Introduces BGATT estimand and influence-function-based estimators for covariate-balanced group treatment effect heterogeneity in DiD under conditional parallel trends, with ML nuisance estimation and asymptotic normality.
High-Dimensional
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
econ.EM 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Group-Level Treatment Effect Heterogeneity in Difference-in-Differences: A Balanced Approach
Introduces BGATT estimand and influence-function-based estimators for covariate-balanced group treatment effect heterogeneity in DiD under conditional parallel trends, with ML nuisance estimation and asymptotic normality.