Twofish's Blog

February 13, 2007

The problem with China Gini coefficient statistics

Filed under: china, finance, law — twofish @ 5:31 pm

It’s interesting how the media moves from traffic accident to traffic accident. Last years story was on how China was getting polarized between rich and poor and how rural unrest was going to bring down the party. You don’t see those stories any more. The problem with news stories is that they start with a general framework and then try to fit information into that framework. So the framework you start with is the old Marxist idea of class revolution, and then evidence is fit within that framework.

Here is a paper that got me thinking….

Here is a revealing paragraph….

Visitors to China and India often report nearly opposite impressions of the two nations. India assaults one’s senses. People living in open squalors, the lack of sanitary facilities, and massive and sprawling slums in metropolises such as Mumbai and New Delhi easily give rise to the impression that is a very poor and unequal society. China induces the opposite reaction. Its urban space is sanitary and is largely free of grotesque manifestations of poverty, such as massive slums. It is not surprising that visitors to China leave the country with the impression that it is one of the most successful countries in tackling income inequality and that India has done the opposite.

The reality is almost exactly the opposite. The most widely used measure of income inequality is the Gini index, which ranges from zero — perfect equality — to 100 — perfect inequality. In 2001, China’s Gini index was 44.7; In India during the 1999-2000 period, the Gini index was 32.5.

This is an interesting paragraph since it basically says that if there is a conflict between the numbers and what you see, you should believe the numbers and forget about what you see.

But lets look a bit deeper, and try to figure out *why* there is this conflict. One interesting fact about China’s Gini coefficient is that it is almost completely a regional phenonmenon. The Gini coefficient for a particular province is rather small, you only get wide variations in Gini coefficients if you look *between* provinces. That is the reason why you see slums in India but not in China. 

Once you see that piece of the puzzle, then a lot of things make sense. The first is why economic reform causes the Gini coefficient to increase. It’s because some provinces are better placed to take advantage of economic growth than others. The second thing is why even with huge Gini coefficents, China seems more equal than Latin America or Africa. It’s the Bassla-Samuelson effect. People make a lot more money in Beijing than they do in Guangxi. People make a lot more money in New York City than they do in Beijing. But a lot of these costs are offset by the fact that the cost of living is higher. If you do things via purchase price parity, the difference is a lot less than they first appear.

Let me quote another section of Huang’s paper that doesn’t quite fit…

One is that in the 1990s and the early 2000s the incidents of unrest were relatively concentrated geographically. For example, Liaoning province experienced 9,559 incidents of unrests between 2000 and 2002. This was a large fraction of the publicized number of incidents — around 50,000 during this period. In many ways, the unrest in that province can be easily explained. Liaoning province was the bastion of socialism, and the SOEmreforms and poor performance have led to joblessness and income stagnation in that province. However, in the last two years, the geographic scope of unrests has widened substantially. Incidents of unrest were recorded not just in struggling provinces but also inprosperous provinces. Zhejiang, Guangdong, and Fujian have all witnessed large-scale protests. Even Shanghai is not immune.

The problem with this explanation is that Liaoning is not a struggling province.  It is in the rust belt, but it is also on the coast, which means that it’s actually one of the more prosperous provinces.  If you look at the spatial distribution of reported incidents they happen in the more prosperous provinces rather than in the less prosperous ones, and this works against the idea of growing class struggle.

So what is going on???

I’m not exactly sure.

But there is one lesson here and that is that things are complex.  The problem with news media reports is that they take a complex story and try to boil it down to one or two numbers.  This is a bad thing because to understand a situation, you shouldn’t look at one or two numbers but rather hundreds of numbers.  If you look at hundreds of numbers as the above paper does, things get more complex.  You have urban versus rural.  Different provinces.  Different macroregions.  Differences over time.  All of which leaves you more confused than before….

And confusion isn’t a bad thing.  As HL Mecklen once said, it’s not what you don’t know that will get you, it’s what you know that isn’t.  The problem with focusing on one number is that this leads to clarity, and clarity is sometimes a bad thing when the actual situation isn’t clear at all.


  1. Wow… what an insightful blog, unique among the riff-raff that usually populate the Internet. As much as I enjoyed my international trade class (and I really did), I never can remember all those theorems.

    Keep up the good work, and I look forward to reading and learning from you in the future.

    Comment by Joshua Xanadu — April 22, 2007 @ 4:10 am

  2. […]  I do think that one can make a judgement on development paths. For me personally, an economic development path is more desirable and healthier if it gave and increased the agency to the largest number of people.  This is not to say that China has done well on this.  It has many many problems, but it has done better than all other developing countries so far.     The following post also question China’s gini for different reasons. […]

    Pingback by China’s gini-coefficience: is China the most unequal country in the developing world? « voice of reason — October 30, 2009 @ 7:00 pm

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