Robert H. Wade is a Professor of Political Economy, London School of Economics and a winner of the Leontief Prize in Economics for 2008. His “Governing the Market” won Best Book in Political Economy from the American Political Science Association. Originally published at Triple Crisis.
It is by now generally accepted that the sharp rise in income and wealth inequality in the US and much of Western Europe over the 1990s and 2000s was one of the bulldozer forces behind the rise in financial fragility. And it has long been accepted that the Gini coefficient is the workhorse measure of inequality. But it is not generally recognized that the coefficient is normally defined in a way which biases the measure in a downward direction, making inequality seem less large than another version of the coefficient would suggest. By this alternative measure inequality is much higher than is generally thought. The standard measure is misleading us into thinking that economic growth is more “inclusive’ than it is.
Recall that the Gini coefficient is a number between zero and one that measures the degree of inequality in the distribution of income in a given society (named after an Italian statistician, Corrado Gini). The coefficient is zero for a society in which each member receives exactly the same income; it reaches its maximum value (bounded from above by 1.0) for a society in which one member receives all the income and the rest nothing.
As normally defined the Gini says that inequality remains constant—growth remains ‘inclusive’—if all individuals (or countries by average income) experience the same rate of growth, and rises only when upper incomes grow faster than lower incomes. So inequality remains constant if a two person (or two country) distribution x = (10, 40) becomes y = (20, 80). Yet the income gap has grown from 10 to 40.
It is at least as plausible to say that inequality remains constant—growth remains inclusive—when all individuals (countries) experience the same absolute addition to their incomes; say from x = (10, 40) to y* = (20, 50). If upper income individuals (countries) experience bigger absolute additions, inequality increases, and growth is not inclusive.
The normal Gini could be called the Relative Gini. The Gini based on absolute changes could be called the Absolute Gini—defined as the Relative Gini multiplied by the mean income. In the above illustration, the Relative Gini for both distributions is the same, at 0.3. But as mean income doubles from 25 to 50 in the transition from x to y, the Absolute Gini doubles, from 7.5 to 15.0.
The Absolute Gini typically rises much more frequently and by much more than than the Relative Gini, and its use would make ‘income inequality’ into a more salient political issue. For obvious reasons, the Relative Gini could be called a ‘rightist’ measure, and the Absolute Gini a ‘leftist’ measure (Kolm 1976a and 1976b).
Economists’ long-standing nonchalance about income inequality is reflected in the fact that the Absolute Gini is rarely used in empirical work. Its unpopularity also reflects the fact that cross-country comparisons of the Absolute Gini are more complicated than for the Relative Gini, because the former depends on the mean of each distribution. This requires that we convert incomes into the same currency (for example, to compare absolute inequality in India with that in the US we have to convert the two means and income distributions either into rupees or into dollars). And to perform comparisons across time we also need to correct for inflation. The choice of appropriate exchange rates and price deflators becomes crucial for making reliable comparisons of absolute inequality.
These inconveniences have often been held up as justification for sticking with relative measures of inequality. But as Kolm explains, ‘these problems are exactly the same ones which are traditionally encountered in the comparisons of national or per capita incomes…and they can be given the same traditional solutions. Anyway, convenience could not be an alibi for endorsing injustice’ (1976a: 419–20).
The bottom line is—all these technical complexities aside—that students of inequality should not ignore trends in absolute income gaps when making inequality comparisons, as most of the literature does.
Thanks to S. Subramanian, Madras Institute of Development Studies, for help on the Absolute Gini.