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Ước lượng Khớp Nối Đa Kỳ×Ước lượng Khớp Động×
Lĩnh vựcSuy luận nhân quảSuy luận nhân quả
HọRegression modelRegression model
Năm ra đời20052010
Người khởi xướngAbadie (2005); Imbens & Wooldridge (2009)Lechner & Miquel (2010); building on Heckman, Ichimura & Todd (1998)
LoạiQuasi-experimental / causal inferenceNonparametric causal inference / matching
Công trình gốcAbadie, A. (2005). Semiparametric Difference-in-Differences Estimators. Review of Economic Studies, 72(1), 1-19. DOI ↗Lechner, M., & Miquel, R. (2010). Identification of the effects of dynamic treatments by sequential conditional independence assumptions. Empirical Economics, 39(1), 111-137. DOI ↗
Tên gọi khácpanel matching estimator, longitudinal matching, multi-wave matching, repeated-cross-section matchingdynamic treatment matching, sequential matching estimator, dynamic selection-on-observables, DME
Liên quan66
Tóm tắtThe multi-period matching estimator extends the standard matching framework to settings with multiple time periods, pairing each treated unit to similar untreated units based on pre-treatment covariates or propensity scores, then using within-pair before-after differences to estimate the average treatment effect on the treated (ATT). Leveraging repeated observations, it simultaneously controls for observed confounders and time-invariant unobserved heterogeneity.The Dynamic Matching Estimator extends standard matching methods to settings where treatment is assigned sequentially over multiple periods. Instead of a single treatment decision, units receive or forgo treatment at each time point, and the estimator identifies causal effects of entire treatment histories by matching on time-varying covariates and past treatment paths, under sequential conditional independence assumptions.
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ScholarGateSo sánh phương pháp: Multi-period Matching Estimator · Dynamic Matching Estimator. Truy cập ngày 2026-06-19 từ https://scholargate.app/vi/compare