"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!
Thanks, those really are nice explanations, and they implicitly bring up a couple of what I assume are commonly discussed caveats:
1. "Arguably exogenous" doesn't necessarily mean actually exogenous and people are often going to debate how exogenous the variation is. For example, I think it's plausible that people born at different times of the year might vary in other aspects of their upbringing besides their school eligibility in ways that would affect their incomes. And the causal inference "more education -> higher income" depends, if I understand correctly, on the assumption that they don't vary in such ways.
2. Extrapolation from small effects of small changes to larger effects on larger changes may make an arguable assumption about dose-response relationship. If 0.1 years more education results in 1% more income, does it really follow that 1 year more education gives you 10% more income? Shouldn't we in fact think that it would be significantly *less* than 10%, i.e. less than a linear dose-response curve, given the ubiquity of diminishing returns?
If the study really finds that 0.1 years more education increases income by 1% (rather than K+0.1 years vs K years where K is a constant) then by definition 1 year more education provides 10% more income.
(2) deals with LATE (local average treatment effect) as well as heterogeneous treatment effects--these may be discussed in the links above, i'll check. in brief, this estimate is the treatment effect among the population brought into the treatment group by the natural experiment. so if the policy is a test score threshold we're comparing students just above versus just below the test threshold. the LATE estimated from this group does not apply to students far above or below the threshold.
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.
"Just as no physicist would claim that “water runs uphill,” no self-respecting economist would claim that increases in the minimum wage increase employment."
This criticism of Buchanan is simply wrong. He wasn't even commenting on the Card/Krueger paper. He was asked about a proposed increase in the minimum wage by Bill Clinton during the 1996 campaign. If anyone was in mind by Buchanan it was probably Robert Reich (not a professional economist by any stretch), Clintons Sec'y of Labor.
Further, Buchanan's own 1954 textbook includes a straightforward explanation of the 'monopsony exception' to minimum wages that could result in higher employment. Of course, that text also includes reasons why this is unlikely to eventuate in the real world.
Also, Milton Friedman's 1976 Price Theory textbook has the same argument. Noah Smith, Mike Huben and David Glasner are way off base.
Then Buchanan and Friedman's "reasons why this is unlikely to eventuate in the real world" have been shown to be wrong by Card and many other experimental economists. Which is precisely why they won the Nobel.
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.
A potential finding has to pass through a lot of gates before it becomes a well-known published result. If there's some selection bias at each gate, even just a little bit, and it's all in the same direction, then published results can be a substantially biased set of all possible potential findings. I do think this happens, and I don't think it's because of any extreme bias at any particular stage. Rather small biases compounding.
For example, stages with potential ideological bias:
* Having the idea for a study in the first place
* Getting approval and/or funding
* Convincing people to give you (or let you collect) the data you need
* Choosing and applying an approach for analysis
* Writing up the findings
* Getting a journal interested
* Clearing the peer reviewers
* Having people notice and circulate your result once published
Note that at several stages, even a totally unbiased researcher will need to clear gates where others may play gatekeeper in a biased way.
As an outside observer, the whole scientific publishing thing seems like a racket. Obviously it has its purpose and uses, but definitely isn't perfect.
Thank you for your insightful comment. This is why I like the comment sections. People offer more than tweet size sound-bits to contribute to the conversation. You really added to my understanding of the issue.
Perhaps I should have added a \s. It is obviously a snide remark. But it is no less of a reasonable reading of the facts than your statement that your are skeptical of results that favor the Liberal point of view.
The facts on average favor the truth. One of the two parties spends it's time complaining about the facts. Ronald Regan proposed healthcare that was less conservative than ObamaCare by many measures. The Republican Party has doubled down repeatedly on, "All Government is bad" and "Tax cuts for the rich benefit everyone."
Ignoring the facts and clinging, eyes tightly closed to ideology, will cause you to wake up where the facts on the ground don't agree with your philosophy.
Rory, I know your posts (largely from another substack) You always come across as fairly moderate. This wasn't directed at you and was not intended to offend. It may, however, have come across as irritated. If so, my apologies.
no worries. I decided to disengage. I'm cranky lately because this job in Argentina is dragging on, with several weeks before I get to go home again. Its one of those subjects that becomes a tit for tat with evidence. I thought I was relatively benign. I've seen even progressive commenters and economists express concern about research. But since its unknowable, and outside of my personal experience, not something I feel comfortable debating, and quite frankly not an entertaining subject.
