EconBase
← All papers

Are Synthetic Control Weights Balancing Score?

Harsh Parikh

arXiv 3 Nov 2022 · Statistics — Methodology

arXiv:2211.01575 · PDF · DOI · OpenAlex · Extracted main text

Abstract

In this short note, I outline conditions under which conditioning on Synthetic Control (SC) weights emulates a randomized control trial where the treatment status is independent of potential outcomes. Specifically, I demonstrate that if there exist SC weights such that (i) the treatment effects are exactly identified and (ii) these weights are uniformly and cumulatively bounded, then SC weights are balancing scores.

Citation extraction

8
references
15
in-text mentions
8
distinct cited
0
self-citations
1,417
main-text words

appendix boundary found by none_found · 100% of the source is main text. Read the extracted text to check this.

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., Diamond, A., and Hainmueller, J (2015) Comparative politics and the synthetic control method0.58531100%
2Ferman, B. and Pinto, C (2017) Placebo tests for synthetic controls0.58531100%
3Abadie, A., Diamond, A., and Hainmueller, J (2010) Synthetic control methods for comparative case studies: Estimating the effect of california’s tobacco control program0.51121100%
4Hansen, B. B (2008) The prognostic analogue of the propensity score0.51121100%
5Rosenbaum, P. R. and Rubin, D. B (1983) The central role of the propensity score in observational studies for causal effects0.51121100%
6Ferman, B. and Pinto, C (2016) Revisiting the synthetic control estimator0.40511100%
7Johnson, C. S (2013) Compared to what? the effectiveness of synthetic control methods for causal inference in educational assessment0.40511100%
8Shi, X., Miao, W., Hu, M., and Tchetgen, E. T (2021) Theory for identification and inference with synthetic controls: a proximal causal inference framework0.40511100%

Showing the top 8 of 8 scored citations.