Regression Discontinuity Marginal Threshold Treatment Effects

Yingying Dong and Arthur Lewbel

No 111205, Working Papers from University of California-Irvine, Department of Economics

Abstract: In regression discontinuity models, where the probability of treatment jumps discretely when a running variable crosses a threshold, an average treatment effect can be nonparametrically identified. We show that the derivative of this treatment effect with respect to the threshold is also nonparametrically identified and easily estimated, in both sharp and fuzzy designs. This marginal threshold treatment effect (MTTE) may be used to estimate the impact on treatment effects of small changes in the threshold. We use it to show how raising the age of Medicare eligibility would change the probability of take up of various types of health insurance.

Keywords: Regression discontinuity; Sharp design; Fuzzy design; Treatment effects; Program evaluation; Threshold; Running variable; Forcing variable (search for similar items in EconPapers)
JEL-codes: C21 C25 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2011-11
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:irv:wpaper:111205

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