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Systematically Misclassified Binary Dependant Variables

Author

Listed:
  • Vidhura Tennekoon
  • Robert Rosenman

    (School of Economic Sciences, Washington State University)

Abstract

When a binary dependant variable is misclassified probit and logit estimates are biased and inconsistent. In this paper we suggest a conceptual basis for endogenous misclassification of the dependant variable due to systematic respondent bias and the use of Likert scales commonly used in measuring categorical variables. We develop an estimation approach that corrects for endogenous misclassification, validate our approach using a simulation study and apply it to the analysis of a treatment program designed to improve family dynamics. Our results show that endogenous misclassification could lead towards potentially incorrect conclusions unless corrected using an appropriate technique.

Suggested Citation

  • Vidhura Tennekoon & Robert Rosenman, 2011. "Systematically Misclassified Binary Dependant Variables," Working Papers 2011-9, School of Economic Sciences, Washington State University.
    • Handle: RePEc:wsu:wpaper:rosenman-13
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    File URL: http://faculty.ses.wsu.edu/WorkingPapers/rosenman/WP2011_9.pdf
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    Citations

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    Cited by:

    1. Matthew Birch & Robert Rosenman, 2019. "How Much Does Merit Aid Actually Matter? Revisiting Merit Aid and College Enrollment When Some Students “Come Anyway”," Research in Higher Education, Springer;Association for Institutional Research, vol. 60(6), pages 760-802, September.
    2. Vidhura Tennekoon & Robert Rosenman, 2013. "Bias in Measuring Smoking Behavior," Working Papers 2013-10, School of Economic Sciences, Washington State University.
    3. Darren J. Mayne & Geoffrey G. Morgan & Bin B. Jalaludin & Adrian E. Bauman, 2019. "Area-Level Walkability and the Geographic Distribution of High Body Mass in Sydney, Australia: A Spatial Analysis Using the 45 and Up Study," IJERPH, MDPI, vol. 16(4), pages 1-29, February.
    4. Tennekoon, Vidhura S., 2016. "The equivalence of three latent class models and ML estimators," Economics Letters, Elsevier, vol. 141(C), pages 147-150.

    More about this item

    Keywords

    misclassification; response shift bias; Likert scale; treatment evaluation;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • I10 - Health, Education, and Welfare - - Health - - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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