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.
This research was first published in the Cambridge University Press on the 10th of August 2023.
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Simon Schnürch Department of Financial Mathematics at Fraunhofer Institute for Industrial Mathematics ITWM, Department of Mathematics at University of Kaiserslautern.
Torsten Kleinow of The Research Centre for Longevity Risk, Amsterdam School of Economics at University of Amsterdam.
Andreas Wagner Department of Financial Mathematics at Fraunhofer Institute for Industrial Mathematics ITWM, Faculty of Management Science and Engineering at Karlsruhe University of Applied Sciences.
COVID 19; Lee-Carter Model; Mortality forecasting; Mortality modeling; Mortality shocks