Logistic Regression for Insured Mortality Experience Studies
North American Actuarial Journal, 19.4 (2015): 241-255.
19 Pages Posted: 10 Jul 2020
Date Written: 2015
Properly adapted statistical modeling methodology can be a powerful tool for coping with a broad range of challenges related to life and annuity insurance industries’ experience studies. In this paper, we present a logistic regression model based U.S. insured mortality experience study with a focus on gaining study efficiency and effectiveness by addressing multiple analytical predicaments within one statistical modeling framework. These predicaments include but not limit to: a) test statistical significances or credibility of potential mortality drivers; b) estimate normalized mortality, slopes, and differentials; c) quantify study reliability; and d) extrapolate for under-experienced mortality, smooth between select and ultimate estimations, and assist basic experience table developments.
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