When people are not trusted, their words, I notice, merely drift about without force in themselves and without inspiring confidence in others. But when people are known to have a respect for the truth, their words are just as powerful as other people’s force in securing any object at which they aim. If they want to bring anyone to a proper sense of his position, I know that threats from them have just as much of a sobering effect as actual punishment inflicted by others. And if people of this sort make promises, they gain their ends just as successfully as others who pay out money on the spot. Think of your own case. How much did you pay us before you gained our alliance? You know that you paid nothing at all. No, we trusted you and believed you would be true to your word, and so you raised a great army to march with you and gain you an empire worth not only the thirty talents, which our men think they should be paid, but many times as much. First of all, then, it is this feeling that you can be trusted–the thing which won you your kingdom–which is being bartered away for this sum of money.Xenophon, The Persian Expedition 341-42 (Rex Warner trans., Penguin Books 1972).
My colleague Brian Frye launches an eloquent attack on the norm against plagiarism (Jot here). But his real target, I think, is the academic ego, and I wonder whether deflating it doesn’t require stronger, rather than weaker, norms.
Economic systems generate value by creating incentives for people to undertake productive activity. In market economies, we do that by giving firms property rights in what they produce. That ensures that firms that produce what consumers want can insist upon payment, and those payments in turn serve as the means by which consumers reward good behavior and ultimately dictate what the economy should produce.
The system falls apart, however, if the signals consumers send to firms through their purchase decisions don’t get routed properly to those who are best able to respond to them. If consumers want more grapes and less tonic, then grape producers need to get the “produce grapes” signal and tonic producers need to get the “stop producing tonic signal.” If tonic producers get the “produce grapes” signal, then more grapes won’t be produced and the system will fail.
The anti-plagiarism norm is just another approach to achieving proper routing of incentive signals, one that is optimized for the production of ideas in which the academic community engages. Academia creates incentives for scholars to produce work that is useful to the community by rewarding influence, rather than mere fact of making something that others are willing to acquire and read, as the market might do. Scholars who generate ideas that other scholars find useful, in the sense that other scholars see fit to discuss the ideas or build upon them, receive promotions and appointments at the most prestigious institutions.
In order for this system to function, faculty promotion and hiring committees must be able to measure influence. They do that by counting citations–the number of times that other scholars have referred to a particular scholar’s work–and by evaluating placement, meaning the prestige of the journals or academic presses in or with which the scholar publishes work. Influence implies originality; a scholar who uses another work to influence a third party merely serves as a conduit for the influence of the other author. Because editors select texts for publication based on originality, placement measures the promise of influence. The editor’s decision to publish at once signals the editor’s belief that the work should exert influence and helps the work toward that end, by giving the work a prominent display.
The anti-plagiarism norm facilitates the measurement of influence, by making it easier for promotion and hiring committees accurately to count instances in which the work of one scholar has been relied upon by other scholars. It also makes it easier for journal editors to determine what part of a scholar’s work is original and what part not. A scholar who scrupulously cites to the work of others whenever the scholar has relied upon it enables committees evaluating those other scholars to observe that the first scholar has been influenced by them. And a scholar who scrupulously cites to the work of others also enables editors to determine quickly the extent of the scholar’s own original contribution to the field. Eliminating the anti-plagiarism norm would make citation counts and placements less accurate measures of influence.
Which is why plagiarism makes scholars so angry. Every failure to cite causes the metrics upon which committees measure influence to diverge from actual influence, with the result that influence, the very end of scholarship (in the sense that truth in science is measured by acceptance), is not rewarded.
I’m tempted to add here that plagiarism makes academics angry because it’s theft. But plagiarism isn’t theft, because academics don’t own ideas, as Brian rightly points out, and the incentives system academics employ is in any case not a market-based incentives system. Plagiarism is only like theft, and gives rise to anger that is only like the anger aroused by theft, in the sense that plagiarism subverts the academic incentive system in the same way that theft subverts the market’s incentive system. A consequence of theft is that you are deprived of what you deserve, because you worked to produce it, or to generate the money you needed to buy it. And that makes you angry. A consequence of plagiarism is that you are deprived of the promotion or job that you deserve, because you generated sufficient influence to merit the promotion or appointment. And that makes you similarly angry.