I appreciate your response. I've done the same thing in the past.
I very much enjoy the comments on this and slow boring blog. I learn a lot. Get to exercise my mind, stretch my understanding. I will also, readily admit when I am wrong and have been known to change my mind.
No hard feelings. Hit me up on another subject, and I will willingly engage.
I get very suspicious when the vast majority of employment policy overwhelmingly leads one way, based on 100+ year old microeconomic models. :-) That alone would justify many people exploring such important policies.
As a rule, if differing policies do not lead to immediate catastrophe, they should not be dismissed as wrong by theoretic economists. Especially when there are working examples throughout the world.
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.
Before the credibility revolution of the 90s, the main way economists studied things was to combine complicated "structural" models that predicted people doing certain things and then running regressions with as many controls as possible. The problem is that you can't control for everything, and adding these variables can even add in more bias. You had to have pretty strong priors about how things work before you even take it to the data. As these techniques have changed, so has economics.
Noah has written about this a lot, but economists don't think humans are all individualistic robots. Institutions, norms, and irrationality all play a big role in research. Elinor Ostrum, another Nobel laureate is just one example of this. The caricature of economists as being all free marketer people who slavishly follow the predictions of models taught to intro students is pretty outdated.
Also, while natural experiments weren't super heavily used before Card and Krueger, these methods weren't completely new. Difference-in-difference techniques, which they use to measure the minimum wage impact, was developed in the 1840s to analyze the causes of a cholera outbreak in London.
Uh, structural models don't work quite like that. Not the good ones, anyway. But it is considerably more difficult to explain, and the weight of the evidence in those models is considerably less transparent, which is their main problem. Ideally, we would have both good structural models and quasi-experimental evidence. I suspect that David Card and Noah Smith would agree.
"Institutions, norms, and irrationality all play a big role in research." I love to see examples of that in top journals. The only form of modelling that can scratch the surface of these issues are ABMs which have very low takeup amongst economists anyway and I am not aware of any articles featuring them in top journals. I actually wrote to all the editors of such journals about whether they had published articles involved such and they couldn't give an example. This was a few years ago but I would be really surprised if that has changed.
And I only just interviewed Eric Nordman about his book on Elinor Ostrom and asked if he thought she had had much influence on economics. And he said basically no. You can watch it here: https://www.themintmagazine.com/commons-concern
The study of institutions is very hot in economics right now, Acemoglu, Alesina, and many many others. For irrationality, there's the entire field of behavioral economics. As for Ostrom, she won a Nobel. That's certainly an endorsement of the importance of not only her work, but the kind of work that she did.
From just going to this issue of the American Economic Review, there are several papers on agglomeration effects and how information and the effects of that spread across space.
The QJE is generally more focused on things like norms, culture, and institutions than other top journals. A quick look through the papers in their current issue shows numerous examples of this.
Thanks for that. I was not aware of this work and great to see these aspects are beginning to be looked at. From a quick review of the papers, I was struck by the commonality of methodologies ie data set regression. I didn't see any qualitative methodologies used. Is this a fair assessment? Is it still the case that most economists shun qualitative methodologies while other disciplines see them as a key part of their toolbox particularly for looking at institutions? Could this bias change, do you think?
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
As a side note, “CK 2000 confirmed lack of job loss” — that’s a pretty positive way to put what’s also a failure to confirm the reported gains from CK 1994.
Yes but the larger point made here is that the Nobel is for the methodology, not necessarily the result of any particular study. Indeed, that other sought to replicate the minimum wage study using different data sources and came to different results makes the case that the Nobel is deserved. As Noah says, the goal is to make Econ a more scientific field. That means falsifiable conjectures and the ability to use evidence to do empirical investigations.
Regardless of any weakness of the initial study, the finding _has_ replicated, using a variety of techniques. The reason the opinions of economists have moved overwhelmingly on this issue is because the evidence has piled up that, at least for small increases over the kinds of minimums that we actually have, there are no job losses, and might even be gains. (I am open to the possibility that $15/hr might be too much for some markets -- that seems to be above the _median_ wage for some counties. Clearly there must be _some_ level where raising the wage would be disruptive.)
