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

This thread demonstrates that a lot of academic writing that *looks* like utter nonsense is merely scholars dressing up a useful but mundane point with a ton of unnecessary jargon.


My theory is that the jargon creates an artificial barrier to entry. https://t.co/MqLyyppdHl

If one must spend years marinating one's brain in jargon to be perceived as an expert on a topic, it protects the status and earning power of people who study relatively easy topics.

In econ, a similar thing is accomplished by what recent Nobel prize winner Paul Romer calls "mathiness": https://t.co/DBCRRc8Mir

But mathiness and jargon are not quite the same...

Jargon usually doesn't force you to change the substance of your central point.

Mathiness often does. By forcing you to write your model in a way that's mathematically tractable (easy to work with), mathiness often impoverishes your understanding of how the world really works.

has written about this problem:

More from Society

Two things can be true at once:
1. There is an issue with hostility some academics have faced on some issues
2. Another academic who himself uses threats of legal action to bully colleagues into silence is not a good faith champion of the free speech cause


I have kept quiet about Matthew's recent outpourings on here but as my estwhile co-author has now seen fit to portray me as an enabler of oppression I think I have a right to reply. So I will.

I consider Matthew to be a colleague and a friend, and we had a longstanding agreement not to engage in disputes on twitter. I disagree with much in the article @UOzkirimli wrote on his research in @openDemocracy but I strongly support his right to express such critical views

I therefore find it outrageous that Matthew saw fit to bully @openDemocracy with legal threats, seeking it seems to stifle criticism of his own work. Such behaviour is simply wrong, and completely inconsistent with an academic commitment to free speech.

I am not embroiling myself in the various other cases Matt lists because, unlike him, I think attention to the detail matters and I don't have time to research each of these cases in detail.

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This is NONSENSE. The people who take photos with their books on instagram are known to be voracious readers who graciously take time to review books and recommend them to their followers. Part of their medium is to take elaborate, beautiful photos of books. Die mad, Guardian.


THEY DO READ THEM, YOU JUDGY, RACOON-PICKED TRASH BIN


If you come for Bookstagram, i will fight you.

In appreciation, here are some of my favourite bookstagrams of my books: (photos by lit_nerd37, mybookacademy, bookswrotemystory, and scorpio_books)
The entire discussion around Facebook’s disclosures of what happened in 2016 is very frustrating. No exec stopped any investigations, but there were a lot of heated discussions about what to publish and when.


In the spring and summer of 2016, as reported by the Times, activity we traced to GRU was reported to the FBI. This was the standard model of interaction companies used for nation-state attacks against likely US targeted.

In the Spring of 2017, after a deep dive into the Fake News phenomena, the security team wanted to publish an update that covered what we had learned. At this point, we didn’t have any advertising content or the big IRA cluster, but we did know about the GRU model.

This report when through dozens of edits as different equities were represented. I did not have any meetings with Sheryl on the paper, but I can’t speak to whether she was in the loop with my higher-ups.

In the end, the difficult question of attribution was settled by us pointing to the DNI report instead of saying Russia or GRU directly. In my pre-briefs with members of Congress, I made it clear that we believed this action was GRU.