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विषम उपचार प्रभाव प्रवणता स्कोर मिलान×अंतर-में-अंतर (डिफ-इन-डिफ)×
क्षेत्रकारणात्मक अनुमानअर्थमिति
परिवारRegression modelRegression model
उद्भव वर्ष1983–20161994
प्रवर्तकRosenbaum & Rubin (PSM foundation, 1983); Athey & Imbens (HTE extensions, 2016)Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
प्रकारCausal inference / matching with effect heterogeneityCausal inference / panel regression
मौलिक स्रोतAthey, S., & Imbens, G. W. (2016). Recursive Partitioning for Heterogeneous Causal Effects. Proceedings of the National Academy of Sciences, 113(27), 7353-7360. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
उपनामHTE-PSM, CATE via PSM, subgroup treatment effect matching, conditional average treatment effect matchingdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
संबंधित55
सारांशHeterogeneous Treatment Effect Propensity Score Matching extends standard PSM to estimate how treatment effects vary across subgroups or individual characteristics. Rather than reporting a single average treatment effect, it uses the matched sample to estimate conditional average treatment effects (CATE), revealing which types of units benefit most or least from a treatment.Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes.
ScholarGateडेटासेट
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  3. PUBLISHED
  1. v1
  2. 2 स्रोत
  3. PUBLISHED

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ScholarGateविधियों की तुलना करें: Heterogeneous Treatment Effect Propensity Score Matching · Difference-in-Differences. 2026-06-18 को यहाँ से प्राप्त https://scholargate.app/hi/compare