So plagiarism is like theft, but still remains its own separate kind of transgression. Indeed, I’d hazard that plagiarism is a more dangerous offense, more likely to elicit a cruel response from its victim, than mere theft, because plagiarism is in the mode of a snub. To snub is to ignore, shun, count out. It inflicts a social wound, in contrast to theft’s harm to property. Social wounds cut deeper.
Although Brian at points acknowledges the limits of the property metaphor, at other points he embraces it. He writes that “academics want to own ideas. Copyright is useless to them, because it can’t protect what they want to own. So they create plagiarism norms that give them what they want, when copyright can’t provide.”
But academics don’t want to own their ideas. Indeed, they give them away for free. They do, however, want credit for them toward promotion and hiring, and perhaps in the eyes of posterity, which is why they decry plagiarism. The anti-plagiarism norm does not erect a property system, but it does facilitate a more accurate accounting of the performance of scholars.
One way to test this incentives account would be to see whether scholars tend to object more to plagiarism in academic work than to plagiarism in media that promotion and hiring committees, or academic peers more generally, do not usually consult.
I suspect that they do. If a high school student plagiarizes my scholarly work for a term paper that only a high school teacher will ever read, I am unlikely to become angry. I might even be flattered that my work has percolated so far. But if a scholar plagiarizes my work in an academic publication, I will be angry. The reason the high schooler gets off is that the value of my influence on him to promotion and hiring committees is zero.
Now, the student’s high school teacher might well object to the student’s plagiarism. But that is consistent with my incentives account. Because the plagiarism undermines the classroom incentives system, even if it does not undermine the academic incentives system. To induce students to do original work, the high school teacher must be able to identify original work, and reward it. Plagiarism undermines the high school teacher’s ability to do that.
The incentives theory also explains why ghostwriting often does not run afoul of the plagiarism norm. The anti-plagiarism norm comes into play only where non-market-based reward systems are concerned. When the only rewards desired or received are through the market, plagiarism is not needed for proper routing of incentives, because the market handles that. So for example the ghostwriting of autobiographies or romance novels raises no hackles because the nominal authors are not going to win any writing awards, or generate any esteem as serious literary figures. These books are written for profit. Nothing more.
But I’m sure that a winner of a Pulitzer or Nobel who relies on ghostwriting would come in for serious censure. Because those awards are about creating incentives for authors to engage in original, influential writing. An author who gets the award despite not having made such contributions takes the award from someone who did make real contributions, and thereby subverts the incentives system.
It’s no use arguing in response that the incentives theory doesn’t fit because a ghostwriter has by definition voluntarily renounced any claim to recognition, and indeed may well be content to create great works without any non-financial incentives whatsoever. Because there must be someone else out there, some other author, who has produced great original work, and who did it in hope of receiving the award. That other author will not get the award because it has gone instead to the undeserving employers of the ghostwriter. So an incentive will still have been lost, routed incorrectly.
I cannot therefore agree with Brian that the differential treatment of ghostwriting suggests that “plagiarism is a crime only when it harms the economic interests of authors, but is fine when it benefits them.” Plagiarism is a crime when rewards are doled out based on influence, but not, as in the case of most ghostwriting, when rewards are doled out only based on consumer demand. In that latter case, the market system is at play, and the goal is to reward those who bring products to market that consumers like best. Unless consumers care how the product is produced, and for most ghostwritten work they don’t, copyright is all that’s needed to ensure that those who bring what consumers want to market get rewarded for doing it.
