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Binary misclassification and identification in regression models

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  • van Hasselt, Martijn
  • Bollinger, Christopher R.

Abstract

We study a regression model with a binary explanatory variable that is subject to misclassification errors. The regression coefficient is then only partially identified. We derive several results that relate different assumptions about the misclassification probabilities and the conditional variances to the size of the identified set.

Suggested Citation

  • van Hasselt, Martijn & Bollinger, Christopher R., 2012. "Binary misclassification and identification in regression models," Economics Letters, Elsevier, vol. 115(1), pages 81-84.
  • Handle: RePEc:eee:ecolet:v:115:y:2012:i:1:p:81-84
    DOI: 10.1016/j.econlet.2011.11.031
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    References listed on IDEAS

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    1. Manski, Charles F, 1990. "Nonparametric Bounds on Treatment Effects," American Economic Review, American Economic Association, vol. 80(2), pages 319-323, May.
    2. Chen, Xiaohong & Hu, Yingyao & Lewbel, Arthur, 2008. "Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments," Economics Letters, Elsevier, vol. 100(3), pages 381-384, September.
    3. Chen, Xiaohong & Hu, Yingyao & Lewbel, Arthur, 2008. "A note on the closed-form identification of regression models with a mismeasured binary regressor," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1473-1479, September.
    4. Arthur Lewbel, 2007. "Estimation of Average Treatment Effects with Misclassification," Econometrica, Econometric Society, vol. 75(2), pages 537-551, March.
    5. Aprajit Mahajan, 2006. "Identification and Estimation of Regression Models with Misclassification," Econometrica, Econometric Society, vol. 74(3), pages 631-665, May.
    6. Kreider, Brent & Pepper, John V., 2007. "Disability and Employment: Reevaluating the Evidence in Light of Reporting Errors," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 432-441, June.
    7. Deng, Ping & Hu, Yingyao, 2009. "Bounding the effect of a dichotomous regressor with arbitrary measurement errors," Economics Letters, Elsevier, vol. 105(3), pages 256-260, December.
    8. Bollinger, Christopher R., 1996. "Bounding mean regressions when a binary regressor is mismeasured," Journal of Econometrics, Elsevier, vol. 73(2), pages 387-399, August.
    9. Klepper, Steven, 1988. "Bounding the effects of measurement error in regressions involving dichotomous variables," Journal of Econometrics, Elsevier, vol. 37(3), pages 343-359, March.
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    Cited by:

    1. repec:eee:econom:v:200:y:2017:i:2:p:282-294 is not listed on IDEAS
    2. Pierre Nguimkeu & Augustine Denteh & Rusty Tchernis, 2017. "On the Estimation of Treatment Effects with Endogenous Misreporting," NBER Working Papers 24117, National Bureau of Economic Research, Inc.
    3. Francis J. DiTraglia & Camilo GarcĂ­a-Jimeno, 2017. "Mis-classified, Binary, Endogenous Regressors: Identification and Inference," NBER Working Papers 23814, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    Misclassification error; Binary regressors; Partial identification; Homoscedasticity;

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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