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Policy Evaluation Fuzzy Regression Discontinuity/Ushahidi
Rekodi ya ushahidi wa mbinu

Policy Evaluation Fuzzy Regression Discontinuity

Fuzzy Regression Discontinuity Design (Fuzzy RDD) estimates the causal effect of a policy when eligibility is determined by crossing a threshold on a continuous score, but actual take-up or compliance is imperfect. Developed formally by Hahn, Todd, and Van der Klaauw (2001), it uses the threshold as an instrumental variable to recover a Local Average Treatment Effect (LATE) among compliers near the cutoff.

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Fuzzy Regression Discontinuity Design for Policy Evaluation
Rekodi ya mbinu ya kiajenda · regression-model / causal-inference
  • Hahn, J., Todd, P., & Van der Klaauw, W. (2001). Identification and estimation of treatment effects with a regression-discontinuity design. Review of Economic Studies, 68(1), 201-209. · DOI 10.1111/1468-0262.00183
  • Imbens, G. W., & Lemieux, T. (2008). Regression discontinuity designs: A guide to practice. Journal of Econometrics, 142(2), 615-635. · DOI 10.1016/j.jeconom.2007.05.001
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Same method familyDifference-in-Differencesmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketFuzzy Regression Discontinuitymachine-suggested · Relational suggestion, not evidence.See alsoInstrumental Variables in Health Researchmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketPolicy Evaluation Regression Discontinuity Designmachine-suggested · Relational suggestion, not evidence.See alsoPropensity Score Matchingmachine-suggested · Relational suggestion, not evidence.

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