IDEAS home Printed from
   My bibliography  Save this paper

Model effect on projected mortality indicators


  • A. Debòn
  • S. Haberman
  • F. Montes
  • E. Otranto



The parametric model introduced by Lee and Carter in 1992 for projecting mortality rates in the US has been a seminal development and has been widely used since then. Different versions of the model, incorporating constraints on the data, and different adjustment methods have led to improvement. All of these changes have increased the complexity of the model with a corresponding improvement in goodness of fit, however, there is little change in the accuracy of forecasts of life expectancy in comparison with the original Lee-Carter model, according to some authors. To evaluate to what point the increments in the complexity and computational cost of the models are reflected in the forecast of such indices as life expectancy and modal age at death, among others, we have compared three different models - the original Lee-Carter with one parameter and the Lee-Carter model with two temporal parameters forecasted by means of two independent time series or by means of a bivariate one. The three sets of predictions so obtained are compared using a mixture of block-bootstrap techniques and functional data analysis.

Suggested Citation

  • A. Debòn & S. Haberman & F. Montes & E. Otranto, 2012. "Model effect on projected mortality indicators," Working Paper CRENoS 201215, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  • Handle: RePEc:cns:cnscwp:201215

    Download full text from publisher

    File URL:
    Download Restriction: no

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Cuevas, Antonio & Febrero, Manuel & Fraiman, Ricardo, 2004. "An anova test for functional data," Computational Statistics & Data Analysis, Elsevier, vol. 47(1), pages 111-122, August.
    2. Debón, A. & Montes, F. & Puig, F., 2008. "Modelling and forecasting mortality in Spain," European Journal of Operational Research, Elsevier, vol. 189(3), pages 624-637, September.
    3. Renshaw, A.E. & Haberman, S., 2006. "A cohort-based extension to the Lee-Carter model for mortality reduction factors," Insurance: Mathematics and Economics, Elsevier, vol. 38(3), pages 556-570, June.
    4. Martínez-Camblor, Pablo & Corral, Norberto, 2011. "Repeated measures analysis for functional data," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3244-3256, December.
    5. Brouhns, Natacha & Denuit, Michel & Vermunt, Jeroen K., 2002. "A Poisson log-bilinear regression approach to the construction of projected lifetables," Insurance: Mathematics and Economics, Elsevier, vol. 31(3), pages 373-393, December.
    6. J. Cuesta-Albertos & M. Febrero-Bande, 2010. "A simple multiway ANOVA for functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(3), pages 537-557, November.
    7. ., 1998. "Rent," Chapters,in: The Elgar Companion to Classical Economics, chapter 127 Edward Elgar Publishing.
    Full references (including those not matched with items on IDEAS)

    More about this item


    mortality indicators; block-bootstrap; functional data analysis;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:cns:cnscwp:201215. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Antonello Pau). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.