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Integrating Climate Covariates into Mortality Forecasting Models: A Feasibility Study for Longevity Risk Pricing
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Resumo(s)
This thesis investigates whether climate-related determinants—specifically extreme heat intensity—can be meaningfully incorporated into actuarial mortality modelling and whether such integration is empirically justified within the context of Southern European populations. Motivated by the growing intersection between environmental risk, demographic change, and longevity risk management, the study examines how exogenous climate variables may enter mortality-intensity frameworks traditionally structured around age, period, and cohort effects. At a conceptual level, the thesis formalizes the integration of a standardized heatanomaly indicator into a mortality modelling architecture consistent with the Generalized Age–Period–Cohort (GAPC) paradigm. At an empirical level, rather than estimating a fully stochastic climate-augmented GAPC model, the study implements a reduced-form Poisson Generalized Linear Model (GLM) panel specification. This approach allows the direct identification of the marginal association between regional annual heat anomalies and mortality rates at ages 65–85, while controlling for flexible age effects, region-specific heterogeneity, and common temporal shocks. Using harmonized mortality, exposure, and climate data for Southern European regions, the analysis finds that the estimated heat coefficients are generally small in magnitude and not consistently statistically significant under cluster-robust inference. Even where statistical significance is detected, the implied proportional change in annual mortality associated with a one-standard-deviation increase in heat intensity remains modest. Within the annual fixed-effects framework adopted, extreme heat anomalies do not emerge as dominant drivers of mortality dynamics. The contribution of the thesis lies in establishing a disciplined methodological bridge between climate indicators and actuarial mortality modelling. By linking demographic forecasting, environmental risk, and actuarial finance, the study offers an early step toward climate-aware longevity modelling systems.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Risk Analysis and Management
Palavras-chave
Climate Change Longevity Risk Human Health Mortality Models