2018
DOI: 10.32614/rj-2018-016
|View full text |Cite
|
Sign up to set email alerts
|

ArCo: An R package to Estimate Artificial Counterfactuals

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-inte… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
6
0

Year Published

2019
2019
2023
2023

Publication Types

Select...
4
1

Relationship

0
5

Authors

Journals

citations
Cited by 6 publications
(6 citation statements)
references
References 15 publications
0
6
0
Order By: Relevance
“…The post-treatment dyanmics of both series largely mimics that of the SCM plots, lending credence to our SCM findings, and their interpretation. 9 We trial multiple ArCo specifications (R package: ArCo) based on examples provided by Fonseca, Masini, Medeiros, and Vasconcelos (2018). The observed trends and results are consistent across all specifications.…”
Section: Robustness Of Synthetic New Hampshire: Arco Estimationmentioning
confidence: 83%
“…The post-treatment dyanmics of both series largely mimics that of the SCM plots, lending credence to our SCM findings, and their interpretation. 9 We trial multiple ArCo specifications (R package: ArCo) based on examples provided by Fonseca, Masini, Medeiros, and Vasconcelos (2018). The observed trends and results are consistent across all specifications.…”
Section: Robustness Of Synthetic New Hampshire: Arco Estimationmentioning
confidence: 83%
“…As the SC method the application of the AC method is based on two key assumptions (Fonseca et al, 2018 ): The control units are not affected by the intervention (the crisis) and The data are trend stationary. …”
Section: Methodsmentioning
confidence: 99%
“…It is characterized by a rapid rise in life expectancy thanks, above all, to a significant reduction in cardiovascular mortality (the so-called cardiovascular revolution). Third, Fonseca et al ( 2018 ) suggest using at least 40–50 observations when applying the AC method. However, since our results may depend on the length of the time series employed in the procedure, we resolved to repeat our tests by also using the shorter period 1990–2019.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“… 1 Carvalho, Masini, and Medeiros (2018) propose statistical inference only for the average treatment effect. However, Fonseca et al (2018) point out that estimation of the covariance matrix is practically challenging for some choices of robust estimators. …”
mentioning
confidence: 99%