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"In the short term, we all want our chosen politics to win out. But if you ignore reality in the name of politics for too long, eventually you’re going to find yourself shouting orders that nature refuses to obey."

A great quote for pragmatists and empiricists everywhere!

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Is there a good intro explainer for people who haven't already taken an econometrics course that covers:

-- how the non-RCT quasi-experimental methods work

-- why they're believed to be epistemologically valid in at least some cases

-- what people should look for in a particular paper to tell whether it's used the methods in an epistemologically valid way?

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Recent relevant post:

https://mattsclancy.substack.com/p/conservatism-in-science

If I understand correctly, the study design by Azoulay et al that looks at research fields where a superstar died unexpectedly vs fields where they didn't is the same kind of quasi-experimental method that the Nobel recipients pioneered, no?

Also, there's an interesting argument here, likely relevant to your interests, that abundant research funding-- abundant relative to the set of viable grant proposals-- is needed to produce more fundamental breakthroughs. Not because more funding -> more science straightforwardly, but because in an environment of funding scarcity, grants tend to go to projects more easily identified as promising, which tend to be more incremental and less likely to produce fundamental breakthroughs.

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Bravo, Noah! Great post.

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Oct 12, 2021Liked by Noah Smith

It's good to see the odious James Buchanan (http://critiques.us/index.php?title=James_Buchanan) put in his place.

"Just as no physicist would claim that “water runs uphill,” no self-respecting economist would claim that increases in the minimum wage increase employment."

Maybe he'd never gone boating and never saw an eddy (https://en.wikipedia.org/wiki/Eddy_(fluid_dynamics) ), or maybe he's never heard of hydraulic ram pumps. (https://en.wikipedia.org/wiki/Hydraulic_ram)

Here's David Glasner's takedown: James Buchanan Calling the Kettle Black. (https://uneasymoney.com/2019/03/22/james-buchanan-calling-the-kettle-black/)

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Browsing Twitter yesterday, there was near universal agreement that this was a good choice. I saw one dissent based on "more white guys".

On liberal bias in results, I wonder if there is a selection bias on what people study. Not that papers are inaccurate, but in asking the questions that you might suspect favor a progressive answer.

I get very suspicious when the vast majority of findings overwhelmingly lead one way. Life is full of inconvenient facts and truths, so seems like more findings should be like... well oh crap that sucks.

Is it possible that people don't ask questions when they know the answer is likely to not show what they want it to show?

Note: none of this is casting shade on these three dudes. I spent all yesterday researching them, reading articles and watching interviews.

If I had life to do over again though, I would love to be an economist though.

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What seems surprising to me is that a field of study that dates back over a century and a half and always sought to ape natural science in its use of maths, only relatively recently got interested in evidence! How has it managed to be an evidence-free space for so long?

However economics will only really move to be more scientific when it expands its theoretical space. For instance, its insistence on methodological individualism and its lack of attention to social structures or institutions in the technical sense, seems to be a glaring omission which will bias what evidence is actually looked for.

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Are you aware that Card's initial paper got its data from phone surveys -- and that when the actual payroll data were obtained (by Neumark & Wascher), Card's findings were reversed? https://www.nber.org/papers/w5224

It's not just that study; other later studies comparing the two come to the same conclusion: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1829847

Seems like a Nobel based on a clever but very weak study...

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I think why small 'c' conservative economists and the Laffer set would impune the Nobel prize committee giving Card et al a Nobel in economics is that Card et al indicate that you can find empirical data that contradicts quite a bit of supply-side theory with the natural experiments we see being run. It's especially relevant in the U.S. where we run supply-side experiments every 4 yrs or so at the Federal level but also continuously at the state and local levels. Despite the evidence, supply-siders will still insist that if they just keep running the same experiment it will result in supply-side economics working when it comes to wage suppression, regressive labor taxation, and tax cuts for top income earners and corporations.

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I put together a web page with links on what I found investigating whether Card-Krueger holds up. It doesn't. Besides having no serious theoretical support, it failed in replication with better data (the NW-2000 paper) and their data sounds ridiculously implausible (Welch's critique) since it has wild swings over 7 months in individual restaurant employment and wages. Has anyone addressed Welch's statements about their data? https://www.rasmusen.org/rasmapedia/index.php?title=Minimum_Wage

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In your blog you cite Card and Kruger's research on the effect of minimum wage on employment by taking data from the New Jersey and Pennsylvania restaurants. Their conclusions were contradicted by the analysis of economists Newmark and Wascher. Please read economic researcher David Henderson's article on this subject.

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On the off chance that there are any readers here actually interested in the facts about minimum wage research as of 2021, here is a paper by Neumark and Shirley:

https://www.nber.org/system/files/working_papers/w28388/w28388.pdf From which:

... our key conclusions are as follows:

• There is a clear preponderance of negative estimates in the literature. In our data, 78.9% of

the estimated employment elasticities are negative, 53.9% are negative and significant at

the 10% level or better, and 46.1% are negative and significant at the 5% level or better.

• This evidence of negative employment effects is stronger for teens and young adults, and

more so for the less-educated.

• The evidence from studies of directly-affected workers points even more strongly to

negative employment effects.

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Too large a proportion of recent 'mathematical' economics are merely concoctions, as imprecise as the initial assumptions they rest on, which allow the author to lose sight of the complexities and interdependencies of the real world in a maze of pretentious and unhelpful symbols.

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What? no cocaine? I thought the Miami boom was all about the cocaine.

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This from Noah Smith is completely wrong: "The basic theory of competitive supply and demand says that when you raise the minimum wage, people get thrown out of work!"

The Laws (not 'the theory') of Supply and Demand say no such thing. Instead they say that less quantity of unskilled labor will be demanded at the artificially higher wage. Not to mention that popularizers of 'Card/Krueger' seem to have ignored 'ceteris paribus'--managers can squeeze more productivity out of their workers by tighter supervision, for one obvious thing--in their enthusiasm.

Btw, monopsony in fast food is a joke. Ever look around a commercial city street? There's usually a Burger King across from a Wendy's, a McDonalds up the street and a taco or fried chicken place a block or so further away.

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<i>Naturally, there has been some pushback to this change. Economists used to dispensing grandiose Big Ideas are annoyed at the idea that those ideas might be knocked down by some rinky-dink little RCT study. Those who just want to do beautiful math are annoyed when reviewers demand they cite papers linking their math with the grubby, impure world outside their windows</i>

I think Huxley (that would be Thomas) said it best: “The great tragedy of science—the slaying of a beautiful hypothesis by an ugly fact.“

President's Address to the British Association for the Advancement of Science, Liverpool Meeting, 14 Sep 1870. The Scientific Memoirs of Thomas Henry Huxley (1901), Vol. 3, 580.

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