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On deck this week

Mon: New course: Street-Fighting Math

Tues: Paxil: What went wrong?

Wed: Pro-PACE, anti-PACE

Thurs: My namesake doesn’t seem to understand the principles of decision analysis

Fri: Risk aversion is a two-way street

Sat: A reanalysis of data from a Psychological Science paper

Sun: The devil really is in the details; or, You’ll be able to guess who I think are the good guys and who I think are the bad guys in this story, but I think it’s still worth telling because it provides some insight into how (some) scientists view statistics

One Comment

  1. urjulun says:

    Hey Andrew, this might grab your interest. In 2014, Greenwood, Jeremy, Nezih Guner, Georgi Kocharkov and Cezar Santos publish “Marry Your Like: Assortative Mating and Income Inequality”in American Economic Review: Papers & Proceedings, 104 (5): 348-353, claiming that assortative mating is a huge driver of the growth in inequality, massively raising the gini from 0.34 to 0.43. This gets very wide press (search for “assortative mating inequality”).
    ungated version of original: http://www.econstor.eu/bitstream/10419/93282/1/dp7895.pdf

    Turns out those numbers are wrong, after correcting errors they now think the difference is more like 0.42 to 0.43, or even 0.429 to 0.430. (“corrigendum”: http://pareto.uab.es/nguner/ggks_corrigendum.pdf). However, they point to a different paper which shows rising divorce rates among the poor “explain” a large share of inequality.

    Maybe this is just a cost of AER P&P which presumably has a lower quality standard than a regular journal — not that the media treats it this way. It just happens to be a very consequential issue at the center of a large amount of public debate, so incorrect “facts” like these can be harmful. I was a little bothered by the approach of the authors, in that the tone of their non-retraction appears to be “we were mostly right.” They reported a huge number when the true number is basically zero. The divorce question is a very different question and plausibly caused by inequality or other factors and hardly validates the initial erroneous analysis.

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