Measuring Wealth Inequality

Written by: Stephen Hsu

Primary Source: Information Processing

 

Recent increases in wealth inequality mainly due to top 0.01%, not top 1%? See this article (The Atlantic) and also here.

The method used to obtain these results is not without uncertainties. From these slides by Saez and Zucman. (Using flows to estimate accumulations.)

We develop a new technique to estimate the distribution of wealth

We capitalize income tax returns

Use IRS data on individual dividends, interest, rents…
Compute rates of return by asset class (Flow of Funds / NIPA)
Combine income and rates of return to obtain wealth

The capitalization method works for foundations
For which we observe both income and wealth

See also Inside the 1 percent:

Net worth distribution within the population of top wealth holders (assets > $2M; about top 1% of adult population): having $10M puts you in the 90th percentile (so, top 0.1% of total population) and $50M puts you in the 99th percentile (top 0.01% of total population).

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Stephen Hsu
Stephen Hsu is vice president for Research and Graduate Studies at Michigan State University. He also serves as scientific adviser to BGI (formerly Beijing Genomics Institute) and as a member of its Cognitive Genomics Lab. Hsu’s primary work has been in applications of quantum field theory, particularly to problems in quantum chromodynamics, dark energy, black holes, entropy bounds, and particle physics beyond the standard model. He has also made contributions to genomics and bioinformatics, the theory of modern finance, and in encryption and information security. Founder of two Silicon Valley companies—SafeWeb, a pioneer in SSL VPN (Secure Sockets Layer Virtual Private Networks) appliances, which was acquired by Symantec in 2003, and Robot Genius Inc., which developed anti-malware technologies—Hsu has given invited research seminars and colloquia at leading research universities and laboratories around the world.
Stephen Hsu

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