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

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.In a seminal work, Preston (1975) outlined the nonlinear relationship between a country's income levels and the expected lifespan of its citizens. Since then labeled the "Preston curve," the hypothesis states that poor countries enjoy a substantial increase in life expectancy when they grow, whereas this effect diminishes, yet remains positive, for richer countries. Recently, however, Preston (2007) himself has questioned this relationship, arguing that GDP per capita may at times explain no more than 16 percent of the variation in life expectancy. Similarly, Spence and Lewis (2009) argue that the Preston curve "may not hold within countries over time" and the unavailability of long-run data to test the Preston curve has been lamented (also see Leon, 2007;Mackenbach, 2007).

Certified Coronavirus Immunity as a Resource and Strategy to Cope with Pandemic Costs

“…There is, for example, strong evidence that banking crises also lead to major, widespread, and lasting psychological losses (Montagnoli and Moro 2018). Furthermore, a strong economy has always been closely linked to the health of its citizens and their life expectancy (Jetter, Laudage, and Stadelmann 2019). Populations with poor health are not very productive, and highly productive populations have good health.…”

Why do some countries do better or worse in life expectancy relative to income? An analysis of Brazil, Ethiopia, and the United States of America

“…These extreme health inequities partly reflect wealth inequities between countries. Generally, wealthier countries have a higher average life expectancy than poorer countries [ 2 – 4 ], which can be argued to be achieved through higher standards of living, more effective health systems, and more resources invested in determinants of health (e.g. sanitation, housing, education) [ 5 ].…”

Developing country

“…[8] People in developing countries usually have a lower life expectancy than people in developed countries, reflecting both lower income levels and poorer public health. [9][10] [11] The burden of infectious diseases, [12] maternal mortality, [13][14] child mortality [15] and infant mortality [16][17] are typically substantially higher in those countries. Developing countries also have less access to medical health services generally, [75] and are less likely to have the resources to purchase, produce and administer vaccines, even though vaccine equity worldwide is important to combatting pandemics, such as the COVID-19 pandemic.…”