Difference-in-differences (DID) is a popular method for estimating causal effects in economics and other social sciences. It compares the outcomes of two groups before and after a policy change or ...

The difference between these outcomes is the individual treatment effect. However, you cannot observe both outcomes for the same unit at the same time, so you need to use econometric data to infer ...

This paper proposes a method to estimate treatment effects in difference-in-differences designs in which the treatment start is staggered over time and treatment effects are heterogeneous by group, ...

We study a difference-in-differences (DiD) framework where groups experience unequal treatment statuses in the pre-policy change period. This approach is commonly employed in empirical studies but it ...

The command estimates the average and quantile treatment effects of a treatment in settings where repeated cross sections of individuals are observed in a treatment group and a control group, before ...

The extrapolation of the model during the treat period (red line) serves as a counterfactual. This counterfactual is compared with the actual outcome (black line), and the difference is the estimated ...

Difference-in-Differences Approach for Analyzing the Effects of the Olympics on the Economy of the Country While it is assumed that hosting the Summer Olympics can positively affect the country’s ...

Author: Thomas A. Hegland, thomashegland.com, @thomas_hegland Citation: Thomas A. Hegland, 2023. "WOOLDID: Stata module to estimate Difference-in-Differences Treatment Effects with Staggered Treatment ...