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A Large-Scale Validation Study of Measurement Errors in Longitudinal Survey Data

  • Kristensen, Nicolai


    (KORA - Danish Institute for Local and Regional Government Research)

  • Westergård-Nielsen, Niels C.


    (Copenhagen Business School)

In this paper, we analyze measurement and classification errors in several key variables, including earnings and educational attainment, in a matched sample of survey and administrative longitudinal data. The data, spanning 1994-2001 and covering all sectors in the Danish economy, are much more comprehensive than usually seen in validation studies. Measurement errors in earnings are found to be much larger than reported in previous studies limited to one single firm. Individuals who attrite from the panel report their earnings significantly less accurate than individuals who are observed throughout the entire sampling period. Furthermore, females are found to report their earnings significantly more precise than males, part-time workers report significantly less accurate than full-time workers and low-income workers report significantly less accurate than workers with relatively higher income. Classification errors in categorical variables are found to be of about the same magnitude as previously found in the literature. We analyze whether response error in one variable makes it more likely that the same respondent will report other variables with error but do not find support for this hypothesis.

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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 2329.

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Length: 38 pages
Date of creation: Sep 2006
Date of revision:
Publication status: published in: Journal of Economic and Social Measurement, 2007, 32 (2-3), 65-92
Handle: RePEc:iza:izadps:dp2329
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  1. Bound, John & Krueger, Alan B, 1991. "The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right?," Journal of Labor Economics, University of Chicago Press, vol. 9(1), pages 1-24, January.
  2. John M. ABOWD & Françis KRAMARZ & Antoine MOREAU, 1996. "Product Quality and Worker Quality," Annales d'Economie et de Statistique, ENSAE, issue 41-42, pages 299-322.
  3. 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.
  4. Bollinger, Christopher R, 1998. "Measurement Error in the Current Population Survey: A Nonparametric Look," Journal of Labor Economics, University of Chicago Press, vol. 16(3), pages 576-94, July.
  5. Duncan, Greg J & Hill, Daniel H, 1985. "An Investigation of the Extent and Consequences of Measurement Error in Labor-Economic Survey Data," Journal of Labor Economics, University of Chicago Press, vol. 3(4), pages 508-32, October.
  6. Erich Battistin & Barbara Sianesi, 2006. "Misreported schooling and returns to education: evidence from the UK," CeMMAP working papers CWP07/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  7. Mellow, Wesley & Sider, Hal, 1983. "Accuracy of Response in Labor Market Surveys: Evidence and Implications," Journal of Labor Economics, University of Chicago Press, vol. 1(4), pages 331-44, October.
  8. Bound, John, et al, 1994. "Evidence on the Validity of Cross-Sectional and Longitudinal Labor Market Data," Journal of Labor Economics, University of Chicago Press, vol. 12(3), pages 345-68, July.
  9. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843 Elsevier.
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