(Occasionally consumers do partake of the cult of authorship and demand that authors not be ghostwriters, in which case a failure to disclose ghostwriting feels, to the consumer, like fraud. This, I suspect, is the origin of the mistaken notion that the anti-plagiarism norm is really an anti-fraud norm. As Brian rightly points out, plagiarism is actually rarely about protecting the reader as a general matter. It is instead, as I have been arguing here, about ensuring that authors are properly rewarded for influence in those communities, such as academia, in which influence is valued.)
The incentives theory also explains why there is no plagiarism norm in court filings. Lawyers, like academics, do strive to influence others through their work, but lawyers’ targets for influence are judges. And judges make clear enough, to the clients who dole out rewards to lawyers, whether their lawyers are influential, by ruling for or against. You don’t need to count cites here, just wins.
Brian asks: “Can I consent to plagiarism? Or rather, do academic plagiarism norms permit me to consent to plagiarism? If not, why not?” The answer, he points out, is of course no. But I do not fully understand his argument that the reason for this “no” is that the anti-plagiarism norm amounts to “cartel rules.”
Academia is not an idea cartel. Cartels restrict output, and thereby drive up price. But academics don’t restrict the output of their ideas in order to extract a higher price from those who buy them. Academics give their ideas away for free. Scholars don’t agree not to publish papers, for example, until the public, or university administrators, consent to pay more for those ideas.
One might argue that universities use common hiring standards artificially to restrict the number of academics they hire, and that this in turn restricts the supply of ideas, since it is difficult for those not employed in academia to find time to produce and disseminate ideas. But universities do not sell their faculties’ ideas. Students pay for teaching. They don’t pay for research. To the extent that there is a hiring cartel (and I don’t think there is), it profits by rationing teaching, not scholarship, which makes the cartel analogy unsuitable to a discussion of the anti-plagiarism norm.
If what Brian means by cartel rules, however, is only that the anti-plagiarism norm is a rule by which a community structures a system of incentives for its members, then I am in agreement. And this does explain why neither Brian nor anyone else can authorize others to plagiarize his work. While many authors do get angry when the norm is violated, the norm is there ultimately to benefit the community, not any one member thereof. Promotion and hiring committees want not only to know that Brian wrote his article attacking the anti-plagiarism norm, but, even if Brian does not care to receive a reward for it, also to know that whoever plagiarized the article did not write it, and therefore should not receive a reward. Only then can the committee ensure that the incentives that it doles out are not wasted.
I am also unsure why Brian calls the anti-plagiarism norm a “tax imposed on junior scholars.” I take his point that because senior scholars have a larger oeuvre, juniors may spend more time citing seniors than seniors spend citing juniors. But it does not follow that juniors spend more time citing overall than do seniors, unless we assume that seniors have more original ideas than do juniors. Seniors will also spend time citing each other, and juniors and seniors both cite the dead, as Brian observers. Indeed, as Brian also observers, all works stand on the shoulders of a very large group of giants. So large, in fact, that the few living giants upon whom juniors may stand surely constitute a negligible part of the whole. Everyone should be doing a lot of citing. And the anti-plagiarism norm helpfully ensures that they do.
What comes across very clearly in Brian’s article is contempt for academic egotism. In my favorite passage, he writes:
I will be blunt. Scholarship is rarely–if ever–original. At best, it is occasionally pithy enough to be quotable, or thoughtful enough to be worth a citation. Even on those rare occasions when a scholarly work actually introduces a novel idea, scholars do not and should not own those ideas, not even to the limited extent of a right to compel attribution. We should be humble. Scholarship is the gift we provide to each other and the public. More often than not, it is a gift better loved by the giver than the recipient. Attribution is also a gift. We should accept it graciously and thankfully when provided. But we should never demand it, or expect others to demand it on our behalf. After all, good scholars copy, but great scholars steal.
