ArCo: An R package to Estimate Artificial Counterfactuals

Yuri R. Fonseca, Ricardo P. Masini, Marcelo C. Medeiros, Gabriel F.R. Vasconcelos

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper we introduce the ArCo package for R which consists of a set of functions to implement the the Artificial Counterfactual (ArCo) methodology to estimate causal effects of an intervention (treatment) on aggregated data and when a control group is not necessarily available. The ArCo method is a two-step procedure, where in the first stage a counterfactual is estimated from a large panel of time series from a pool of untreated peers. In the second-stage, the average treatment effect over the post-intervention sample is computed. Standard inferential procedures are available. The package is illustrated with both simulated and real datasets.

Original languageEnglish (US)
Pages (from-to)91-108
Number of pages18
JournalR Journal
Volume10
Issue number1
DOIs
StatePublished - Jul 1 2018
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty

Fingerprint Dive into the research topics of 'ArCo: An R package to Estimate Artificial Counterfactuals'. Together they form a unique fingerprint.

Cite this