cic: Change in Changes

In qte: Quantile Treatment Effects

Change in Changes

Description

Computes Quantile Treatment effects on the Treated (QTT) and the Average Treatment Effect on the Treated (ATT) using the Change in Changes identification strategy of Athey and Imbens (2006). Handles two-period data and staggered treatment adoption uniformly: a two-period, two-group dataset is the degenerate single-(g,t) case. Supports both panel and repeated cross sections data.

Usage

cic(
  yname,
  gname,
  tname,
  idname = NULL,
  data,
  panel = TRUE,
  xformula = ~1,
  weightsname = NULL,
  control_group = "notyettreated",
  anticipation = 0,
  alp = 0.05,
  cband = TRUE,
  biters = 100,
  cl = 1,
  ret_quantile = NULL,
  gt_type = "att",
  probs = NULL
)

Arguments

yname	Name of the outcome variable in data.
gname	Name of the treatment group variable (first treatment period; 0 for never-treated units).
tname	Name of the time period variable.
idname	Name of the unit id variable. Required when panel = TRUE.
data	A data frame.
panel	Logical; TRUE (default) for panel data, FALSE for repeated cross sections.
xformula	One-sided formula for covariates used in the covariate adjustment. Default ~1 uses no covariates.
weightsname	Name of the column in data containing sampling weights. Default NULL uses equal weights.
control_group	Which units to use as the comparison group: "notyettreated" (default) or "nevertreated".
anticipation	Number of periods of anticipation. Default 0.
alp	Significance level for confidence bands. Default 0.05.
cband	Logical; if TRUE (default) compute a uniform confidence band rather than pointwise intervals.
biters	Number of bootstrap iterations. Default 100.
cl	Number of clusters for parallel computation. Default 1.
ret_quantile	Passed through to ptetools for the "qott" case. Ignored when gt_type = "qtt" (use probs instead).
gt_type	Type of group-time effect to compute. "att" (default) returns ATT(g,t). "qtt" returns the full QTT curve over probs using mixture-CDF aggregation. "qott" returns the quantile of the individual treatment effect distribution under rank invariance (panel only).
probs	For gt_type = "qtt", the quantile grid at which to evaluate the QTT curve. Default is seq(0.05, 0.95, 0.05).

Value

For gt_type = "att", a pte_results object from ptetools. For gt_type = "qtt", a pte_qtt object with overall, group-specific, and dynamic QTT curves and bootstrap SEs.

References

Athey, Susan and Guido Imbens. “Identification and Inference in Nonlinear Difference-in-Differences Models.” Econometrica 74(2), pp. 431-497, 2006.

Examples

data(mpdta, package = "did")

## ATT aggregated across all groups and periods
res_att <- cic(yname = "lemp", gname = "first.treat", tname = "year",
               idname = "countyreal", data = mpdta,
               gt_type = "att", biters = 20)
summary(res_att)

## Full QTT curve at selected quantiles
res_qtt <- cic(yname = "lemp", gname = "first.treat", tname = "year",
               idname = "countyreal", data = mpdta,
               gt_type = "qtt", probs = seq(0.1, 0.9, 0.1), biters = 20)
summary(res_qtt)

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