CONCLUSION

Rising top income shares in many countries have pushed inequality up the public agenda, while globalization has given this concern a global reach: people no longer compare their lot only to those within their own country.

A number of studies have estimated the global distribution of income using a variety of data and methods. Recent advances in data collection have provided us with a much more detailed and accurate view of the global distribution of income than was possible even a decade ago. Household surveys now cover the vast majority of the population of the world, whereas intercountry real income comparisons have been greatly improved with the 2005 round of the ICP. This chapter has also highlighted and used the additional information provided by the growing database of top incomes from tax records. Because survey data typically underestimate or underreport the incomes of the very rich, we have estimated global inequality by appending top income data to the available survey data.

This chapter has described the conceptual foundations of the analysis of the global distribution of income, the confusions that can arise by conflating different concepts of that distribution, and the divergent inequality trends that they can display. Its main focus was the global interpersonal distribution of income, or the concept 3 global distri­bution. Implicitly this analysis assumes a cosmopolitan symmetric social welfare function, according to which the country or location of an individual in the world is irrelevant.

Our calculations show that when the global interpersonal distribution of income is estimated through household survey data without top incomes, inequality in this distribu­tion is very high but remains virtually unchanged from 1988 to 2005.

We argued that the method used in all of these estimates, which take household incomes directly from surveys, was preferable to the method of “scaling” within-country distributions to NA means. Moreover, we argued that if one were to scale in such a way, then HFCE would be preferable to GDP. Bourguignon (2011) scaled within-country distributions to per capita GDP and found a substantial decline in the global Gini coef­ficient during 1989—2006, which we also find when we use HFCE. However, we find that the divergence in global inequality estimated using HFCE-means and survey-means is due to a reduced coverage of HFCE data relative to survey data in the first year, 1988, and to the sharp divergence between the survey and HFCE means in India in particular.

When we append data on top incomes to the survey distributions, including imputed incomes for countries without such data, we find that inequality is higher, and there is some indication of an increase in global inequality. In this case the Gini, which is less sensitive to inequality at the top end of the distribution, remains virtually unchanged over the period, at a higher level of 0.722 to 0.735. But MLD and Theil T increase over the period—MLD only slightly from 1.136 to 1.156, and Theil T from 1.114 to 1.188. Given the diverse sources of potential error in estimates of the global distribution of income, these changes may not be statistically significant. A larger proportional rise occurs in the income share of the top percentile—from 17.3% to 20.7%. Thus the increase in estimated global inequality over time with top income data added appears to be driven by the rising income share of the top percentile in the global distribution.

Inequality in the global distribution can be decomposed into within-country and between-country components using decomposable inequality measures. We find that between-country inequality declined modestly during 1988—2005, whereas within- country inequality increased substantially. Between-country inequality is the larger com­ponent of global inequality, comprising 64—81% of overall inequality, depending on the inequality measure (MLD or Theil T) and year. Nevertheless, even if between-country inequality were eliminated, global inequality would remain at about the same level as in a high-inequality country such as China.

Although the extent to which global inequality has risen depends on the measure used, global poverty has declined substantially in recent decades. Given that inequality within countries has tended to rise, this decline has been driven by aggregate growth in low- and middle-income countries. It does not follow, however, that continued aggregate growth is the only way to continue to reduce global poverty. Redistribution of income within countries—by checking or reversing the rise in within-country inequality—could also make a significant contribution to the reduction of global poverty.

ACKNOWLEDGMENTS

We are very grateful to the editors, Tony Atkinson and Francois Bourguignon, for their detailed comments, and to Branko Milanovic for discussions regarding data. For helpful comments, we would also like to thank Angus Deaton and participants of the “Income Distribution Handbook Conference” at the Paris School of Economics in April 2013.

APPENDIX. ESTIMATES OF GLOBAL INEQUALITY BASED ON THE COMMON SAMPLE OVER TIME

The common sample over time for which we have both survey and PPP data in all five benchmark years comprises 67 countries.

Table 11.A1 Country and population coverage of common sample over time

Source: Authors' calculations.

Table 11.A2 Global inequality with and without top incomes, 1988-2005, for common sample over time

With top incomes

Without top incomes

Source: Authors' calculations.

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