compute.spatt

<code>compute.spatt</code> implements the method of Abadie (2005); this is
computed automatically in several other methods in the qte package
but this function provides a standalone result when quantiles are not
wanted/needed.
<code>compute.ddid2</code> uses two periods of data (repeated cross sections
or panel) to estimate the Quantile Treatment Effect on the Treated (QTET)

internal

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

compute.spatt function

<dl><dt>qp</dt>
<dd>QTEparams object containing the parameters passed to ciqte</dd></dl>

Arguments

compute.spatt — compute.spatt

<dl>

<dt>qp</dt>
<dd>QTEparams object containing the parameters passed to ciqte</dd>

</dl>

compute.spatt: compute.spatt

Description

Usage

Value

Arguments