I'm sure there are people who are committed to trying to poke holes, just as there area few percent of people with degrees related to climatology who cherry-pick evidence for reasons why we shouldn't do anything about anthropogenic climate change. But the reason the field moved isn't because it became full of ideologues, it's because of the evidence.
Papers that go out 5 or even 7 years don't really show losses either. Here's one that uses the best data in existence: https://kevinrinz.github.io/minwage.pdf
This paper is almost 30 years old. One would hope that better studies have come out since. That's the point of making econ more of a science. That said, the finding that minimum wage increases don't necessarily increase unemployment is so well replicated, that most economists who actually study the issue are well past it at this point. People like Neumark are critical of this consensus, but the majority of labor economists agree that minimum wage hikes don't necessarily drive up unemployment.
The Neumark and Wascher study was published as a very long comment in the December 2000 issue of the AER. Card and Krueger had an equally long response in the same issue, where they did two things (maybe 2 1/2.). First, in response to the criticisms of their phone survey, they repeated their initial study of the 1992 increase in the NJ minimum wage using Unemployment Insurance data for NJ and PA. They then repeated it again for the 1996 increase in the Federal minimum wage, which raised the minimum wage in PA but not NJ since its minimum was at least as high as the new Federal level (this is the half mentioned above). Both of these analyses replicated their original results. Finally, they took a very close look at Neumark and Wascher's data, and identified a large chunk of it that was not in any way a random sample. When they removed this chunk from N&W's data and re-ran the analysis, it again supported their findings. You can read all about it on pp 25-28 of my book, "What Does the Minimum Wage Do?" (free pdf <b><a href="https://research.upjohn.org/up_press/227/">here</a></b>: https://research.upjohn.org/up_press/227/)
When you say they “replicated their analysis” do you mean the original finding that min wage *increased* employment, or that they found no effect? If the former, why do the later analyses all discuss the latter (no effect)? (For example, the second link in my comment, but others as well, like the tweet-thread Noah linked to.)
Looking now at what I wrote about it in my book (no time now to find and reread the article):
"Once again, Card and Krueger (2000) find no evidence of employment responding to the minimum wage."
I don't believe that C&K (or Dube in any of his many co-authored articles) ever estimated a positive employment effect that was statistically significant.* That the estimated effect in a well-designed study came up positive was worthy of note, though though less so than that the estimated effect was not both negative and statistically significant. At the time of the first study, the belief in the negative employment effect of the minimum wage was so deep-seated that a positive effect (even if not statistically significant) was remarkable.
*For those who are not esp. knowledgeable or sophisticated about statistics, statistically significant means that one is reasonably confident that the estimated effect is non-zero with the estimated sign (i.e., positive or negative). It is an indicator of how precisely you are measuring what you are trying to measure. Oversimplifying a bit, this is basically a function of the size of the effect and the size of the sample. An analogy about statistical significance: if your observations & measurements are a lens, statistical significance is a measure of how well you can focus the lens, how unfuzzy the image is.
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.
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
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.
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:
Here's a good idea; try reading the things you link to (or think about their implications!).
Did you notice that Tim Taylor cited the same Neumark-Shirley paper that I did? Or, this from the CBO paper;
"CBO projects that, on net, the Raise the Wage Act of 2021 would reduce employment by increasing amounts over the 2021–2025 period. In 2025, when the minimum wage reached $15 per hour, employment would be reduced by 1.4 million workers (or 0.9 percent), according to CBO’s average estimate. In 2021, most workers who would not have a job because of the higher minimum wage would still be looking for work and hence be categorized as unemployed; by 2025, however, half of the 1.4 million people who would be jobless because of the bill would have dropped out of the labor force, CBO estimates. Young, less educated people would account for a disproportionate share of those reductions in employment."
The latter would seem to directly contradict your assertions.
You've forgotten your assertions already? How about this one:
"Then Buchanan and Friedman's "reasons why this is unlikely to eventuate in the real world" have been shown to be wrong by Card and many other experimental economists. Which is precisely why they won the Nobel."
