Triple DiD

The triple DiD (DDD) module provides estimators for settings where units must satisfy two criteria to be treated: belonging to a group that enables treatment and being in an eligible partition of the population. This design allows for both group-specific and partition-specific violations of parallel trends, relaxing the assumptions required by standard DiD. The implementation follows Ortiz-Villavicencio and Sant’Anna (2025).

Main Functions

ddd	Compute the doubly robust Triple Difference-in-Differences estimator for the ATT.
agg_ddd	Aggregate group-time average treatment effects for triple differences.

Two-Period Estimators

ddd_panel	Compute the 2-period doubly robust DDD estimator for the ATT with panel data.
ddd_rc	Compute the 2-period doubly robust DDD estimator for the ATT with repeated cross-section data.

Multi-Period Estimators

ddd_mp	Compute the multi-period doubly robust DDD estimator for the ATT with panel data.
ddd_mp_rc	Compute the multi-period doubly robust DDD estimator for the ATT with repeated cross-section data.

Result Objects

DDDMultiPeriodResult	Container for multi-period DDD estimation results.
DDDMultiPeriodRCResult	Container for multi-period DDD repeated cross-section estimation results.
DDDPanelResult	Container for DDD panel estimation results.
DDDRCResult	Container for DDD repeated cross-section estimation results.
DDDAggResult	Container for aggregated DDD treatment effect parameters.