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Tulot, eläke ja eläkeikä: empiirisiä tuloksia vuoden 1947 ikäkohortin kohdalta
[Incomes, pension and retirement age: empirical results with the birth year 1947 cohort]

Author

Listed:
  • Linden, Mikael
  • Väänänen, Niko

Abstract

Tutkimuksen tavoitteena on arvioida, nostiko vuoden 2005 eläkejärjestelmän ns. superkarttumasääntö eläköitymisikää 63 ikävuoden jälkeen. Tarkastelun kohteena on vuoden 1947 syntymäkohortin siirtyminen vuosina 2007-2015 vanhuuseläkkeelle. Superkarttuma mahdollisti paremman eläketason työntekoa jatkamalla ikävuoden 63 jälkeen. Tavoitteena oli, että eläkeikä nousisi. Tällöin talousteorian mukainen tulos, että korkea työtulo- ja eläketaso johtavat eläkeiän laskuun, ei välttämättä toteudu. Muuttujakolmikon {tulot, eläke, eläkeikä} rakenteellista riippuvuutta tutkitaan aluksi systeemimallin estimoinnin kautta. Saatuja tuloksia tarkennetaan tämän jälkeen IV-estimoinnilla eläkeiän kohdalta. Lopuksi tarkastellaan eläkeikämallin tuloksia uuden KLS-estimaattorin yhteydessä, joka huomioi tulo- ja eläkemuuttujien endogeenisuuden suoraan OLS-estimoinnin yhteydessä. Saavutetut tulokset tukevat päätelmää, että superkarttumasääntö johti eläkeiän nousuun keskimäärin n. 1.3 vuotta negatiivisesta tulovaikutuksesta huolimatta. Tulos antaa lisävalaistusta yksilötason eläkeiän määräytymisestä. Tästä voi olla hyötyä eläkejärjestelmän edelleen kehittämisen yhteydessä.

Suggested Citation

  • Linden, Mikael & Väänänen, Niko, 2024. "Tulot, eläke ja eläkeikä: empiirisiä tuloksia vuoden 1947 ikäkohortin kohdalta [Incomes, pension and retirement age: empirical results with the birth year 1947 cohort]," MPRA Paper 123064, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:123064
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    References listed on IDEAS

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    1. Gary S. Fields & Olivia S. Mitchell, 1984. "Economic Determinants of the Optimal Retirement Age: An Empirical Investigation," Journal of Human Resources, University of Wisconsin Press, vol. 19(2), pages 245-262.
    2. Aviv Nevo & Adam M. Rosen, 2012. "Identification With Imperfect Instruments," The Review of Economics and Statistics, MIT Press, vol. 94(3), pages 659-671, August.
    3. Angrist, Joshua & Kolesár, Michal, 2024. "One instrument to rule them all: The bias and coverage of just-ID IV," Journal of Econometrics, Elsevier, vol. 240(2).
    4. Mikusheva, Anna, 2013. "Survey on statistical inferences in weakly-identified instrumental variable models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 29(1), pages 117-131.
    5. Kiviet, Jan F., 2023. "Instrument-free inference under confined regressor endogeneity and mild regularity," Econometrics and Statistics, Elsevier, vol. 25(C), pages 1-22.
    6. Linden, Mikael, 2024. "Optimal Retirement Age: Death Hazard Rate Approach," MPRA Paper 120786, University Library of Munich, Germany.
    7. Michael Keane & Timothy Neal, 2021. "A Practical Guide to Weak Instruments," Discussion Papers 2021-05c, School of Economics, The University of New South Wales.
    8. Cremer, Helmuth & Lozachmeur, Jean-Marie & Pestieau, Pierre, 2004. "Social security, retirement age and optimal income taxation," Journal of Public Economics, Elsevier, vol. 88(11), pages 2259-2281, September.
    9. Sebastian Kripfganz & Jan F. Kiviet, 2021. "kinkyreg: Instrument-free inference for linear regression models with endogenous regressors," Stata Journal, StataCorp LLC, vol. 21(3), pages 772-813, September.
    10. Vincent P. Crawford & David M. Lilien, 1981. "Social Security and the Retirement Decision," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 96(3), pages 505-529.
    11. Young, Alwyn, 2022. "Consistency without Inference: Instrumental Variables in Practical Application," European Economic Review, Elsevier, vol. 147(C).
    12. Gruber, Jonathan & Kanninen, Ohto & Ravaska, Terhi, 2022. "Relabeling, retirement and regret," Journal of Public Economics, Elsevier, vol. 211(C).
    13. Isaiah Andrews & James H. Stock & Liyang Sun, 2019. "Weak Instruments in Instrumental Variables Regression: Theory and Practice," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 727-753, August.
    14. Young, Alwyn, 2022. "Consistency without inference: instrumental variables in practical application," LSE Research Online Documents on Economics 115011, London School of Economics and Political Science, LSE Library.
    15. Chen, An & Hentschel, Felix & Steffensen, Mogens, 2021. "On retirement time decision making," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 107-129.
    16. Mao, Hong & Ostaszewski, Krzysztof M. & Wang, Yuling, 2014. "Optimal retirement age, leisure and consumption," Economic Modelling, Elsevier, vol. 43(C), pages 458-464.
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    More about this item

    Keywords

    Incomes; pensions; accrual rate; retirement age;
    All these keywords.

    JEL classification:

    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • J26 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Retirement; Retirement Policies
    • J32 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Nonwage Labor Costs and Benefits; Retirement Plans; Private Pensions

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