ScholarGate
助手

方法对比

并排查看您选择的方法;存在差异的行会高亮显示。

异质性处理效应倾向得分匹配×双重差分法 (Diff-in-Diff)×
领域因果推断计量经济学
方法族Regression modelRegression model
起源年份1983–20161994
提出者Rosenbaum & Rubin (PSM foundation, 1983); Athey & Imbens (HTE extensions, 2016)Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
类型Causal inference / matching with effect heterogeneityCausal inference / panel regression
开创性文献Athey, 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
别名HTE-PSM, CATE via PSM, subgroup treatment effect matching, conditional average treatment effect matchingdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
相关55
摘要Heterogeneous 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.
ScholarGate数据集
  1. v1
  2. 2 来源
  3. PUBLISHED
  1. v1
  2. 2 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: Heterogeneous Treatment Effect Propensity Score Matching · Difference-in-Differences. 于 2026-06-18 检索自 https://scholargate.app/zh/compare