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The Consequences of Non-Classical Measurement Error for Distributional Analysis

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Author Info
D. O'Neill (Department of Economics, Finance and Accounting, Maynooth, Ireland)
Sweetman. O.
Van de gaer D.

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Abstract

This paper analyzes the consequences of non-classical measurement error for distributional analysis. We show that for a popular set of distributions negative correlation between the measurement error (u) and the true value (y) may reduce the bias in the estimated distribution at every value of y. For other distributions the impact of non-classical measurement di¤ers throughout the support of the distribution. We illustrate the practical importance of these results using models of unemployment duration and income.

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Publisher Info
Paper provided by Department of Economics, Finance and Accounting, National University of Ireland - Maynooth in its series Economics, Finance and Accounting Department Working Paper Series with number n1490205.

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Length: 11 pages
Date of creation: Feb 2005
Date of revision:
Handle: RePEc:may:mayecw:n1490205

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Postal: Maynooth, Co. Kildare
Phone: 353-1-7083728
Fax: 353-1-7083934
Web page: http://www.may.ie/academic/economics/
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Related research
Keywords: Distribution functions; Non-classical measurement error;

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Andrew Chesher & Christian Schluter, 2001. "Welfare measurement and measurement error," CeMMAP working papers CWP03/01, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. [Downloadable!]
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  2. Kiefer, Nicholas M, 1988. "Economic Duration Data and Hazard Functions," Journal of Economic Literature, American Economic Association, vol. 26(2), pages 646-79, June. [Downloadable!] (restricted)
  3. 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. [Downloadable!] (restricted)
  4. Pieter Serneels, 2004. "Explaining Non-Negative Duration Dependence Among the Unemployed," Development and Comp Systems 0409013, EconWPA. [Downloadable!]
  5. 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. [Downloadable!] (restricted)
  6. Chesher, Andrew & Dumangane, Montezuma & Smith, Richard J., 2002. "Duration response measurement error," Journal of Econometrics, Elsevier, vol. 111(2), pages 169-194, December. [Downloadable!] (restricted)
  7. 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. [Downloadable!] (restricted)
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Cited by:
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  1. Donal O’Neill & Olive Sweetman & Dirk Van de gaer, 2007. "The effects of measurement error and omitted variables when using transition matrices to measure intergenerational mobility," Journal of Economic Inequality, Springer, vol. 5(2), pages 159-178, August. [Downloadable!] (restricted)
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