Researchers at Department of Statistics and Actuarial Science Release New Study Findings on Probability and Statistics (Assessing the Performance of the Discrete Generalised Pareto Distribution in Modelling Non-Life Insurance Claims)

2021 JUL 06 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Fresh data on probability and statistics are presented in a new report. According to news originating from the Department of Statistics and Actuarial Science by NewsRx editors, the research stated, “The generalised Pareto distribution (GPD) offers a family of probability spaces which support threshold exceedances and is thus suitable for modelling high-end actuarial risks. Nonetheless, its distributional continuity presents a critical limitation in characterising data of discrete forms.”

Our news journalists obtained a quote from the research from Department of Statistics and Actuarial Science: “Discretising the GPD, therefore, yields a derived distribution which accommodates the count data while maintaining the essential tail modelling properties of the GPD. In this paper, we model non-life insurance claims under the three-parameter discrete generalised Pareto (DGP) distribution. Data for the study on reported and settled claims, spanning the period 2012-2016, were obtained from the National Insurance Commission, Ghana. The maximum likelihood estimation (MLE) principle was adopted in fitting the DGP to yearly and aggregated data. The estimation involved two steps. First, we propose a modification to the m and m+1 frequency method in the literature. The proposal provides an alternative routine for generating initial estimators for MLE, in cases of varied count intervals, as is a characteristic of the claim data under study. Second, a bootstrap algorithm is implemented to obtain standard errors of estimators of the DGP parameters.”

According to the news reporters, the research concluded: “The performance of the DGP is compared to the negative binomial distribution in modelling the claim data using the Akaike and Bayesian information criteria. The results show that the DGP is appropriate for modelling the count of non-life insurance claims and provides a better fit to the regulatory claim data considered.”

For more information on this research see: Assessing the Performance of the Discrete Generalised Pareto Distribution in Modelling Non-Life Insurance Claims. Journal of Probability and Statistics, 2021,2021. (Journal of Probability and Statistics - https://www.hindawi.com/journals/jps/). The publisher for Journal of Probability and Statistics is Hindawi Limited.

A free version of this journal article is available at https://doi.org/10.1155/2021/5518583.

Our news editors report that additional information may be obtained by contacting S. K.-B. Dzidzornu, Department of Statistics and Actuarial Science.

(Our reports deliver fact-based news of research and discoveries from around the world.)