I was thinking more about the this story, where a series of economists took an story based on someone’s childhood memories and elaborated upon it in different ways until it eventually appeared in a major journal in the field. A few years after that, enough people got irritated that the journal ran a correction:
There is an error in “Self-Control at Work” (Kaur, Kremer, and Mullainathan 2015), published in the October 2015 edition of this journal (vol. 123, no. 6). In section VI, on page 1274, the paper includes the following incorrect quote from a paper by Steven N. S. Cheung:
The second view—that joint production necessitates the need for monitoring (Alchian and Demsetz 1972)—is summarized in a story by Steven Cheung (1983, 8): “On a boat trip up China’s Yangtze River in the 19th Century, a titled English woman complained to her host of the cruelty to the oarsmen. One burly coolie stood over the rowers with a whip, making sure there were no laggards. Her host explained that the boat was jointly owned by the oarsmen, and that they hired the man responsible for flogging.”
While the incorrect quote also appears in other earlier sources, it does not appear in Cheung’s original article. [For example, the incorrect version of the quote also appears in Jensen et al. (1998).]
The accurate quotation from Cheung (1983, 8) is as follows:
My own favorite example is riverboat pulling in China before the communist regime, when a large group of workers marched along the shore towing a good-sized wooden boat. The unique interest of this example is that the collaborators actually agreed to the hiring of a monitor to whip them. The point here is that even if every puller were perfectly “honest,” it would still be too costly to measure the effort each has contributed to the movement of the boat, but to choose a different measurement agreeable to all would be so difficult that the arbitration of an agent is essential.
The inaccurate quote was included simply as a way to illustrate the idea that joint production might necessitate the need for monitoring. . . . However, the quote is in no way central to the core point of the paper, or even for the discussion in section VI of the paper. . . . Consequently, this incorrect quote can be omitted from the paper without any impact on the substance of the paper.
To start with, the story was changed in many important ways! To call this an “incorrect quote” is an extreme understatement of what happened here. Second, that last bit about removal having no impact on the substance—it makes me wonder why it was included in the article at all. Surely it must have some impact, no?
After reading through the comments to the above-linked post and thinking more about this, I think I’ve come up with an answer.
How was the story changed?
The revised story has several elaborations, most of which seem like the result of unthinking ignorance:
– Changing from an unspecified river to the Yangtze: That’s the #1 river that Americans think of, when they hear about a river in China. According to the original teller of the story, it was a “journey from Liuzhou to Guiping,” which according to the map is not near the Yangtze. Kind of like how that buffoonish business-school professor took a story about the Alps and moved it to Switzerland.
– Changing from the 20th century to the 19th: The scenario sounds old-fashioned, so the storyteller unthinkingly moves it back in time.
– Introducing the word “coolie”: Adding this slur contributes to placing the story in the more distant past. We wouldn’t refer to a modern worker as a coolie, partly because it’s rude but also because it’s an old-fashioned word to use, even descriptively.
– Adding the physical description, “burly”: This is the kind of detail that can make a story seem more real; also, “burly” is another old-fashioned word, again placing the story back in the mists of time.
– Changing from riverboat pullers to oarsmen: A boat being rowed is more familiar than a boat being pulled, so if you’re telling from memory a story that you’ve never fully visualized, you might unthinkingly make that change.
But three of the elaborations are particularly striking because they don’t just elaborate the story, they also make it more compatible with the usual ideology of academic economists:
– Changing from “the collaborators actually agreed to the hiring of a monitor to whip them” to “the boat was jointly owned by the oarsmen, and that they hired the man responsible for flogging”: In this new version, the workers actually own the boat. As independent agents—owners of capital, in fact!—these workers are now unambiguously hiring the whipper out of their own free will, not acting out of some desperate economic necessity.
– Adding the “titled English woman”: At first this elaboration might seem the most puzzling, as it transforms a Chinese refugee into an upper-class foreigner, introducing an entirely new element to the story. From the economists’ perspective, though, it’s perfect, as this upper-class twit is a perfect foil to the down-to-earth economists who understand the real world (as here and here, for example).
