Description: The widening gap in life span between high- and low-income Americans may be eroding the progressivity of Social Security retirement benefits. Differential longevity trends have had the effect of raising lifetime benefits for high earners but not for low earners. Social Security’s long-term financial problems result in part from an increase in average life expectancy driven by wealthier people living longer, and, thereby, collecting more benefits. Policymakers should not use funding shortfalls attributable to these trends as an excuse to cut monthly benefits alike for those who have gained (high earners) and for those who haven’t (low earners).

Description: This article discusses the risk mix related mathematical rationale for national average ACA premium rates dropping for the first time in 2019.

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: 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: "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: "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: Actuaries have the business acumen, problem-solving capabilities, and technical skills to develop innovative and data-driven solutions in the social insurance space. It is time we expand our scope and embrace an increased role in making a positive impact within the health care ecosystem. The primary focus of this paper is on social insurance programs dedicated to the most vulnerable population: low-income families accessing care through Medicaid. While there are numerous challenges that require other subject matter experts to take the lead, this article highlights topics where actuaries can be key players in developing and implementing tangible solutions to improve the care for the most vulnerable. Issues and solutions in this paper focus on the following three areas: 1. Access to appropriate care, 2. continuity of care, and 3. social determinants of health.

Description: The article first tries to determine a consensus view of what social security should accomplish and then tries to measure how well the current level of benefits succeeds in meeting these goals. Assessing benefit adequacy is an essential element in putting the overall program on a sound financing footing.

Description: Discover an introduction to decomposing differences in life expectancy by age and cause of death. Take a look into demographic techniques that decompose life expectancies at birth and older ages into the portions contributed by later age groups and causes of death-. These have been in existence for some time and provide a convenient device for analyzing mortality change over time as well as differences between sexes, countries, and ethnic groups. The methods will be described and illustrated by spreadsheet examples.

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"