You have backed off that one and are now reduced to 'possibilities' that monopsony or oligopsony 'could be' present.
Even David Card doesn't agree with you about that. For proof listen to his press conference, it's full of equivocation about the practical significance of his and Krueger's work.
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.
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.
Oligopsony, is a 'small number of buyers', which is clearly not the case with the market for unskilled labor. Not even if you restrict buyers to fast food outlets. But try again, I'd probably enjoy another joke.
The Gittins piece says nothing, other than oligopsony explains it. Unfortunately, it doesn't specify how. It's just a guy blowing smoke (which, I'm pretty sure now, is what you are doing.
So, unless you've actually got an argument to make, don't bother linking to some other piece of fluff. I'm used to debating actual economists.
Oooo, I'm quaking in my boots! What do you do, cite Austrian economists at them?
If you had any reading skills, you would have noticed that he DID list at least one source of oligopsony power. However, sinc eyou want more and I don't mind educating you, here's a source that lists at least 5 causes:
LABOR MARKET MONOPSONY:TRENDS, CONSEQUENCES, AND POLICY RESPONSES
I'm not so sure what you are not so sure about, however if you are suggesting that those corporations are few in number and thus constitute oligopsony, forget it. Most fast food outlets are franchises, hence they compete with not only their fellow franchisees, but the greater market (and not only in fast food).
It took you all night 'think'ing to come up with that one? I've already pointed out to you that the franchises do the hiring (often at the individual outlet), not the corporate parents. So, franchisees of the same brands compete with each other, as well as compete with franchisees of competitor corporations, for the same pool of unskilled/low skilled labor, in a geographic locality.
They also compete with other industries, such as construction/landscaping for workers. To argue that Burger King franchises are in the position of a mining company paying for '16 tons' with that pay only redeemable at the company store (or Hershey PA), is to mark yourself as a buffoon.
Yet they all stand to gain if they keep labor prices low. Even Adam Smith noted this. "The masters, being fewer in number, can combine much more easily ... Masters are always and everywhere in a sort of tacit, but constant and uniform, combination, not to raise the wages of labor above their actual rate."
'Yet they all stand to gain if they keep labor prices low. "
Wow, what a sharpie you are. Boy I can't sneak anything past a guy like you. However, you have forgotten to explain just exactly HOW hundreds of small businesses are going to collaborate to keep wages down.
I.e., the quote from Smith includes the qualifier, 'fewer in number'.
Maybe you should read the Labor Market Monopsony article I linked. Among other things, it talks about non-compete clauses, which are actually used a lot in minimum wage jobs.
Another possibility is the ubiquitous chambers of commerce.
<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.
"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!
or hit your head on a building
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?
Angrist's "Mostly Harmless Econometrics"...though it's a book!
the nobel prize documentation is actually quite good for general readers.
"popular science" background:
https://www.nobelprize.org/uploads/2021/10/popular-economicsciencesprize2021-3.pdf
deeper dive:
https://www.nobelprize.org/uploads/2021/10/advanced-economicsciencesprize2021.pdf
Thanks, those really are nice explanations, and they implicitly bring up a couple of what I assume are commonly discussed caveats:
1. "Arguably exogenous" doesn't necessarily mean actually exogenous and people are often going to debate how exogenous the variation is. For example, I think it's plausible that people born at different times of the year might vary in other aspects of their upbringing besides their school eligibility in ways that would affect their incomes. And the causal inference "more education -> higher income" depends, if I understand correctly, on the assumption that they don't vary in such ways.
2. Extrapolation from small effects of small changes to larger effects on larger changes may make an arguable assumption about dose-response relationship. If 0.1 years more education results in 1% more income, does it really follow that 1 year more education gives you 10% more income? Shouldn't we in fact think that it would be significantly *less* than 10%, i.e. less than a linear dose-response curve, given the ubiquity of diminishing returns?
apparently (1) is argued in this paper, for example:
http://www.djaeger.org/research/pubs/rle2000.pdf
Thanks!
If the study really finds that 0.1 years more education increases income by 1% (rather than K+0.1 years vs K years where K is a constant) then by definition 1 year more education provides 10% more income.
