A Study on Modeling of Lifetime with Right-Truncated Composite Lognormal-Pareto Distribution: Actuarial Premium Calculations
Abstract
The modeling of lifetime is important to compute actuarial quantities such as the premium on insurance and annuity products. De Moivre, Gompertz, and Makeham are laws of mortality frequently used in lifetime modeling. Composite distributions have also been used to model lifetime, recently. However, there are not many actuarial applications of these models in the literature. Therefore, the main aim of the study is to perform a case study that gives a comparison of marginal and composite models on premiums. For this purpose, firstly, it is aimed to achieve a new mortality function for a lifetime using composite distribution. The second aim is to analytically compute premiums for whole life and term life insurance products. Here, it is assumed that lifetime distribution is modeled with lognormal, Type 2 Pareto (Pareto) and composite lognormal-Pareto. Firstly, the right truncated distributions of the models were obtained under the consideration that the last age of death was 100. Afterwards, the survival and mortality functions were inferenced using Mathematica 10.2 for the right truncated models. Finally, premium coefficients were analytically presented for whole life and term life insurances in single and joint life statuses. The results show that there are significantly differences in these premium coefficients. It has been observed that the premium coefficients for the term life insurance were higher than the premium coefficients for whole life insurance. In addition, the premium coefficients of the insurances issued for the joint life were smaller than the premium coefficients for the single life.
Keywords
References
- [1] Klugman, S.A., Panjer, H.H. and Willmot, G.E., Loss models: from data to decisions (second edition), New York: John Wiley and Sons, (2004).
- [2] Cooray, K. and Ananda, M.M., “Modeling actuarial data with a composite lognormal-Pareto model”, Scandinavian Actuarial Journal, (5): 321-334, (2005).
- [3] Scollnik, D.P., “On composite lognormal-Pareto models”, Scandinavian Actuarial Journal, (1): 20-33, (2007).
- [4] Dominicy, Y. and Sinner, C., Distributions and Composite Models for Size-Type Data. Advances in Statistical Methodologies and Their Application to Real Problems, 159. (2017).
- [5] Lindeboom, M. and Van den Berg, G.J., “Heterogeneity in models for bivariate survival: the importance of the mixing distribution.”, Journal of the Royal Statistical Society: Series B (Methodological), 56(1): 49-60, (1994).
- [6] Parner, E.T., “A composite likelihood approach to multivariate survival data”, Scandinavian Journal of Statistics, 28(2): 295-302, (2001).
- [7] Teodorescu, S. and Vernic, R., “Some composite Exponential-Pareto models for actuarial prediction”, Romanian Journal of Economic Forecasting, 12(4): 82-100, (2009).
- [8] Nadarajah, S. and Bakar, S.A., “New composite models for the Danish fire insurance data”, Scandinavian Actuarial Journal, (2): 180-187, (2014).
Details
Primary Language
English
Subjects
Engineering
Journal Section
Research Article
Authors
Publication Date
March 1, 2021
Submission Date
November 14, 2019
Acceptance Date
August 10, 2020
Published in Issue
Year 2021 Volume: 34 Number: 1
Cited By
Actuarial premium calculation for beekeeping insurance in Turkiye
The Geneva Papers on Risk and Insurance - Issues and Practice
https://doi.org/10.1057/s41288-024-00329-wGenerating Mortality Rate Intensity for Life Insurance Applications through Novel Method of Successive Differencing Under the Parsimonious Generalised Makeham’s Framework
Lafia Journal of Scientific and Industrial Research
https://doi.org/10.62050/ljsir2024.v2n2.338The Health Economics of Life Expectancy
Lafia Journal of Scientific and Industrial Research
https://doi.org/10.62050/ljsir2025.v3n1.352A study on life insurance premiums under asymmetric dependence using Canadian insurance data
Hacettepe Journal of Mathematics and Statistics
https://doi.org/10.15672/hujms.1522471