Victor Chernozhukov, Kaspar Wuthrich, Yinchu Zhu
arXiv 27 Dec 2018 · Econometrics · publishedJournal of Political Economy (2026) · 15 citations (OpenAlex)
arXiv:1812.10820 · PDF · DOI · OpenAlex · Extracted main text
We propose a practical and robust method for making inferences on average treatment effects estimated by synthetic controls. We develop a $K$-fold cross-fitting procedure for bias correction. To avoid the difficult estimation of the long-run variance, inference is based on a self-normalized $t$-statistic, which has an asymptotically pivotal $t$-distribution. Our $t$-test is easy to implement, provably robust against misspecification, and valid with stationary and non-stationary data. It demonstrates an excellent small sample performance in application-based simulations and performs well relative to other methods. We illustrate the usefulness of the $t$-test by revisiting the effect of carbon taxes on emissions.
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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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Andersson, J. J (2019) Carbon taxes and CO2 emissions: Sweden as a case study | 1.000 | 17 | 5 | 100% |
| 2 | Chernozhukov, V., Wüthrich, K., and Zhu, Y (2021) An exact and robust conformal inference method for counterfactual and synthetic controls self | 1.000 | 9 | 4 | 100% |
| 3 | Cattaneo, M. D., Feng, Y., and Titiunik, R (2021) Prediction intervals for synthetic control methods | 1.000 | 7 | 3 | 100% |
| 4 | Cattaneo, M. D., Feng, Y., Palomba, F., and Titiunik, R (2023) Uncertainty quantification in synthetic controls with staggered treatment adoption | 1.000 | 7 | 3 | 100% |
| 5 | Li, K. T (2020) Statistical inference for average treatment effects estimated by synthetic control methods | 0.977 | 15 | 6 | 93% |
| 6 | Arkhangelsky, D., Athey, S., Hirshberg, D. A., Imbens, G. W., and Wa… (2021) Synthetic difference-in-differences | 0.969 | 11 | 5 | 91% |
| 7 | Abadie, A (2021) Using synthetic controls: Feasibility, data requirements, and methodological aspects | 0.928 | 5 | 4 | 80% |
| 8 | Ben-Michael, E., Feller, A., and Rothstein, J (2021) The augmented synthetic control method | 0.928 | 5 | 3 | 80% |
| 9 | Doudchenko, N. and Imbens, G. W (2016) Balancing, regression, difference-in-differences and synthetic control methods: A synthesis | 0.928 | 4 | 3 | 100% |
| 10 | Abadie, A., Diamond, A., and Hainmueller, J (2010) Synthetic control methods for comparative case studies: Estimating the effect of Californias tobacco control program | 0.843 | 20 | 8 | 60% |
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