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The Evolution of Inequality, Heterogeneity and Uncertainty in Labor Earnings in the U.S. Economy

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Author Info
Flavio Cunha () (University of Pennsylvania)
James J. Heckman () (University of Chicago and IZA)

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Abstract

A large empirical literature documents a rise in wage inequality in the American economy. It is silent on whether the increase in inequality is due to greater heterogeneity in the components of earnings that are predictable by agents or whether it is due to greater uncertainty faced by agents. Applying the methodology of Cunha, Heckman, and Navarro (2005) to data on agents making schooling decisions in different economic environments, we join choice data with earnings data to estimate the fraction of future earnings that is forecastable and how this fraction has changed over time. We find that both predictable and unpredictable components of earnings have increased in recent years. The increase in uncertainty is substantially greater for unskilled workers. For less skilled workers, roughly 60% of the increase in wage variability is due to uncertainty. For more skilled workers, only 8% of the increase in wage variability is due to uncertainty. Roughly 26% of the increase in the variance of returns to schooling is due to increased uncertainty. Using conventional measures of income inequality masks the contribution of rising uncertainty to the rise in the inequality of earnings for less educated groups.

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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 3115.

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Length: 55 pages
Date of creation: Oct 2007
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Handle: RePEc:iza:izadps:dp3115

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Related research
Keywords: wage inequality uncertainty sorting inequality accounting

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Find related papers by JEL classification:
D3 - Microeconomics - - Distribution
J8 - Labor and Demographic Economics - - Labor Standards

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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. Matzkin, Rosa L, 1992. "Nonparametric and Distribution-Free Estimation of the Binary Threshold Crossing and the Binary Choice Models," Econometrica, Econometric Society, vol. 60(2), pages 239-70, March. [Downloadable!] (restricted)
  2. James J. Heckman & Paul A. LaFontaine, 2007. "The American High School Graduation Rate: Trends and Levels," IZA Discussion Papers 3216, Institute for the Study of Labor (IZA). [Downloadable!]
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  3. Richard Blundell & Ian Preston, 1998. "Consumption Inequality And Income Uncertainty," The Quarterly Journal of Economics, MIT Press, vol. 113(2), pages 603-640, May. [Downloadable!] (restricted)
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  4. Carneiro, Pedro & Hansen, Karsten & Heckman, James, 2003. "Estimating distributions of treatment effects with an application to the returns to schooling and measurement of the effects of uncertainty on college choice," Working Paper Series 2003:9, IFAU - Institute for Labour Market Policy Evaluation. [Downloadable!]
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  5. 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. [Downloadable!] (restricted)
  6. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College," NBER Working Papers 9546, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  7. Blundell, Richard William & Pistaferri, Luigi & Preston, Ian, 2002. "Partial Insurance, Information, and Consumption Dynamics," CEPR Discussion Papers 3666, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  8. MaCurdy, Thomas, 2007. "A Practitioner's Approach to Estimating Intertemporal Relationships Using Longitudinal Data: Lessons from Applications in Wage Dynamics," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 62 Elsevier. [Downloadable!] (restricted)
  9. Flavin, Marjorie A, 1981. "The Adjustment of Consumption to Changing Expectations about Future Income," Journal of Political Economy, University of Chicago Press, vol. 89(5), pages 974-1009, October. [Downloadable!] (restricted)
  10. Susanne M. Schennach, 2004. "Estimation of Nonlinear Models with Measurement Error," Econometrica, Econometric Society, vol. 72(1), pages 33-75, 01. [Downloadable!] (restricted)
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Cited by:
(explanations, 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. Steven J. Davis & James A. Kahn, 2007. "Macroeconomic implications of changes in micro volatility," Proceedings, Federal Reserve Bank of San Francisco, issue Nov. [Downloadable!]
  2. Steven J. Davis & James A. Kahn, 2008. "Interpreting the Great Moderation: Changes in the Volatility of Economic Activity at the Macro and Micro Levels," NBER Working Papers 14048, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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