and reports on which inequality measures are included; on the nature of the individual welfare indicator for which inequality is calculated; and on whether various adjustments are made to the microdata. Panels B and C refer to the three databases in Groups 2 and 3, and include additional information on, _inter alia_ , the documentation of primary sources; on how multiple sources of information for the same country/year combination are treated during compilation; and on whether other secondary sources are also used as inputs, in addition to primary sources.

In terms of the choice of summary inequality measure, the Gini coefficient is the most common metric used to describe inequality but it is certainly not the only option. A good overview of inequality metrics can be found in Jenkins and Van Kerm (2009). CEPALSTAT, LIS, and SEDLAC all report the Gini Coefficient, the Theil Index, the Atkinson Index, and other statistics about income shares or decile ratios. WDI/PovcalNet reports both the Gini coefficient and income shares.

Summary inequality indicators are almost invariably computed from samples, rather than full populations, and are therefore subject to sampling error. It is good practice to report standard errors or confidence intervals for each estimate, as done by SEDLAC and sometimes by the IDD. CEPALSTAT and LIS’s Key Figures do not report them.

Arguably more fundamental is the choice of the individual welfare concept, for the distribution of which inequality is measured. CEPAL, IDD, LIS, and SEDLAC all focus on current income. WDI/ PovcalNet uses both income and consumption welfare concepts, depending on the country, and the secondary sources aggregate statistics regardless of welfare concept. WIID simply notes the welfare concept for each of its Gini Coefficients. ATG prioritizes measures of income inequality and SWIID’s reported Gini Coefficients are estimates of income inequality. However, it is unclear whether these choices were made because of a preference for income as a welfare concept or because of the preponderance of primary sources that use income as their welfare concept.

The prevalence of current income as the individual welfare indicator of choice is, to a large extent, a result of the fact that inequality indicators are disproportionately available in Europe and the Americas, where statistical agencies have typically preferred income to consumption as a measure of individual well-being. Conversely, in most of Asia and Africa, researchers tend to prefer measures of consumption expenditure to assess well-being. Arguably, these historical practices reflect sound judgment: In industrialized economies where most people earn wages from one or two sources, and where savings can be nontrivial, incomes may be both easier to collect accurately and more informative of total purchasing power. In predominantly agrarian economies, where an accurate computation of income would require complex valuations of many different types of output and the netting out of farm inputs, many have argued that income statistics are misleading. In addition, consumption expenditures may be argued to better approximate permanent incomes (at least for the bulk of the population, for whom bequests are rare). Nevertheless, the issue is far from settled, as the debate between Ravallion and Gornick et al. in the pages that follow illustrates.

Of course, whether income or consumption is used, there are a number of additional important decisions an analyst must make before an inequality index can be computed. Should the chosen welfare 9