qte (version 2.0.0)

qdid: Quantile Difference-in-Differences

Description

Computes Quantile Treatment effects on the Treated (QTT) and the Average Treatment Effect on the Treated (ATT) using the Quantile Difference-in-Differences identification strategy of Athey and Imbens (2006). Handles two-period data and staggered treatment adoption uniformly. Supports both panel and repeated cross sections data.

Usage

qdid(
  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
)

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.

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.

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 (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).

References

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

Examples

# \donttest{
data(mpdta, package = "did")

## ATT aggregated across all groups and periods
res_att <- qdid(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 <- qdid(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)
# }