Debiasing and $t$-tests for synthetic control inference on average causal effects
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2018
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| _version_ | 1866909620391378944 |
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| author | Chernozhukov, Victor Wuthrich, Kaspar Zhu, Yinchu |
| author_facet | Chernozhukov, Victor Wuthrich, Kaspar Zhu, Yinchu |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1812_10820 |
| institution | arXiv |
| publishDate | 2018 |
| record_format | arxiv |
| spellingShingle | Debiasing and $t$-tests for synthetic control inference on average causal effects Chernozhukov, Victor Wuthrich, Kaspar Zhu, Yinchu Econometrics 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. |
| title | Debiasing and $t$-tests for synthetic control inference on average causal effects |
| topic | Econometrics |
| url | https://arxiv.org/abs/1812.10820 |