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Constructing Full Adult Life-cycles from Short Panels

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  • Peter Levell

    (Institute for Fiscal Studies, London, United Kingdom)

  • Jonathan Shaw

    (Institute for Fiscal Studies, London, United Kingdom)

Abstract

In this paper we discuss two alternative approaches to constructing complete adult life-cycles using data from an 18-year panel. The first of these is a splicing approach - closely related to imputation - that involves stitching together individuals observed at different ages. The second is a microsimulation approach that uses panel data to estimate transition probabilities between different states at adjacent ages and then simulates a large number of individuals with different initial values. Our aim throughout is to construct life-cycle profiles of employment, earnings and family circumstances that are representative of UK individuals born between 1945 and 1954. On balance, we find the microsimulation approach is to be preferred because it allows us to correct for observable differences across cohorts, and it is more amenable to counterfactual modelling.

Suggested Citation

  • Peter Levell & Jonathan Shaw, 2016. "Constructing Full Adult Life-cycles from Short Panels," International Journal of Microsimulation, International Microsimulation Association, vol. 9(2), pages 5-40.
    • Handle: RePEc:ijm:journl:v:9:y:2016:i:2:p:5-40
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    Cited by:

    1. Timm Bönke & Holger Lüthen, 2020. "Die Ungleichheit von Lebenserwerbseinkommen," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 100(4), pages 241-245, April.
    2. Fischer, Benjamin & Hügle, Dominik, 2020. "The private and fiscal returns to higher education: A simulation approach for a young German cohort," Discussion Papers 2020/21, Free University Berlin, School of Business & Economics.
    3. Peter Levell & Barra Roantree & Jonathan Shaw, 2021. "Mobility and the lifetime distributional impact of tax and transfer reforms," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 28(4), pages 751-793, August.
    4. Bonin, Holger & Reuss, Karsten & Stichnoth, Holger, 2015. "Life-cycle incidence of family policy measures in Germany: Evidence from a dynamic microsimulation model," ZEW Discussion Papers 15-036, ZEW - Leibniz Centre for European Economic Research.
    5. Glaubitz, Rick & Harnack-Eber, Astrid & Wetter, Miriam, 2022. "The gender gap in lifetime earnings: The role of parenthood," Discussion Papers 2022/3, Free University Berlin, School of Business & Economics.
    6. Bönke, Timm & Glaubitz, Rick & Göbler, Konstantin & Harnack, Astrid & Pape, Astrid & Wetter, Miriam, 2020. "Die Entwicklung und Prognose von Lebenserwerbseinkommen in Deutschland," Discussion Papers 2020/5, Free University Berlin, School of Business & Economics.
    7. Peter Levell & Barra Roantree & Jonathan Shaw, 2015. "Redistribution from a lifetime perspective," IFS Working Papers W15/27, Institute for Fiscal Studies.
    8. Holger Bonin & Karsten Reuss & Holger Stichnoth, 2016. "The Monetary Value of Family Policy Measures in Germany over the Life Cycle: Evidence from a Dynamic Microsimulation Model," CESifo Economic Studies, CESifo Group, vol. 62(4), pages 650-671.
    9. Westin, Kerstin & Holm, Einar, 2018. "Do trees make people more rooted? Private forest owners' migration behaviour," Forest Policy and Economics, Elsevier, vol. 94(C), pages 11-20.
    10. Rick Glaubitz & Astrid Harnack-Eber & Miriam Wetter, 2022. "The Gender Gap in Lifetime Earnings: The Role of Parenthood," Discussion Papers of DIW Berlin 2001, DIW Berlin, German Institute for Economic Research.

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    More about this item

    Keywords

    Microsimulation models; Lifetime income distribution;

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

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