เปรียบเทียบวิธี

	ตัวประมาณค่าการจับคู่แบบพลวัต	ไดนามิก ดิฟ-อิน-ดิฟ (Dynamic Difference-in-Differences)
สาขาวิชา	การอนุมานเชิงสาเหตุ	การอนุมานเชิงสาเหตุ
ตระกูล	Regression model	Regression model
ปีกำเนิด	2010	2021
ผู้ริเริ่ม	Lechner & Miquel (2010); building on Heckman, Ichimura & Todd (1998)	Callaway & Sant'Anna; Sun & Abraham
ประเภท	Nonparametric causal inference / matching	Causal inference / quasi-experimental
แหล่งต้นตำรับ	Lechner, M., & Miquel, R. (2010). Identification of the effects of dynamic treatments by sequential conditional independence assumptions. Empirical Economics, 39(1), 111-137.	Callaway, B., & Sant'Anna, P. H. C. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics, 225(2), 200-230.
ชื่อเรียกอื่น	dynamic treatment matching, sequential matching estimator, dynamic selection-on-observables, DME	Dynamic DiD, Staggered DiD, Event-time DiD, Heterogeneous-timing DiD
ที่เกี่ยวข้อง	6	4
สรุป	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.	Dynamic Difference-in-Differences extends the classic DiD framework to settings where units adopt treatment at different times. Rather than collapsing all variation into a single 2x2 comparison, it estimates group-time average treatment effects for each adoption cohort at each calendar period, then aggregates them into interpretable summaries of the causal effect over event time.