The Devil is in the Tails: Regression Discontinuity Design with Measurement Error in the Assignment Variable
Zhuan Pei and
Additional contact information
Yi Shen: University of Waterloo
Working Papers from Princeton University, Department of Economics, Industrial Relations Section.
Identification in a regression discontinuity (RD) design hinges on the discontinuity in the probability of treatment when a covariate (assignment variable) exceeds a known threshold. If the assignment variable is measured with error, however, the discontinuity in the first stage relationship between the probability of treatment and the observed mismeasured assignment variable may disappear. Therefore, the presence of measurement error in the assignment variable poses a challenge to treatment effect identification. This paper provides sufficient conditions for identification when only the mismeasured assignment variable, the treatment status and the outcome variable are observed. We prove identification separately for discrete and continuous assignment variables and study the properties of various estimation procedures. We illustrate the proposed methods in an empirical application, where we estimate Medicaid takeup and its crowdout effect on private health insurance coverage.
Keywords: Regression Discontinuity Design; Measurement Error (search for similar items in EconPapers)
JEL-codes: C10 C18 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
Chapter: The Devil is in the Tails: Regression Discontinuity Design with Measurement Error in the Assignment Variable (2017)
Working Paper: The Devil is in the Tails: Regression Discontinuity Design with Measurement Error in the Assignment Variable (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:pri:indrel:606
Access Statistics for this paper
More papers in Working Papers from Princeton University, Department of Economics, Industrial Relations Section. Contact information at EDIRC.
Bibliographic data for series maintained by Bobray Bordelon ().