"United Around High Human Values"

Robert Clark, Associate Professor |

Department of Sociology |

University of Oklahoma |

Norman, OK 73019 |

robclark@ou.edu |

World Income Inequality


Typically, those who study income inequality analyze disparities that exist within countries or those that exist between them. For many years, these were distinct literatures that followed their own trajectories. Many studies describe (and attempt to explain) inequality trends that occur within individual societies (with more attention usually given to wealthy nations). Other studies examine cross-national variation in economic growth rates in order to ascertain whether poor countries are catching up to rich countries, and what factors have (or might) help them do so. More recently, though, a number of studies attempt to combine information on these two forms of inequality (within countries and between countries) in order to generate estimates on income inequality across the entire world (Clark 2011; Goesling 2001; Hung and Kucinskas 2011; Milanovic 2005, 2009; Sala-i-Martin 2006). While this line of research has stimulated much debate, a consensus appears to be emerging: world income inequality has declined slightly in recent years, with its larger between-country component now shrinking and its smaller within-country component now growing.

Overall, these trends are fairly new. Between the early 1800s and the mid-1900s, world income inequality grew rapidly. Western industrialization served as the catalyst for this inequality boom, producing large income disparities between countries, such that between-country inequality has come to explain a large majority of the world total (Bourguignon and Morrisson 2002). More recently, though, a number of countries in Asia (many of which are large and poor) began experiencing rapid economic growth, moving significant portions of the global population out of poverty. To be sure, this trend has been partially offset by the simultaneous rise in inequality within a number of these same nations, as well as many others in the West and Eastern Europe. Nevertheless, world income inequality stopped growing during most of the post-WWII era, and has now recently started to decline slightly, with incomes converging between nations and diverging within them.

Generating Estimates

To generate my own estimates of world income inequality, I used national income means (GDP PC based on purchasing power parity from the World Bank) to calculate the between-country component of total inequality, after which I estimated the dispersion around these means using national levels of income inequality (Gini scores based on net income from the Standardized World Income Inequality Database). Ultimately, 151 countries appear in my dataset, representing more than 95% of the world’s population, and covering the 1990 – 2008 period. I then divided each country into 100 income groups (producing a total of 15,100 income groups in my dataset) and assigned each group a unique income value based on two pieces of information: (1) that country’s GDP PC (which tells us the average income value across the 100 income groups), and (2) that country’s Gini coefficient (which tells us the dispersion around the mean for the 100 income groups).

Finally, I calculated a world-level Gini across these 15,100 income groups to represent world income inequality, repeating this exercise for every year between 1990 and 2008. The Gini is a popular measure of inequality, based on the location of the Lorenz curve within a triangular region. The triangular region is formed by (a) the x-axis, indicating the cumulative percent of the population, (b) the y-axis, indicating the cumulative percent of the good being distributed, and (c) the diagonal line, indicating a perfectly equitable distribution. The Gini refers to the ratio of (a) the area between the diagonal line of equality and the observed line of inequality (i.e., the Lorenz curve) to (b) the entire triangular region. The more the observed line departs from the diagonal line, the more the ratio increases in size. Thus, larger ratios indicate greater inequality, with the coefficient ranging from 0 (perfect equality) to 1 (perfect inequality).

What do the results show? First, world income inequality declined slightly during the time period, from a Gini of about .70 in 1990 to a Gini of about .65 in 2008. However, virtually all of the decline in inequality occurs during the post-2000 period, suggesting that income convergence is a relatively recent phenomenon. Second, when decomposing inequality into its between-country and within-country components, I found countervailing trends. While incomes are converging between countries, inequality is rising within most countries. Third, more than two-thirds of world income inequality is comprised of the between-country portion, suggesting that what happens to the disparities between countries drives most of the overall trend. Consequently, world income inequality is declining because between-country inequality is declining.

