MF-SCM constructs synthetic control weights from mixed-frequency data, proves the estimator achieves the lowest possible squared prediction error among averaging methods, and derives asymptotic inference for the average treatment effect.
arXiv preprint arXiv:2211.12095 , year=
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The distributional synthetic control estimator achieves the lowest possible squared prediction error for quantile treatment effects and has established convergence rates for its weights.
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Synthetic Control Method with Mixed Frequency Data
MF-SCM constructs synthetic control weights from mixed-frequency data, proves the estimator achieves the lowest possible squared prediction error among averaging methods, and derives asymptotic inference for the average treatment effect.
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Asymptotic Properties of the Distributional Synthetic Controls
The distributional synthetic control estimator achieves the lowest possible squared prediction error for quantile treatment effects and has established convergence rates for its weights.