(2) deals with LATE (local average treatment effect) as well as heterogeneous treatment effects--these may be discussed in the links above, i'll check. in brief, this estimate is the treatment effect among the population brought into the treatment group by the natural experiment. so if the policy is a test score threshold we're comparing students just above versus just below the test threshold. the LATE estimated from this group does not apply to students far above or below the threshold.
Check out this course. It's all about real world applications of quasi experiments using big data
https://opportunityinsights.org/course/
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.
Bravo, Noah! Great post.
Thanks!
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/)
This criticism of Buchanan is simply wrong. He wasn't even commenting on the Card/Krueger paper. He was asked about a proposed increase in the minimum wage by Bill Clinton during the 1996 campaign. If anyone was in mind by Buchanan it was probably Robert Reich (not a professional economist by any stretch), Clintons Sec'y of Labor.
Further, Buchanan's own 1954 textbook includes a straightforward explanation of the 'monopsony exception' to minimum wages that could result in higher employment. Of course, that text also includes reasons why this is unlikely to eventuate in the real world.
Also, Milton Friedman's 1976 Price Theory textbook has the same argument. Noah Smith, Mike Huben and David Glasner are way off base.
Then Buchanan and Friedman's "reasons why this is unlikely to eventuate in the real world" have been shown to be wrong by Card and many other experimental economists. Which is precisely why they won the Nobel.
For example?
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.
A potential finding has to pass through a lot of gates before it becomes a well-known published result. If there's some selection bias at each gate, even just a little bit, and it's all in the same direction, then published results can be a substantially biased set of all possible potential findings. I do think this happens, and I don't think it's because of any extreme bias at any particular stage. Rather small biases compounding.
For example, stages with potential ideological bias:
* Having the idea for a study in the first place
* Getting approval and/or funding
* Convincing people to give you (or let you collect) the data you need
* Choosing and applying an approach for analysis
* Writing up the findings
* Getting a journal interested
* Clearing the peer reviewers
* Having people notice and circulate your result once published
Note that at several stages, even a totally unbiased researcher will need to clear gates where others may play gatekeeper in a biased way.
As an outside observer, the whole scientific publishing thing seems like a racket. Obviously it has its purpose and uses, but definitely isn't perfect.
There is not in fact a Liberal bias in results. The Right has just moved Rightward from reality.
Thank you for your insightful comment. This is why I like the comment sections. People offer more than tweet size sound-bits to contribute to the conversation. You really added to my understanding of the issue.
Perhaps I should have added a \s. It is obviously a snide remark. But it is no less of a reasonable reading of the facts than your statement that your are skeptical of results that favor the Liberal point of view.
The facts on average favor the truth. One of the two parties spends it's time complaining about the facts. Ronald Regan proposed healthcare that was less conservative than ObamaCare by many measures. The Republican Party has doubled down repeatedly on, "All Government is bad" and "Tax cuts for the rich benefit everyone."
Ignoring the facts and clinging, eyes tightly closed to ideology, will cause you to wake up where the facts on the ground don't agree with your philosophy.
Have a great and merry day.
Rory, I know your posts (largely from another substack) You always come across as fairly moderate. This wasn't directed at you and was not intended to offend. It may, however, have come across as irritated. If so, my apologies.
no worries. I decided to disengage. I'm cranky lately because this job in Argentina is dragging on, with several weeks before I get to go home again. Its one of those subjects that becomes a tit for tat with evidence. I thought I was relatively benign. I've seen even progressive commenters and economists express concern about research. But since its unknowable, and outside of my personal experience, not something I feel comfortable debating, and quite frankly not an entertaining subject.
I appreciate your response. I've done the same thing in the past.
I very much enjoy the comments on this and slow boring blog. I learn a lot. Get to exercise my mind, stretch my understanding. I will also, readily admit when I am wrong and have been known to change my mind.
No hard feelings. Hit me up on another subject, and I will willingly engage.
I get very suspicious when the vast majority of employment policy overwhelmingly leads one way, based on 100+ year old microeconomic models. :-) That alone would justify many people exploring such important policies.
As a rule, if differing policies do not lead to immediate catastrophe, they should not be dismissed as wrong by theoretic economists. Especially when there are working examples throughout the world.
I dont know anything about employment policy. Or this subject. Do you have a dummies primer?
Here I simply mean "market prices" versus "minimum wage."
