Thursday, April 25, 2024
4/25/2024
Project Summary The broad goals of this proposal are to increase understanding of the dynamics of human mortality change and to develop improved methods to forecast national and regional mortality. Better forecasts are central to the management and pricing of health and pension programs (including Social Security and Medicare in the US and elsewhere) and to the insurance industry (for life insurance, annuities, and longevity bonds). Most current stochastic mortality forecasts are based on work by Lee and Carter (LC) and technical and actuarial modifications of the LC. It is well known that mortality change follows a time-varying dynamic: in the long run (multi-decadal periods) there has been a shift from younger to older ages in the rate and significance of change; in the medium term (decade based) the LC method based on a dominant time signal and correlated age-change captures dynamics well; and finally in the short term (year based) particular age-related forces (disease epidemics, the opioid crisis) can cause notable year-on-year variation. In the LC methods, and here, these short term changes are treated as stochastic fluctuations and are analyzed in terms of their statistical properties. This project aims to improve analytical understanding of mortality dynamics in the medium and long terms. Preliminary work (by the proposers) has focused on the shape of old-age mortality, accurately described by the dynamics of percentiles of the human death distribution. Past the 25th, these percentiles have advanced at a nearly constant speed over the last five decades. The first specific aim is to extend this work to analyze trends in the shape and level of old-age mortality using percentiles. The preliminary results on old-age mortality suggest the analyses and extensions of LC: improvements to the forecast trend and error; analyses of the sensitivity of LC to noise at old ages and to the choice of base period. This project aims to analyze mortality change over long (many decades) time periods via multiple-timescale methods. In order to successfully apply LC methods more widely, this project will develop and test relational methods to produce life tables for countries with limited data in some years. Finally, this project aims to examine the nature of period relationships between income and mortality that are consistent with aggregate change.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).
