Demographic Issues in Longevity Risk Analysis

Journal of Risk & Insurance, Vol. 73, No. 4, pp. 575-609, December 2006

33 Pages Posted: 17 Aug 2023

Date Written: July 21, 2006

Abstract

Fundamental to the modeling of longevity risk is the specification of the assumptions used in demographic forecasting models that are designed to project past experience into future years, with or without modifications based on expert opinion about influential factors not represented in the historical data. Stochastic forecasts are required to explicitly quantify the uncertainty of forecasted cohort survival functions, including uncertainty due to process variance, parameter errors, and model misspecification errors. Current applications typically ignore the latter two sources although the potential impact of model misspecification errors is substantial. Such errors arise from a lack of understanding of the nature and causes of historical changes in longevity and the implications of these factors for the future.

This paper reviews the literature on the nature and causes of historical changes in longevity and recent efforts at deterministic and stochastic forecasting based on these data. The review reveals that plausible alternative sets of forecasting assumptions have been derived from the same sets of historical data, implying that further methodological development will be needed to integrate the various assumptions into a single coherent forecasting model. Illustrative calculations based on existing forecasts indicate that the ranges of uncertainty for older cohorts’ survival functions will be at a manageable level. Uncertainty ranges for younger cohorts will be larger and the need for greater precision will likely motivate further model development.

Keywords: demographic forecasting, life expectancy, life tables, longevity, mortality, survival

JEL Classification: J11

Suggested Citation

Stallard, P. J. Eric, Demographic Issues in Longevity Risk Analysis (July 21, 2006). Journal of Risk & Insurance, Vol. 73, No. 4, pp. 575-609, December 2006, Available at SSRN: https://ssrn.com/abstract=4539775 or http://dx.doi.org/10.2139/ssrn.4539775

P. J. Eric Stallard (Contact Author)

Duke University - BARU/SSRI ( email )

P. O. Box 90408
Durham, NC 27708-0408
United States

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