• Login
    View Item 
    •   Repository Home
    • Staff Publications
    • School of Pure and Applied Sciences
    • View Item
    •   Repository Home
    • Staff Publications
    • School of Pure and Applied Sciences
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Poisson Incorporated Credibility Regression Modelling of Systematic Mortality Risk for Populations with Finite Data

    Thumbnail
    View/Open
    Main Article (1.260Mb)
    Date
    2021-12-21
    Author
    Odhiambo, Joab
    Weke, Patrick
    Naryongo, Raphael
    Sewe, Stanley
    Metadata
    Show full item record
    Abstract
    This study considered the modeling of systematic mortality risk for populations with finite data using the Poisson incorporated Credibility regression model. For novelty, we have included the credibility regression approach to modelling mortality by assuming the number of annual deaths follow a Poisson distribution. Our model shows improvement in precision levels when estimating mortality risk compared to classical models used in European countries. We have illustrated that our model works optimally when using Kenyan mortality data, comparing male and female lives under the different strategies, thus making better predictions than the classical Lee–Carter (LC) and Cairns–Blake–Dowd (CBD) models. e mean absolute forecast error (MAFE), mean absolute percentage forecast error (MAPFE), root mean square error (RMSE), and root mean square forecast error (RMSFE) under the incorporated credibility regression model are much lower than the values obtained without incorporation of the Buhlmann credibility approach. The findings of this research will help insurance companies, pension firms, and government agencies in sub-Saharan countries model and forecast systematic mortality risks accurately. Finally, the results are essential in actuarial modelling and pricing, thus making life assurance products affordable for most people in low-income African countries.
    URI
    http://repository.must.ac.ke/handle/123456789/787
    Collections
    • School of Pure and Applied Sciences [160]

    MUST Repository copyright © 2002-2016  MUST Repository
    Contact Us | Send Feedback
    Theme by 
    MUST Repository
     

     

    Browse

    All of the RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    MUST Repository copyright © 2002-2016  MUST Repository
    Contact Us | Send Feedback
    Theme by 
    MUST Repository