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.
Before the credibility revolution of the 90s, the main way economists studied things was to combine complicated "structural" models that predicted people doing certain things and then running regressions with as many controls as possible. The problem is that you can't control for everything, and adding these variables can even add in more bias. You had to have pretty strong priors about how things work before you even take it to the data. As these techniques have changed, so has economics.
Noah has written about this a lot, but economists don't think humans are all individualistic robots. Institutions, norms, and irrationality all play a big role in research. Elinor Ostrum, another Nobel laureate is just one example of this. The caricature of economists as being all free marketer people who slavishly follow the predictions of models taught to intro students is pretty outdated.
Also, while natural experiments weren't super heavily used before Card and Krueger, these methods weren't completely new. Difference-in-difference techniques, which they use to measure the minimum wage impact, was developed in the 1840s to analyze the causes of a cholera outbreak in London.
Uh, structural models don't work quite like that. Not the good ones, anyway. But it is considerably more difficult to explain, and the weight of the evidence in those models is considerably less transparent, which is their main problem. Ideally, we would have both good structural models and quasi-experimental evidence. I suspect that David Card and Noah Smith would agree.
"Institutions, norms, and irrationality all play a big role in research." I love to see examples of that in top journals. The only form of modelling that can scratch the surface of these issues are ABMs which have very low takeup amongst economists anyway and I am not aware of any articles featuring them in top journals. I actually wrote to all the editors of such journals about whether they had published articles involved such and they couldn't give an example. This was a few years ago but I would be really surprised if that has changed.
And I only just interviewed Eric Nordman about his book on Elinor Ostrom and asked if he thought she had had much influence on economics. And he said basically no. You can watch it here: https://www.themintmagazine.com/commons-concern
The study of institutions is very hot in economics right now, Acemoglu, Alesina, and many many others. For irrationality, there's the entire field of behavioral economics. As for Ostrom, she won a Nobel. That's certainly an endorsement of the importance of not only her work, but the kind of work that she did.
From just going to this issue of the American Economic Review, there are several papers on agglomeration effects and how information and the effects of that spread across space.
https://www.aeaweb.org/issues/652
The QJE has many other papers that get into this. They even have a focus on the interplay of religion and economics.
https://academic.oup.com/qje/pages/religion-and-economics-collection
The QJE is generally more focused on things like norms, culture, and institutions than other top journals. A quick look through the papers in their current issue shows numerous examples of this.
https://academic.oup.com/qje/issue/136/4
Econ is certainly more individually based in it's analysis than other social science fields, but it most certainly doesn't ignore these other things.
Thanks for that. I was not aware of this work and great to see these aspects are beginning to be looked at. From a quick review of the papers, I was struck by the commonality of methodologies ie data set regression. I didn't see any qualitative methodologies used. Is this a fair assessment? Is it still the case that most economists shun qualitative methodologies while other disciplines see them as a key part of their toolbox particularly for looking at institutions? Could this bias change, do you think?
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...
Here's a good thread about how the paper held up over time:
https://twitter.com/arindube/status/1447763757459980288
As a side note, “CK 2000 confirmed lack of job loss” — that’s a pretty positive way to put what’s also a failure to confirm the reported gains from CK 1994.
But it’s indeed also not a job loss!
I mean, that's called replication, right?
Yes but the larger point made here is that the Nobel is for the methodology, not necessarily the result of any particular study. Indeed, that other sought to replicate the minimum wage study using different data sources and came to different results makes the case that the Nobel is deserved. As Noah says, the goal is to make Econ a more scientific field. That means falsifiable conjectures and the ability to use evidence to do empirical investigations.
Regardless of any weakness of the initial study, the finding _has_ replicated, using a variety of techniques. The reason the opinions of economists have moved overwhelmingly on this issue is because the evidence has piled up that, at least for small increases over the kinds of minimums that we actually have, there are no job losses, and might even be gains. (I am open to the possibility that $15/hr might be too much for some markets -- that seems to be above the _median_ wage for some counties. Clearly there must be _some_ level where raising the wage would be disruptive.)
