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Disegno di Regressione a Discontinuità con Dati Panel×Regression Discontinuity Design Fuzzy×
CampoInferenza causaleInferenza causale
FamigliaRegression modelRegression model
Anno di origine1960 (original RDD); panel extension codified 2000s–2010s2001
IdeatoreThistlethwaite & Campbell (1960); panel extension developed through Lee & Lemieux (2010) and related applied workHahn, Todd & van der Klaauw
TipoCausal inference / quasi-experimentalQuasi-experimental causal inference
Fonte seminaleLee, D. S., & Lemieux, T. (2010). Regression Discontinuity Designs in Economics. Journal of Economic Literature, 48(2), 281-355. DOI ↗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 ↗
AliasPanel RD, Panel RDD, Longitudinal Regression Discontinuity, Fixed-Effects RDDFuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD
Correlati55
SintesiPanel data regression discontinuity design (Panel RDD) combines the sharp local identification of a regression discontinuity with the within-unit variation available in repeated-observation panel data. Units are observed across multiple periods, and treatment is assigned based on whether a running variable crosses a known threshold. By leveraging both the discontinuity and panel structure, researchers can control for unobserved unit-level heterogeneity while estimating a causal treatment effect near the threshold.Fuzzy Regression Discontinuity Design (Fuzzy RDD) estimates causal effects when eligibility for a treatment is determined by a threshold on a running variable but actual take-up of that treatment is imperfect — some eligible units do not receive treatment and some ineligible units do. The cutoff acts as an instrument, and the estimand is a Local Average Treatment Effect (LATE) for compliers near the threshold.
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ScholarGateConfronta i metodi: Panel Data Regression Discontinuity Design · Fuzzy Regression Discontinuity. Consultato il 2026-06-18 da https://scholargate.app/it/compare