Tag Archives: academia

University incentives not to punish cheating

Universities have incentives not to expel cheaters, because these students would stop paying fees. By extension, there is a motive to avoid punishing academic dishonesty in any way that increases the chance of the student dropping out, like giving a cheater a failing grade. The university then gives a similar incentive not to punish academic dishonesty to its departments, who then pass on these incentives to faculty. In every university I have been in, it is far easier for a faculty member to do nothing about cheating – it requires no work, as opposed to a lot of bureaucracy documenting the cheating, imposing the punishment, dealing with the appeals, etc. There is no punishment for a faculty member who fails to report cheating, but to be fair, also no punishment for a false accusation of cheating, or an accusation that does not have sufficient evidence or gets overturned on appeal.

Even if a faculty member tries to punish academic dishonesty, the cheating student appeals to the university hierarchy and the higher-ups overturn the punishment. If not the first level of the hierarchy, then one of the higher levels. Thus even an inherently honest professor who for psychological reasons would be willing to spend the time to document academic dishonesty if it led to the cheater getting punished does not do so, because in the end there is no punishment.

A solution is to change university incentives: the students who are expelled because of cheating must pay their fees in full for their entire course of studies. A problem is that this leads to legal challenges because the student is not getting the education service but must pay for it. One solution is to require the tuition paid up front, non-refundable on expulsion for cheating. However, in this case students have to take a loan (which may be prevented by credit constraints or risk aversion) and may instead choose universities that do not charge them up front.

The university-side incentives also seem problematic if tuition is fully paid for expelled cheaters, because the university could save on the teaching costs by kicking out all the students on fabricated charges and keep the money. The long-term reputation cost for the university prevents such rip-offs.

A milder way to improve the university incentives is to require the cheater to re-take the course. This may delay the time at which the cheater can take follow-up courses that have the re-taken course as a prerequisite. The resulting delay in graduation may require the cheater to pay extra fees for the additional time, but the extra payment of course depends on the specific regulations of the university.

Preventing cheating is hopeless in online learning

Technology makes cheating easy even in in-person exams with invigilators next to the test-taker. For example, in-ear wireless headphones not visible externally can play a loop recording of the most important concepts of the tested material. A development of this idea is to use a hidden camera in the test-takers glasses or pen to send the exam contents to a helper who looks up the answers and transmits the spoken solutions via the headphones. Without a helper, sophisticated programming is needed: the image of the exam from the hidden camera is sent to a text-recognition (OCR) program, which pipes it to a web search or an online solver such as Wolfram Alpha, then uses a text-to-speech program to speak the results into the headphones.

A small screen on the inside of the glasses would be visible to a nearby invigilator, so is a risky way to transmit solutions. A small projector in the glasses could in theory display a cheat sheet right into the eye. The reflection from the eye would be small and difficult to detect even looking into the eyes of the test-taker, which are mostly pointed down at the exam.

If the testing is remote, then the test-taker could manipulate the cameras through which the invigilators watch, so that images of cheat sheets are replaced with the background and the sound of helpers saying answers is removed. The sound is easy to remove with a microphone near the mouth of the helper, the input of which is subtracted from the input of the computer webcam. A more sophisticated array of microphones feeding sound into small speakers near the web camera’s microphone can be used to subtract a particular voice from the web camera’s stereo microphone’s input. The technology is the same as in noise-cancelling headphones.

Replacing parts of images is doable even if the camera and its software are provided by the examiners and completely non-manipulable. The invigilators’ camera can be pointed at a screen which displays an already-edited video of the test-taker. The editing is fast enough to make it nearly real-time. The idea of the edited video is the same as in old crime movies where a photo of an empty room is stuck in front of a stationary security camera. Then the guard sees the empty room on the monitor no matter what actually goes on in the room.

There is probably a way to make part of the scene invisible to a camera even with 19th century technology, namely the Pepper’s Ghost illusion with a two-way mirror. The edges of the mirror have to be hidden somehow.

If top people have families and hobbies, then success is not about productivity

Assume:

1 Productivity is continuous and weakly increasing in talent and effort.

2 The sum of efforts allocated to all activities is bounded, and this bound is similar across people.

3 Families and hobbies take some effort, thus less is left for work. (For this assumption to hold, it may be necessary to focus on families with children in which the partner is working in a different field. Otherwise, a stay-at-home partner may take care of the cooking and cleaning, freeing up time for the working spouse to allocate to work. A partner in the same field of work may provide a collaboration synergy. In both cases, the productivity of the top person in question may increase.)

