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Stochastic Process Models And The Distribution Of Earnings

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  • Lars Osberg

Abstract

This article examines several hypotheses concerning the stochastic nature of year to year variations in individual incomes in light of newly available microdata on individual earnings. In particular, the models of Solow (1951), Champernowne (1953), and Rutherford (1955) are examined in some detail, and their predictions as to changes to be expected in the distribution of individual incomes are tested. The author concludes that the distributions arrived at using these models are not very similar either to each other or to the actual distribution of earnings. Thus, he believes that as an “explanation” of earnings dynamics stochastic process models are unsatisfactory. He further criticizes these models on the grounds that they foster a bias toward the belief in the inevitability, and perhaps desirability, of the current distribution of earnings.

Suggested Citation

  • Lars Osberg, 1977. "Stochastic Process Models And The Distribution Of Earnings," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 23(3), pages 205-215, September.
    • Handle: RePEc:bla:revinw:v:23:y:1977:i:3:p:205-215
    DOI: 10.1111/j.1475-4991.1977.tb00014.x
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    Cited by:

    1. Louis Chauvel, 2014. "The Intensity and Shape of Inequality: The ABG Method of Distributional Analysis," LIS Working papers 609, LIS Cross-National Data Center in Luxembourg.
    2. Anderson, Gordon, 2012. "Boats and tides and "trickle down" theories: What economists presume about wellbeing when they employ stochastic process theory in modeling behavior," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-44.

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