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Heterogeneous treatment effect Counterfactual impact evaluation/Evidence
Method evidence record

Heterogeneous treatment effect Counterfactual impact evaluation

Heterogeneous Treatment Effect Counterfactual Impact Evaluation (HTE-CIE) extends standard counterfactual impact evaluation by estimating how the causal effect of a policy or intervention varies across subgroups defined by pre-treatment characteristics. Rather than reporting a single average treatment effect, it maps the Conditional Average Treatment Effect (CATE) across the covariate space, revealing who benefits most or least from an intervention.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Heterogeneous Treatment Effect Counterfactual Impact Evaluation
Taxonomic method record · regression-model / causal-inference
  • 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. · URL
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketCounterfactual Impact Evaluationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketHeterogeneous Treatment Effect Difference-in-Differencesmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMarginal Structural Modelmachine-suggested · Relational suggestion, not evidence.See alsoPropensity Score Matchingmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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