Description: This fact sheet provides an overview of the Long-Term Care and Middle Market report.

Description: This article explores the possibility of using innovations from the financial markets to reduce some portion of the LTC risk and thus encourage the growth of the product.

Description: In this session, morbidity and life expectancy trends are discussed. In addition, a case study in R on how to model the uncertainty associated with incidence of disability, disabled and active deaths and other terminations is presented.

Description: Read the November 2020 issue of Long-Term Care News published by the Long-Term Care Insurance Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: As the topic of affordable long-term care (LTC) insurance comes into focus in political conversations, we often find ourselves thinking, “What is going to happen to the private LTC insurance industry going forward?” The need for LTC in the United States is not going away, especially as the population continues to age. With this in mind, this article explores three possible future paths for LTC insurance funding and the associated implications for the private LTC industry.

Description: Understanding How Families Search for Long-Term Services and Supports

Description: Table constructed from lifetime long-term care cost studies conducted by P.J. Eric Stallard, ASA, FCA, MAAA, Center for Demographic Studies, Duke University.

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: "Living to 100 in the time of COVID-19: A Study of Late –Life Mortality Trajectories, Leonid A. Gavrilov, Ph.D., Natalia S. Gavrilova, Ph.D., Academic Research Centers, NORC at the University of Chicago Swedish Mortality Does Not Decelerate in Recent Cohorts, or Does it? – Roland Rau, Ph. D., Professor, University of Rostock & Max Planck Institute for Demographic Research, Rostock, Germany; Marcus Ebeling, Ph.D., Karin Modig, Ph.D., Associate Professor, Anders Ahlbom, Ph.D., Professor Emeritus, Karolinska Institute, Stockholm Sweden; Kai Kaufhold, Aktuar DAV, Ad Res Advanced Reinsurance Services GmbH, Cologne, Germany; Annika Ziegler, Lukas Stake, Hochschule Koblenz & Ad Res, Germany"

Description: Discussant comments for the 2009 Housing Wealth monograph paper, “Home Equity and At-Need Annuities—A Dynamic Long-Term Care Funding Duo”. The author finds that the ideas discussed in this paper should stimulate more thinking about financial products and public sector programs and how they can better serve older homeowners.