– Adding the bit where the woman “complained to her host of the cruelty to the oarsmen”: This bit helps to make the woman unsympathetic (she “complains”; it is her host who gets to “explain”) and also reinforces the idea of the economists as taboo-busters who can marshal the cold facts to support apparent “cruelty.”
Whether or not the story is “central to the core point of the paper,” it does seem central to a certain way that economists often present themselves, and I do think some reflection on their part is in order.
What should the correction notice have said?
As discussed earlier, I was unsatisfied by the original correction notice (“this incorrect quote can be omitted from the paper without any impact on the substance of the paper”), both because “incorrect quote” doesn’t begin to describe the many ways that the story from Cheung (1983, 8) was changed, and second because . . . what does it mean that they included this story that had no impact on the substance? That’s not usually done in academic articles, is it? Even a story is merely illustrative, the fact that it presumably actually happened is relevant, no? To put it another way, if the best story you can use to illustrate a point is a made-up story, that in itself should be telling you something.
Actually, the quote is not inaccurate at all! It’s a direct quote from one of the practice exam questions in Jensen et al. (1998). The inaccuracy was in the attribution to Cheung and, indirectly, in repeating a highly-distorted version of a story without noting the distortion.
In any case, I think the inclusion of this ridiculous story in the published article is informative. Not directly informative on the economic theory described in the paper, but indirectly informative, in that this fake-o story about the “titled English woman” has spread widely among economists—indeed, so widely that the authors write, “the incorrect quote [sic] also appears in other earlier sources,” and so widely that they didn’t even think to check it, they just blindly attributed it to Cheung (1983, 8). A story so well known it didn’t need to be checked.
Now that’s interesting to me—that this elaborate story, originally based on someone’s childhood memory and then transposed to a different part of China, in a different century, with an entirely different cast of characters, became common currency in some academic circles.
It’s interesting what people will believe without questioning, if it fits with their model of the world. In this case, hard-nosed economists, self-employed laborers, boat rowing on the Yangtze, and, as a foil, a soft-hearted upper-class reformer who doesn’t understand the real world.
So here’s what I think the correction notice should have said:
In our paper, we attributed to Cheung (1983, 8) a story that actually appeared in Jensen et al. (1998). The Chung (1983) story is:
My own favorite example is riverboat pulling in China before the communist regime, when a large group of workers marched along the shore towing a good-sized wooden boat. The unique interest of this example is that the collaborators actually agreed to the hiring of a monitor to whip them.
Further background is supplied by Chung (2018):
In 1970, Toronto’s John McManus was my guest in Seattle. I chatted to him about what happened when I was a refugee in wartime Guangxi. The journey from Liuzhou to Guiping was by river, and there were men on the banks whose job was to drag the boat with ropes. There was also an overseer armed with a whip. According to my mother, the whipper was hired to do just that by the boatmen!
Here is the story as printed in Jensen et al. (1998), which is a collection of practice exam questions:
On a boat trip up China’s Yangtze River in the 19th Century, a titled English woman complained to her host of the cruelty to the oarsmen. One burly coolie stood over the rowers with a whip, making sure there were no laggards. Her host explained that the boat was jointly owned by the oarsmen, and that they hired the man responsible for flogging. (Source: Steven Chung [sic].) Explain why such an organizational arrangement would arise voluntarily.
This differs from Cheung’s original version in several minor ways (moving the location from Guangxi to the Yangtze river, changing the time from the twentieth to the nineteenth century, changing from boat pulling to rowing, and adding the colorful phrase “burly coolie”) and in a few major ways (stating that the laborers were owners of the boat, which was not in the original story, changing the female character from a Chinese refugee to a “titled English woman,” having the woman “complain,” and adding a new character whose job is to explain the situation to her.
This is a story some economists like to tell. Our retelling of this story that so neatly fits our theoretical model, without reflection on the story’s fictional nature, perhaps reflects an excess of faith on our part, and suggests we should be careful when trying to apply this model to the real world.
That would do it. Or, if such a correction would be too long, here’s something shorter, to the point, and without defensiveness:
In our paper, we attributed to Cheung (1983, 8) a story that actually appeared in Jensen et al. (1998), which is a collection of practice exam questions. The story as related by Jensen et al. and copied by us is a much distorted version of Cheung (1983), which according to Cheung (2018) derives from a memory of a story told to him as a child.