Noah wrote about that at length, in a post he linked to: https://noahpinion.substack.com/p/why-15-minimum-wage-is-pretty-safe
I'm sure there are people who are committed to trying to poke holes, just as there area few percent of people with degrees related to climatology who cherry-pick evidence for reasons why we shouldn't do anything about anthropogenic climate change. But the reason the field moved isn't because it became full of ideologues, it's because of the evidence.
yeah, fair points. There does seem to be evidence that moderate increases do not cause significant short-term loss.
The graph in Noah's post you link to does show more job losses than gains from min wage... but it is indeed mild.
Papers that go out 5 or even 7 years don't really show losses either. Here's one that uses the best data in existence: https://kevinrinz.github.io/minwage.pdf
This paper is almost 30 years old. One would hope that better studies have come out since. That's the point of making econ more of a science. That said, the finding that minimum wage increases don't necessarily increase unemployment is so well replicated, that most economists who actually study the issue are well past it at this point. People like Neumark are critical of this consensus, but the majority of labor economists agree that minimum wage hikes don't necessarily drive up unemployment.
The Neumark and Wascher study was published as a very long comment in the December 2000 issue of the AER. Card and Krueger had an equally long response in the same issue, where they did two things (maybe 2 1/2.). First, in response to the criticisms of their phone survey, they repeated their initial study of the 1992 increase in the NJ minimum wage using Unemployment Insurance data for NJ and PA. They then repeated it again for the 1996 increase in the Federal minimum wage, which raised the minimum wage in PA but not NJ since its minimum was at least as high as the new Federal level (this is the half mentioned above). Both of these analyses replicated their original results. Finally, they took a very close look at Neumark and Wascher's data, and identified a large chunk of it that was not in any way a random sample. When they removed this chunk from N&W's data and re-ran the analysis, it again supported their findings. You can read all about it on pp 25-28 of my book, "What Does the Minimum Wage Do?" (free pdf <b><a href="https://research.upjohn.org/up_press/227/">here</a></b>: https://research.upjohn.org/up_press/227/)
When you say they “replicated their analysis” do you mean the original finding that min wage *increased* employment, or that they found no effect? If the former, why do the later analyses all discuss the latter (no effect)? (For example, the second link in my comment, but others as well, like the tweet-thread Noah linked to.)
Looking now at what I wrote about it in my book (no time now to find and reread the article):
"Once again, Card and Krueger (2000) find no evidence of employment responding to the minimum wage."
I don't believe that C&K (or Dube in any of his many co-authored articles) ever estimated a positive employment effect that was statistically significant.* That the estimated effect in a well-designed study came up positive was worthy of note, though though less so than that the estimated effect was not both negative and statistically significant. At the time of the first study, the belief in the negative employment effect of the minimum wage was so deep-seated that a positive effect (even if not statistically significant) was remarkable.
*For those who are not esp. knowledgeable or sophisticated about statistics, statistically significant means that one is reasonably confident that the estimated effect is non-zero with the estimated sign (i.e., positive or negative). It is an indicator of how precisely you are measuring what you are trying to measure. Oversimplifying a bit, this is basically a function of the size of the effect and the size of the sample. An analogy about statistical significance: if your observations & measurements are a lens, statistical significance is a measure of how well you can focus the lens, how unfuzzy the image is.
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.
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
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.
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.
It's so sweet that you cherry pick a paper that fits your prior conclusions.
Two articles that show the situation is much more complicated (and cite other papers as well) are:
The Minimum Wage Controversy https://conversableeconomist.blogspot.com/2021/02/the-minimum-wage-controversy.html
and
The True Story of the Minimum-Wage Fight https://freakonomics.com/podcast/minimum-wage/
Here's a good idea; try reading the things you link to (or think about their implications!).
Did you notice that Tim Taylor cited the same Neumark-Shirley paper that I did? Or, this from the CBO paper;
"CBO projects that, on net, the Raise the Wage Act of 2021 would reduce employment by increasing amounts over the 2021–2025 period. In 2025, when the minimum wage reached $15 per hour, employment would be reduced by 1.4 million workers (or 0.9 percent), according to CBO’s average estimate. In 2021, most workers who would not have a job because of the higher minimum wage would still be looking for work and hence be categorized as unemployed; by 2025, however, half of the 1.4 million people who would be jobless because of the bill would have dropped out of the labor force, CBO estimates. Young, less educated people would account for a disproportionate share of those reductions in employment."
