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Robust Regression Discontinuity Design

Robust RDD extends the classical regression discontinuity design with bias correction and robust confidence intervals, addressing the under-coverage problem of conventional RDD inference. Developed by Calonico, Cattaneo, and Titiunik (2014), it uses local polynomial estimation with a bias-corrected point estimate and a wider variance term that accounts for the added uncertainty, yielding confidence intervals with correct asymptotic coverage.

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Robust Bias-Corrected Regression Discontinuity Design

Taksonoomiline meetodikirje · regression-model / causal-inference

Calonico, S., Cattaneo, M. D., & Titiunik, R. (2014). Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs. Econometrica, 82(6), 2295-2326. · DOI 10.3982/ECTA11757
Cattaneo, M. D., Idrobo, N., & Titiunik, R. (2019). A Practical Introduction to Regression Discontinuity Designs: Foundations. Cambridge University Press. · ISBN 978-1108710206

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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.See alsoPropensity Score Matchingmachine-suggested · Relational suggestion, not evidence.