Inference in Regression Discontinuity Designs with a Discrete Running Variable

Arbeitspapier

We consider inference in regression discontinuity designs when the running variable only takes a moderate number of distinct values. In particular, we study the common practice of using confidence intervals (CIs) based on standard errors that are clustered by the running variable. We derive theoretical results and present simulation and empirical evidence showing that these CIs have poor coverage properties and therefore recommend that they not be used in practice. We also suggest alternative CIs with guaranteed coverage properties under easily interpretable restrictions on the conditional expectation function.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: IZA Discussion Papers ; No. 9990

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Estimation: General ; Semiparametric and Nonparametric Methods: General ; Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions ; Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
• Thema: regression discontinuity design ; discrete running variable ; clustered standard errors

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Kolesár, Michal ; Rothe, Christoph
• Ereignis: Veröffentlichung
• (wer): Institute for the Study of Labor (IZA)
• (wo): Bonn
• (wann): 2016

Weitere Informationen

• Handle: http://hdl.handle.net/10419/145281
• Letzte Aktualisierung: 10.03.2025, 11:43 MEZ