The latter would seem to directly contradict your assertions.
Yes, I did read them. And what I noticed was that Taylor did not simply cherry pick one paper the way you did: he presented both sides.
As for "my assertions", please cite them. You're imagining things.
You've forgotten your assertions already? How about this one:
"Then Buchanan and Friedman's "reasons why this is unlikely to eventuate in the real world" have been shown to be wrong by Card and many other experimental economists. Which is precisely why they won the Nobel."
You have backed off that one and are now reduced to 'possibilities' that monopsony or oligopsony 'could be' present.
Are you confusing plural with singular?
In any event, I supported that assertion with two citations. No backing off present.
Even David Card doesn't agree with you about that. For proof listen to his press conference, it's full of equivocation about the practical significance of his and Krueger's work.
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.
What? no cocaine? I thought the Miami boom was all about the cocaine.
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.
"monopsony in fast food is a joke" Maybe you should learn about oligopsony, which can also have those effects.
Oligopsony, is a 'small number of buyers', which is clearly not the case with the market for unskilled labor. Not even if you restrict buyers to fast food outlets. But try again, I'd probably enjoy another joke.
I'll keep it simple for you: https://www.smh.com.au/business/the-economy/the-oligopsony-model-what-it-is-and-why-it-explains-australias-situation-20170331-gvaowi.html
Maybe you should learn something before you spout.
The Gittins piece says nothing, other than oligopsony explains it. Unfortunately, it doesn't specify how. It's just a guy blowing smoke (which, I'm pretty sure now, is what you are doing.
So, unless you've actually got an argument to make, don't bother linking to some other piece of fluff. I'm used to debating actual economists.
Oh, and if you want a book-length treatment, see:
Manning, Alan. 2003. Monopsony in Motion. Princeton University Press.
https://b-ok.lat/book/3605990/1ec0fd
> I'm used to debating actual economists.
Oooo, I'm quaking in my boots! What do you do, cite Austrian economists at them?
If you had any reading skills, you would have noticed that he DID list at least one source of oligopsony power. However, sinc eyou want more and I don't mind educating you, here's a source that lists at least 5 causes:
LABOR MARKET MONOPSONY:TRENDS, CONSEQUENCES, AND POLICY RESPONSES
https://obamawhitehouse.archives.gov/sites/default/files/page/files/20161025_monopsony_labor_mrkt_cea.pdf
Is down the street populated by a KFC, Taco Bell and a Pizza Hut? Because then I'm not so sure.
I'm not so sure what you are not so sure about, however if you are suggesting that those corporations are few in number and thus constitute oligopsony, forget it. Most fast food outlets are franchises, hence they compete with not only their fellow franchisees, but the greater market (and not only in fast food).
They're all the same corporation (Yum Brands). And I would think it provides guidance on wages.
It took you all night 'think'ing to come up with that one? I've already pointed out to you that the franchises do the hiring (often at the individual outlet), not the corporate parents. So, franchisees of the same brands compete with each other, as well as compete with franchisees of competitor corporations, for the same pool of unskilled/low skilled labor, in a geographic locality.
They also compete with other industries, such as construction/landscaping for workers. To argue that Burger King franchises are in the position of a mining company paying for '16 tons' with that pay only redeemable at the company store (or Hershey PA), is to mark yourself as a buffoon.
Yet they all stand to gain if they keep labor prices low. Even Adam Smith noted this. "The masters, being fewer in number, can combine much more easily ... Masters are always and everywhere in a sort of tacit, but constant and uniform, combination, not to raise the wages of labor above their actual rate."
'Yet they all stand to gain if they keep labor prices low. "
Wow, what a sharpie you are. Boy I can't sneak anything past a guy like you. However, you have forgotten to explain just exactly HOW hundreds of small businesses are going to collaborate to keep wages down.
I.e., the quote from Smith includes the qualifier, 'fewer in number'.
Maybe you should read the Labor Market Monopsony article I linked. Among other things, it talks about non-compete clauses, which are actually used a lot in minimum wage jobs.
Another possibility is the ubiquitous chambers of commerce.
Maybe you should acquaint yourself with the difference between possibility and actuality.
<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.