simulation_dgp: Simulating observations from the data-generating process...

In ATbounds: Bounding Treatment Effects by Limited Information Pooling

Simulating observations from the data-generating process considered in Lee and Weidner

Description

Simulates observations from the data-generating process considered in Lee and Weidner

Usage

simulation_dgp(n, ps_spec = "overlap", x_discrete = FALSE)

Arguments

n	sample size
ps_spec	specification of the propensity score: "overlap" or "non-overlap" (default: "overlap")
x_discrete	TRUE if the distribution of the covariate is uniform on the grid -3.0, -2.9, ..., 3.0 and FALSE if the distribution of the covariate is uniform on [-3,3] (default: FALSE)

Value

An S3 object of type "ATbounds". The object has the following elements.

outcome	n observations of binary outcomes
treat	n observations of binary treatments
covariate	n observations of a scalar covariate
ate_oracle	the sample analog of E[Y(1) - Y(0)]
att_oracle	the sample analog of E[D * (Y(1) - Y(0)) | D = 1]

References

Sokbae Lee and Martin Weidner. Bounding Treatment Effects by Pooling Limited Information across Observations. Forthcoming at the Journal of Econometrics.

Examples

  data <- simulation_dgp(100, ps_spec = "overlap")
  y <- data$outcome
  d <- data$treat
  x <- data$covariate
  ate <- data$ate_oracle
  att <- data$att_oracle

ATbounds documentation built on May 8, 2026, 1:06 a.m.