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Improving the assessment of longevity risk using survey data on subjective beliefs.
Type
conference speech
Date Issued
2019-09-11
Author(s)
Abstract (De)
It is well-documented that mortality is highly heterogeneous (Pitacco2004), i.e., depends on many observable factors such as socioeconomic conditions, living environment, health conditions, biological and physiological characteristics, and individual lifestyle, as well as on unobservable factors such as individuals' susceptibility to death (the so-called frailty). Currently, the degree of heterogeneity considered for the pricing and design of insurance products is limited. However, heterogeneity has important implications for insurers that are exposed to both active and passive selection (see Finkelstein2014). Indeed, on the one hand, individuals base their purchase decisions on their private knowledge on prospective mortality and, on the other hand, insurance companies expose themselves to observable or unobservable individual risk factors that are not properly priced. Therefore, it is important to manage mortality-related information on annuity buyers. As documented in a number of scientific contributions (e.g, in Sherris2019), individual-level longitudinal data (as the "U.S. Health and Retirement Study" and "SHARE - Survey of Health, Ageing and Retirement in Europe"(cf. Bergmann2017) include precious information about revelent mortality risk factors. Our research studies longevity dynamics by putting actuarial data in relation to this information, more specifically to subjective survival probabilities. We show that subjective survival probabilities capture relevant risk factors, but could also be biased, e.g., overreact to private information. Our study applies insights from behavioural economics to analyse the relation between actuarial and subjective probabilities, and then integrate subjective probabilities to improve the assessment of longevity risk.
Language
English
Keywords
Mortality
selection effects
survey data
subjective beliefs.
HSG Classification
contribution to scientific community
HSG Profile Area
SEPS - Quantitative Economic Methods
Event Title
43rd Annual Meeting of the Italian Association for Mathematics Applied to Economic and Social Sciences (AMASES)
Event Location
Perugia, Italy
Event Date
September, 9-11, 2019
Subject(s)
Eprints ID
258005