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Measuring the Impact of Longevity Risk on Pension Systems: The Case of Italy

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  • Emilio Bisetti
  • Carlo A. Favero

Abstract

This paper estimates the impact of longevity risk on pension systems by combining the prediction based on a Lee-Carter (1992) mortality model with the projected pension payments for different cohorts of retirees. We measure longevity risk by the difference between the upper bound of the total old-age pension expense and its mean estimate. This difference is as high as 4 per cent of annual GDP over the period 2040-2050. The impact of longevity risk is sizeably reduced by the introduction of indexation of retirement age to expected life at retirement. Our evidence speaks in favour of a market for longevity risk and calls for a closer scrutiny of the potential redistributive effects of longevity risk. Keywords: stochastic mortality, longevity risk, social security reform JEL Classification Numbers J11,J14

Suggested Citation

  • Emilio Bisetti & Carlo A. Favero, 2012. "Measuring the Impact of Longevity Risk on Pension Systems: The Case of Italy," Working Papers 439, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  • Handle: RePEc:igi:igierp:439
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    References listed on IDEAS

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    1. Ignazio Visco, 2009. "Retirement saving and the payout phase: How to get there and how to get the most of it," OECD Journal: Financial Market Trends, OECD Publishing, vol. 2009(1), pages 143-162.
    2. David Blake & Tom Boardman & Andrew Cairns, 2014. "Sharing Longevity Risk: Why Governments Should Issue Longevity Bonds," North American Actuarial Journal, Taylor & Francis Journals, vol. 18(1), pages 258-277.
    3. Andrew Cairns & David Blake & Kevin Dowd & Guy Coughlan & David Epstein & Alen Ong & Igor Balevich, 2009. "A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States," North American Actuarial Journal, Taylor & Francis Journals, vol. 13(1), pages 1-35.
    4. Nicola Sartor & Laurence J. Kotlikoff & Willi Leibfritz, 1999. "Generational Accounts for Italy," NBER Chapters, in: Generational Accounting around the World, pages 299-324, National Bureau of Economic Research, Inc.
    5. Andrew J. G. Cairns & David Blake & Kevin Dowd, 2006. "A Two‐Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 73(4), pages 687-718, December.
    6. Vladimir Canudas-Romo, 2008. "The modal age at death and the shifting mortality hypothesis," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 19(30), pages 1179-1204.
    7. Alan J. Auerbach & Laurence J. Kotlikoff & Willi Leibfritz, 1999. "Generational Accounting around the World," NBER Books, National Bureau of Economic Research, Inc, number auer99-1.
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    Citations

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    Cited by:

    1. Leng, Xuan & Peng, Liang, 2016. "Inference pitfalls in Lee–Carter model for forecasting mortality," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 58-65.
    2. Blake, David & Cairns, Andrew J.G., 2021. "Longevity risk and capital markets: The 2019-20 update," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 395-439.
    3. Lorenzo Fratoni & Susanna Levantesi & Massimiliano Menzietti, 2022. "Measuring Financial Sustainability and Social Adequacy of the Italian NDC Pension System under the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(23), pages 1-23, December.
    4. Blake, David & El Karoui, Nicole & Loisel, Stéphane & MacMinn, Richard, 2018. "Longevity risk and capital markets: The 2015–16 update," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 157-173.
    5. Samuel Asante Gyamerah & Janet Arthur & Saviour Worlanyo Akuamoah & Yethu Sithole, 2023. "Measurement and Impact of Longevity Risk in Portfolios of Pension Annuity: The Case in Sub Saharan Africa," FinTech, MDPI, vol. 2(1), pages 1-20, January.
    6. R. Melis & A. Trudda, 2014. "Mixed pension systems sustainability," Working Paper CRENoS 201413, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    7. Mariarosaria Coppola & Maria Russolillo & Rosaria Simone, 2019. "An Indexation Mechanism for Retirement Age: Analysis of the Gender Gap," Risks, MDPI, vol. 7(1), pages 1-13, February.
    8. Benedetta Frassi & Fabio Pammolli & Luca Regis, 2017. "The potential costs of Longevity Risk on Public Pensions. Evidence from Italian data," Working Papers 01/2017, IMT School for Advanced Studies Lucca, revised Jan 2017.
    9. Helena Chuliá & Montserrat Guillén & Jorge M. Uribe, 2015. "Mortality and Longevity Risks in the United Kingdom: Dynamic Factor Models and Copula-Functions," Working Papers 2015-03, Universitat de Barcelona, UB Riskcenter.
    10. Séverine Arnold & Anca Jijiie, 2020. "Retirement Ages by Socio-Economic Class," Risks, MDPI, vol. 8(4), pages 1-40, October.
    11. Anca-Stefania Jijiie & Jennifer Alonso Garcia & Séverine Arnold (-Gaille), 2019. "Mortality by socio-economic class and its impact on the retirement schemes: How to render the systems fairer?," ULB Institutional Repository 2013/300032, ULB -- Universite Libre de Bruxelles.

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    More about this item

    Keywords

    stochastic mortality; longevity risk; social security reform jel classification numbers j11; j14;
    All these keywords.

    JEL classification:

    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination

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