DiSCo_per_rank

This function ranks the squared Wasserstein distances and returns the p-values for each time period

internal

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

Florian Gunsilius

Siyun He

DiSCo_per_rank function

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

Arguments

DiSCo_per_rank — DiSCo_per_rank

<dl>

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


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

</dl>

DiSCo_per_rank: DiSCo_per_rank

Description

Usage

Value

Arguments