4 The talent distribution is similar for people with and without families or hobbies. This assumption would be violated if for example talented people are much better at finding a partner and starting a family.

Under these assumptions, reasonably rational people would be more productive without families or hobbies. If success is mostly determined by productivity, then people without families should be more successful on average. In other words, most top people in any endeavour would not have families or hobbies that take time away from work.

In short, if responsibilities and distractions cause lower productivity, and productivity causes success, then success is negatively correlated with such distractions. Therefore, if successful people have families with a similar or greater frequency as the general population, then success is not driven by productivity.

One counterargument is that people first become successful and then start families. In order for this to explain the similar fractions of singles among top and bottom achievers, the rate of family formation after success must be much greater than among the unsuccessful, because catching up from a late start requires a higher rate of increase.

Another explanation is irrationality of a specific form – one which reduces the productivity of high effort significantly below that of medium effort. Then single people with lots of time for work would produce less through their high effort than those with families and hobbies via their medium effort. Productivity per hour naturally falls with increasing hours, but the issue here is total output (the hours times the per-hour productivity). An extra work hour has to contribute negatively to success to explain the lack of family-success correlation. One mechanism for a negative effect of hours on output is burnout of workaholics. For this explanation, people have to be irrational enough to keep working even when their total output falls as a result.

If the above explanations seem unlikely but the assumptions reasonable in a given field of human endeavour, then reaching the top and staying there is mostly not about productivity (talent and effort) in this field. For example, in academic research.

A related empirical test of whether success in a given field is caused by productivity is to check whether people from countries or groups that score highly on corruption indices disproportionately succeed in this field. Either conditional on entering the field or unconditionally. In academia, in fields where convincing others is more important than the objective correctness of one’s results, people from more nepotist cultures should have an advantage. The same applies to journals – the general interest ones care relatively more about a good story, the field journals more about correctness. Do people from more corrupt countries publish relatively more in general interest journals, given their total publications? Of course, conditional on their observable characteristics like the current country of employment.

Another related test for meritocracy in academia or the R&D industry is whether coauthored publications and patents are divided by the number of coauthors in their influence on salaries and promotions. If there is an established ranking of institutions or job titles, then do those at higher ranks have more quality-weighted coauthor-divided articles and patents? The quality-weighting is the difficult part, because usually there is no independent measure of quality (unaffected by the dependent variable, be it promotions, salary, publication venue).

Prefereeing increases the inequality of research output

Why do top researchers in economics publish almost exclusively in the top 5 journals? Random idea generation and mistakes in the course of its implementation should imply significant variance of the quality of finished research projects even for the best scientists. So top people should have more of all quality levels of papers.

Nepotism is not necessary to explain why those at top universities find it easier to publish in top journals. Researchers at the best departments have frequent access to editors and referees of top journals (their colleagues), so can select ideas that the editors and referees like and further tailor the project to the tastes of these gatekeepers during writing. Researchers without such access to editors and referees choose their projects “blindly” and develop the ideas in directions that only match gatekeeper tastes by chance. This results in much “wasted work” if the goal is to publish well (which may or may not be correlated with the social welfare from the research).

In addition to selecting and tailoring projects, those with access can also better select journals, because they know the preferences of the editorial board. So for any given project, networking with the gatekeepers allows choosing a journal where editors are likely to like this project. This reduces the number of rejections before eventual acceptance, allowing accumulating publications quicker and saving the labour of some rounds of revision of the paper (at journals that reject after a revise-and-resubmit for example).

A similar rich-get-richer positive feedback operates in business, especially for firms that sell to other firms (B2B). Top businesspeople get access to decisionmakers at other organisations, so can learn what the market desires, thus can select and tailor products to the wants of potential customers. Better selection and targeting avoids wasting product development costs. The products may or may not increase social welfare.

Information about other business leaders’ preferences also helps target the marketing of any given product to those predisposed to like the product. Thus successful businesspeople (who have access to influential decisionmakers) have a more popular selection of products with lower development and marketing costs.

On the seller side, firms would not want their competitors to know what the buyers desire, but the buyer side has a clear incentive to inform all sellers, not just those with access. Empirically, few buyers publish on their websites any information about their desired products. One reason may be that info is costly to provide, e.g. requests for product characteristics reveal business secrets about the buyer. However, disclosure costs would also prevent revealing info via networking. Another reason buyers do not to publicly announce their desired products may be that the buyers are also sellers of other products, so trade information for information with their suppliers who are also their customers. The industry or economy as a whole would benefit from more information-sharing (saving the cost of unwanted products), so some trading friction must prevent this mutually beneficial exchange.

