diffQ


<div class="section" id="takes-a-single-set-of-quantiles">
<h3>takes a single set of quantiles</h3><p></p><p>
</p><p>(not qtes as in diffquantiles)
and returns the difference between particular ones</p>
</div>


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) <doi:10.3982/QE935>, Callaway, Li, and Oka (2018) <doi:10.1016/j.jeconom.2018.06.008>).

Brantly Callaway

Quantile Treatment Effects

diffQ function

<dl><p></p><p><dt>qvec</dt>
<dd><p>vector of quantiles</p></dd></p><p>
<dt>tauvec</dt>
<dd><p>vector of tau (should be same length as qvec)</p></dd></p><p>
<dt>hightau</dt>
<dd><p>upper quantile</p></dd></p><p>
<dt>lowtau</dt>
<dd><p>lower quantile</p></dd></p><p></p></dl>

Arguments


<div class='section' id='takes-a-single-set-of-quantiles'>
<h3>takes a single set of quantiles</h3>


<p>(not qtes as in diffquantiles)
and returns the difference between particular ones</p>
</div>


diffQ — diffQ

<dl>

<dt>qvec</dt>
<dd><p>vector of quantiles</p></dd>


<dt>tauvec</dt>
<dd><p>vector of tau (should be same length as qvec)</p></dd>


<dt>hightau</dt>
<dd><p>upper quantile</p></dd>


<dt>lowtau</dt>
<dd><p>lower quantile</p></dd>

</dl>

diffQ: diffQ

Description

takes a single set of quantiles

Usage

Value

Arguments