เปรียบเทียบวิธี

	Dynamic Propensity Score Matching	ไดนามิก ดิฟ-อิน-ดิฟ (Dynamic Difference-in-Differences)
สาขาวิชา	การอนุมานเชิงสาเหตุ	การอนุมานเชิงสาเหตุ
ตระกูล	Regression model	Regression model
ปีกำเนิด	1986-2010	2021
ผู้ริเริ่ม	Robins (1986) on sequential treatments; Lechner & Miquel (2010) on dynamic matching	Callaway & Sant'Anna; Sun & Abraham
ประเภท	Sequential causal 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 PSM, sequential propensity score matching, longitudinal propensity matching, DPSM	Dynamic DiD, Staggered DiD, Event-time DiD, Heterogeneous-timing DiD
ที่เกี่ยวข้อง	6	4
สรุป	Dynamic Propensity Score Matching (DPSM) extends classic propensity score matching to settings where treatment is assigned repeatedly over time and earlier treatment choices influence later ones. It estimates the causal effect of entire treatment sequences or regime changes by constructing matched comparisons at each decision point using the full history of covariates and prior treatments.	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.