Fair enough. And I tend to agree with Brian’s argument elsewhere in the paper that the anti-plagiarism norm is vague in ways that sometimes lead to gross injustice for well-meaning authors. Oliver Sacks’s essays, The Fallibility of Memory and The Creative Self, speak powerfully to the way copying can often not only be unintentional, but an essential part of the creative process, which goes as well to Brian’s point that “great scholars steal.” Sacks writes:
Webster’s defines “plagiarize” as “to steal and pass off as one’s own the ideas or words of another; use . . . without crediting the source . . . to commit literary theft; present as new and original an idea or product derived from an existing source.” There is a considerable overlap between this definition and that of cryptomnesia, and the essential difference is this: plagiarism, as commonly understood and reprobated, is conscious and intentional, whereas cryptomnesia is neither. Perhaps the term “cryptomnesia” needs to be better known, for though one may speak of “unconscious plagiarism,” the very word “plagiarism” is so morally charged, so suggestive of crime and deceit, that it retains a sting even if it is unconscious.”Oliver Sacks, The Fallibility of Memory, in The River of Consciousness 101, 108-09 (2017).
What is at issue is not the fact of “borrowing” or “imitating,” of being “derivative,” being “influenced,” but what one does with what is borrowed or imitated or derived; how deeply one assimilates it, takes it into oneself, compounds it with one’s own experiences and thoughts and feelings, places it in relation to oneself, and expresses it in a new way, one’s own.Oliver Sacks, The Creative Self, in The River of Consciousness 129, 142 (2017).
Sacks goes on to reproduce a speech given by Mark Twain at the 70th birthday of Oliver Wendell Homes, father of the Supreme Court Justice, and a well-known physician and poet in his day.
Oliver Wendell Holmes [was] the first great literary man I ever stole any thing from–and that is how I came to write to him and he to me. When my first book was new, a friend of mine said to me, “The dedication is very neat.” Yes, I said, I though it was. My friend said, “I always admired it, even before I saw it in The Innocents Abroad.”
I naturally said, “What do you mean” Where did you ever see it before?”
“Well, I saw it first some years ago as Doctor Holmes’s dedication to his Songs in Many Keys.”
Of course, my first impulse was to pare this man’s remains for burial, but upon reflection I said I would reprieve him for a moment or two and give him a chance to prove his assertion if he could: We stepped into a book-store, and he did prove it. I had really stolen that dedication, almost word for word . . . .
Well, of course, I wrote to Doctor Holmes and told him I hadn’t meant to steal, and he wrote back and said in the kindest way that it was all right and no harm done; and added that he believed we all unconsciously worked over ideas gathered in reading and hearing, imagining that they were original with ourselves.
He stated a truth, and did it in such a pleasant way . . . that I was rather glad I had committed the crime, for the sake of the letter. I afterwards called on him and told him to make perfectly free with any ideas of mine that struck him as being good protoplasm for poetry. He could see by that that there wasn’t anything mean about me; so we got along right from the start.Oliver Sacks, The Fallibility of Memory, in The River of Consciousness 101, 111-112 (2017).
Moral censure is useful against the intentional plagiarist. But I suspect that in many, many cases, intent is lacking, and what is required is only a good-natured acknowledgement that the author either didn’t read enough before putting pen to paper, or read too much, combined with ex post attribution, to keep the incentives system properly triaged. Brian is right to call out the intemperance and “mob rule” that characterize many plagiarism events.
One hopes, in fact, that technology will make the anti-plagiarism norm obsolete before too long. One can imagine an AI-super-charged version of Turnitin that provides scholars–and in particular promotion and hiring committees–with accurate measures of a scholar’s influence without anyone needing to cite the scholar’s work. The program would comb through the sum total of human intellectual output, identify unique ideas, and trace their influence. We wouldn’t need to acknowledge each other’s work anymore; the computer would keep track of that.
Whether that comes to be or not, I can’t help wondering whether the solution to the problem of big egos that vexes Brian isn’t to have more academic policing, not less. If the system is promoting and rewarding people who don’t deserve their egos because they don’t do original work, that can only be because those people are not doing a good job of attribution themselves, and the system is failing to call them out for it. The problem may not be that they are recycling others’ work, but that they are simply failing to make themselves fully aware of what has come before. The solution is to strengthen the plagiarism-related norm that quality scholarship must reflect deep research.
