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Misclassification of the dependent variable in binary choice models: evidence from five Latin American countries

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  • Evangelos Falaris

Abstract

Misclassification of the dependent variable in binary choice models can result in inconsistency of the parameter estimates. I estimate probit models that treat misclassification probabilities as estimable parameters for three labour market outcomes: formal sector employment, pension contribution and job change. I use Living Standards Measurement Study (LSMS) data from Nicaragua, Peru, Brazil, Guatemala and Panama. I find that there is a significant misclassification in 11 of the 16 cases that I investigate. If misclassification is present but is ignored, estimates of the probit parameters and their SEs are biased toward zero. In most cases, predicted probabilities of the outcomes are significantly affected by misclassification of the dependent variable. Even a moderate degree of misclassification can have substantial effects on the estimated parameters and on many of the predictions.

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  • Evangelos Falaris, 2011. "Misclassification of the dependent variable in binary choice models: evidence from five Latin American countries," Applied Economics, Taylor & Francis Journals, vol. 43(11), pages 1315-1327.
    • Handle: RePEc:taf:applec:v:43:y:2011:i:11:p:1315-1327
    DOI: 10.1080/00036840802600483
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    Cited by:

    1. Adele Bergin, 2015. "Employer Changes and Wage Changes: Estimation with Measurement Error in a Binary Variable," LABOUR, CEIS, vol. 29(2), pages 194-223, June.
    2. Ijeoma P. Edoka, 2017. "Implications of Misclassification Errors in Empirical Studies of Adolescent Smoking Behaviours," Health Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 486-499, April.
    3. Sadikoglu, Serhan, 2019. "Essays in econometric theory," Other publications TiSEM 99d83644-f9dc-49e3-a4e1-5, Tilburg University, School of Economics and Management.
    4. Kent Eliasson & Robert Nakosteen & Olle Westerlund & Michael Zimmer, 2014. "All in the family: Self-selection and migration by couples," Papers in Regional Science, Wiley Blackwell, vol. 93(1), pages 101-124, March.
    5. P Čížek & S Sadıkoğlu, 2022. "Misclassification-robust semiparametric estimation of single-index binary-choice models [Local NLLS estimation of semi-parametric binary choice models]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 433-454.
    6. Aller, Carlos & González Chapela, Jorge, 2013. "Misclassification of the dependent variable in a debt–repayment behavior context," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 162-172.

    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • O17 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Formal and Informal Sectors; Shadow Economy; Institutional Arrangements
    • J26 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Retirement; Retirement Policies
    • J62 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Job, Occupational and Intergenerational Mobility; Promotion

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