ggqte

qteobj

main

ylab

ylim

ybreaks

xbreaks

<p>options are "pointwise", "uniform" or both; pointwise confidence
intervals cover the QTE at each particular point with a fixed probability,
uniform confidence bands cover the entire curve with a fixed
probability.  Uniform confidence bands will tend to be wider.  The option
"both" will plot both types of confidence intervals</p>

setype

<p>Makes somewhat nicer plots of quantile treatment effects
 by using ggplot</p>

Provides several methods for computing the Quantile Treatment Effect (QTE) and Quantile Treatment Effect on the Treated (QTT). The main cases covered are (i) Treatment is randomly assigned, (ii) Treatment is as good as randomly assigned after conditioning on some covariates (also called conditional independence or selection on observables) using the methods developed in Firpo (2007) <doi:10.1111/j.1468-0262.2007.00738.x>, (iii) Identification is based on a Difference in Differences assumption (several varieties are available in the package e.g. Athey and Imbens (2006) <doi:10.1111/j.1468-0262.2006.00668.x> Callaway and Li (2019) <https://ssrn.com/abstract=3013341>, Callaway, Li, and Oka (2018) <doi:10.1016/j.jeconom.2018.06.008>).

Brantly Callaway

Quantile Treatment Effects

ggqte function

ggqte — ggqte

ggqte: ggqte

Description

Usage

Arguments

Value