IDEAS home Printed from https://ideas.repec.org/a/rjr/romjef/vy2016i2p152-168.html
   My bibliography  Save this article

Common Stochastic Trends in European Mortality Levels: Testing and Consequences for Modeling Longevity Risk in Insurance

Author

Listed:
  • Dorina Lazar

    (Corresponding author. Faculty of Economics and Business Administration, Babes-Bolyai University of Cluj-Napoca.)

  • Anuta Buiga

    (Faculty of Economics and Business Administration, Babes-Bolyai University of Cluj-Napoca.)

  • Adela Deaconu

    (Faculty of Economics and Business Administration, Babes-Bolyai University of Cluj-Napoca.)

Abstract

This paper highlights the long-term trends of general mortality levels in the European countries, investigates the existence of some common stochastic trends determining the mortality of the elderly population, and proposes to forecast the mortality rates taking into account these common stochastic trends. As a first step, a method for regionalization is used in order to provide homogeneous contiguous clusters. The tests for cointegration detect the number of common stochastic trends determining the mortality indices, derived from the Lee-Carter model, for countries from a homogeneous cluster; forecasts are generated by the vector error correction model. Based on out-of- sample forecasts, this approach leads to estimates of life expectancy near those provided by the Lee Carter model. In addition, using the VEC approach, the common stochastic trends, developed by the long-term mortality experience for countries from a cluster are preserved in the long run.

Suggested Citation

  • Dorina Lazar & Anuta Buiga & Adela Deaconu, 2016. "Common Stochastic Trends in European Mortality Levels: Testing and Consequences for Modeling Longevity Risk in Insurance," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 152-168, June.
    • Handle: RePEc:rjr:romjef:v::y:2016:i:2:p:152-168
    as

