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Detailed Estimation Of Worklife Expectancy For The Measurement Of Human Capital: Accounting For Marriage And Children

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  • Daniel L. Millimet
  • Michael Nieswiadomy
  • Daniel Slottje

Abstract

Measuring an individual's human capital at a point in time as the present actuarial value of expected net lifetime earnings has a lengthy history. Calculating such measures requires accurate estimates of worklife expectancy. Here, worklife estimates for men and women in the USA categorized by educational attainment, race, marital status, parental status and current labour force status are presented. Race has a much larger impact on the worklife expectancy of men than women. Education is associated with larger worklife differentials for women. The association between marriage and worklife expectancy is significant, but of opposite sign, for men and women: married women (men) have a lower (higher) worklife expectancy than single women (men). Parenthood is associated with a reduction in the worklife expectancy of women; the association is smaller and varies from positive for some education/marital status groups to negative for others for men.

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  • Daniel L. Millimet & Michael Nieswiadomy & Daniel Slottje, 2010. "Detailed Estimation Of Worklife Expectancy For The Measurement Of Human Capital: Accounting For Marriage And Children," Journal of Economic Surveys, Wiley Blackwell, vol. 24(2), pages 339-361, April.
    • Handle: RePEc:bla:jecsur:v:24:y:2010:i:2:p:339-361
    DOI: 10.1111/j.1467-6419.2009.00618.x
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    Cited by:

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    2. Dudel, Christian & López Gómez, María Andrée & Benavides, Fernando G. & Myrskylä, Mikko, 2018. "The length of working life in Spain: levels, recent trends, and the impact of the financial crisis," LSE Research Online Documents on Economics 86990, London School of Economics and Political Science, LSE Library.
    3. Christian Dudel & María Andrée López Gómez & Fernando G. Benavides & Mikko Myrskylä, 2018. "The Length of Working Life in Spain: Levels, Recent Trends, and the Impact of the Financial Crisis," European Journal of Population, Springer;European Association for Population Studies, vol. 34(5), pages 769-791, December.
    4. Daniel Slottje, 2010. "Human Capital Measurement: Theory And Practice," Journal of Economic Surveys, Wiley Blackwell, vol. 24(2), pages 201-205, April.
    5. Christian Dudel & Mikko Myrskylä, 2017. "Working Life Expectancy at Age 50 in the United States and the Impact of the Great Recession," Demography, Springer;Population Association of America (PAA), vol. 54(6), pages 2101-2123, December.
    6. Pietro Giorgio Lovaglio, 2010. "The Estimation Of Human Capital By Administrative Archives In A Static And Longitudinal Perspective: The Case Of Milan," Journal of Economic Surveys, Wiley Blackwell, vol. 24(2), pages 280-308, April.
    7. Rusty Tchernis, 2010. "Measuring Human Capital And Its Effects On Wage Growth," Journal of Economic Surveys, Wiley Blackwell, vol. 24(2), pages 362-387, April.
    8. Jenny Lye & Joe Hirschberg, 2010. "Alcohol Consumption And Human Capital: A Retrospective Study Of The Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 24(2), pages 309-338, April.
    9. Giuseppe Folloni & Giorgio Vittadini, 2010. "Human Capital Measurement: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 24(2), pages 248-279, April.
    10. Christian Dudel, 2017. "Expanding the Markov chain tool box: distributions of occupation times and waiting times," MPIDR Working Papers WP-2017-017, Max Planck Institute for Demographic Research, Rostock, Germany.

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