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| Bayesian Fuzzy Regression Discontinuity× | Differenz-in-Differenzen (DiD)× | |
|---|---|---|
| Fachgebiet≠ | Kausale Inferenz | Ökonometrie |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 2001 (fuzzy RD identification); 2016 (Bayesian formulation by Chib & Jacobi) | 1994 |
| Urheber≠ | Chib & Jacobi (Bayesian formulation); Hahn, Todd & Van der Klaauw (fuzzy RD identification) | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) |
| Typ≠ | Bayesian causal inference / quasi-experimental design | Causal inference / panel regression |
| Wegweisende Quelle≠ | 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 ↗ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 |
| Aliasnamen | Bayesian Fuzzy RD, Bayesian Fuzzy RDD, Fuzzy RD with Bayesian Inference | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) |
| Verwandt | 5 | 5 |
| Zusammenfassung≠ | 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. | Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes. |
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