Synthetic Difference in Differences

@article{Arkhangelsky2018SyntheticDI,
  title={Synthetic Difference in Differences},
  author={D. Arkhangelsky and Susan Athey and David A. Hirshberg and Guido Imbens and Stefan Wager},
  journal={NBER Working Paper Series},
  year={2018}
}
We present a new perspective on the Synthetic Control (SC) method as a weighted least squares regression estimator with time fixed effects and unit weights. This perspective suggests a generalization with two way (both unit and time) fixed effects, and both unit and time weights, which can be interpreted as a unit and time weighted version of the standard Difference In Differences (DID) estimator. We find that this new Synthetic Difference In Differences (SDID) estimator has attractive… 
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129 Citations
Highly Influential Citations
14
Background Citations
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Methods Citations
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Results Citations
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129 Citations

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TLDR
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A Penalized Synthetic Control Estimator for Disaggregated Data
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This work proposes a synthetic control estimator that penalizes the pairwise discrepancies between the characteristics of the treated units and the Characteristics of the units that contribute to their synthetic controls.
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