Not long ago, I had the privilege of chatting with an eminent historian. What struck me was the importance that he placed on reading, and reading deeply, in his chosen subjects. Of course, as a historian, he meant reading not just in secondary sources, but primary sources as well. “How can you write a book about X,” he seemed to say, “if you haven’t dug into the private, unpublished, papers of Y? How can you presume to know everything that’s been thought about this subject before you have done that?” Legal scholars can’t always go that far, but my sense is that often they could go much further than they do.
Legal scholars don’t, because the academic police aren’t on the beat.
But they should be.
[H]e engraved on a stone the whole story.The Epic of Gilgamesh 61 (N. K. Sanders trans., Penguin Books 1960).
Bronze age rulers erected steles so that their words would endure. We do that today with blockchain.
Almost everything we know about ancient Egypt, for example, even the name “Ramses,” comes to us from steles and other inscribed stones dug out of the sand as many as 5000 years after pharaohs ordered them carved. Inscriptions in stone endure because stone is difficult to work. Hard to destroy; harder to recarve in ways that do not betray the fact that recarving has taken place. When the pharaohs made a record in monumental stone, they made public records the authenticity of which could be verified, even by scholars working millennia hence.
But that’s just what blockchain does for the internet. Blockchain inscribes information onto computer memory in a manner that, like a stone carving, is very difficult to change.
Making the information stored in computer memory permanent is not easy, because computer memory is engineered for rapid change. Computers record data by rearranging the electrons adhering to the physical material of a disk, tape, or chip. Changing the data therefore requires no more than an application of electricity.
The ease with which data can be changed in computer memory is the source of computing’s power, driving the cost of communication almost to zero. In the millennia following the carving of the first steles, which are very costly to create, civilization succeeded at finding increasingly inexpensive methods of recording information. But even the most inexpensive methods devised, such as paper, still required costly manipulation of matter on a macro scale–the application of inks–to be useful. Computer memory outdid all alternatives by requiring only manipulation of the utterly insubstantial electron.
But with the reduction in costs came impermanence. You, or a hacker, could change your data without leaving a trace of what came before. Indeed, without anybody being able to say for sure whether your data had been changed at all.
Blockchain tries to solve the problem of data impermanence, while preserving all of the advantages of electronic computing and communication, by storing data in an encrypted format. Changes to the data not made using the proper format can immediately be detected by readers. So merely changing the data electronically, while just as easy as it has always been, won’t fool readers, who can see that the changes don’t conform to the standard.
Indeed, the fact that blockchain solves the impermanence problem without changing the basic ease of storing data with electrons means that blockchain allows computers to continue to communicate quickly and cheaply. Data endures because it has been tied to encryption cyphers, not because it has been tied to the physical world, as in the case of a pharaoh’s steles.
A different approach to the problem of internet permanence would be to rig up a computer system in which robots would store data by automatically carving the data onto stone tablets. That too would solve the permanence problem. Anyone who wanted to verify the data could inspect the stone tablets to ensure that they had not been altered, just as archeologists inspect ancient steles today. But having computers write data to steles would make it difficult to copy and transfer that data even when the data has not been altered. Blockchain captures the unalterability of stone inscriptions without suffering from limits on communicability associated with the use of stone as a medium.
But why exactly does encryption breed permanence? Can’t you just crack the code and change the data in a way that respects the encryption format and therefore is not detectable by others? The answer is no because cracking codes is hard, requiring powerful computers, lots of electricity to run them, and time. Just as effectively rechiseling a stone inscription requires expertise, energy, and time. So blockchain uses encryption to restore the permanence in data that the information age destroyed.
With one important difference. Blockchain is an effective check on the undetected rewriting of data, as are steles, but, unlike steles, blockchain is no check on destruction of data, in the sense that blockchain makes deleting data from computer systems no harder to do than before. That is the price blockchain pays for allowing users to continue to communicate quickly with each other. Blockchain sits on top of the electron-based storage systems of computers, making it very hard to change the data undetected, but no harder to destroy the data on those systems. An electric shock will still suffice for that.
