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A distributional synthetic control method for policy evaluation

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  • Yi‐Ting Chen

Abstract

We extend the synthetic control method to evaluate the distributional effects of policy intervention in the possible presence of poor matching. The counterfactuals (or intervention effects) are identified by matching a vector of pre‐intervention quantile residuals of the treated unit and a convex combination of its potential‐control counterparts. The residuals are orthogonal to a set of observable common factors that control for the potentially poor matching. We also apply our method to a set of case studies that explore the distributional effects of state‐level minimum‐wage hikes in the USA.

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  • Yi‐Ting Chen, 2020. "A distributional synthetic control method for policy evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 505-525, August.
    • Handle: RePEc:wly:japmet:v:35:y:2020:i:5:p:505-525
    DOI: 10.1002/jae.2778
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    Cited by:

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    3. Shengli Dai & Weimin Zhang & Linshan Lan, 2022. "Quantitative Evaluation of China’s Ecological Protection Compensation Policy Based on PMC Index Model," IJERPH, MDPI, vol. 19(16), pages 1-24, August.
    4. Zhang, Cheng & Zhou, Xinxin & Zhou, Bo & Zhao, Ziwei, 2022. "Impacts of a mega sporting event on local carbon emissions: A case of the 2014 Nanjing Youth Olympics," China Economic Review, Elsevier, vol. 73(C).
    5. Li, Yuansen & Tolhurst, Tor N., 2024. "Adoption of Genetically Engineered Seeds in China: Predicting Treatment Effects on the Crop-Yield Distribution by Synthetic Control," 2024 Annual Meeting, July 28-30, New Orleans, LA 343921, Agricultural and Applied Economics Association.
    6. Kraft, Kornelius & Lammers, Alexander, 2021. "Bargaining Power and the Labor Share - a Structural Break Approach," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242342, Verein für Socialpolitik / German Economic Association.
    7. Ricardo Masini, 2022. "Distributional Counterfactual Analysis in High-Dimensional Setup," Papers 2202.11671, arXiv.org, revised Sep 2023.

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