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Risks
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Advancement in Mortality Forecasting and Mortality/Longevity Risk Management
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Advancement in Mortality Forecasting and Mortality/Longevity Risk Management

A special issue of Risks (ISSN 2227-9091).

Deadline for manuscript submissions: 15 March 2025 | Viewed by 4595

Special Issue Editor

Dr. Han Li

E-Mail Website
Guest Editor
Centre for Actuarial Studies, Department of Economics, University of Melbourne, Melbourne, VIC 3010, Australia
Interests: mortality modelling and forecasting; mortality and longevity risk management; ageing and retirement; impact of climate change on insurance industry

Special Issue Information

Dear Colleagues,

Recent advancements in modeling mortality/longevity risk have deepened our understanding of mortality dynamics and enhanced risk management practices in aging populations. Events like the COVID-19 pandemic have provided us with an opportunity to improve our understanding and management of extreme mortality risk. Exploring innovative capital market solutions is worthwhile as an alternative means to transfer longevity risks.

This Special Issue aims to compile recent breakthroughs in mortality modelling and forecasting, and longevity risk management, recognizing events like the COVID-19 pandemic as extreme mortality experiences. We invite papers presenting original research on related topics including, but not limited to, the following:

  1. Innovative mortality modeling techniques;
  2. Mortality forecasting in single and multiple populations;
  3. Assessment of extreme mortality risk;
  4. Capital market solutions for longevity risk transfer;
  5. Cause-specific mortality modeling.

We anticipate your valuable contributions to enrich this discourse.

Dr. Han Li
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Risks is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • mortality modelling and forecasting
  • longevity risk management
  • assessment of extreme mortality risk

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

25 pages, 4986 KiB  
Article
Estimating Disease-Free Life Expectancy Based on Clinical Data from the French Hospital Discharge Database
by Oleksandr Sorochynskyi, Quentin Guibert, Frédéric Planchet and Michaël Schwarzinger
Risks 2024, 12(6), 92; https://doi.org/10.3390/risks12060092 - 3 Jun 2024
Viewed by 870
Abstract
The development of health indicators to measure healthy life expectancy (HLE) is an active field of research aimed at summarizing the health of a population. Although many health indicators have emerged in the literature as critical metrics in public health assessments, the methods [...] Read more.
The development of health indicators to measure healthy life expectancy (HLE) is an active field of research aimed at summarizing the health of a population. Although many health indicators have emerged in the literature as critical metrics in public health assessments, the methods and data to conduct this evaluation vary considerably in nature and quality. Traditionally, health data collection relies on population surveys. However, these studies, typically of limited size, encompass only a small yet representative segment of the population. This limitation can necessitate the separate estimation of incidence and mortality rates, significantly restricting the available analysis methods. In this article, we leverage an extract from the French National Hospital Discharge database to define health indicators. Our analysis focuses on the resulting Disease-Free Life Expectancy (Dis-FLE) indicator, which provides insights based on the hospital trajectory of each patient admitted to hospital in France during 2008–2013. Through this research, we illustrate the advantages and disadvantages of employing large clinical datasets as the foundation for more robust health indicators. We shed light on the opportunities that such data offer for a more comprehensive understanding of the health status of a population. In particular, we estimate age-dependent hazard rates associated with sex, alcohol abuse, tobacco consumption, and obesity, as well as geographic location. Simultaneously, we delve into the challenges and limitations that arise when adopting such a data-driven approach. Full article
(This article belongs to the Special Issue Advancement in Mortality Forecasting and Mortality/Longevity Risk Management)
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17 pages, 494 KiB  
Article
Two-Population Mortality Forecasting: An Approach Based on Model Averaging
by Luca De Mori, Pietro Millossovich, Rui Zhu and Steven Haberman
Risks 2024, 12(4), 60; https://doi.org/10.3390/risks12040060 - 27 Mar 2024
Cited by 1 | Viewed by 1560
Abstract
The analysis of residual life expectancy evolution at retirement age holds great importance for life insurers and pension schemes. Over the last 30 years, numerous models for forecasting mortality have been introduced, and those that allow us to predict the mortality of two [...] Read more.
The analysis of residual life expectancy evolution at retirement age holds great importance for life insurers and pension schemes. Over the last 30 years, numerous models for forecasting mortality have been introduced, and those that allow us to predict the mortality of two or more related populations simultaneously are particularly important. Indeed, these models, in addition to improving the forecasting accuracy overall, enable evaluation of the basis risk in index-based longevity risk transfer deals. This paper implements and compares several model-averaging approaches in a two-population context. These approaches generate predictions for life expectancy and the Gini index by averaging the forecasts obtained using a set of two-population models. In order to evaluate the eventual gain of model-averaging approaches for mortality forecasting, we quantitatively compare their performance to that of the individual two-population models using a large sample of different countries and periods. The results show that, overall, model-averaging approaches are superior both in terms of mean absolute forecasting error and interval forecast accuracy. Full article
(This article belongs to the Special Issue Advancement in Mortality Forecasting and Mortality/Longevity Risk Management)
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17 pages, 2884 KiB  
Article
Adding Shocks to a Prospective Mortality Model
by Frédéric Planchet and Guillaume Gautier de La Plaine
Risks 2024, 12(3), 57; https://doi.org/10.3390/risks12030057 - 20 Mar 2024
Viewed by 1488
Abstract
This work proposes a simple model to take into account the annual volatility of the mortality level observed on the scale of a country like France in the construction of prospective mortality tables. By assigning a frailty factor to a basic hazard function, [...] Read more.
This work proposes a simple model to take into account the annual volatility of the mortality level observed on the scale of a country like France in the construction of prospective mortality tables. By assigning a frailty factor to a basic hazard function, we generalise the Lee–Carter model. The impact on prospective life expectancies and capital requirements in the context of a life annuity scheme is analysed in detail. Full article
(This article belongs to the Special Issue Advancement in Mortality Forecasting and Mortality/Longevity Risk Management)
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