to 513 (Hurun Report, 2015). Finally, account holdings leaked from a number of tax havens show considerable wealth in developing countries (ICIJ, 2016).

According to our analysis, global inequality as measured by the Gini index has declined very slightly between 1988 and 2008. As the solid line in Figure 1 shows, the global Gini index fell from 72.2% in 1988 to 70.5% in 2008, a fall of almost 2 percentage points which was particularly strong since 2003. Not surprisingly, global inequality is much higher than what is found within individual countries. For example, in 2008 the Gini index of South Africa, one of the most unequal countries, was 63%. The results are robust to using the same countries throughout, as shown by the dashed line in Figure 1.<sup>5</sup> But given the numerous margins of errors involved in these calculations, both sampling and non-sampling (e.g. PPP exchange rates) (Anand and Segal, 2015), it would be premature to claim that global inequality declined robustly. Furthermore, once we attempt to impute top incomes (Figure 1, dotted line), global inequality has remained almost unchanged over these 20 years, although the decline in the last five years remains.<sup>6</sup> Taken together this suggests that at the very least, there is no evidence pointing toward _increasing_ inequality at the global level. Newer data for 2011 finds that the downward trend is accelerating (Milanovic, 2016, p. 120). Although different methods and inequality measures disagree over the timing and size of the decline, the fall since the mid-2000s is robust across a number of sources.<sup>7</sup> Viewed over the long run, this is a remarkable development. Bourguignon and Morrisson (2002) find that global inequality rose steadily between 1820 and the 1990s, by some 15 percentage points. Therefore, as Bourguignon (2015) and Milanovic (2016) point out, global inequality has stabilized or even declined for the first time since the Industrial Revolution.

The decline in inequality has been driven by falling inequality between countries. Figure 2 decomposes global inequality into differences within and between countries. The total height of the bars shows total global inequality as measured by the GE(0) (or mean log deviation, Theil-L) inequality index.<sup>8</sup> The striped bars depict that part of total inequality that is due to differences within every country. The solid bars capture the contribution of differences in mean incomes across

> 5 The baseline results use the largest possible sample of countries in every year. A closely connected issue, which cannot be addressed, is the unavailability of surveys for some countries. This problem is most acute in the Middle East and the African continent. The affected countries account for around 5% of global GDP and 10% of global population.

> 6 Anand and Segal (2015) use a different approach to account for missing top incomes, which results in an upward adjustment to the level of the global Gini index that is approximately half of the difference presented in Figure 1. They assume that the household survey fails to capture the top 1%. They then append the top 1% income share either directly from tax record data or predict it from a cross-country regression that uses the survey-based top 10% share and the survey mean income. While their procedure also increases a country’s mean, this effect is smaller than the nationalaccounts-based adjustment in Lakner and Milanovic (2016) (shown in Figure 1). Regarding the time trend, Anand and Segal also find a fall in the most recent period (between 2002 and 2005 in their data), although the level remains marginally higher in 2005 than in 1988 (72.7% and 72.6%, respectively).

> 7 According to the review by Anand and Segal (2015), methodologies differ primarily in their (1) use of GDP per capita or average incomes from household surveys, (2) adjustments for differences between income and consumption surveys, and (3) PPP exchange rates. Bourguignon (2016), who rescales survey incomes to GDP per capita, finds a faster decline than what is presented in Figure 1, beginning in the early 1990s.

> 8 I use an alternative measure of inequality because the Gini index cannot be decomposed in this manner.

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