5 papers · 1 filter
Climate-Driven Mortality Forecasting Using Deep Learning
Kenrick So, Karim Barigou, Jens Robben
Climate extremes have become important drivers of mortality, producing sudden spikes that traditional mortality models fail to predict. To address this gap, we propose a two-step m…
A penalized distributed lag non-linear Lee-Carter framework for regional weekly mortality forecasting
Jens Robben, Karim Barigou
Accurate forecasts of weekly mortality are essential for public health and the insurance industry. We develop a forecasting framework that extends the Lee-Carter model with age- an…
Mortality Modeling and Forecasting with the Actuaries Climate Index
Karim Barigou, Melanie Patten, Kenneth Q. Zhou
Climate change poses increasing challenges for mortality modeling and underscores the need to integrate climate-related variables into mortality forecasting. This study introduces…
Granular mortality modeling with temperature and epidemic shocks: a three-state regime-switching approach
Jens Robben, Karim Barigou, Torsten Kleinow
This paper develops a granular regime-switching framework to model mortality deviations from seasonal baseline trends driven by temperature and epidemic shocks. The framework featu…
Bayesian mortality modelling with pandemics: a vanishing jump approach
Julius Goes, Karim Barigou, Anne Leucht
This paper extends the Lee-Carter model for single- and multi-populations to account for pandemic jump effects of vanishing kind, allowing for a more comprehensive and accurate rep…