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Identification of the Binary Choice Model with Misclassification

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  • Arthur Lewbel

    () (Boston College)

Abstract

Misclassification in binary choice (binomial response) models occurs when the dependent variable is measured with error, that is, when an actual "one" response is sometimes recorded as a zero, and vice versa. This paper shows that binary choice models with misclassification are semiparametrically identified, even when the probabilities of misclassification depend in unknown ways on model covariates, and the distribution of the errors is unknown.

Suggested Citation

  • Arthur Lewbel, 2000. "Identification of the Binary Choice Model with Misclassification," Boston College Working Papers in Economics 457, Boston College Department of Economics.
    • Handle: RePEc:boc:bocoec:457
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    References listed on IDEAS

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    1. Brown, James N & Light, Audrey, 1992. "Interpreting Panel Data on Job Tenure," Journal of Labor Economics, University of Chicago Press, vol. 10(3), pages 219-257, July.
    2. repec:cup:etheor:v:11:y:1995:i:3:p:560-96 is not listed on IDEAS
    3. Andrews, Donald W.K., 1995. "Nonparametric Kernel Estimation for Semiparametric Models," Econometric Theory, Cambridge University Press, vol. 11(03), pages 560-586, June.
    4. Hausman, J. A. & Abrevaya, Jason & Scott-Morton, F. M., 1998. "Misclassification of the dependent variable in a discrete-response setting," Journal of Econometrics, Elsevier, vol. 87(2), pages 239-269, September.
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    Cited by:

    1. Arthur Lewbel, 2007. "Estimation of Average Treatment Effects with Misclassification," Econometrica, Econometric Society, vol. 75(2), pages 537-551, March.
    2. Arie Beresteanu & Francesca Molinari, 2008. "Asymptotic Properties for a Class of Partially Identified Models," Econometrica, Econometric Society, vol. 76(4), pages 763-814, July.
    3. Arrieta, Alejandro, 2007. "A Structural Misclassifcation Model to Estimate the Impact of Physician Incentives on Healthcare Utilization," MPRA Paper 6718, University Library of Munich, Germany.
    4. Molinari, Francesca, 2008. "Partial identification of probability distributions with misclassified data," Journal of Econometrics, Elsevier, vol. 144(1), pages 81-117, May.
    5. Shiu, Ji-Liang, 2016. "Identification and estimation of endogenous selection models in the presence of misclassification errors," Economic Modelling, Elsevier, vol. 52(PB), pages 507-518.
    6. Peter Moffatt & Simon Peters, 2001. "Testing for the Presence of a Tremble in Economic Experiments," Experimental Economics, Springer;Economic Science Association, vol. 4(3), pages 221-228, December.
    7. Brown, Sarah & Harris, Mark N. & Srivastava, Preety & Taylor, Karl, 2018. "Mental Health and Reporting Bias: Analysis of the GHQ-12," IZA Discussion Papers 11771, Institute for the Study of Labor (IZA).
    8. Échevin, Damien, 2009. "Employment and Education Discrimination against Disabled Persons in Cape Verde," MPRA Paper 19497, University Library of Munich, Germany.
    9. Bellemare, Charles, 2007. "A life-cycle model of outmigration and economic assimilation of immigrants in Germany," European Economic Review, Elsevier, vol. 51(3), pages 553-576, April.
    10. Tennekoon, Vidhura S., 2016. "The equivalence of three latent class models and ML estimators," Economics Letters, Elsevier, vol. 141(C), pages 147-150.
    11. Eivind Bernhardsen & Bjorne Dyre Syversten, 2009. "Stress Testing the Enterprise Sector's Bank Debt: A Micro Approach," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 111-138, September.
    12. Donald S. Kenkel & Dean R. Lillard & Alan D. Mathios, 2004. "Accounting for misclassification error in retrospective smoking data," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 1031-1044.
    13. repec:eee:econom:v:200:y:2017:i:2:p:295-311 is not listed on IDEAS
    14. Dimitri Romanov, 2003. "Costs and Benefits of Marginal Reallocation of Tax Agency Resources in Pursuit of the Hard-to-Tax," International Center for Public Policy Working Paper Series, at AYSPS, GSU paper0323, International Center for Public Policy, Andrew Young School of Policy Studies, Georgia State University.

    More about this item

    Keywords

    binary choice; misclassification; measurement error; semiparametric; latent variable;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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