Interestingly, because income gaps are narrowing between countries and widening within them, we are seeing a “new geography” of inequality (Firebaugh 2003), in that nationality is not as good a predictor of one’s income today as it was in the past, while one’s class position within a society is increasingly important for determining welfare. Nevertheless, the country where one is born remains a crucial determinant for shaping an individual’s life chances, and migration remains one of the most effective ways to achieve income mobility (Korzeniewicz and Moran 2009). Consider the fact that over 90% of Africa lives in the bottom 70% of the world, while over 95% of the West lives in the top 30%. Thus, the two regions remain economically segregated from one another. In this way, geography remains quite salient.

Explaining the Trends

Economic globalization and the spread of industrialization remain popular explanations for the income convergence observed between rich and poor countries (Bhalla 2002; Firebaugh 2003; Firebaugh and Goesling 2004). Intuitively, if the North-South gap between countries originally resulted from Western industrialization, then it stands to reason that the spread of industrial production to the developing world explains why inequality between nations has started to reverse course. Globalization has facilitated this process, shifting industrial production away from rich countries via capital mobility and the liberalization of exchange policies. Moreover, globalization may be playing a direct role in producing income convergence by diffusing technology and advanced knowledge across the world (Sachs and Warner 1995).

However, while the spread of industrialization may help produce convergence between rich and poor countries, it may also stretch income distributions internally for all countries involved, in accordance with (a) the rising portion of the “Kuznets curve” among industrializing countries, and (b) the “Great U-Turn” among deindustrializing nations. Kuznets (1955) originally proposed that national levels of inequality will start to rise as countries begin to industrialize, and then begin to fall during late/advanced industrialization. Thus, inequality follows an inverted U-curve, or “Kuznets curve,” as it is now widely known. The initial stages of industrialization correspond to the rising portion of the curve for two reasons: (1) industrial wages are higher than agricultural wages, and (2) there is greater economic inequality within the industrial sector than the agricultural sector. Thus, the initial shift to industrial production is accompanied by rising inequality, as a small (but growing) number of people begin entering a higher-paying sector whose wages show greater dispersion around the mean. It is only until advanced industrialization that income inequality peaks and begins to dissipate, where agricultural workers constitute a small (and shrinking) portion of the workforce, thereby corresponding to the falling portion of the Kuznets curve. The amount of this decline will, of course, depend on (1) how much of a gap exists between industrial and agricultural wages (larger gaps portend a greater decline), and (2) how much of a difference there is between industrial wage inequality and agricultural wage inequality (larger differences portend a smaller decline). However, in recent decades, a number of deindustrializing economies in the advanced world have experienced an inequality uptick, now widely known as the Great U-Turn (Harrison and Bluestone 1988), whereby the transition to a service economy implies the loss of middle-income industrial occupations, as well as a decline in union density. Collectively, then, deindustrialization and the spread of industrial production to the developing world both anticipate rising inequality within a large number of countries across the globe, rich and poor alike.

Globalization may pose similar consequences. Global integration may draw countries closer together via economic mechanisms (e.g., the diffusion of technology) and political mechanisms (e.g., the homogenization of national policies that affect growth, thereby placing countries on similar economic trajectories). Conversely, integration also has the capacity to weaken labor by expanding the pool of competition across national borders, thereby widening disparities within countries (Beckfield 2006, 2009). In sum, similar to the spread of industrial production, globalization may have also played a role in producing countervailing effects on the between-country and within-country components of world income inequality.

Convergence, But…

While it is true that world income inequality has started to decline, several important qualifications are in order. First, the convergence trend (overall and between countries) is largely driven by one country: China. Although a number of developing countries in East Asia have experienced remarkable economic growth in recent years, China’s growth carries greater weight due to its enormous population. Thus, what happens to world inequality is heavily dependent on China’s trajectory. Without China in my sample, I find that world income inequality no longer declines (it actually increases very slightly), and the decline in between-country inequality is much smaller. More importantly, China’s role as an equalizing force in the world may be drawing to a close. Because of China’s dramatic growth, it is now a middle-income country whose economic success (should it continue) will eventually start contributing to between-country divergence, pulling its large population ever further from the world’s bottom half.

