Robust Synthetic Control
@article{Amjad2018RobustSC, title={Robust Synthetic Control}, author={Muhammad J. Amjad and D. Shah and Dennis Shen}, journal={J. Mach. Learn. Res.}, year={2018}, volume={19}, pages={22:1-22:51} }
We present a robust generalization of the synthetic control method for comparative case studies. Like the classical method, we present an algorithm to estimate the unobservable counterfactual of a treatment unit. A distinguishing feature of our algorithm is that of de-noising the data matrix via singular value thresholding, which renders our approach robust in multiple facets: it automatically identifies a good subset of donors, overcomes the challenges of missing data, and continues to work… CONTINUE READING
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