Correcting for Misclassified Binary Regressors Using Instrumental Variables

No 27797, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Estimators that exploit an instrumental variable to correct for misclassification in a binary regressor typically assume that the misclassification rates are invariant across all values of the instrument. We show that this assumption is invalid in routine empirical settings. We derive a new estimator that is consistent when misclassification rates vary across values of the instrumental variable. In cases where identification is weak, our moments can be combined with bounds to provide a confidence set for the parameter of interest.

JEL-codes: C18 C26 (search for similar items in EconPapers)
Date: 2020-09
New Economics Papers: this item is included in nep-ecm
Note: CH EH LS PE TWP
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.nber.org/papers/w27797.pdf (application/pdf)

Related works:
Working Paper: Correcting for Misclassied Binary Regressors Using Instrumental Variables (2020)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberwo:27797

Ordering information: This working paper can be ordered from
http://www.nber.org/papers/w27797

Access Statistics for this paper

More papers in NBER Working Papers from National Bureau of Economic Research, Inc National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.. Contact information at EDIRC.
Bibliographic data for series maintained by ().