    Download full text from publisher

    File URL: http://www.ipe.ro/rjef/rjef2_16/rjef2_2016p152-168.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jarner, Søren Fiig & Kryger, Esben Masotti, 2011. "Modelling Adult Mortality in Small Populations: The Saint Model," ASTIN Bulletin, Cambridge University Press, vol. 41(2), pages 377-418, November.
    2. William Easterly & Ross Levine, 1997. "Africa's Growth Tragedy: Policies and Ethnic Divisions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(4), pages 1203-1250.
    3. Wolfgang Keller, 2002. "Geographic Localization of International Technology Diffusion," American Economic Review, American Economic Association, vol. 92(1), pages 120-142, March.
    4. Heather Booth & Rob Hyndman & Leonie Tickle & Piet de Jong, 2006. "Lee-Carter mortality forecasting: a multi-country comparison of variants and extensions," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 15(9), pages 289-310.
    5. Wolfgang Keller, 2004. "International Technology Diffusion," Journal of Economic Literature, American Economic Association, vol. 42(3), pages 752-782, September.
    6. Rob Hyndman & Heather Booth & Farah Yasmeen, 2013. "Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models," Demography, Springer;Population Association of America (PAA), vol. 50(1), pages 261-283, February.
    7. Dorina Lazar & Michel M. Denuit, 2009. "A multivariate time series approach to projected life tables," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(6), pages 806-823, November.
    8. Han Lin Shang & Heather Booth & Rob Hyndman, 2011. "Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 25(5), pages 173-214.
    9. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    10. David Blake & Christophe Courbage & Richard MacMinn & Michael Sherris, 2011. "Longevity Risk and Capital Markets: The 2010–2011 Update," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 36(4), pages 489-500, October.
    11. Nan Li & Ronald Lee, 2005. "Coherent mortality forecasts for a group of populations: An extension of the lee-carter method," Demography, Springer;Population Association of America (PAA), vol. 42(3), pages 575-594, August.
    12. Dinu. Marin & Marinas, Marius Corneliu & Socol Cristian & Socol, Aura Gabriela, 2012. "Clusterization, Persistence, Dependency and Volatility of Business Cycles in an Enlarged Euro Area," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-23, June.
    13. David Blake & Pat Brockett & Samuel Cox & Richard MacMinn, 2011. "Longevity Risk and Capital Markets," North American Actuarial Journal, Taylor & Francis Journals, vol. 15(2), pages 141-149.
    14. Blake, David & Brockett, Patrick & Cox, Samuel & MacMinn, Richard, 2011. "Longevity risk and capital markets: The 2009-2010 update," MPRA Paper 28868, University Library of Munich, Germany.
    15. Johnny Li & Mary Hardy, 2011. "Measuring Basis Risk in Longevity Hedges," North American Actuarial Journal, Taylor & Francis Journals, vol. 15(2), pages 177-200.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jarner, Søren F. & Jallbjørn, Snorre, 2020. "Pitfalls and merits of cointegration-based mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 90(C), pages 80-93.
    2. Feng, Lingbing & Shi, Yanlin & Chang, Le, 2021. "Forecasting mortality with a hyperbolic spatial temporal VAR model," International Journal of Forecasting, Elsevier, vol. 37(1), pages 255-273.
    3. Rob Hyndman & Heather Booth & Farah Yasmeen, 2013. "Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models," Demography, Springer;Population Association of America (PAA), vol. 50(1), pages 261-283, February.
    4. Katrien Antonio & Anastasios Bardoutsos & Wilbert Ouburg, 2015. "Bayesian Poisson log-bilinear models for mortality projections with multiple populations," Working Papers Department of Accountancy, Finance and Insurance (AFI), Leuven 485564, KU Leuven, Faculty of Economics and Business (FEB), Department of Accountancy, Finance and Insurance (AFI), Leuven.
    5. 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.
    6. David Blake & Marco Morales & Enrico Biffis & Yijia Lin & Andreas Milidonis, 2017. "Special Edition: Longevity 10 – The Tenth International Longevity Risk and Capital Markets Solutions Conference," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(S1), pages 515-532, April.
    7. 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.
    8. Basellini, Ugofilippo & Camarda, Carlo Giovanni & Booth, Heather, 2023. "Thirty years on: A review of the Lee–Carter method for forecasting mortality," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1033-1049.
    9. de Jong, Piet & Tickle, Leonie & Xu, Jianhui, 2016. "Coherent modeling of male and female mortality using Lee–Carter in a complex number framework," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 130-137.
    10. Liu, Yanxin & Li, Johnny Siu-Hang, 2016. "It’s all in the hidden states: A longevity hedging strategy with an explicit measure of population basis risk," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 301-319.
    11. Hunt, Andrew & Blake, David, 2018. "Identifiability, cointegration and the gravity model," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 360-368.
    12. Danesi, Ivan Luciano & Haberman, Steven & Millossovich, Pietro, 2015. "Forecasting mortality in subpopulations using Lee–Carter type models: A comparison," Insurance: Mathematics and Economics, Elsevier, vol. 62(C), pages 151-161.
    13. Hunt, Andrew & Blake, David, 2015. "Modelling longevity bonds: Analysing the Swiss Re Kortis bond," Insurance: Mathematics and Economics, Elsevier, vol. 63(C), pages 12-29.
    14. Lenny Stoeldraijer & Coen van Duin & Leo van Wissen & Fanny Janssen, 2013. "Impact of different mortality forecasting methods and explicit assumptions on projected future life expectancy: The case of the Netherlands," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(13), pages 323-354.
    15. Li, Hong & Lu, Yang, 2017. "Coherent Forecasting Of Mortality Rates: A Sparse Vector-Autoregression Approach," ASTIN Bulletin, Cambridge University Press, vol. 47(2), pages 563-600, May.
    16. Christina Bohk-Ewald & Marcus Ebeling & Roland Rau, 2017. "Lifespan Disparity as an Additional Indicator for Evaluating Mortality Forecasts," Demography, Springer;Population Association of America (PAA), vol. 54(4), pages 1559-1577, August.
    17. Pascariu, Marius D. & Canudas-Romo, Vladimir & Vaupel, James W., 2018. "The double-gap life expectancy forecasting model," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 339-350.
    18. Li, Hong & Shi, Yanlin, 2021. "Forecasting mortality with international linkages: A global vector-autoregression approach," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 59-75.
    19. Shang, Han Lin & Haberman, Steven, 2017. "Grouped multivariate and functional time series forecasting:An application to annuity pricing," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 166-179.
    20. Syazreen Shair & Sachi Purcal & Nick Parr, 2017. "Evaluating Extensions to Coherent Mortality Forecasting Models," Risks, MDPI, vol. 5(1), pages 1-20, March.

    More about this item

    Keywords

    longevity risk; forecasts; spatial clusters; cointegration; Lee-Carter model;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rjr:romjef:v::y:2016:i:2:p:152-168. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Corina Saman (email available below). General contact details of provider: https://edirc.repec.org/data/ipacaro.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.