Causality in Econometrics: Choice vs Chance

• 成果类型: Article
• 署名作者: Imbens, Guido W. W.
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA21204
• 发表日期: 2022
• 页码: 2541-2566
• 关键词: instrumental variables; propensity score; inference; models; identification; sensitivity; POLICY; randomization; statistics; estimators

摘要

This essay describes the evolution and recent convergence of two methodological approaches to causal inference. The first one, in statistics, started with the analysis and design of randomized experiments. The second, in econometrics, focused on settings with economic agents making optimal choices. I argue that the local average treatment effects framework facilitated the recent convergence by making key assumptions transparent and intelligible to scholars in many fields. Looking ahead, I discuss recent developments in causal inference that combine the same transparency and relevance.