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The Intimate Link Between Income Levels and Life Expectancy: Global Evidence from 213 Years*

2019/04/23 by Michael Jetter, Sabine Laudage, David Stadelmann · 1 citation
Health Professions · Economics, Econometrics and Finance · Social Sciences · #Global Health Care Issues #Economic Growth and Productivity #Insurance, Mortality, Demography, Risk Management #Life expectancy #Panel data #Proxy (statistics) #Quantile regression #Demographic economics #Per capita income #Economics #Per capita #Instrumental variable #Causality (physics) #Demography #Econometrics #Population #Statistics #Sociology

paper · doi:10.1111/ssqu.12638

openalex publication_date 2019/04/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

Objectives What is the main driver of life expectancy across societies and over time? This study aims to document a systematic and quantitatively sizeable relationship between income levels and life expectancy. Method A panel data set of 197 countries over 213 years is analyzed with different regression methods. Robustness tests are provided. Results By itself, GDP per capita explains more than 64 percent of the variation in life expectancy. The Preston curve prevails even when accounting for country‐ and time‐fixed effects, country‐specific time trends, and alternative explanatory variables such as health‐care expenditure, malaria prevalence, or political institutions. If anything, this link has become stronger over recent decades when data quality has improved. Results from instrumental variable estimations suggest this finding to be largely unaffected by reverse causality. Quantile regression results suggest the relationship between income and life expectancy to be persistent across different levels of life expectancy. Conclusion Income matters for life expectancy. If policymakers want to prolong people's lives, economic growth appears to be the predominant medicine.

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