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Calculating compensation for loss of future earnings: estimating and using work life expectancy

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  • Zoltan Butt
  • Steven Haberman
  • Richard Verrall
  • Victoria Wass

Abstract

Summary. Where personal injury results in displacement and/or continuing disability (or death), damages include an element of compensation for loss of future earnings. This is calculated with reference to the loss of future expected time in gainful employment. We estimate employment risks in the form of reductions to work life expectancies for the UK workforce by using data from the Labour Force Survey with the purpose of improving the accuracy of the calculation of future lifetime earnings. Work life expectancies and reduction factors are modelled within the framework of a multiple‐state Markov process, conditional on age, sex, starting employment state, educational attainment and disability.

Suggested Citation

  • Zoltan Butt & Steven Haberman & Richard Verrall & Victoria Wass, 2008. "Calculating compensation for loss of future earnings: estimating and using work life expectancy," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(4), pages 763-805, October.
    • Handle: RePEc:bla:jorssa:v:171:y:2008:i:4:p:763-805
    DOI: 10.1111/j.1467-985X.2007.00539.x
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    References listed on IDEAS

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    1. Christian Dudel & Mikko Myrskylä, 2016. "Recent trends in US working life expectancy at age 50 by gender, education, and race/ethnicity and the impact of the Great Recession," MPIDR Working Papers WP-2016-006, Max Planck Institute for Demographic Research, Rostock, Germany.
    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. Gabriella Piscopo & Marina Resta, 2017. "Applying spectral biclustering to mortality data," Risks, MDPI, vol. 5(2), pages 1-13, April.
    5. Lorenti, Angelo & Dudel, Christian & Myrskylä, Mikko, 2018. "The legacy of the great recession in Italy: a wider geographical, gender, and generational gap in working life expectancy," LSE Research Online Documents on Economics 88302, London School of Economics and Political Science, LSE Library.
    6. Angelo Lorenti & Christian Dudel & Mikko Myrskylä, 2019. "The Legacy of the Great Recession in Italy: A Wider Geographical, Gender, and Generational Gap in Working Life Expectancy," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(1), pages 283-303, February.
    7. Jędrzychowska Anna & Kwiecień Ilona, 2019. "Economic Factors in the Process of Calculation of Annuities in Bodily Injury Compensation Claims Under Liability Insurance," Financial Sciences. Nauki o Finansach, Sciendo, vol. 24(1), pages 25-38, March.
    8. 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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