They could leave it to the readers to decide whether this error affected the substance of the paper.
The best part is that the whole story relies on “according to my mother” a fairy tale told by the mother of a refugee child in a war torn country so her child doesn’t have to confront the truth… Which is likely that the boat pullers were slave labor and being whipped by a slave driver.
Economics in one lesson.
Daniel:
Yes, as the correction notice unfortunately didn’t say, these economists’ retelling of this story that so neatly fits their theoretical model, without reflection on the story’s fictional nature, perhaps reflects an excess of faith on their part, and suggests they should be careful when trying to apply this model to the real world.
The bigger story is Economic models more generally. How much of what people learn about economics, particularly in the undergrad or masters level is totally unsupported by any real facts? or supported by straw-man NHST, or works theoretically but in the real world is extremely poor at predicting what happens because it ignores important real-world considerations (the equivalent of sliding a block down a frictionless ramp compared to rolling a tennis ball down a rocky mountain?)
Let’s just take one simple interesting recent example… the 5 year history of chicken egg production and retail prices.
There are some relevant facts:
Chicken production has been rolled up into an oligopoly (there’s even a word for it in farming “chickenization”).
The COVID pandemic disrupted a lot of industries supply chains etc. This is certainly true
The COVID pandemic disruption was widely known in consumer circles.
A severe Bird Influenza did just pandemically circle the globe killing a large number (though a small fraction) of chickens.
The federal govt overnight increased the M1 money supply multiplying it by a factor of 4 in early 2020.
A lot of individuals had money and savings excess of their previous values during the pandemic because of either direct relief, student loan relief, eviction prevention, etc.
There are of course a bunch of other relevant pieces of info which might need to be admitted, including for example changes in patterns of food consumption like reduced restaurant consumption and/or changes in food waste.
Retail egg prices skyrocketed. I don’t have exact numbers but in 2019 maybe eggs were $2/doz and in first half of 2023 they were somewhere around $8 in CA. I’m sure the Consumer Expenditures Survey or something has the history.
Now, my task for the economists is to *provide a detailed model of how that worked* and support it with both theoretical model as well as empirical data. Specifically, I want a state-space model which describes the evolution of price as a function of “the current state” with whatever relevant state they want included.
I don’t think they’re anywhere close to being able to do that. There’s plenty of handwaving and theory, but if anyone can point me to a state space model through time that describes the time-series in the way that for example lotke-volterra + Bayes did for Lynx data https://statmodeling.stat.columbia.edu/2012/01/28/the-last-word-on-the-canadian-lynx-series/ I would admit that Economists have some idea what they’re up to. Otherwise, it just feels like they’re the new high priestesses advising the king on the basis of religious beliefs. There’s no way to either confirm or falsify their discussions of how important various factors are, because there’s no real empirical basis for their results.
Note that I’m posing a question which is both micro-economic and macro-economic. But it’s primarily micro-economic. Chicken egg prices should be predictable from household income, household expenses, egg-laying numbers, chicken stock, chicken deaths, chicken maturation to egg-laying, transportation prices, changes in restaurant consumption, and a few other things related to households and chicken production. It shouldn’t be required that you know the price of tea or steel or the aggregate demand for explosives or hard drives or exchange rates for Brazilian Reals.
The M1 value is an artifact:
https://fredblog.stlouisfed.org/2021/05/savings-are-now-more-liquid-and-part-of-m1-money/
Really for money supply you need to add all public debt (~ $30 trillion) to the private debt (~$60 trillion).
Then there is all the off-shore dollar-denominated debt (“eurodollars”). No one knows how much of that exists, probably at least $10 trillion but more likely in the $100s of trillions.
So the first issue with a quantitative model is not knowing the money supply.
The second is knowing the dynamics of how money flows from the debt issuers into particular product. Imagine the snowcap melting on a mountain and trying to calculate how much water is collected in a particular cranny halfway down the side, at a given point in time. Afaict there is little interest in figuring this out either. I mean Cantillon effect doesn’t even have a wikipedia page.
