• Table of Contents
    • Abstract
    • Keywords
    • Article
      • Introduction
      • Simple regression model
      • Allowing misclassification to be related to the regression error
      • When the misclassified variable is the dependent variable
      • Conclusions
    • See Also
    • Bibliography
    • How to cite this article

misclassification in binary variables

Christopher R. Bollinger
From The New Palgrave Dictionary of Economics, Online Edition, 2010
Edited by Steven N. Durlauf and Lawrence E. Blume
Back to top


Misclassification of binary variables is the first case of non-classical measurement error considered. Similar to the classical errors-in-variables result, misclassification of a binary regressor leads to attenuation of slope coefficient estimates in linear regression. Classical instrumental variables will not address the problem. Bounds results under a number of different sets of assumptions can be derived. When the dependent variable is binary, misclassification also leads to slope attenuation. Some identification results are available in this case.
Back to top


Back to top


Back to top

How to cite this article

Bollinger, Christopher R. "misclassification in binary variables." The New Palgrave Dictionary of Economics. Online Edition. Eds. Steven N. Durlauf and Lawrence E. Blume. Palgrave Macmillan, 2010. The New Palgrave Dictionary of Economics Online. Palgrave Macmillan. 18 January 2018 <http://www.dictionaryofeconomics.com/article?id=pde2010_M000617> doi:10.1057/9780230226203.3832

Download Citation:

as RIS | as text | as CSV | as BibTex