So the pharaohs still have something on computers, at least with respect to preventing data destruction, rather than just the alteration of data. (Of course, unlike data stored on steles, internet data is stored in multiple locations, forcing the destroyer to travel to be effective.)
Blockchain is so much an artifact of information technology that it could not be useful without that technology. The basic blockchain concept of using encryption to prevent alteration of data has been around forever. People wrote in code in the 16th century as much to keep their words secret as to ensure that what they did write could not be altered imperceptibly. But encoding and decoding are expensive and time intensive, even when you have the key to the code, and are not trying to crack it. Blockchain is feasible on a large scale only because users can rely on computers to determine whether data conforms to the required format. Thus information technology, despite feeding on impermanence, also enables a new kind of permanence.
The tearing down of constraints, so feted in our technological age, is not always a good thing. Nature is constraint. Technology, in mastering nature, removes constraint. But a lack of constraint is chaos, the opposite of civilization. One way to retain constraint is through law, but that has proven a feeble method. The only alternative is therefore to use technology to build artificial constraints back into nature, albeit in ways that are more suitable to our needs than natural constraints once were. Blockchain is an installment in that enterprise.
(I thank Thibault Schrepel and Sam Weinstein for piquing my interest in blockchain.)
Ibn Khaldun famously observed that asabiya (social cohesion) explains the arc of history, and Peter Turchin has done a marvelous job of showing how modern statistical analysis supports this view. Peoples caught at the focal points of conflict develop strong social bonds that eventually propel them to dominance, but dominance and the associated lack of threats erodes cohesion, and over time these groups are replaced by new groups forged in the cauldron of conflict.
The game of chess does a great job of modeling conflict. No other game captures the way circumstance (the juxtaposition of pieces on the board) can create positions of great power and then wipe them away in the blink of an eye.
But while individual chess players learn over time from playing the game, improving as their strategies are tested under conflict, the rules of the game themselves do not take asabiya into account.
One small tweak that would take the game in the right direction would be to upgrade pieces based on the amount of pressure to which they are subject from other pieces on the board. In particular, I would suggest that any piece that could be taken by any one of more than three other opposing pieces on the following move be automatically upgraded one level in value.
So, for example, if white’s pawn could be captured on the next move by black’s bishop, rook, pawn, and queen, then white’s pawn could be replaced with a knight or bishop (the two pieces traditionally considered to be immediately higher in value relative to pawns). If the piece subject to attack from those four pieces is a bishop, then white could substitute a rook for the bishop, because the rook is the next level up in power relative to the bishop, and so on.
The idea behind this substitution rule would be to model the way subjecting a particular group to pressure and conflict–placing it at the center of battle–makes the group stronger. The rule might also help solve the problem of boredom in modern chess, by discouraging the buildup of pressure on particular pieces and encouraging capturing and sacrifices for positional advantage, a la the 19th century era of romantic chess.
There are admittedly some shortcoming to this rule as a step toward modeling asabiya. For one thing, the rule doesn’t really strengthen cohesion between the pieces, unless you think of more powerful pieces as being better able to coordinate with others because more powerful pieces have more freedom of movement under chess rules. The rule seems more to model increases in individual strength. But the rule does do a good job of modeling the power-increasing character of nexuses of conflict.
Perhaps a better rule from the standpoint of modeling asabiya would be to allow any piece subject to attacks from four or more adversaries to swap positions with any laterally or diagonally adjacent piece, as a reflection of the way people in proximity to each other work together to repel threats. But that is too complex to be a good rule for chess.
In her column on congestion pricing, Emily Badger exhibits the unquestioning acceptance of the legitimacy of the price system that lamentably characterizes so much work by progressives today. She argues that because driving has a cost, drivers should be asked to pay that cost through congestion pricing, and she suggests that our current system, in which driving in the city is free, was the uneconomic product of lobbying by the car industry. Hence the title of her column: The Streets Were Never Free. Congestion Pricing Finally Makes That Plain.