Anoneuoid: it is worse than that. Dan Davies points out that there is a lot of short-term commercial debt which is rarely centrally tracked and only sometimes recorded in accounts. Its just inconvenient to have every sale be simultaneous, so usually one side provides the money or goods then the other provides the goods or money. These days it happens on a colossal scale, as when a supermarket takes in goods and pays for them exactly 59.5 days later so it can invest the money in the meantime but not have to pay a penalty to the supplier, but it is one of the aspects of the economy which is very hard to track, especially in smaller businesses which don’t perfectly implement accounting rules.
After thinking a bit, I’m not sure how or if such debt would contribute to the money supply. When a bank “prints” there is new money added to a ledger that then gets spent on something. It seems like in your case the supermarket has the money but the supplier doesn’t, which affects *where* the money goes but not the total amount.
I couldn’t find a link of him talking about it, but would be interested to learn more.
Anoneuoid: I don’t understand any of the definitions of ‘money supply’ but in double-entry bookkeeping I think in this situation the supermarket gains 1 talent worth of goods and a debt of 1 talent to the supplier. It therefore controls an extra 1 talent worth of assets until the debt is due, and can use those extra assets for things like selling them for cash and lending the cash on the money market. The creditor has a contract saying that the supermarket will pay them 1 talent within 60 days, but that is an asset which is harder to use. In double-entry bookkeeping, every debt is balanced by a credit, so ‘expanding the money supply’ just increases the magnitude of the total debts and credits in society.
Dan Davies explains the importance of short-term commercial debt which is never mediated through a bank in his book “Lying for Money.” He also explains how this kind of debt is fundamental to a class of frauds, and the general principle that controlling assets or seeming to control assets is useful even if you promised to give them back.
Anoneuoid, thanks for that, I didn’t realize that they added an entire class of stuff to the M1 supply (savings accounts). Still, M2 should show us better what happened, and M2 increased overnight by like 20%.
Ironically, the Lotka-Volterra predator-prey model is *exactly* the same kind of toy model that you’re criticizing in economics. You’re doing the opposite of the typical physicist-caricature approach of assuming that other fields are easy (obxkcd https://xkcd.com/793/), and assuming that the toy models in other fields must be *better* than yours. L-V models do convey a grain of truth, which is that ‘natural enemy-victim’ systems (predator-prey, host-parasite, etc.) tend toward dynamical instability due to (effectively) time-lagged feedbacks. However: (1) predator numerical responses are not linear functions of prey density; (2) prey populations are limited by other factors as well as predators [and indeed may undergo pred-prey dynamics with their food sources]; (3) lynx and hare are embedded in a giant food web of other species doing other stuff; (4-n) behavioural responses, genetic/evolutionary effects, exogeneous drivers such as the weather, …
Wengersky (1978): “Perhaps the most famous examples have been found in the fluctuations of arctic animals: the snowshoe hare-lynx (50),and the brown lemming-grass (206) interactions. Neither of these cycles has yet been demonstrated conclusively to be due to a prey-predator interaction, in spite of many years of work. It is unlikely that any amount of statistical analysis or collection of data in the field will settle this question; long-term field experiments are clearly necessary. Somewhat better data and analyses are available from insect populations (88,218), in part because of the shorter life spans of the organisms involved.”
This is from 1978, but even after the Kluane project (https://www.zoology.ubc.ca/~krebs/kbook.html) spent 10 years 1986-1996 doing extensive experiments in the Canadian Arctic; the answer is still “it’s complicated” …
Wangersky, Peter J. 1978. “Lotka-Volterra Population Models.” Annual Review of Ecology and Systematics 9 (1): 189–218. https://doi.org/10.1146/annurev.es.09.110178.001201.
PS now that I have written that long response, I see that many ecologists chimed in with the same general points 11 years ago, in the 2012 thread that you link to above … the discussion was more about “appropriate statistical methods for fitting models to data” rather than “status of toy models”, but still …
Hey Ben, hoping your “long response” is being held and will come through soon rather than having gotten lost entirely. looking forward to it.
Here is what I think:
1) A customer gets a loan for $100 from the bank.
