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Bayesian Fuzzy Regression Discontinuity/Evidence
Method evidence record

Bayesian Fuzzy Regression Discontinuity

Bayesian Fuzzy Regression Discontinuity (Bayesian Fuzzy RD) combines the quasi-experimental logic of fuzzy regression discontinuity design with full Bayesian inference. It estimates a local average treatment effect at a policy threshold where treatment assignment is probabilistic rather than deterministic, placing prior distributions over all unknowns and recovering a complete posterior distribution of the causal effect rather than a single point estimate.

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

Bayesian Fuzzy Regression Discontinuity Design
Taxonomic method record · 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
  • Chib, S., & Jacobi, L. (2016). Bayesian fuzzy regression discontinuity analysis and returns to compulsory schooling. Journal of Applied Econometrics, 31(6), 1026-1047. · DOI 10.1002/jae.2481
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Related methods

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

Taxonomic bucketBayesian Instrumental Variablesmachine-suggested · Relational suggestion, not evidence.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.Same method familyLocal Average Treatment Effectmachine-suggested · Relational suggestion, not evidence.

Evidence status

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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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