It is certainly the case that income (and consumption) exhibits diminishing marginal utility. That is, a relatively small increase in income to a person living in poverty is very important to a poor person and family – no disagreement there. In fact, a small increase for a poor person lot produces more ‘happiness’ (or utility in ‘econ-speak’) than the same dollar increase for a rich person.

There is also no doubt that there has been significant progress in poverty eradication globally. As noted in Oxfam’s Inequality Report ‘Economy for the 1%’ – “Over the past 30 years, average annual GDP growth has been higher in low and middle-income countries than in richer ones. Average incomes in poorer countries are catching up with those in richer ones, and inequality between nations is falling. Emerging economy powerhouses are leading this catch-up process: China and India, for example, have driven much of the dramatic increase in the combined GDP of Asian countries. Between 1990 and 2011 economic growth in the region helped nearly a billion people to escape extreme poverty; 700 million in these two countries alone.”

However, the analysis in this post should be read in the context of understanding income inequality.

These ‘Growth Incidence Curves’ can be misleading because the percentage increases in income are measured against vastly different bases (denominators). I know it is a rather ‘technical’ point – but comparing percentage increases for variables with vastly different starting points can be misleading, as it gives the impression that the bottom decile, and top percentile have experienced similar income gains – when in fact the real income increase are vastly different. And, as I have noted in the post, Lakner and Milanovic rightly note this limitation, too.

It is for this reason that I argue that using a common denominator (such as average income in the starting year) would produce a more accurate comparison of percentile income growth rates. The other option is to focus on absolute (level) increases in income by percentile. Such measures will paint a more accurate picture regarding the extent to which income growth has contributed to the reduction in income inequality.

Hope that makes sense.

There is a very good reason why we don’t rely solely on absolute measures of inequality when thinking about income differences within and across countries: we get a lot of weird, counter-intuitive results. If you rank countries based on the absolute income version of the Palma Index, you find that Denmark is as unequal as South Africa. Most of us would think that is pretty silly because the median person in Denmark is doing a lot better than the median person in South Africa. http://aidthoughts.org/?p=4250

Of course, if changes in absolute levels of income are massive enough that might imply an increase in inequality in these dimensions, but that extra year of life expectancy or rung of the happiness ladder remains pretty elusive at the upper levels of the income distribution. We should definitely be worried absolute inequality in dimensions where there are not diminishing returns to income (political power, for instance) as well as the fact that global incomes are converging too slowly.

But the idea that the elephant graph is somehow wrong or misleading – or that the intellectual integrity of Lakner and Milanovic’s analysis has somehow been compromised – is plain daft. It’s perfectly ok to celebrate the massive gains the poorer-half of the global distribution has realized during those two decades AND be concerned about future convergence.

Here is a challenge: why focus on income at all? Why not focus on changes in the global distribution of different proxies of human welfare? I suspect it would run up against the unrelenting narrative that the world is getting worse all the time.