– The bank adds $100 to their checking account. It then simultaneously marks down a $100 liability (the bank owes the customer) and a $100 asset (the customer owes the bank). So everything is balanced but $100 that didn’t exist before has been “printed” into existence.
2) Customer spends $100 at the supermarket on some items being sold at-cost.
– The bank transfers the $100 from the customer’s account to the supermarket’s account. No new dollars were created.
3) Supermarket pays suppliers $100.
– Once again, no new dollars were created they are only transfered from one account to the other. It does not matter if payment is delayed two months, that only determines where else those dollars may flow/sit in the meantime.
However, the supplier has an asset ($100 owed by supermarket) it can use as collateral for its own loan. This can be from its own suppliers or the bank. If the latter, it is once again the bank “printing”. If the former, eventually some upstream supplier is going to terminate the chain, either as collateral for a loan from the bank or simply be owed money for some time.
So maybe these short term commercial loans can increase money supply, but only via the banks. It should be counted already.
It still seems the size of the eurodollar market is the big unknown. If the measured M2 increases by $5 trillion, that does not mean the total money supply increased by that much. The number of eurodollars can decrease to cancel it out or also grow to amplify it.
We just don’t know. Like if the US started paying off the public debt, at first glance that seems deflationary. But would that mean a bigger market for private/offshore debt?
Ben, sure Lotka-Volterra is about the simplest thing that will get you the dynamics you need to explain booms and busts in lynx and hares. It’s kind of stupid simple, but it still seems dramatically more realistic than whatever Econ explanation you’d likely get for egg prices. Have you read any articles on egg prices? Economists get quoted saying stuff that’s just articles of faith about bird flu and increased demand due to pandemic savings and low marginal elasticity and whatever. None of those things are measured.
Have you ever heard of an economics model that even has time involved at anything other than a PhD research level? An undergrad first year in physics will start with balls falling under gravity. Position is a function of time. Is there even a toy econ model in the first 5 years of college level study with time involved? I’ve only taken a few econ classes so maybe a year of instruction, but I never once saw time mentioned anywhere. I have it on authority from a professor of econ that most undergrads in econ at a UC system school never take an ODE class.
I would just like to know, what factors contributed most to egg price dynamics? Total egg lay changed at most a couple percent across the entire time period. Yes some of those eggs had to be used to replace the 5-10% of laying hens that were lost to bird flu of course. And maybe some of them had to be wasted after outbreaks. That should all be measurable. And prices are set at the margin… So ~10% reduction in supply resulted in a 4x increase in price? That seems unlikely. We’ve had those kinds of fluctuations in production in the past without such price shenanigans. So what role did cooperative price fixing among the 5 largest “chickenized” integrated oligopolists play? Where does that enter into the model? Also, what about changes in restaurant demand? Maybe people suddenly increased their patronage of breakfast restaurants after a couple years of COVID? Etc etc. Just give me **any data based quantitative explanation for the time history of egg prices since 2019 which even approximately fits the data at all**
Just show me that economists have any clue at all. I really want to believe they aren’t scammers primarily existing to provide cover for powerful politicians and oligopolists… I LIKE economics. I’m a pushover. Just show me anything that shows they are actually addressing the issue with appropriate tools.
Some egg articles:
“It’s california’s proposition 12” https://www.dailybreeze.com/2023/02/18/prop-12-is-behind-egg-price-spikes/
“It’s pandemic avian flu and the COVID supply chain and cage free eggs, and supply and demand” https://money.usnews.com/money/personal-finance/spending/articles/why-are-eggs-so-expensive-right-now
similar story:
https://www.latimes.com/california/story/2023-01-07/7-a-dozen-why-california-eggs-are-so-expensive-and-increasingly-hard-to-find
The story about how 57 million birds were culled… seems to be pretty significant, until you realize that there are 9.2 Billion broiler chickens produced alone in the US, and most of the culled chickens were broiler. So, we’re talking about a reduction in chicken population of 0.6% but sure a lot of these chickens are turned over every 2 months or so… so let’s see the population might be closer to 9B*2/12 at any given time so it could represent a 3-4% reduction in actual stock of chickens, still mostly broiler. Hardly a catastrophe resulting in 4x the price. Av
Essentially everything you read in the news including everything said by any Agricultural economist is pure unadulterated quantitative-free propaganda made to sound like they have a clue what they’re talking about.
