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パネルイベントスタディ×合成コントロール法(SCM)×
分野因果推論因果推論
系統Regression modelRegression model
提唱年1990s–2020s (modern panel formulation)2003–2010
提唱者Formalized by Freyaldenhoven, Hansen, Perez-Orive & Shapiro (2021); widely applied in finance (Fama et al. 1969) and policy evaluationAlberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
種類Quasi-experimental / causal panel designQuasi-experimental causal inference
原典Freyaldenhoven, S., Hansen, C., Perez-Orive, J., & Shapiro, J. M. (2021). Visualization, Identification, and Estimation in the Linear Panel Event-Study Design. NBER Working Paper 29170. National Bureau of Economic Research. link ↗Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505. DOI ↗
別名event-study regression, dynamic DiD, relative-time regression, distributed-lag panel modelSCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
関連44
概要A panel event study estimates the dynamic causal effect of a treatment or policy by regressing an outcome on a full set of relative-time indicators — one for each period before and after the event — while controlling for unit and time fixed effects. The resulting coefficient plot shows how the treated units diverged from untreated units at each point in calendar time relative to their treatment date, making both pre-treatment trend violations and post-treatment effect trajectories immediately visible.The Synthetic Control Method estimates the causal effect of a treatment or policy on a single treated unit by constructing a weighted combination of untreated units — the synthetic control — that closely resembles the treated unit before the intervention. The gap between the treated unit and its synthetic counterpart after the intervention is the estimated treatment effect.
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ScholarGate手法を比較: Panel Event Study · Synthetic Control Method. 2026-06-17に以下より取得 https://scholargate.app/ja/compare