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Accounting for COVID-19-type shocks in mortality modeling: a comparative study

Published online by Cambridge University Press:  10 August 2023

Simon Schnürch ,
Torsten Kleinow  and
Andreas Wagner
Simon Schnürch*
Affiliation:
Department of Financial Mathematics, Fraunhofer Institute for Industrial Mathematics ITWM, Fraunhofer-Platz 1, 67663 Kaiserslautern, Germany Department of Mathematics, University of Kaiserslautern, Gottlieb-Daimler-Straße 48, 67663 Kaiserslautern, Germany
Torsten Kleinow
Affiliation:
Department of Actuarial Mathematics and Statistics and the Maxwell Institute for Mathematical Sciences, School of Mathematical and Computer Sciences, Heriot-Watt University, EH14 4AS Edinburgh, UK
Andreas Wagner
Affiliation:
Department of Financial Mathematics, Fraunhofer Institute for Industrial Mathematics ITWM, Fraunhofer-Platz 1, 67663 Kaiserslautern, Germany Faculty of Management Science and Engineering, Karlsruhe University of Applied Sciences, Moltkestraße 30, 76133 Karlsruhe, Germany
*
Corresponding author: E-mail: schnuerch.itwm@web.de
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Abstract

Mortality shocks such as the one induced by the COVID-19 pandemic have substantial impact on mortality models. We describe how to deal with them in the period effect of the Lee–Carter model. The main idea is to not rely on the usual normal distribution assumption as it is not always justified. We consider a mixture distribution model based on the peaks-over-threshold method, a jump model, and a regime switching model and introduce a modified calibration procedure to account for the fact that varying amounts of data are necessary for calibrating different parts of these models. We perform an extensive empirical study for nine European countries, comparing the models with respect to their parameters, quality of fit, and forecasting performance. Moreover, we define five exemplary scenarios regarding the future development of pandemic-related mortality. As a result of our evaluations, we recommend the peaks-over-threshold approach for applications with a possibility of extreme mortality events.

Keywords

COVID-19Lee–Carter modelmortality forecastingmortality modelingmortality shocks

JEL classification

C53: Forecasting and Prediction Methods • Simulation Methods G22: Insurance • Insurance Companies • Actuarial Studies J11: Demographic Trends, Macroeconomic Effects, and Forecasts

Information

Type
Research Paper
Information
Journal of Demographic Economics , Volume 89 , Special Issue 3: International Longevity Risk and Capital Markets Solutions , September 2023 , pp. 483 - 512
Copyright
Copyright © Université catholique de Louvain 2023

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