Rekodi ya ushahidi wa mbinu

Heterogeneous treatment effect Instrumental variables

Heterogeneous treatment effect IV applies instrumental variables estimation while explicitly acknowledging and modelling that the treatment effect differs across units. Rather than recovering a single average effect, it focuses on the Local Average Treatment Effect (LATE) — the causal effect for compliers, the subpopulation whose treatment status is actually shifted by the instrument — and extends analysis to variation in that effect across observed subgroups.

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Instrumental Variables Estimation with Heterogeneous Treatment Effects

Rekodi ya mbinu ya kiajenda · regression-model / causal-inference

Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475. · DOI 10.2307/2951620
Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. · ISBN 978-0691120355

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Same method family2SLS Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketHeterogeneous Treatment Effect Propensity Score Matchingmachine-suggested · Relational suggestion, not evidence.See alsoInstrumental Variables in Health Researchmachine-suggested · Relational suggestion, not evidence.Same method familyLocal Average Treatment Effectmachine-suggested · Relational suggestion, not evidence.