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Gompertz Law Revisited: Forecasting Mortality with a Multi-factor Exponential Model

Wenjun Zhu

Wenjun Zhu, PhD, FSA, CERA

  • Associate Professor
  • Deputy Head, Division of Finance
  • Co-Director, Insurance Risk and Finance Research Centre (IRFRC)

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Nanyang Business School, 91 Nanyang Ave, Wee Cho Yaw Plaza, 639956

Journal article

Hong Li; Ken Seng Tan; Shripad Tuljapurkar; Wenjun Zhu

Insurance: Mathematics and Economics · 2021-07 · Volume 99 · pp. 268-281
DOI: 10.1016/j.insmatheco.2021.03.018 · Download citation (BibTeX)

Source · SSRN · PDF

Abstract

This paper provides a flexible multi-factor framework to address some ongoing challenges in mortality modeling, with a special focus on the mortality curvature and possible mortality plateau for extremely old ages. We extend the Gompertz law Gompertz (1825) by proposing a multi-factor exponential model. The proposed framework is based on the Laguerre approximating functions, and is able to capture flexible mortality patterns, and allows for a convenient estimation and prediction algorithm. An extensive empirical analysis is conducted using the proposed framework with a merged mortality database containing a large number of countries and regions with credible old-age mortality data. We find that the proposed exponential model leads to superior goodness-of-fit to historical data, and better out-of-sample forecast performance. Moreover, the exponential model predicts more balanced mortality improvements across ages, and thus leads to higher projected remaining life expectancy for the old ages than existing Gompertz-based mortality models. Finally, the modeling capacity of the proposed exponential model is further demonstrated by a multi-population extension, and an illustrative example of estimation and forecast is provided.

Keywords: Old Age Mortality Forecasting, Gompertz Law, Factor Model

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