The Rise in Life Expectancy and Economic Growth in the 20th Century

Abstract

This research exploits conditional exogenous variation in mortality from the diffusion of modern medicine to study the effect of growth in life expectancy on the growth in GDP per capita. The empirical analysis establishes that countries that obtained higher growth rates of life expectancy due to this shock to mortality in the mid-twentieth century experienced lower growth rates of GDP per capita in the second half of the twentieth century. In addition, a negative relationship between initial level of life expectancy and the subsequent growth rate of GDP per capita is found.How did the unprecedented rise in life expectancy during the second half of the 20th century affect the economic development of nations? Relying on cross-country variation, the most studies find positive correlations between life expectancy and income. 1 In contrast to these studies, Acemoglu and Johnson (2007), henceforth AJ, exploit exogenous sources of within-country variations in life expectancy due to the diffusion of modern medicine from the 1950s onward and find a negative effect of the level of life expectancy on the level of GDP per capita.This article asks the question: How do the level and the growth rate of life expectancy affect the growth rate of GDP per capita? To answer this question, we extend the data set used by AJ with data on the variables of interest in 1900. These extra observations enable us to obtain growth rates of life expectancy and GDP per capita for two periods. Having two observations on growth rates allows us to control for unobserved country fixed effects which we show is crucial for the results. We follow AJ by using the potential treatment of 15 infectious diseases as an instrument for the growth rate of life expectancy. We show that this instrumental variable, which follows the same logic as a differences-in-differences estimator with continuous treatment, has strong predictive power for the growth rate of life expectancy even conditionally on initial life expectancy.The empirical analysis establishes that the growth rate of life expectancy had a negative impact on the growth rate of GDP per capita. This finding is robust to controlling for initial life expectancy and economic conditions as measured by log life demonstrate that the reverse mechanism, that is the influence of income on health, explains a large part of the positive cross-country correlations between life expectancy and GDP per capita. See also Weil (2014) for a comprehensive overview of the literature.

Urbanization and mortality decline

“…Bleakley, for an overview), but do not examine any macro‐economic effects on urbanization or economic growth. As both Packard () and Hansen and Lønstrup () have noted, these micro‐ and macro‐economic effects are not contradictory.…”

Modern Infectious Diseases: Macroeconomic Impacts and Policy Responses

“…These data, too, would need to be aggregated.4 Acemoglu andJohnson (2007) is an exception in that the authors find a negative effect of increasing life expectancy on economic growth. Their results change, however, when controlling for initial health and when splitting the sample into predemographic transition countries in which increasing life expectancy raises population growth and post-demographic transition countries in which increasing life expectancy reduces population growth (seeAghion et al, 2011;Cervellati and Sunde, 2011;Bloom et al, 2014;Hansen and Lønstrup, 2015;Klasing and Milionis, 2020). 5 A 10-percentage-point improvement in adult survival rates is approximately equal to going from the adult survival rate of India (82.2% in 2016; World Health Organization, 2020) to that of China (92%).…”

Fertility Transitions in Developing Countries: Convergence, Timing, and Causes

“…This 4 Dichlorodiphenyl trichloroethylene. 5 See also Hansen and Lønstrup (2015). index has been derived with the aim of measuring the basic potential transmission of the disease at regional level in the world.…”

“…Hence, a valid instrument has no direct relation with the dependent variable in the structural equation. The approach of several papers that analyze cross-country econometric models, and in particular of those dealing with the determinants of population growth (see, e.g., Acemoglu and Johnson, 2007;Cervellati and Sunde, 2011;Brueckner and Schwandt, 2015;Hansen and Lønstrup, 2015), relies on the estimation of models with one endogenous explanatory variable. These papers use IV whose validity and relevance have been carefully argued.…”