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Do earnings really decline for older workers?

Author

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  • Kadija Charni

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Stephen Bazen

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

Abstract

Cross section data suggest that the relationship between age and hourly earnings is an inverted-U shape. Evidence from panel data does not necessarily confirm this finding suggesting that older workers may not experience a reduction in earnings at the end of their working life. In this paper we use panel data on males for Great Britain in order to examine why the two types of data provide conflicting conclusions. Concentrating on the over 50s, several hypotheses are examined: overlapping cohorts, job tenure, job-changing, labour supply behaviour and selectivity bias. Cohort and individual fixed effects partly explain the divergent conclusions. However, for fully, year-on-year employed individuals, there is no evidence of earnings decline at the end of working life. We find no role for selectivity due to retirement, although shorter working hours or partial retirement along with job-changing late in life do provide an explanation for why hourly earnings decline for certain older workers. We find no evidence that the process of ageing itself leads to lower earnings as suggested by the cross section profile.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Kadija Charni & Stephen Bazen, 2017. "Do earnings really decline for older workers?," Post-Print hal-01691116, HAL.
    • Handle: RePEc:hal:journl:hal-01691116
    DOI: 10.1108/IJM-02-2016-0043
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    Cited by:

    1. Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2017. "Econom\'etrie et Machine Learning," Papers 1708.06992, arXiv.org, revised Mar 2018.
    2. Paulina Broniatowska & Aleksandra Majchrowska & Maciej Nasiński, 2020. "Age Structure of Employment and Wages. An Analysis Across Occupational Groups," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(3), pages 227-250, September.
    3. Sarah Le Duigou, 2020. "Endogenous Unemployment Benefits in an Equilibrium Job Search Model over the Life-Cycle," Post-Print hal-03884234, HAL.
    4. Kadija Charni, 2016. "Is it Better to Work When We Are Older? An Empirical Comparison Between France and Great Britain," AMSE Working Papers 1640, Aix-Marseille School of Economics, France.
    5. Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2018. "Économétrie & Machine Learning," Working Papers hal-01568851, HAL.
    6. Majchrowska Aleksandra & Broniatowska Paulina, 2018. "The workforce’s age structure and wages—Do age and the type of occupation matter?," Lodz Economics Working Papers 8/2018, University of Lodz, Faculty of Economics and Sociology.
    7. Axel Börsch-Supan & Irene Ferrari & Nicolas Goll & Johannes Rausch, 2023. "Retirement Decisions in Germany: Micro-Modeling," NBER Chapters, in: Social Security Programs and Retirement around the World: The Effects of Reforms on Retirement Behavior, pages 165-203, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs
    • J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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