In fact, the elimination of bridge and road tolls that took place alongside the popularization of the automobile sat on a sound economic foundation: when the marginal cost of adding another driver to the roads is low, you should encourage as many drivers to use the roads as possible. Charging a price for access discourages use, and therefore unnecessarily limits the number of drivers on the roads.
Accordingly, argued Columbia economist Harold Hotelling in 1938, the proper way to pay for the cost of building and maintaining bridges and roads is to make people pay for them regardless how much they use them — because that way the price won’t limit use — and the only way to do that is to pay for roads and bridges through taxes, rather than by charging tolls. Of course, traffic was not a thing unknown to economists in the early 20th century. But they thought cities would eliminate congestion by building more and bigger roads — expanding supply to meet demand — not by rationing supply, and the efficient way to do that was again by paying for bigger roads through taxes and granting drivers access to them for free. The car industry may have helped the process of de-tolling along, but it was sound economics.
For the time. What everyone missed was that there are more costs to roads than just those of their creation and maintenance: they also destroy the climate, by enabling energy-inefficient driving, as opposed to energy-efficient public transportation. And it turned out that roads simply could not be built big enough to eliminate congestion. So it was not efficient to maximize the number of drivers after all, and the marginal cost of allowing an additional driver onto the roads was therefore not always near zero.
That has led Badger, and the climate movement more generally, to the conclusion that we should have been charging a price for access to roads all along. But that does not follow at all. As Badger points out, congestion and climate concerns make driving a scarce resource, meaning that no matter how high the price charged for access to the resource, more cannot be brought online. So the price system here isn’t needed to stimulate supply; the only work it would do is to winnow down demand to match the fixed level of supply of the resource. That in turn makes price here no more than a rationing mechanism.
And not a necessary one at that. For there are an infinity of ways to ration scarce resources. By birth year. By height. By how early you wake up in the morning. Etc. Price rations based on wealth, and that’s why progressives interested in solving the congestion problem should reject price as the means to that end.
Badger seems unaware that there are alternatives to the price system when it comes to rationing. She observes that:
If we had that problem with other kinds of infrastructure or commodities, we’d charge people more for them. If airline tickets were particularly in demand, their prices would go up. If there were a run on avocados, grocers wouldn’t respond by keeping them as cheap as possible.
All true, but those are all markets in which the goods in fixed supply are sold by private enterprise. Of course private enterprise will use price to ration access, because rationing with price is profitable. But roads and bridges are owned by governments, and governments both have goals other that profit maximization — such as ensuring that everyone has access to basic infrastructure, regardless of wealth — and other ways than price of raising revenue — such as through the tax system. Why is the behavior of markets in the face of shortage a good model for the way governments should behave in the face of shortage?
Moreover, in all the markets Badger mentions, higher prices are capable of calling forth greater supply. When airline prices rise, new airlines enter the market. When avocado prices rise, Mexico sends more avocados. But we aren’t trying to encourage private firms to flood the market with other ways to drive to work. We just want to limit use. We don’t need price for that.
In the information age, non-price approaches to rationing are easier to implement than ever before. I’ve argued that New York should just create an app to grant access to roads during busy periods, routing users to public transportation when congestion is bad. But that doesn’t have to be the only way. A little imagination and attention to technological alternatives could certainly reveal more.
But what we don’t need is unquestioning acceptance of the neoliberal playbook as the solution to our climate problems, or the sacrifice of our values — like the civic value of equal access to public space — that the playbook requires.
To her credit, Badger does seem concerned about the classism of charging for access to the city. But the solution she suggests, subsidized rates for the poor, just can’t work. Any subsidy that truly puts the poor on an equal footing with the rich will defeat the purpose of congestion pricing, by failing to price drivers out of the market. The utilities that subsidize rates to the poor, to which Badger points as a model, don’t use their rates to ration access, as congestion pricing would do, but rather use their rates to cover the fixed costs of maintaining the utilities, so the utilities don’t mind if the subsidy increases demand. Congestion pricing advocates often suggest that the class consequences of congestion pricing can be solved with an administrative tweak; but these tweaks work only to salve guilty consciences.
