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Title: Regression Discontinuity Design with Continuous Measurement Error in the Running Variable

Author(s): Laurent Davezies and Thomas Le Barbanchon

Publication Date: January 2017

Keyword(s): Measurement error, regression discontinuity design and Unemployment insurance

Programme Area(s): Labour Economics

Abstract: Since the late 90s, Regression Discontinuity (RD) designs have been widely used to estimate Local Average Treatment Effects (LATE). When the running variable is observed with continuous measurement error, identification fails. Assuming nondifferential measurement error, we propose a consistent nonparametric estimator of the LATE when the discrepancy between the true running variable and its noisy measure is observed in an auxiliary sample of treated individuals, and when there are treated individuals at any value of the true running variable - two-sided fuzzy designs. We apply our method to estimate the effect of receiving unemployment benefits.

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Bibliographic Reference

Davezies, L and Le Barbanchon, T. 2017. 'Regression Discontinuity Design with Continuous Measurement Error in the Running Variable'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=11775