Data
• Policy Learning with Observational Data