Description: This presentation explores the applicability of multiple population versions of the Lee-Carter model in the modelling of mortality by cause of death and socio-economic stratification.

Description: This is a paper from the session on Mortality Projection and Cause of Death at the January 15-18, 2023, 2023 Living to 100 Symposium in Orlando, Florida.

Description: We develop a model based on causal mortality in order to better understand inequalities in life expectancy across socioeconomic circumstances.

Description: In this session, panelists discuss the rationale behind aging research. They will explore recent demographic and biological insights. They will then explore when those breakthroughs could happen, what would their impact be on our understanding of mortality and mortality rates and the effect on different groups. Finally, it will be a chance to have your questions answered by that eminent set of panelists.

Description: We develop a model based on causal mortality in order to better understand inequalities in life expectancy across socioeconomic circumstances.

Description: The study identifies significant U.S. mortality improvement/deterioration trends since 1959 including, but not limited to, those described in the SOA report, Components of Historical Mortality Improvement, using cause-of-death and other relevant data sources to quantify the likely degree of causality.

Description: This is A Value-Based Longevity Index for Hedging Retirement Income Portfolios abstract authored by Jonathan Ziveyi, Kevin Krahe, Michael Sherris, Andres M Villegas for Session 1A of the January 13-15, 2020 Living to 100 Symposium in Orlando, Florida.

Description: The study identifies significant U.S. mortality improvement/deterioration trends since 1959 including, but not limited to, those described in the SOA report, Components of Historical Mortality Improvement, using cause-of-death and other relevant data sources to quantify the likely degree of causality.

Description: This article proposes a framework for estimating mortality improvement models and analyzing the parameter uncertainty in such models.

Description: In this session, attendees will learn to model historical mortality rates and to forecast their possible future scenarios, using a freely available and well-tested toolkit written in open source R. The core of the toolkit is implemented in the R package StMoMo (https://CRAN.R-project.org/package=StMoMo) and enables a practitioner to derive best estimate and measurements of uncertainty using academically robust demographic and actuarial mortality projection models.