Robert H. Wade

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 1976*a* and 1976*b*).

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’ (1976*a*: 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.

*Triple Crisis Welcomes Your Comments. Please Share Your Thoughts Below.*

[…] 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. […]

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As always, Prof. Robert Wade gives us a clear snapshot of an issue that has long gone under the radar screen and deserves the full attention of scholars and practitioners who care about reducing social inequality. I stumbled into this article after discovering that Brazil’s absolute inequality had actually increased while the relative inequality had decreased in the 2000s. Till then, I had never read any comments in the press or in academic papers noting this important disjunction. Again, many thanks to Prof. Wade. Peace, Miguel Carter

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Suppose we have a society of three people with incomes of 3, 4 and 5. How do you calculate the New Gini of this society?

If the social product of this society grows and the proportions stay the same (so that the new distribution is, say, 6, 8, and 10), then the New Gini doubles, right? The New Gini is thus not bounded by 1, but rather can increase beyond any limit.

In order to compare, in terms of the New Gini, the inequality in two different societies — existing perhaps at different times — one would need to have a conversion rate for the currencies, presumably based on purchasing power.

I think the New Gini would be proportional to the average economic (income or wealth) difference between two members of the population (measured as a currency amount).

And the anchoring of the scale would be purely conventional (arbitrary). You would call some arbitrarily chosen level of inequality “1” and would then calculate any other New Gini value by reference to this anchor.

[…] Robert Wade argues that this is a highly misleading measurement, as it obscures the true extent of inequality. We should be using the absolute Gini index, he […]

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