ddid_gt: Distributional DiD: group-time estimator

In qte: Quantile Treatment Effects

Distributional DiD: group-time estimator

Description

Computes the distributional DiD ATT and counterfactual outcome distribution for a single 2x2 (pre/post x treated/control) data subset. Serves directly as the attgt_fun argument to ptetools::pte.

Identification. Under distributional parallel trends and a copula restriction (Callaway, Li, and Oka 2018), the counterfactual outcome for each control unit j is

kcf_j = \Delta Y_{\text{ctrl},j} + Q_{1,\text{pre}}(u_j)

where \Delta Y_{\text{ctrl},j} = Y_{\text{post},j} - Y_{\text{pre},j} is the observed change for control unit j, u_j = F_{0,\text{pre}}(Y_{\text{pre},j}) is that unit's rank in the control pre-period distribution, and Q_{1,\text{pre}} is the quantile function of the treated pre-period distribution. The unconditional counterfactual distribution F_{Y(0),\text{post}|D=1} is then the (weighted) empirical CDF of \{kcf_j\}.

Unlike CiC, QDiD, and MDiD, the counterfactual is indexed over control units, not treated units. Consequently F0 and the ATT counterfactual term are weighted by w_pre_ctrl, and no individual treatment effect distribution (Fte) is returned.

Panel data required. The estimator needs the actual change \Delta Y_{\text{ctrl},j} for each control unit, which requires observing the same units in both periods.

Usage

ddid_gt(gt_data, xformula = ~1, ...)

Arguments

gt_data	A data frame (typically a gt_data_frame from ptetools) with columns name ("pre" or "post"), D (treatment dummy), Y (outcome), id (unit identifier), .w (sampling weights), and any covariate columns referenced by xformula. Control units must be observed in both periods.
xformula	One-sided formula for covariates. Default ~1 uses no covariates. With covariates, the unconditional rank u_j is replaced by a conditional rank estimated via quantile regression on the control pre-period (QR0tmin1), and the treated pre-period quantile is replaced by a conditional quantile (QR1tmin1) evaluated at that rank and the control unit's own covariate values.
...	Additional arguments passed through by ptetools; not used directly.

Value

A ptetools::attgt_noif object with the ATT estimate and, in extra_gt_returns, F0 (weighted ECDF of counterfactual outcomes indexed over control units), F1 (weighted ECDF of observed treated post-period outcomes), and Fte = NULL (individual treatment effect distribution is not identified for this estimator).

References

Callaway, Brantly, Tong Li, and Tatsushi Oka. “Quantile Treatment Effects in Difference in Differences Models under Dependence Restrictions and with Only Two Time Periods.” Journal of Econometrics 206(2), pp. 395-413, 2018.

qte documentation built on July 23, 2026, 5:13 p.m.