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.

Public Health Relevance

This proposal aims to increase understanding of human mortality change and to develop improved methods to forecast national and regional mortality. Both are central to the management and pricing of health, pension and insurance products and programs.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21AG061639-01
Application #
9649566
Study Section
Social Sciences and Population Studies A Study Section (SSPA)
Program Officer
Karraker, Amelia Wilkes
Project Start
2019-01-01
Project End
2020-11-30
Budget Start
2019-01-01
Budget End
2019-11-30
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Stanford University
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304