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Tree-based Synthetic Control Methods: Consequences of moving the US Embassy

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  • rp20_04

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We recast the synthetic controls for evaluating policies as a counterfactual prediction problem and replace its linear regression with a nonparametric model inspired by machine learning. The proposed method enables us to achieve more accurate counterfactual predictions. We apply our method to a highly-debated policy: the move of the US embassy to Jerusalem. In Israel and Palestine, we find that the average number of weekly conflicts has increased by roughly 103% over 48 weeks since the move was announced on December 6, 2017. Using conformal inference and placebo tests, we justify our model and find the increase to be statistically significant.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages56
Publication statusPublished - May 2020
SeriesCREATES Research Papers

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