Causal Models for Longitudinal and Panel Data: A Survey

73 Pages Posted: 11 Dec 2023

See all articles by Dmitry Arkhangelsky

Dmitry Arkhangelsky

Centre for Monetary and Financial Studies (CEMFI)

Guido W. Imbens

Stanford Graduate School of Business

Date Written: December 2023

Abstract

This survey discusses the recent causal panel data literature. This recent literature has focused on credibly estimating causal effects of binary interventions in settings with longitudinal data, with an emphasis on practical advice for empirical researchers. It pays particular attention to heterogeneity in the causal effects, often in situations where few units are treated. The literature has extended earlier work on difference-in-differences or two-way-fixed-effect estimators and more generally incorporated factor models or interactive fixed effects. It has also developed novel methods using synthetic control approaches.

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Suggested Citation

Arkhangelsky, Dmitry and Imbens, Guido W., Causal Models for Longitudinal and Panel Data: A Survey (December 2023). NBER Working Paper No. w31942, Available at SSRN: https://ssrn.com/abstract=4660267

Dmitry Arkhangelsky (Contact Author)

Centre for Monetary and Financial Studies (CEMFI) ( email )

Casado del Alisal 5
28014 Madrid
Spain

Guido W. Imbens

Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States

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