Does economic growth lead to greater inequality? Less inequality? About the same? It depends on other policies and underlying factors? An analysis from the staff of the IMF for provides an overview of these issues in “G-20 Background Note on the Impact of Growth on Inequality and Social Outcomes” (IMF, July 2024). (For those not familiar with the term “G-20,” it refers to a group of the 19 largest national economies in the world, with the European Union includes as a 20th member, and now the African Union as an additional member.)

I was intrigued to see that this note resurrects the “Kuznets curve” as a useful tool of analysis. For those not familiar with the term, the great economist Simon Kuznets proposed back in 1954 that inequality in a given country over time would follow an “inverted-U” pattern: that is, inequality would first rise as economic development started in certain locations and industries in a country, but then inequality would eventually decline as development became widespread. The theory held up reasonably well through the 1970s, but after that, inequality started rising in high-income countries around the world.

The G-20 report illustrates the pattern of recent decades this way. If you look at inequality within countries (blue line), it’s risen. If you look at inequality between countries, it’s fallen. Put these together, and overall global inequality has declined. For some intuition here, think about the rapid economic growth in China since the 1980s. This growth increased the within-country inequality in China, but decreased between-country inequality between China and high-income countries.

The report describes the current relationship between growth and inequality this way (citations and references to figures are omitted):

Although advanced economies, on average, have a lower level of inequality than emerging market and developing economies, any relationship between development—captured by output per capita—and inequality measured by the Palma ratio— the income share of the richest 10 percent of the population relative to the income share of the poorest 40 percent—is less clear over time, when the data is corrected for differences in average incomes between countries. For African Union members, a 10 percent increase in output per capita is associated with a 0.8 percent lower Palma ratio. For G20 advanced and emerging market economies, the relationship is instead positive—for example, for advanced economies, a 10 percent increase in output per capita is associated with a Palma Ratio that is about 3.5 percent higher. These findings are broadly consistent with a larger literature documenting a lack of any systematic correlation between growth and inequality change. In turn, this lack of a clear empirical relationship reflects the fact that growth and inequality can be driven by several distinct factors and, moreover, affect each other directly.

The report suggests that the Kuznets curve can serve as a useful framework for thinking about economic development and inequality. In the left-hand panel, the blue line is the classic Kuznets curve: that is, it first rises and then falls. The red dashed line for “policies” suggests that higher-income countries have ways of redistributing income that tend to reinforce the pattern of higher development leading to lower inequality (after taxes and transfers are taken into account).

However, the black line showing “other structural factors” suggests that there are factors, not accounted for in the Kuznets analysis back in the 1950s, which can tend to increase inequality as an economy grows. Two factors are mentioned. One is “skill-biased technical change,” which is the econo-speak way of saying that development in technology may in some cases tend to benefit those with certain skills. The other is a rise in globalization, which may in some cases tend to benefit those who are well-positioned to take advantage of it. Just to be clear, there is no implication here that all technology change or all global trade must necessarily increase inequality, only that the specific kinds of digital and information technology during the last few decades, and the form that globalization has taken over that time, have tended to have that effect in high-income countries.

The right-hand-side of the panel above first repeats the original Kuznets curve (solid blue line). The dashed blue line is a hypothetical one. If policy is directed at reducing inequality, then the Kuznets curve could bend more sharply, perhaps even in a way that would offset other structural economic factors pushing toward greater inequality.

The inequality-reducing policies here are not just about tax-and-transfer mechanisms, although that’s part of the picture. Another dimension is that in a world of skill-biased technical change, helping people get more skills through education and job training will spread the benefits of technical change more broadly. Similarly, helping workers get connected with the benefits of globalization would help limit an increase in inequality as well. Thinking about the structure of income support programs and labor markets, and whether they have incentives that may trap workers in lower-income jobs or unemployment, rather than helping them climb the ladder to better jobs, can also matter. A broad underlying insight back in the original Kuznets curve, before the days of computerization and globalization, is that inequality is reduced as economic growth spreads across places and industries.

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