Description: "On the decomposition of mortality models into causes of death – Andrés M Villegas Ph.D – UNSW Australia, Madhavi Bajekal, Ph.D.,HONFIA, University of London, UK, Steven Haberman, Ph.D. – Bayes Business School, University of London, UK Forecasting cause-specific mortality rates using the insights from the cointegration analysis, Séverine Arnold, PhD, Viktoriya Glushko, Department of Actuarial Science, Faculty of Business and Economics (HEC Lausanne), University of Lausanne, Switzerland"

Description: "COVID-19 and excess mortality: an actuarial study – Camille Delbrouck, Aon Benfield, Belgium, Jennifer Alonso-García, Department of Mathematics, Université Libre de Bruxelles, Belgium, ARC Centre of Excellence in Population Ageing Research (CEPAR), UNSW Sydney, Australia Netspar, The Netherlands How did COVID-19 change the dependence structure across major causes of death – Han Li, Ph.D., Associate Professor, Centre for Actuarial Studies | Faculty of Business and Economics, The University of Melbourne, Victoria, Australia"

Description: "Demographic components of Future Potential Old-Age Support Ratios – Kirill Andreev, Ph.D., United Nations, Population Division, New York, Mila Andreeva, KAMA Consulting Effect of internal Migration on the Health of Taiwan’s Elderly People – Jack C. Yue, Ph.D., – National Chengchi University, Department of Statistics, Taipei, TaiwanPopulation Aging and Canada’s Social Contract: Covid-19 Catalyst for Change – Douglas Andrews, FSA, FCIA, Ph.D., Lori J. Curtis, Ph.D., – University of Waterloo"

Description: "Population Aging, Global Climate Change and Social Security – Sally Shen, Research Associate, Global Risk Institute, John A. Turner, Ph.D., Director, Pension PolicyClimate Change and Mortality Time for Actuaries to Pay Attention – Sam Gutterman. FSA, CERA, FCAS, FCA, HONFIA, MAAA"

Description: Navigate a perspective on the process of developing estimates and projections of mortality rates, based on a Living to 100 paper by the teacher. Discover the approach and considerations an actuary (or others) can take to develop a mortality rate assumption for five time periods. It will describe techniques to estimate historical mortality rates from which to project future mortality rates.

Description: "How long is long in longevity? – Jesús-Adrian Álvarez, Ph.D. - Danish Labour Market Supplementary Pension Fund (ATP), The Rate of Aging in humans is constant. New evidence – Marcus Ebeling, PhD., Research Group Mathematical and Actuarial Demography, Max Planck Institute for Demographic Research, Rostock, Germany, Department of Sociology and Demography, University of Rostock, Rostock, Germany; Roland Rau, Ph.D., Professor, Research Group Mathematical and Actuarial Demography, Max Planck Institute for Demographic Research, Rostock, Germany, C6 Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Håkan Malmström, Ph.D., C6 Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Anders Ahlbom, Ph.D., Professor Emeritus, Karen Modig, Ph.D., Associate Professor, C6 Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden Human Lifetimes: Finite But Not Necessarily Bounded – Fei Huang, PhD., School of Risk & Actuarial Studies, UNSW Sydney; Ross Maller, Ph.D., Emeritus Professor, Xu Ning, Ph.D., Research School of Finance, Actuarial Studies & Statistics, Australian National University, Brandon Milholland, Ph.D., IQVIA Plymouth Meeting, PA."

Description: Mortality Model Selection and Combination in RAlternative approaches for selecting mortality models and forecasting mortality have been proposed. The usual practice is to base mortality forecasts on a single mortality model selected using in-sample goodness-of-fit measures. However, cross-validation and other alternative out-of-sample measures are increasingly being used in model selection, and model combination methods are becoming a common alternative to using a single mortality model. Such methods combine predictions from multiple mortality models to reduce model choice uncertainty and improve forecast accuracy. Explore techniques to select and combine mortality models using the freely available open source R package CoMoMo (https://github.com/kessysalvatory/CoMoMo), which extends the widely used R package StMoMo (https://CRAN.R-project.org/package=StMoMo). We will use data for the USA and other countries to discuss and demonstrate four different model combination approaches including simple model averaging, Bayesian model averaging, model confidence set, and stacked regression ensembles.

Description: This article describes one of the keys to successful marketing in the current environment - build a relational database that will help the agent communicate with a client in an organized way, so that we can educate, inform, present choices and help these clients navigate their financial future. This article provides the elements of such a database.

Description: General Session

Description: Explore the National Academy of Medicine’s Global Roadmap for Healthy Longevity.AARP has been a primary sponsor of the Roadmap. The Roadmap defines Healthy Longevity as when years of good health approach the biological life span, with physical, cognitive, and social functioning that enables well-being and establishes 2050 as the target year to achieve this goal globally. This Roadmap establishes five overarching principles for healthy longevity.