Assessing Longevity Inequality in the U.S.: What Can be Said about the Future?

18 Pages Posted: 2 Apr 2020

See all articles by Han Li

Han Li

Macquarie University

Rob Hyndman

Monash Business School

Date Written: December 31, 2019

Abstract

This paper investigates longevity inequality across U.S. states by modelling and forecasts mortality rates via a forecast reconciliation approach. Understanding the heterogeneity in state-level mortality experience is of fundamental importance, as a key challenge of multi-population mortality modeling is the curse of dimensionality, and the resulting complex dependence structures across sub-populations. Moreover, when projecting future mortality rates, it is important to ensure that the state-level forecasts are coherent with the national-level forecasts. We address these issues by first obtaining independent state-level forecasts based on classical stochastic mortality models, and then incorporating the dependence structure in the forecast reconciliation process. Both traditional bottom-up reconciliation and the cutting-edge trace minimization reconciliation methods are considered. Based on the U.S. total mortality data for the period 1969-2017, we project the 10-year-ahead mortality rates at both national-level and state-level up to 2027. We found that the geographical inequality in the longevity levels is likely to continue in the future, and the mortality improvement rates will tend to slow down in the coming decades.

Keywords: Mortality Modeling, Longevity, Heterogeneity, Forecast Reconciliation

JEL Classification: C53, I14

Suggested Citation

Li, Han and Hyndman, Rob, Assessing Longevity Inequality in the U.S.: What Can be Said about the Future? (December 31, 2019). Available at SSRN: https://ssrn.com/abstract=3550683 or http://dx.doi.org/10.2139/ssrn.3550683

Han Li (Contact Author)

Macquarie University ( email )

New South Wales 2109
Australia

Rob Hyndman

Monash Business School ( email )

Wellington Road
Clayton, Victoria 3168
Australia

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
66
Abstract Views
291
rank
363,230
PlumX Metrics