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Are Earnings Inequality and Mobility Overstated? The Impact of Non-Classical Measurement Error

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  • Gottschalk, Peter T.

    ()
    (Boston College)

  • Huynh, Minh

    ()
    (U.S. Social Security Administration)

Abstract

Measures of inequality and mobility based on self-reported earnings reflect attributes of both the joint distribution of earnings across time and the joint distribution of measurement error and earnings. While classical measurement error would increase measures of inequality and mobility there is substantial evidence that measurement error in earnings is not classical. In this paper we present the analytical links between non-classical measurement error and measures of inequality and mobility. The empirical importance of non-classical measurement error is explored using the Survey of Income and Program Participation matched to tax records. We find that the effects of non-classical measurement error are large. However, these non-classical effects are largely offsetting when estimating mobility. As a result SIPP estimates of mobility are similar to estimates based on tax records, though SIPP estimates of inequality are smaller than estimates based on tax records.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 2327.

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Length: 33 pages
Date of creation: Sep 2006
Date of revision:
Publication status: published in: Review of Economics and Statistics, 2010, 92 (2), 302 - 315
Handle: RePEc:iza:izadps:dp2327

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Keywords: earnings mobility and inequality; measurement error;

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  1. Pischke, Jorn-Steffen, 1995. "Measurement Error and Earnings Dynamics: Some Estimates from the PSID Validation Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 305-14, July.
  2. 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.
  3. 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.
  4. MaCurdy, Thomas E., 1982. "The use of time series processes to model the error structure of earnings in a longitudinal data analysis," Journal of Econometrics, Elsevier, vol. 18(1), pages 83-114, January.
  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. 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.
  7. Shorrocks, Anthony, 1978. "Income inequality and income mobility," Journal of Economic Theory, Elsevier, vol. 19(2), pages 376-393, December.
  8. 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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Cited by:
  1. Jo Blanden & Paul Gregg & Lindsey Macmillan, 2011. "Intergenerational Persistence in Income and Social Class: The Impact of Within-Group Inequality," The Centre for Market and Public Organisation 11/277, Department of Economics, University of Bristol, UK.
  2. Audra J. Bowlus & Jean-Marc Robin, 2012. "An International Comparison Of Lifetime Inequality: How Continental Europe Resembles North America," Journal of the European Economic Association, European Economic Association, vol. 10(6), pages 1236-1262, December.
  3. Akee, Randall, 2011. "Errors in self-reported earnings: The role of previous earnings volatility and individual characteristics," Journal of Development Economics, Elsevier, vol. 96(2), pages 409-421, November.
  4. Jantti, Markus & Jenkins, Stephen P., 2013. "Income mobility," ISER Working Paper Series 2013-23, Institute for Social and Economic Research.
  5. Akee, Randall K. Q., 2007. "Errors in Self-Reported Earnings: The Role of Previous Earnings Volatility," IZA Discussion Papers 3263, Institute for the Study of Labor (IZA).
  6. Kässi, Otto, 2011. "Earnings Dynamics of Men and Women in Finland: Permanent Inequality versus Earnings Instability," MPRA Paper 34301, University Library of Munich, Germany.
  7. Daniel D. Schnitzlein, 2009. "Struktur und Ausmaß der intergenerationalen Einkommensmobilität in Deutschland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 229(4), pages 450-466, August.
  8. Van Kerm, Philippe & Pi Alperin, Maria Noel, 2013. "Inequality, growth and mobility: The intertemporal distribution of income in European countries 2003–2007," Economic Modelling, Elsevier, vol. 35(C), pages 931-939.
  9. Kruppe, Thomas & Matthes, Britta & Unger, Stefanie, 2014. "Effectiveness of data correction rules in process-produced data : the case of educational attainment," IAB Discussion Paper 201415, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].

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