Package: DiSCos 0.1.1

DiSCos: Distributional Synthetic Controls Estimation

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.

Authors:David Van Dijcke [aut, cre], Florian Gunsilius [aut], Siyun He [aut]

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DiSCos.pdf |DiSCos.html
DiSCos/json (API)
NEWS

# Install 'DiSCos' in R:
install.packages('DiSCos', repos = c('https://davidvandijcke.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/davidvandijcke/discos/issues

Datasets:

On CRAN:

6 exports 1 stars 2.02 score 72 dependencies 8 scripts 301 downloads

Last updated 6 days agofrom:d79d3d8140. Checks:OK: 6 ERROR: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 11 2024
R-4.5-winERRORSep 11 2024
R-4.5-linuxOKSep 11 2024
R-4.4-winOKSep 11 2024
R-4.4-macOKSep 11 2024
R-4.3-winOKSep 11 2024
R-4.3-macOKSep 11 2024

Exports:DiSCoDiSCo_iterDiSCoTDiSCoTEAex_gmmpermut

Dependencies:abindberryFunctionsbitbit64clarabelclicolorspacecvarCVXRdata.tabledistilleryECOSolveRevdevirevmixextRemesextremeStatfansifarverfastICAfBasicsfExtremesfGarchgbutilsggplot2gluegmpgoftestgslgssgtableismevisobandlabelinglatticelifecyclelmomcoLmomentsmagrittrMASSMatrixmgcvmunsellnlmenumDerivosqppbapplypillarpkgconfigpracmaR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackRenextrlangRmpfrscalesscsSparseMspatialstabledisttibbletimeDatetimeSeriesutf8vctrsviridisLitewithr

Empirical Application in Gunsilius (2023)

Rendered fromDube2019.Rmdusingknitr::rmarkdownon Sep 11 2024.

Last update: 2024-07-23
Started: 2023-11-27