Causal Inference with Panel Data

• Department of Economics

Guido Imbens, Stanford University, will present the paper: "Causal Inference with Panel Data"

Guido Imbens is Professor of Economics at Stanford University and a leading expert in applied econometrics. He was awarded the 2021 Nobel Prize in Economic Sciences for his methodological contributions to the analysis of causal relationships, enabling more reliable interpretation of observational data in the social sciences.

Abstract of the paper:

Panel data offer powerful opportunities for identifying causal effects, and have motivated one of the most active areas of modern econometric research. This talk surveys recent developments in this rapidly evolving literature, with an emphasis on practical relevance and methodological clarity. A central focus is the difference-in-differences (DiD) framework, which has undergone substantial expansion in recent years. We discuss how the literature has moved beyond the classical two-period, two-group setting to accommodate staggered treatment adoption, heterogeneous treatment effects, and violations of the parallel trends assumption. Along the way, we highlight the critical identifying assumptions that underpin DiD estimation and the conditions under which conventional approaches can mislead. We also discuss the complementary literature on synthetic control methods and factor models, which have emerged as powerful alternatives to difference-in-differences. These methods offer flexible strategies for constructing credible counterfactuals when traditional assumptions are difficult to sustain, and have seen considerable methodological development of their own. Throughout, the talk is oriented toward practitioners.