1/OK, data mystery time.

This New York Times feature shows China with a Gini Index of less than 30, which would make it more equal than Canada, France, or the Netherlands. https://t.co/g3Sv6DZTDE

That's weird. Income inequality in China is legendary.

Let's check this number.

2/The New York Times cites the World Bank's recent report, "Fair Progress? Economic Mobility across Generations Around the World".

The report is available here: https://t.co/mrvWz1IzIe
3/The World Bank report has a graph in which it appears to show the same value for China's Gini - under 0.3.

The graph cites the World Development Indicators as its source for the income inequality data.
4/The World Development Indicators are available at the World Bank's website.

Here's the Gini index: https://t.co/MvylQzpX6A

It looks as if the latest estimate for China's Gini is 42.2.

That estimate is from 2012.
5/A Gini of 42.2 would put China in the same neighborhood as the U.S., whose Gini was estimated at 41 in 2013.

I can't find the <30 number anywhere. The only other estimate in the tables for China is from 2008, when it was estimated at 42.8.
6/FRED, which gets its Gini estimates from the World Bank, shows the same numbers: https://t.co/1y911qazo9

Everyone except the "Fair Progress?" report, and the New York Times feature, seems to agree that the World Bank's most recent estimate of China's Gini is 42.2.
7/It appears that China's own estimate of its Gini was 46.5 in 2016: https://t.co/dG58kH3LiS
8/So where the heck is the "Fair Progress?" report getting its super-low China Gini number? It seems like it's NOT from the World Bank's World Development Indicators, which is what the report cites.
9/I notice that in the "Fair Progress?" report cited by the NYT, the U.S. Gini is also a bit fishy. It's less than 40, when the World Development Indicators say it's a bit over 40.
10/The only other source the "Fair Progress?" report cites is the World Bank's Global Database on Intergenerational Mobility: https://t.co/95RnPYxMsB

But the GDIM doesn't have income GINIs. So that can't be where these weird numbers were from (unless the data was mislabeled).
11/Anyway I've been searching high and low for where the "Fair Progress?" report and the NYT got these weird Gini numbers, and I just can't find it. If anyone else can help me find where this comes from, I'd appreciate it.
12/As of right now, it's looking like the New York Times used some bad data for an incredibly widely read report, thus convincing a ton of people (incorrectly) that China is a far more economically equal place than the United States.

https://t.co/vmzz57YeFf
13/But if someone finds a reliable source for these Gini numbers, then please let me know!

(end...for now)
14/UPDATE: The mystery has been solved! https://t.co/Qw9aB7Qg9D

The Gini number the NYT used was from the 1980s. It was not labeled as such.
15/The people who wrote the New York Times story appeared not to realize this. Here's the caption and graph from their piece:
16/The NYT seems to have just made a mistake, and should change the text and the graph to reflect that these numbers are from the 1980s, not current.

(end)

More from Noah Smith

Today's @bopinion post is about how poor countries started catching up to rich ones.

It looks like decolonization just took a few decades to start

Basic econ theory says poor countries should grow faster than rich ones.

But for much of the Industrial Revolution, the opposite happened.
https://t.co/JjjVtWzz5c

Why? Probably because the first countries to discover industrial technologies used them to conquer the others!

But then colonial empires went away. And yet still, for the next 30 years or so, poor countries fell further behind rich ones.
https://t.co/hilDvv0IQV

Why??

Possible reasons:
1. Bad institutions (dictators, communism, autarkic trade regimes)
2. Civil wars
3. Lack of education

But then, starting in the 80s (for China) and the 90s (for India and Indonesia), some of the biggest poor countries got their acts together and started to catch up!


Global inequality began to fall.

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The article is, at heart, deeply weird, even essentialist. Here, for example, is the claim that proposing climate engineering is a "man" thing. Also a "man" thing: attempting to get distance from a topic, approaching it in a disinterested fashion.


Also a "man" thing—physical courage. (I guess, not quite: physical courage "co-constitutes" masculinist glaciology along with nationalism and colonialism.)


There's criticism of a New York Times article that talks about glaciology adventures, which makes a similar point.


At the heart of this chunk is the claim that glaciology excludes women because of a narrative of scientific objectivity and physical adventure. This is a strong claim! It's not enough to say, hey, sure, sounds good. Is it true?
A brief analysis and comparison of the CSS for Twitter's PWA vs Twitter's legacy desktop website. The difference is dramatic and I'll touch on some reasons why.

Legacy site *downloads* ~630 KB CSS per theme and writing direction.

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44 media queries
36 unique colors
50 unique background colors
46 unique font sizes
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https://t.co/qyl4Bt1i5x


PWA *incrementally generates* ~30 KB CSS that handles all themes and writing directions.

735 rules
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730 unique declarations
0 media queries
11 unique colors
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The legacy site's CSS is what happens when hundreds of people directly write CSS over many years. Specificity wars, redundancy, a house of cards that can't be fixed. The result is extremely inefficient and error-prone styling that punishes users and developers.

The PWA's CSS is generated on-demand by a JS framework that manages styles and outputs "atomic CSS". The framework can enforce strict constraints and perform optimisations, which is why the CSS is so much smaller and safer. Style conflicts and unbounded CSS growth are avoided.