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Synthetic Controls in Action
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In this article we propose a set of simple principles to guide empirical practice in synthetic control studies. The proposed principles follow from formal properties of synthetic control estimators, and pertain to the nature, implications, and prevention of over-fitting biases within a synthetic control framework, to the interpretability of the results, and to the availability of validation exercises. We discuss and visually demonstrate the relevance of the proposed principles under a variety of data configurations.
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Cited by 1 Pith paper
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Bayesian Donor Set Selection in Synthetic Controls
A Gamma–Bernoulli hierarchical prior lets Bayesian synthetic controls select donors and put exact zeros on excluded units while staying on the simplex, with posterior consistency and better recovery of sparse donors i...
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