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Title: Financial consequences of climate changes on forecasting mortality rates
Author: Seklecka, M.
ISNI:       0000 0004 7428 4595
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2017
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Changes in mortality rates have an impact on the life insurance industry, the fi nancial sector (as a signi cant proportion of the financial markets is driven by pension funds), the governmental agencies, and the decision and policymakers. Thus, the pricing of financial, pension and insurance products that are contingent upon survival or death and which is related to the accuracy of central mortality rates is of key importance. This thesis discusses the impact of a climate change-related factor and economic fluctuations on mortality rates. Furthermore, how the inclusion of the new factor impacts on actuarial pricing. First, we focus on the relationship between trends in mortality and trends in temperature change (as a proxy) using annual data and for speci ed (warm and cold) periods during the year in the United Kingdom. A thoughtful statistical analysis is implemented and a new stochastic, central mortality rate model is proposed. The new model encompasses the good features of the Lee and Carter (1992) model and its recent extensions, and for the very rst time includes an exogenous factor which is a temperature-related factor. The temperature-related model (TRM) is shown to provide a significantly better fitting performance and more interpretable forecasts. Next, we look at the impact of uncertainty on the various parameters involved in the TRM model is examined. We demonstrate a number of ways to quantify model risk in the estimation of the temperature-related parameters, the choice of the forecasting methodology, the structures of actuarial products chosen (e.g., annuity, endowment and life insurance), the interest rate, and the actuarial reserve. Finally, we extend a previous study into excess deaths as a result of climate change to also investigate the impact of economic changes using annual data for Australia, France, Germany, Japan and the United Kingdom. A new stochastic mortality model is proposed which extends the Lee-Carter model and recent extensions by including an additional economic factor alongside a temperature-related term. This model is shown to provide better fitting and forecasting results.
Supervisor: Pantelous, Athanasios ; Boado-Penas, María del Carmen Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral