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Using Longitudinal Data to Estimate Age, Period and Cohort Effects in Earnings Equations

  • Chapter
Cohort Analysis in Social Research

Abstract

The literature on the determinants of earnings suggest an earnings function for individual i which depends on age ai, year t, “vintage” or “cohort” schooling level si, and experience ei. Adopting a linear function to facilitate exposition we may write

$${Y_i}(t,{a_i},{c_i},{e_i},{s_i}) = {\alpha _0} + {\alpha _1}{a_i} + {\alpha _2}t + {\alpha _3}{e_i} + {\alpha _4}{s_i} + {\alpha _5}{c_i}$$
((1))

where ei is experience, usually defined for males as age minus schooling, (ei = ai – si),1 and Yi may be any monotone transformation of earnings.

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Author information

Authors and Affiliations

  1. Department of Economics, University of Chicago, USA

    James Heckman & Richard Robb

  2. National Opinion Research Center, University of Chicago, USA

    James Heckman & Richard Robb

Authors
  1. James Heckman
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  2. Richard Robb
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Editor information

Editors and Affiliations

  1. The Population Studies Center, University of Michigan, 48104, Ann Arbor, Michigan, USA

    William M. Mason

  2. Department of Statistics, Carnegie-Mellon University, 15213, Pittsburgh, Pennsylvania, USA

    Stephen E. Fienberg

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© 1985 Springer-Verlag New York Inc.

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Heckman, J., Robb, R. (1985). Using Longitudinal Data to Estimate Age, Period and Cohort Effects in Earnings Equations. In: Mason, W.M., Fienberg, S.E. (eds) Cohort Analysis in Social Research. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-8536-3_5

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  • DOI: https://doi.org/10.1007/978-1-4613-8536-3_5

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4613-8538-7

  • Online ISBN: 978-1-4613-8536-3

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