REVIEW 2 cited by
Synthetic Controls with spillover effects: A comparative study
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Signed reviews
read the original abstract
Iterative Synthetic Control Method is introduced in this study, a modification of the Synthetic Control Method (SCM) designed to improve its predictive performance by utilizing control units affected by the treatment in question. This method is then compared to other SCM modifications: SCM without any modifications, SCM after removing all spillover-affected units, Inclusive SCM, and the SP SCM model. For the comparison, Monte Carlo simulations are utilized, generating artificial datasets with known counterfactuals and comparing the predictive performance of the methods. Generally, the Inclusive SCM performed best in all settings and is relatively simple to implement. The Iterative SCM, introduced in this paper, was in close seconds, with a small difference in performance and a simpler implementation.
Forward citations
Cited by 2 Pith papers
-
Learning about Treatment Effects in Panels under Unknown Interference
Under unknown interference, the sharp identified set for a panel treatment effect is characterized exactly by feasibility of a finite linear system, enabling uniform candidatewise bootstrap inference.
-
Accounting for spillover when using the augmented synthetic control method: estimating the effect of localized COVID-19 lockdowns in Chile
ASCM-SC stratifies donor units by neighbor-treatment status to estimate direct, total, and spillover effects under interference; in the Chilean COVID-19 application, most confidence intervals include zero.
Discussion (0). Continue with ORCID to comment.