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Point identification in the presence of measurement error in discrete variables: application - wages and disability

  • Eirini-Christina Saloniki


  • Amanda Gosling


This paper addresses the problem of point identification in the presence of measurement error in discrete variables; in particular, it considers the case of having two "noisy" indicators of the same latent variable and without any prior information about the true value of the variable of interest. Based on the concept of the fourfold table and creating a nonlinear system of simultaneous equations from the observed proportions and predicted wages, we examine the need for different assumptions in order to obtain unique solutions for the system. We show that by imposing a simple restriction(s) for the joint misclassification probabilities, it is possible to measure the extent of the misclassification error in that specific variable. The proposed methodology is then used to identify whether people misreport their disability status using data from the British Household Panel Survey. Our results show that the probability of underreporting is greater than the probability of overreporting disability.

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Paper provided by School of Economics, University of Kent in its series Studies in Economics with number 1214.

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Date of creation: Nov 2012
Date of revision:
Handle: RePEc:ukc:ukcedp:1214
Contact details of provider: Postal: School of Economics, University of Kent, Canterbury, Kent, CT2 7NP
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  1. Kreider, Brent & Pepper, John V., 2003. "Disability and Employment: Reevaluating the Evidence in Light of Reporting Errors," Staff General Research Papers 10229, Iowa State University, Department of Economics.
  2. Brent Kreider & John Pepper, 2008. "Inferring disability status from corrupt data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 329-349.
  3. Melanie K. Jones & Paul L. Latreille & Peter J. Sloane, 2006. "Disability, gender, and the British labour market," Oxford Economic Papers, Oxford University Press, vol. 58(3), pages 407-449, July.
  4. Jones, Melanie K. & Latreille, Paul L. & Sloane, Peter J., 2007. "Disability and Work: A Review of the British Evidence," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 25, pages 473-498, Abril.
  5. Kreider, Brent, 2006. "Partially Identifying the Prevalence of Health Insurance Given Contaminated Sampling Response Error," Staff General Research Papers 12588, Iowa State University, Department of Economics.
  6. Aigner, Dennis J., 1973. "Regression with a binary independent variable subject to errors of observation," Journal of Econometrics, Elsevier, vol. 1(1), pages 49-59, March.
  7. Phelps, Edmund S, 1972. "The Statistical Theory of Racism and Sexism," American Economic Review, American Economic Association, vol. 62(4), pages 659-61, September.
  8. Christopher R. Bollinger, 2003. "Measurement Error in Human Capital and the Black-White Wage Gap," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 578-585, August.
  9. David Madden, 2004. "Labour market discrimination on the basis of health: an application to UK data," Applied Economics, Taylor & Francis Journals, vol. 36(5), pages 421-442.
  10. Horowitz, Joel L & Manski, Charles F, 1995. "Identification and Robustness with Contaminated and Corrupted Data," Econometrica, Econometric Society, vol. 63(2), pages 281-302, March.
  11. Melanie K. Jones & Peter J. Sloane, 2010. "Disability and Skill Mismatch," The Economic Record, The Economic Society of Australia, vol. 86(s1), pages 101-114, 09.
  12. Bound, John & Burkhauser, Richard V., 1999. "Economic analysis of transfer programs targeted on people with disabilities," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 51, pages 3417-3528 Elsevier.
  13. Melanie K. Jones, 2009. "The Employment Effect of the Disability Discrimination Act: Evidence from the Health Survey for England," LABOUR, CEIS, vol. 23(2), pages 349-369, 06.
  14. Marjorie L. Baldwin & Edward J. Schumacher, . "Job Mobility among Workers with Disabilities," Working Papers 9805, East Carolina University, Department of Economics.
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