Maya Forstater on Twitter: "Thanks. How does this drive the difference between the 'torso' of the elephant vs the flat back of the loch ness monster between the 50th and 75th percentiles? Where WID seems to disagree with the surveys https://t.co/dLTCIwSyz7… https://t.co/qAj1SRQ1b0"

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Justin Sandefur‏ @JustinSandefur 6 Apr 2018

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Replying to @BrinaSeidel @MForstater

Good point. Though... wouldn't this bias things in the opposite direction? (Lower growth in survey estimate in that range)

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Brina Seidel‏ @BrinaSeidel 6 Apr 2018

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Replying to @JustinSandefur @MForstater

Not really- WID's top income data is so detailed (0.001% of population) that the ultra-rich in any country, the type of people we think are missing from surveys, end up at the top of the global distribution.

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Brina Seidel‏ @BrinaSeidel 6 Apr 2018

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Replying to @BrinaSeidel @JustinSandefur @MForstater

So while we have the richest 10% of people from Cote d'Ivoire somewhere in the global middle, I'd bet WID has the richest 0.01% of people from CIV in the global top 1%. WID probably also has the 90-95th pctile of CIV in the global middle but they didn't experience crazy growth.

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Justin Sandefur‏ @JustinSandefur 6 Apr 2018

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Replying to @BrinaSeidel @MForstater

Just out of curiosity, do you know where the bottom of the top 1% in India and China (according to WID) fall in the global distribution?

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Brina Seidel‏ @BrinaSeidel 6 Apr 2018

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Replying to @JustinSandefur @MForstater

Mean income for p99.0 to p99.1 in 2013 was $316,020 for China and $1,334,763 for India in PPP. That puts the Chinese closest to the global p99.8 and the Indians closest to the global p99.97.

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Brina Seidel‏ @BrinaSeidel 6 Apr 2018

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Replying to @BrinaSeidel @JustinSandefur @MForstater

But I'm comparing country data from their API to global data from the WIR replication data and I'm not totally sure that's right given the regional aggregation process. Looking at the table above though their data has 22% (!) of the global top 1% as Asian.

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Justin Sandefur‏ @JustinSandefur 6 Apr 2018

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Replying to @BrinaSeidel @MForstater

Thanks. Ok, so to your original point, omission of the top 1% in the countries big enough to matter couldn't really be affecting the middle of that graph. So... I'm back to Maya's default bias in favor of trusting survey data more.

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Maya Forstater‏ @MForstater 8 Apr 2018

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Replying to @JustinSandefur @BrinaSeidel

Maybe this chart shows an elephant morphing into a loch ness monster? @wid_inequality has distributed nat accounts for individual countries in blue, red, green lines. Getting to yellow involves lots of merging & rescaling across regions @gabriel_zucman @ChancelLucas @BrankoMilanpic.twitter.com/ganEmur1X8

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Branko Milanovic‏ @BrankoMilan 8 Apr 2018

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Replying to @MForstater @JustinSandefur and

Informal sector is included in surveys. Most (I think practically all) of the difference btw WID and L-K data comes not from the top 1% but from the assumption on how are undistributed corporate profits allocated across the distribution.

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Lucas Chancel‏ @lucas_chancel 9 Apr 2018

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Replying to @BrankoMilan @MForstater and

Actually, it is the use of tax data at the top (rather than assumptions on undistributed profits) that explain the bulk of the difference between WID data and survey data, at least in China, India, Brazil. For details see for instance http://wir2018.wid.world/part-1.html (below box 1.1)

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Maya Forstater‏ @MForstater 9 Apr 2018

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Replying to @lucas_chancel @BrankoMilan and

Maya Forstater Retweeted Justin Sandefur

Thanks. How does this drive the difference between the 'torso' of the elephant vs the flat back of the loch ness monster between the 50th and 75th percentiles? Where WID seems to disagree with the surveyshttps://twitter.com/JustinSandefur/status/982258333221470209 …

Maya Forstater added,

Justin Sandefur @JustinSandefur

Trunk differences don't bother me -- we know surveys miss top incomes -- but the discrepancy between the 50th and 75th percentiles is still staggering, and depressing re our knowledge of global income distribution. https://twitter.com/MForstater/status/982192529691983873 …

3:29 AM - 9 Apr 2018

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