“It’s supply and demand” is like saying “it’s the water cycle” to explain why california had more rain this year than in the last 10 years combined. It’s not a model it’s just words meant to keep you from asking questions.
Here’s egg lay in the US https://unitedegg.com/facts-stats/ it was flat 2020 and 2021 but up 2022. And demand for eggs declined every year since 2020…
So put that in your economics pipe and smoke it…
I just ask Father Guido Sarducci when I have Economics questions https://www.youtube.com/watch?v=kO8x8eoU3L4
Just saw this part of the thread – about the definition of the “money supply.” One of the many reasons I never teach macroeconomics (there are many) is that I never understood the traditional textbook definition. Almost every introductory text contains a section along the lines of “are credit cards money?” The answer is always no – credit cards simply are a device that permits you to more efficiently use money – the money is ultimately what you have in cash and checking accounts (and sometimes other types of accounts). But in my view, the unused credit balances people have on their cards is something that people can draw on if they want to make more purchases. In that way, the Fed can’t “control” the money supply very well – they can tighten M1 and M2, but if people want to spend, they can just use more of their credit lines on their cards. In that way, credit card lines can be part of the money supply – and a part particularly difficult for the Fed to control.
But my thoughts are apparently wrong, as virtually every intro economics book tells me.
My first reaction on revisiting this (meta) story is that it reflects a cynical approach to story-telling. According to this view, only large-sample data with desirable statistical properties contribute anything empirical of substance; less than this is anecdote. So it doesn’t matter if an illustrative story is straight or embellished, factual or fictitious. Its role is just to provide an intuition. Hence, there’s nothing important to correct.
Then I thought some more and realized this disdain for single cases reflects the empirical morass that economics (and maybe not only) has fallen into. Causal inference is assumed to be something best approached through experimental design: control for confounders, properly identify and you can infer causation. Well, yes, that can generate evidence, but in most sciences causal interpretation benefits from direct observation and case-level testing on the presumed mechanism. You don’t get causation just from epidemiologists even if they do RCTs, you need someone pecking away at tissue samples, sequencing virions, etc. I spent decades on the fringes of the compensating differentials/occupational H&S literature, and I can’t recall a single economist studying a single cluster of cases, like a workplace with workers and managers who can be interviewed.
The story and its correction both imply that there is nothing to actually learn from such a story. I think exactly the opposite. If there were an instance of a group of self-managing workers who hired an overseer to punish them into productivity, we could learn a lot from close examination of it, including how self-management might be extended without resorting to this crude device. (Coop contract design….)
Next you’re going to tell me The Garden of Forking Paths isn’t a true story either! How will I shape my intuitions without a factual story?
Jackson:
Fake stories are just fine. I’m always talking about how I loooove fake-data simulation. I also enjoy reading fiction and I think I’ve learned a lot from it.
If an economist wants to have a theory and illustrate it with a made-up story to help our intuitions, that’s great! Pin factory, whatever. My problem with the riverboat story is that all these economists were presenting it as real when it wasn’t.
I checked what the job would be like to see if the modifications changed the context of the story. Check out the terrain. Its all tower karst, caverns, and sink holes: https://en.wikipedia.org/wiki/Guangxi
Imagine dragging a boat along those banks for 200 km, maybe you would hire a guy with a whip.
I wonder if they were nudged into believing this story was true.
I’m reminded of Frederic Bartlett’s work on the social transmission of information from the 1920s (i.e., the “war of the ghosts” stuff), in which undergraduates read stories containing unusual (to them) features, and then passed their accounts of the stories on in a chain. As the chains continued, the stories became both more error-prone, and more consistent with the undergraduates’ expectations. See: https://www.tandfonline.com/doi/abs/10.1080/0015587X.1920.9719123
(I guess a major difference is that, whereas the undergraduates didn’t have subsequent access to the original story to correct their accounts, these authors easily could have done so.)