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Modelling Techniques for Life Premium Ratings


  • Mirela Cristea
  • Marijan Cingula


The paper presents the modelling techniques used on international practice for establishing life premiums quota. Thus, the calculus techniques used by the insurers are generally based on a series of indicators named mortality indicators which mainly point out the insured persons’ survival probability, the death probability and life expectancy at certain age. In Romania, these indicators are settled by National Institute of Statistics and they represent the basis for the calculation of the premiums quotes and for the elaboration by the insurers of premium tables. The benefit for the policyholder is to obtain insurance at a fair and competitive price and for the insurer, to maintain the experience of its portfolio in line with mortality assumptions.

Suggested Citation

  • Mirela Cristea & Marijan Cingula, 2008. "Modelling Techniques for Life Premium Ratings," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 39-48.
  • Handle: RePEc:ers:journl:v:xi:y:2008:i:4:p:39-48

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    References listed on IDEAS

    1. Taylor, John B, 1980. "Aggregate Dynamics and Staggered Contracts," Journal of Political Economy, University of Chicago Press, vol. 88(1), pages 1-23, February.
    2. Arratibel, Olga & Rodriguez-Palenzuela, Diego & Thimann, Christian, 2002. "Inflation dynamics and dual inflation in accession countries: a 'New Keynesian' perspective," Working Paper Series 0132, European Central Bank.
    3. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    4. Gali, Jordi & Gertler, Mark & Lopez-Salido, J. David, 2001. "European inflation dynamics," European Economic Review, Elsevier, vol. 45(7), pages 1237-1270.
    5. Gali, Jordi & Gertler, Mark & David Lopez-Salido, J., 2005. "Robustness of the estimates of the hybrid New Keynesian Phillips curve," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1107-1118, September.
    6. Jordi Galí & J David López-Salido, 2001. "A New Phillips curve for Spain," BIS Papers chapters,in: Bank for International Settlements (ed.), Empirical studies of structural changes and inflation, volume 3, pages 174-203 Bank for International Settlements.
    7. Matheson, Troy D., 2008. "Phillips curve forecasting in a small open economy," Economics Letters, Elsevier, vol. 98(2), pages 161-166, February.
    8. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
    9. Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 195-222, October.
    10. Campbell Leith & Jim Malley, 2007. "Estimated Open Economy New Keynesian Phillips Curves for the G7," Open Economies Review, Springer, vol. 18(4), pages 405-426, September.
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    Cited by:

    1. Carlos Pestana Barrosa & Milton Nektariosb & Nicolas Peypochc, 2009. "A Luenberger Index for the Greek Life Insurance Industry," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 3-18.

    More about this item


    premium ratings; life insurance; modeling techniques; mortality indicators;

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies


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