Knowledge of causal effects is of great importance to decision makers in a wide variety of
settings. In many cases, however, these causal effects are not known to the decision makers …

This paper synthesizes recent advances in the econometrics of difference-in-differences
(DiD) and provides concrete recommendations for practitioners. We begin by articulating a …

Linear regressions with period and group fixed effects are widely used to estimate policie's
effects: 26 of the 100 most cited papers published by the American Economic Review from …

A recent literature has shown that when adoption of a treatment is staggered and average
treatment effects vary across groups and over time, difference-in-differences regression …

Difference-in-differences is one of the most used identification strategies in empirical work in
economics. This chapter reviews a number of important, recent developments related to …

We develop a framework for difference-in-differences designs with staggered treatment
adoption and heterogeneous causal effects. We show that conventional regression-based …

Does market-incentivized energy policy encourage low-carbon growth in resource-based
cities (RBCs)? How to turn the resource curse and the carbon curse into blessings depends …

Existing research shows that distrust of the police is widespread and consequential for
public safety. However, there is a shortage of interventions that demonstrably reduce …

This paper considers identification and estimation of causal effect parameters from
participating in a binary treatment in a difference in differences (DID) setup when the parallel …

In this survey we discuss the recent causal panel data literature. This recent literature has
focused on credibly estimating causal effects of binary interventions in settings with …