Legal forms that were well adapted to a world in which wealth was zero sum, and borrowing against an estate could serve no purpose other than to carry out a slow transfer of it to others, were poorly adapted to a world in which wealth could be created, and borrowing against an estate could fund investment that would improve its productivity:
In Hitel Széchenyi argued that Hungary’s agriculture remained unproductive because of its reliance on the unpaid labor of serfs. If they wanted to raise production, landowners should instead employ wage labor on their estates. But in order to afford large numbers of wage laborers or the luxury of experimenting with new technologies, Hungary would also have to rid itself of the legal tradition of entailed estates. Entail prevented the estates of the magnates—the highest aristocrats—from being partitioned or sold. It required that land be passed down undivided according to specific inheritance rules. An entailed estate could not be used as collateral for raising mortgage loans, nor could any of it be sold off to raise funds. These laws made it impossible to use land as a resource for raising the money needed to invest in new technologies or to develop a system that paid wages to free peasant laborers. Széchenyi pointed out that while nobles owned more than two thirds of the arable land in Hungary, a surprisingly high percentage of that land remained uncultivated. And this in a time where 920,000 peasant families in Hungary were registered as “landless.” If nobles could sell or mortgage their lands for credit, they could invest in new technologies of production, and they could pay wages to peasant workers. If they could raise credit, nobles could also fund new manufactures that could employ landless peasants. Széchenyi criticized many other aspects of the feudal system in Hungary, especially the nobles’ continued immunity to taxation, the inability of most peasants to own land, the restrictions that the guild system placed on the free development of manufactures, and the lack of legal equality for the vast majority of the population.Pieter M. Judson, The Habsburg Empire: A New History 111 (2016).
Nine are enough.
You have a set of samples and you are interested in learning something about the probability distribution from which they are drawn. That something is the parameter of interest. It might be the mean. If you do something to the samples, add them together, for example, then you might lose some piece of information that they contain regarding the parameter. But you also might not. Whether you lose information or not by manipulating your samples depends on what you do to them.
For example, if you are sampling from a binomial distribution for which success has value 1 and failure value 0, then adding up the results of the samples won’t destroy information about the mean of the distribution (i.e., the probability of success). That’s because the mean is expressed in the number of successes, rather than their order. You know just as much about the mean of the distribution if your first nine samples are successes and your tenth a failure as if your first is a failure and the next 9 successes. In other words, when you add up the results, you lose information on the order with which the successes occurred, but the mean does not determine that order, and so you don’t lose any information relevant to determining the mean.
When the mean increases, the sample results change because you end up with more successes. So a statistic that counts successes changes too. Both the sample and the statistic change in the same way. That is what happens when a statistic is “sufficient.”
That’s why for a sufficient statistic the probability of drawing a particular sample, conditional on a particular result for the statistic, is independent of the parameter. As the parameter changes, both the sample and the statistic change in the same way. So their relationship to each other remains constant regardless of what happens to the parameter. In a sense, the sufficient statistic transforms the sample, instead of altering it. So any change to the parameter doesn’t change the relationship between the samples and the statistic. Sample and statistic are just different ways of expressing the same thing about the parameter.
The sample conditional on the statistic is just the ratio of the probability of the sample to that of the statistic. This means that if the statistic is sufficient, the probabilities of the sample and the statistic must both be products of the parameter, so that the parameter will cancel out and therefore have no effect on this conditional probability.
Raise taxes until philanthropy disappears. Why should the unelected rich decide how your taxes are spent on public projects?
Saying that adverse selection in insurance is a problem to be eliminated because it frustrates marginal cost pricing is like saying that R&D fixed costs leading to innovation and product improvement are a problem to be eliminated because they frustrate marginal cost pricing.