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Lassoing the Determinants of Retirement

Author

Listed:
  • Malene Kallestrup-Lamb

    (Aarhus University and CREATES)

  • Anders Bredahl Kock

    (Aarhus University and CREATES)

  • Johannes Tang Kristensen

    (Aarhus University and CREATES)

Abstract

This paper uses Danish register data to explain the retirement decision of workers in 1990 and 1998.Many variables might be conjectured to influence this decision such as demographic, socio-economic, financially and health related variables as well as all the same factors for the spouse in case the individual is married. In total we have access to 399 individual specific variables that all could potentially impact the retirement decision.We use variants of the Lasso and the adaptive Lasso applied to logistic regression in order to uncover determinants of the retirement decision. To the best of our knowledge this is the first application of these estimators in microeconometrics to a problem of this type and scale. Furthermore, we investigate whether the factors influencing the retirement decision are stable over time, gender and marital status. It is found that this is the case for core variables such as age, income, wealth and general health. We also point out themost important differences between these groups and explain why these might be present.

Suggested Citation

  • Malene Kallestrup-Lamb & Anders Bredahl Kock & Johannes Tang Kristensen, 2013. "Lassoing the Determinants of Retirement," CREATES Research Papers 2013-21, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2013-21
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    References listed on IDEAS

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    1. Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
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    5. Heij, Christiaan & de Boer, Paul & Franses, Philip Hans & Kloek, Teun & van Dijk, Herman K., 2004. "Econometric Methods with Applications in Business and Economics," OUP Catalogue, Oxford University Press, number 9780199268016.
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    Cited by:

    1. Mehmet Caner & Anders Bredahl Kock, 2016. "Oracle Inequalities for Convex Loss Functions with Nonlinear Targets," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1377-1411, December.

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    More about this item

    Keywords

    Retirement; Register data; High-dimensional data; Lasso; Adaptive Lasso; Oracle property; Logistic regression;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • J0 - Labor and Demographic Economics - - General
    • J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination
    • J62 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Job, Occupational and Intergenerational Mobility; Promotion

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