Parenthetically, while China’s rapid growth has been egalitarian at the global level, it has been stratifying at the national level. Several decades ago, about 85% of China lived on less than $2/day. Today, that percentage is closer to 25%. And while lifting a majority of the population out of absolute poverty is certainly a good thing, not everyone has been able to participate in this national success. As a result, this combination of winners and losers in China’s post-socialist transition means that income inequality within China is now much greater than it was before (Feng 2008). In fact, about two-thirds of the world’s countries now feature lower levels of inequality than China. Consequently, when we exclude China from our sample, it’s not just that the decline in between-country inequality evaporates, but the rise in within-country inequality also shrinks substantially.

A second qualification to the convergence narrative is that the degree of convergence in world income inequality should not overshadow the very high level of inequality that remains. A decline in the Gini by several points (from .70 to .65) does not qualify as a transformative event. By contrast, the current level of world income inequality is much more notable. The wealthiest 10% of the world owns about half of the world’s income, while the poorest half owns about 10%. If this distribution of income were replicated within a single country, it would represent one of the most stratified distributions on the planet. Very few countries (if any) feature a Gini score that is as large as the world’s (.649) simply because this level of inequality is difficult to sustain within a single nation-state in the modern era. At the world level, of course, the relative immobility of labor across political boundaries (combined with the high mobility of capital across the planet) allows for much higher levels of inequality. In sum, while scholars spend a great deal of time debating whether world income inequality has increased or declined by a few points, these short-term trends are greatly overshadowed by persistently high levels of inequality.

A final qualification, and related to the second point, is that the convergence we’ve seen in recent years is not very surprising in light of how much inequality there was to begin with. In a separate project, I use simulation data to demonstrate that large cross-national disparities will actually induce convergence when economic growth rates are randomly distributed across countries. In other words, when initial levels of inequality are high, countries should be converging. It is only when initial conditions approach parity that divergence becomes the more likely long-term outcome.

Consider a scenario in which one country owns virtually all the world’s income, while all other countries are nearly penniless. The wealthy country would have to monopolize practically all subsequent income growth across the world just to sustain this level of inequality, let alone elevate it higher. Anything short of this, and inequality will surely fall. Conversely, imagine a scenario in which all countries possess almost the exact same amount of wealth. Every country in the world would have to experience almost identical growth rates in order to prevent incomes from diverging. In sum, when initial levels of inequality are very high, the number of growth scenarios that will produce convergence grows larger (making this outcome more and more likely). Conversely, when initial levels of inequality are very low, the number of growth scenarios that will produce convergence shrinks considerably (making this outcome less and less likely).

So when is inequality sufficiently moderate, such that convergence is no more (and no less) likely than divergence? As it turns out, the point of transition occurs when the initial Gini is .384. Gini scores that are higher tend to induce convergence, while Gini scores that are lower tend to induce divergence.

What’s more amazing is that, when I apply these principles to real income data, I find that the point of transition occurs at almost the exact same point. Using GDP PC data from 127 countries covering the 1980 – 2010 period, I manipulate the initial level of cross-national inequality in GDP PC, while holding constant each country’s observed growth rate during the sample period. I find that the growth dynamics of GDP PC will produce either convergence or divergence based simply on the initial distribution of income. And the point of transition is remarkably similar to that found in the simulation data, whether I use population weights (Gini = .365) or not (Gini = .377). Thus, the recent convergence observed in GDP PC is primarily a function of large income gaps between countries and would probably not have materialized at more moderate levels of initial inequality.


In closing, we have witnessed an interesting change in the global distribution of income in recent decades. World income inequality is no longer rising, but has plateaued and even started to decline slightly. This trend is driven by a reduction in the massive disparities that exist between countries, which itself is a function of East Asia’s rapid economic ascendance, especially China. However, these trends are partially offset by rising inequality within many countries in the West, Eastern Europe, and East Asia. Moreover, as a middle-income country, China’s role as an equalizing force in the world is near the end. Thus, if China’s rapid economic growth continues alongside rising inequality within a large number of countries, the decline in world income inequality will have been both temporary and mild.


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Last modified: July 7, 2023