Regression modelQuasi-experimental / causal inference
异质性处理效应反事实影响评估
异质性处理效应反事实影响评估 (HTE-CIE) 通过估计政策或干预措施的因果效应在由干预前特征定义的亚组之间如何变化，从而扩展了标准反事实影响评估。它不报告单一的平均处理效应，而是绘制协变量空间上的条件平均处理效应 (CATE) 图，揭示谁从干预中获益最多或最少。
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来源
- Cerulli, G. (2010). Modelling and measuring the effect of public subsidies on business R&D: A critical review of the econometric literature. Economic Record, 86(274), 421-449. DOI: 10.1111/j.1475-4932.2009.00615.x ↗
- Athey, S., & Wager, S. (2019). Estimating treatment effects with causal forests: An application. Observational Studies, 5(2), 37-51. link ↗
如何引用本页
ScholarGate. (2026, June 3). Heterogeneous Treatment Effect Counterfactual Impact Evaluation. ScholarGate. https://scholargate.app/zh/causal-inference/heterogeneous-treatment-effect-counterfactual-impact-evaluation
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将本方法与其最相近的同类并置，并排研读——本馆将书籍铺陈于案上，取舍则由您定夺。
- 反事实影响评估 (CIE)因果推断↔ 比较
- 异质性处理效应双重差分法 (HTE-DiD)因果推断↔ 比较
- Marginal Structural Model (MSM)因果推断↔ 比较
- 倾向得分匹配研究统计学↔ 比较
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