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Learning your Earning: Are Labor Income Shocks Really That Persistent?


  • Fatih Guvenen


In this paper we examine the risk situation facing individuals in the labor market. The current consensus in the literature is that the labor income process has a large random walk component. We argue two points. First, the direct estimates of this parameter (from labor income data) appear to be upward biased due to the omission of heterogeneity in income profiles across the population that would be implied, for example, by a human capital model with heterogeneity. When we allow for differences in profiles, the estimated persistence falls from 0.99 to about 0.8. Moreover, the main evidence against profile heterogeneity in the existing literature---that the autocorrelations of income changes are small and typically negative---is in fact also replicated by the profile heterogeneity model we estimate, casting doubt on the previous interpretation of this evidence. Second, we embed this process in a life-cycle model to examine how it alters the consumption-saving decision of individuals. We assume that---as seems plausible---individuals do not know their profiles exactly at the beginning of life, but learn in a Bayesian way with successive income observations. We find that learning is very slow and affects consumption choice throughout the life-cycle. The model generates substantial rise in consumption inequality over the life-cycle, which matches empirical observations (Deaton and Paxson 1994). Moreover, the shape of the age-inequality profile is non-concave as in the data, but unlike in a model with very persistent shocks. Finally, the consumption profiles of college graduates are steeper than high-school graduates in the model consistent with the data because they face a wider dispersion of, and hence uncertainty about, income growth rates. Overall this evidence indicates that income shocks may be significantly less persistent than what is currently assumed.

Suggested Citation

  • Fatih Guvenen, 2004. "Learning your Earning: Are Labor Income Shocks Really That Persistent?," 2004 Meeting Papers 177, Society for Economic Dynamics.
  • Handle: RePEc:red:sed004:177

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    Cited by:

    1. Fatih Guvenen & Burhanettin Kuruscu, 2010. "A Quantitative Analysis of the Evolution of the U.S. Wage Distribution, 1970-2000," NBER Chapters,in: NBER Macroeconomics Annual 2009, Volume 24, pages 227-276 National Bureau of Economic Research, Inc.
    2. Richard Blundell & Hamish Low & Ian Preston, 2013. "Decomposing changes in income risk using consumption data," Quantitative Economics, Econometric Society, vol. 4(1), pages 1-37, March.
    3. Richard Blundell & Luigi Pistaferri & Itay Saporta-Eksten, 2016. "Consumption Inequality and Family Labor Supply," American Economic Review, American Economic Association, vol. 106(2), pages 387-435, February.
    4. Wang, Neng, 2004. "Precautionary saving and partially observed income," Journal of Monetary Economics, Elsevier, vol. 51(8), pages 1645-1681, November.
    5. Tom Krebs & Moritz Kuhn & Mark L. J. Wright, 2015. "Human Capital Risk, Contract Enforcement, and the Macroeconomy," American Economic Review, American Economic Association, vol. 105(11), pages 3223-3272, November.
    6. Josep Pijoan-Mas & Virginia Sanchez-Marcos, 2010. "Spain is Different: Falling Trends of Inequality," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 13(1), pages 154-178, January.
    7. Scott Fulford, 2012. "The precaution of the rich and poor," Boston College Working Papers in Economics 814, Boston College Department of Economics.
    8. Crawford, Ron, 2009. "Variations in earnings growth: evidence from earnings transitions in the NZ Linked Income Survey," ISER Working Paper Series 2009-18, Institute for Social and Economic Research.

    More about this item


    earnings process; idiosyncratic shocks; learning; inequality;

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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