文章基本信息

标题：ArCo: An R package to Estimate Artificial Counterfactuals
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作者：Yuri R. Fonseca ; Ricardo P. Masini ; Marcelo C. Medeiros 等
期刊名称：R News
印刷版ISSN：1609-3631
出版年度：2018
卷号：10
期号：1
页码：91-108
语种：English
出版社：The R Foundation for Statistical Computing
摘要：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.