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Difference-in-Differences Meets Synthetic Control: Doubly Robust Identification and Estimation
Difference-in-Differences (DiD) and Synthetic Control (SC) are widely used methods for causal inference in panel data, each with distinct strengths and limitations. We propose a novel method for short-panel causal inference that integrates the advantages of both approaches. Our method delivers a dou
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