permut

Object to hold results of permutation test

The method of synthetic controls is a widely-adopted tool for evaluating causal effects of policy changes in settings with observational data. In many settings where it is applicable, researchers want to identify causal effects of policy changes on a treated unit at an aggregate level while having access to data at a finer granularity. This package implements a simple extension of the synthetic controls estimator, developed in Gunsilius (2023) <doi:10.3982/ECTA18260>, that takes advantage of this additional structure and provides nonparametric estimates of the heterogeneity within the aggregate unit. The idea is to replicate the quantile function associated with the treated unit by a weighted average of quantile functions of the control units. The package contains tools for aggregating and plotting the resulting distributional estimates, as well as for carrying out inference on them.

David Van Dijcke

DiSCos

Distributional Synthetic Controls Estimation

permut function

<dl><dt>distp</dt>
<dd>List of squared Wasserstein distances between the control units</dd>
<dt>distt</dt>
<dd>List of squared Wasserstein distances between the target unit and the control units</dd>
<dt>p_overall</dt>
<dd>Overall p-value</dd>
<dt>J_1</dt>
<dd>Number of control units</dd>
<dt>q_min</dt>
<dd>Minimum quantile</dd>
<dt>q_max</dt>
<dd>Maximum quantile</dd>
<dt>plot</dt>
<dd>ggplot object containing plot of squared Wasserstein distances over time for all permutations.</dd></dl>

Arguments

permut — permut

<dl>

<dt>distp</dt>
<dd>List of squared Wasserstein distances between the control units</dd>


<dt>distt</dt>
<dd>List of squared Wasserstein distances between the target unit and the control units</dd>


<dt>p_overall</dt>
<dd>Overall p-value</dd>


<dt>J_1</dt>
<dd>Number of control units</dd>


<dt>q_min</dt>
<dd>Minimum quantile</dd>


<dt>q_max</dt>
<dd>Maximum quantile</dd>


<dt>plot</dt>
<dd>ggplot object containing plot of squared Wasserstein distances over time for all permutations.</dd>

</dl>

permut: permut

Description

Usage

Value

Arguments