It is well known that China’s role in reductions of global poverty and global inequality was crucial. For example, according to Chen and Ravallion, between 1981 and 2005, 98 percent (yes, ninety-eight percent) of reduction of global poverty, calculated using the poverty line $1 per person per day, was due to China. China’s role was similarly impressive when it comes to reduction of global inequality (income inequality between all individuals in the world).
Consider the dotted red line in Figure 1 below. It shows the evolution of global inequality without China. The line is rising up to 2003 and is mildly decreasing between 2003 and 2011 (our latest data). Now, consider the thick line in the same figure. It includes China: it is decreasing throughout and especially strongly in the last period. The conclusion is simple: without China, global inequality would have been broadly constant over the past 25 years, and in effect its 2011 level would have been higher than in 1988. With China, however, global inequality has decreased.
Moreover, note that until 2003, the inclusion of China would add to global inequality, but that more recently, the addition of China makes the level of global inequality less. The reason is simple: in 1988, China (proxied in this thought experiment by its mean income) was relatively poor and thus low in the global income distribution so the sum of income gaps between it and all the other countries (which goes into the construction of the Gini coefficient) was large. But as China became richer and moved closer to the mean of the global income distribution, the gaps between China and other countries become smaller. (These calculations are not simple: obviously China’s gap with respect to some poor countries that did not grow fast increased, but its gap with respect to the US for example, became less. On balance, the latter elements were stronger.)
Figure 1. Global inequality of inter-personal income, Gini 1988-2011
Most of the China effect (as is implicit in the discussion so far) comes from China’s catch up, that is from the movement in its mean income. This is confirmed if one looks at Figure 2 which shows the between component of global inequality, that is inequality calculated across population-weighted countries’ mean incomes. The two graphs look very similar: thus most of the global inequality reducing effects comes (as we would expect) from high average income growth of China, while some offset of that effect comes from rising inequality within China.
Figure 2. Inequality of population-weighted mean incomes in the world
Now, this undesirable “offset” (China adding to global inequality because it is becoming more unequal internally) is not shown directly in the graphs, but can be deduced. How? Look back at Figure 1. In 1988, global Gini with China was 4 Gini points greater than global Gini without China; in the same year, Gini calculated from the national means was 5 points higher with China than without it. In other words, China’s (then) relatively low domestic inequality reduced its contribution to global inequality. In 2011, however, things got reversed: if we look at the means only China’s reduces global inequality by 4 Gini points, but if we look at the entire world distribution it reduces its inequality by only 3 points. So the contribution of internal inequality in China moved from being minus 1 Gini point to being plus 1 Gini point. In other words, rising internal inequality in China added some 2 Gini points to global inequality. Luckily, however China’s fast growth more than compensated for that.
But the question can be asked next, what happens if China continues growing fast? Will its inequality reducing effects wane, and eventually reverse? The intuition is helpful here: if China were to become the richest country in the world, surely its further faster growth than the world mean, will be inequality-augmenting. Therefore, there must be a point when China becomes so rich that its further growth adds to global inequality. If we use Gini coefficient (G), that point occurs when China’s percentile rank, with all countries in the world ranked by their mean incomes, becomes greater than ½(G+1) (see Branko Milanovic "The Gini-type Functions: An Alternative Derivation", Bulletin of Economic Research, 1994). Note that this turning point depends also on the size of the Gini coefficient and is equal to the median (1/2) only when Gini is 0. Now, with global Gini around 0.7, the percentile rank at which countries begin to add to global inequality is around 0.85 (that is, only if they are mean-richer than 85% of other countries). China’s mean income is still far from that point. In 2011, it is around the 60th percentile with urban China around the 70th percentile and rural China around the 35th percentile. According to IMF’s World Economic Outlook’s projections (October 2015), in 2020, China’s mean income would be around the 65th global percentile. If urban-to-rural income ratio remains what it is now, urban mean will be situated around the 80th global percentile, similar to the positions of Estonia, Czech Republic and Poland while the rural mean will be much lower, around the 40th global percentile, close to Honduras and El Salvador. Thus, while growth in urban China’s income will, by 2020, be close to contributing to increasing global inequality, its rural mean will be far from that position. Perhaps nothing illustrates the political dangers of China’s internal inequality better than the fact that people with incomes of the Czech Republic and Honduras will have to coexist in the same country…“harmoniously”.