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misclassification in binary variables

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  • Christopher R. Bollinger

Abstract

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.

Suggested Citation

  • Christopher R. Bollinger, 2010. "misclassification in binary variables," The New Palgrave Dictionary of Economics, Palgrave Macmillan.
  • Handle: RePEc:pal:dofeco:v:4:year:2010:doi:3832
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    More about this item

    Keywords

    binary variables; dependent variable; measurement error; misclassification; regression;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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