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Identifying the effect of a mis-classified, binary, endogenous regressor

Francis J. DiTraglia and Camilo García-Jimeno

Journal of Econometrics, 2019, vol. 209, issue 2, 376-390

Abstract: This paper studies identification of the effect of a mis-classified, binary, endogenous regressor when a discrete-valued instrumental variable is available. We begin by showing that the only existing point identification result for this model is incorrect. We go on to derive the sharp identified set under mean independence assumptions for the instrument and measurement error. The resulting bounds are novel and informative, but fail to point identify the effect of interest. This motivates us to consider alternative and slightly stronger assumptions: we show that adding second and third moment independence assumptions suffices to identify the model.

Keywords: Instrumental variables; Measurement error; Endogeneity (search for similar items in EconPapers)
JEL-codes: C10 C25 C26 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:209:y:2019:i:2:p:376-390

DOI: 10.1016/j.jeconom.2019.01.007

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Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

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