autoplot.QTE

Plot a <code>QTE</code> object as a quantile treatment effect curve
with optional confidence bands.

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 covariates (selection on
observables) using the methods of Firpo (2007)
<doi:10.1111/j.1468-0262.2007.00738.x>, and (iii) identification is based
on a Difference in Differences assumption, with support for several
varieties including Athey and Imbens (2006)
<doi:10.1111/j.1468-0262.2006.00668.x>, Callaway and Li (2019)
<doi:10.3982/QE935>, and Callaway, Li, and Oka (2018)
<doi:10.1016/j.jeconom.2018.06.008>. Version 2.0 adds a unified staggered
treatment adoption API (built on 'ptetools') for all DiD-based estimators,
as well as a new lagged-outcome unconfoundedness estimator ('lou_qtt').

Brantly Callaway

Quantile Treatment Effects

autoplot.QTE function

<dl><dt>object</dt>
<dd>a <code>QTE</code> object, as returned by <code>unc_qte</code>.</dd>
<dt>cband</dt>
<dd>logical; if <code>TRUE</code> (default), show the uniform confidence
band stored in <code>object$qte.upper</code> / <code>object$qte.lower</code>.
If <code>FALSE</code>, show pointwise intervals computed from <code>object$qte.se</code>.</dd>
<dt>ylab</dt>
<dd>label for the y-axis. Default <code>"QTE"</code>.</dd>
<dt>...</dt>
<dd>unused.</dd></dl>

Arguments

autoplot.QTE — autoplot.QTE

<dl>

<dt>object</dt>
<dd>a <code>QTE</code> object, as returned by <code>unc_qte</code>.</dd>


<dt>cband</dt>
<dd>logical; if <code>TRUE</code> (default), show the uniform confidence
band stored in <code>object$qte.upper</code> / <code>object$qte.lower</code>.
If <code>FALSE</code>, show pointwise intervals computed from <code>object$qte.se</code>.</dd>


<dt>ylab</dt>
<dd>label for the y-axis. Default <code>"QTE"</code>.</dd>


<dt>...</dt>
<dd>unused.</dd>

</dl>

autoplot.QTE: autoplot.QTE

Description

Usage

Value

Arguments