Earlier today I spent some time shitting on this paper without a broader discussion of why I was doing so I shall hold forth on this matter now as I think it is revealing of the absolute state of empirical social science and microeconometrics in particularhttps://twitter.com/RRHDr/status/1295488617125687297 …
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generally when a model produces fantastical results you should feel good about discarding the model. and this is absolute insanity there are a million things that can go wrong in this kind of estimation and the approach used by the authors handles like . . . five of them
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this kind of cockup is the *norm* in reduced form microeconometrics it is remarkable only for being wildly unreasonable, and nevertheless making it through a paper-thin review process (by people whos careers are built on the same methods) because it produced the Correct result
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the authors are careful to run through a series of apotropaic tests to ensure that a few well-understood issues did not obtain in their model its thorough, people myself included spend years learning these Rituals its akin to making sure submarine screen doors are up to code
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if you complete the Ceremony it is extremely unlikely that anyone will bother observing that your results are absolutely cockamamie its econometrics-by-recipe "order the data in such a way, run all the standard tests, publish, gib tenure" no iota of reflection necessary
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This paper is so egregious that it knocked me awake If they'd claimed /using the same methods/ like "5% increase in mortality" I would have slept through it But--those methods would have been equally bad /had they produced a reasonable result/!
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I want to emphasize that in closing Everything is fucked and you don't usually see it because it's not egregious enough to break the surface but everything in social science is fucked. Don't succumb to Gell-Mann Amnesia just stop reading empirical papers. Ed Prescott was right.pic.twitter.com/g20u9dGCXE
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Special thanks to
@RRHDr,@Fixed_Effects,@aaronsojourner &@LauraHuangLA for the object lesson And to@PNASNews, which my old undergrad advisor helpfully explained stands for "Prints Nearly Any Shit" You should all be embarrassed but I bet you won't beShow this thread
End of conversation
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