How to achieve inclusive growth? Income inequality and health in G20 countries

How to achieve inclusive growth? Income inequality and health in G20 Countries

The G20 leader’s summit took place in November in Istanbul, Turkey. The emphasis of Turkey’s G20 presidency this year is on “inclusive and robust global growth.” Turkey recognizes inequality as a major problem within countries as well as across national borders and stresses the need for reducing inequality in order to achieve mutual growth. In this article, I examine the relationship between income inequality and health among G20 countries. I find that as income inequality lessens, key health outcomes, such as child mortality and life expectancy, also improve substantially. This is an important finding that could provide guidance for ADB member economies in formulating their domestic policies to foster inclusive growth.

A substantive amount of academic research has been conducted on the link between income inequality and health. In a recent comprehensive review of the literature, Pickett and Wilkinson (2015) conclude that there exists overwhelming scientific evidence for a causal relationship between income inequality and health. In other words, wider income differences lead to worse health outcomes. Do we find evidence for such a relationship for the case of the G20 countries?

Why are income inequality and health correlated?

In order to answer this question, I focus on two major health indicators of health outcomes: child mortality and life expectancy. First, child mortality is a good indicator of the performance of health systems. Child mortality tends to be higher in countries where attendance by health care professionals at birth is low. Another leading cause of child mortality is infectious diseases, such as pneumonia, caused by a lack of hygiene or overcrowded living conditions. High child mortality can also indicate that young parents do not have access to life-saving drugs for their newborns. Second, we study life expectancy. Longevity is determined by genetic predisposition, but also by environmental and medical factors. These factors might be affected by income inequality. Income inequality can result in poor living conditions and social as well as psychological stress. In addition, higher income inequality can lead to lower income groups not having the financial means to pay for adequate or sufficient preventive or curative health care, or even cause them to forego health care in the worst cases. Finally, the relationship between individual income and health is not linear. A small rise in the income of poor households can have a greater impact on health than an equivalent rise in income for the rich (Pickett and Wilkinson, 2015).

Data on infant mortality (deaths per 1,000 births) and life expectancy (years, genders combined) by country are freely available from the World Bank’s World Development Indicators database. I used the year 2013 as the base year, then combined this data with the data on income inequality. Various sources exist for country-specific data on income inequality. I used the 2013 or most recent data published in the Standardized World Income Inequality Database (SWIID). All G20 countries were covered, except for Saudi Arabia for which I used an alternative data source (Alvaredo and Piketty 2014).

Strong correlation between child mortality and income inequality

Figure 1 show the correlation between the Gini coefficient and the infant mortality. The figure clearly illustrates how infant mortality rates fall as income distribution becomes more equal. Child mortality is particularly high in South Africa and Indonesia; two countries that also have highly unequal income distributions. Several European countries, together with Japan and the Republic of Korea, have the lowest rates of child mortality and low levels of income inequality. These findings thus corroborate earlier studies, such as that of Mayer and Sarin (2005).

Figure 1: Infant mortality and income inequality

Figure 1: Infant mortality and income inequality

PRC = People’s Republic of China.
Note: Data are for 2013 or the latest available year.
Source: Author.

Life expectancy tends to be higher in more equal societies

The relationship between life expectancy and income inequality shows a very similar close relationship, as shown in Figure 2. Lower income inequality is associated with higher life expectancy, as found in many other studies, for example by Moore (2006). Life expectancy is highest in Japan, which is also the country with the most equal income distribution. Life expectancy is obviously also determined by gross domestic product (GDP) per capita, as higher income typically allows for better health care. However, this relationship does not always hold. The United States has the highest GDP per capita in the G20 group, but only ranks ninth in terms of life expectancy. Its relatively unequal income distribution might explain at least part of this rather weak performance.

Figure 2: Life expectancy and income inequality

Figure 2: Life expectancy and income inequality

PRC = People’s Republic of China.
Note: Data are for 2013 or the latest available year.
Source: Author.

In summary, we have seen that for the G20, income inequality seems to be a major determinant of health outcomes. Achieving inclusive growth, as advocated by the Turkish G20 presidency, would thus bring considerable health benefits. A fall in child mortality, for example, is not only an obvious sign of progress for health, but also translates into a concrete economic benefit for society. Reducing inequality can thus indeed lead to mutually reinforcing outcomes: lowering inequality results in better health, which leads to more sustainable growth.

Alvaredo, Facundo, and Thomas Piketty. 2014. Measuring Top Incomes and Inequality in the Middle East: Data Limitations and Illustration with the Case of Egypt (July 2014). CEPR Discussion Paper No. DP10068. London: Centre for Economic Policy Research.
Mayer, Susan E., and Ankur Sarin. 2005. An Assessment of Some Mechanisms Linking Economic Inequality and Infant Mortality. Social Science & Medicine 60(3):439–660.
Moore, Spencer. 2006. Peripherality, Income Inequality, and Life Expectancy: Revisiting the Income Inequality Hypothesis. International Journal of Epidemiology 35(3):623–632.
Pickett, Kate E., and Richard G. Wilkinson. 2015. Income Inequality and Health: A Causal Review. Social Science & Medicine 128: 316–26.

Matthias Helble

About the Author

Matthias Helble is an Economist in the Asian Development Bank’s Economic Research and Regional Cooperation Department and an Adjunct Fellow at ADBI.

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