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Methoden vergelijken

Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.

Robuuste Regressie Discontinuïteit Ontwerp×Difference-in-Differences (DiD)×
VakgebiedCausale inferentieEconometrie
FamilieRegression modelRegression model
Jaar van ontstaan20141994
GrondleggerCalonico, Cattaneo & TitiunikCard & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
TypeQuasi-experimental causal inferenceCausal inference / panel regression
Oorspronkelijke bronCalonico, S., Cattaneo, M. D., & Titiunik, R. (2014). Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs. Econometrica, 82(6), 2295-2326. DOI ↗Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
AliassenRobust RDD, Bias-corrected RDD, CCT estimator, rdrobustdiff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Verwant45
SamenvattingRobust 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.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.
ScholarGateGegevensset
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  1. v1
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  3. PUBLISHED

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ScholarGateMethoden vergelijken: Robust Regression Discontinuity Design · Difference-in-Differences. Geraadpleegd op 2026-06-17 via https://scholargate.app/nl/compare