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The inclusive Synthetic Control Method

Roberta Di Stefano, Giovanni Mellace

arXiv 26 Mar 2024 · Econometrics · 10 citations (OpenAlex)

arXiv:2403.17624 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We introduce the inclusive synthetic control method (iSCM), a modification of synthetic control methods that includes units in the donor pool potentially affected, directly or indirectly, by an intervention. This method is ideal for situations where including treated units in the donor pool is essential or where donor units may experience spillover effects. The iSCM is straightforward to implement with most synthetic control estimators. As an empirical illustration, we re-estimate the causal effect of German reunification on GDP per capita, accounting for spillover effects from West Germany to Austria.

Citation extraction

26
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Abadie, A., A. Diamond, and J. Hainmueller (2015) Comparative Politics and the Synthetic Control Method1.000114100%
2Abadie, A (2021) Using synthetic controls: Feasibility, data requirements, and methodological aspects0.9285480%
3Abadie, A., A. Diamond, and J. Hainmueller (2010) Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program0.92844100%
4Abadie, A. and J. L'Hour (2021) A penalized synthetic control estimator for disaggregated data0.92843100%
5Ben-Michael, E., A. Feller, and J. Rothstein (2022) Synthetic controls with staggered adoption0.73732100%
6Ferman, B. and C. Pinto (2021) Synthetic controls with imperfect pretreatment fit0.73732100%
7Kellogg, M., M. Mogstad, G. A. Pouliot, and A. Torgovitsky (2021) Combining matching and synthetic control to tradeoff biases from extrapolation and interpolation0.73732100%
8Amjad, M., D. Shah, and D. Shen (2018) Robust synthetic control0.64422100%
9Ben-Michael, E., A. Feller, and J. Rothstein (2021) The augmented synthetic control method0.64422100%
10Cao, J. and C. Dowd (2019) Estimation and Inference for Synthetic Control Methods with Spillover Effects, Papers 1902.07343, arXiv.org0.64422100%

Showing the top 10 of 26 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Estimation and Inference for Synthetic Control Methods with Spillover Effects0.87452
2Direct and spillover effects of a new tramway line on the commercial vitality of peripheral streets. A synthetic-control approach0.51121
3To Adopt or Not to Adopt: Heterogeneous Trade Effects of the Euro0.40511