One friction is an agency conflict between managers and shareholders. If managers are evaluated based on relative performance, then the managers of some firms may collude to only share useful information with each other, not with those outside their circle. The firms managed by the circle would benefit from wider sharing of their product needs, because outside companies would enter the competition to supply them, reducing their costs. However, those outside firms would get extra profit, making their managers look good, thus lowering the relative standing of the managers in the circle.

The smartest professors need not admit the smartest students

The smartest professors are likely the best at targeting admission offers to students who are the most useful for them. Other things equal, the intelligence of a student is beneficial, but there may be tradeoffs. The overall usefulness may be maximised by prioritising obedience (manipulability) over intelligence or hard work. It is an empirical question what the real admissions criteria are. Data on pre-admissions personality test results (which the admissions committee may or may not have) would allow measuring whether the admission probability increases in obedience. Measuring such effects for non-top universities is complicated by the strategic incentive to admit students who are reasonably likely to accept, i.e. unlikely to get a much better offer elsewhere. So the middle- and bottom-ranked universities might not offer a place to the highest-scoring students for reasons independent of the obedience-intelligence tradeoff.

Similarly, a firm does not necessarily hire the brightest and individually most productive workers, but rather those who the firm expects to contribute the most to the firm’s bottom line. Working well with colleagues, following orders and procedures may in some cases be the most important characteristics. A genius who is a maverick may disrupt other workers in the organisation too much, reducing overall productivity.

Why research with more authors gets cited more

Empirically, articles with more authors are cited more, according to Wuchty et al. (2007). The reasons may be good or bad. A good reason is that coauthored papers may have higher quality, e.g. due to division of labour increasing the efficiency of knowledge production. I propose the following bad reasons, independent of potential quality differences between coauthored and solo articles. Suppose that researchers cite the works of their friends more frequently than warranted. A given scientist is more likely to have a friend among the authors of an article with a greater number of collaborators, which increases its probability of getting a „friendly citation”.

Another reason is defensive citing, i.e. including relatively unrelated papers in the reference list before submitting to a journal, in case the referees happen to be the authors of those works. The reason for adding these unnecessary citations is the belief, warranted or not, that a referee is more likely to recommend acceptance of a paper if it cites the referee’s publications. The probability that the set of referees overlaps with the set of authors of a given prior work increases in the number of authors of that work. Thus defensive citing is more effective when targeted to collaborative instead of solo papers.

The referees may also directly ask the author to cite certain papers in the revision (I have had this experience). If the referees are more likely to request citations to their own or their coauthors’ work, then articles with more authors are again referenced more.

Valderas et al. (2007) offer some additional explanations. One is measurement error. Suppose that letters to the editor, annual reports of the learned society, its presidential inaugural addresses, and other non-research in scientific journals are counted as publications. These have both fewer authors and citations than regular research articles, which creates a positive correlation between the popularity of a piece of writing and its number of authors.

If self-citations are not excluded and researchers cite their own work more frequently than that of others, then papers with more authors get cited more.

Articles with more collaborators are presented more frequently, thus their existence is more widely known. Awareness of a work is a prerequisite of citing it, so the wider circulation of multi-author publications gives them a greater likelihood of being referenced, independent of quality.

Giving oneself tenure

Senior academics tell juniors that an assistant professor does not have to get tenure at his or her current university, but “in the profession”, i.e. at some university. To extend this reasoning, one does not have to get tenure at all, just guarantee one’s ability to pay one’s living costs with as low effort as possible. Government jobs are also secure – not quite tenure, but close.
Economically, tenure is guaranteed income for life (or until a mandatory retirement age) in exchange for teaching and administrative work. The income may vary somewhat, based on research and teaching success, but there is some lower bound on salary. Many nontenured academics are obsessed about getting tenure. The main reason is probably not the prestige of being called Professor, but the income security. People with families seem especially risk averse and motivated to secure their job.
Guaranteed income can be obtained by other means than tenure, e.g. by saving enough to live off the interest and dividends (becoming a rentier). Accumulating such savings is better than tenure, because there is no teaching and administration requirement. If one wishes, one can always teach for free. Similarly, research can be done in one’s free time. If expensive equipment is needed for the research, then one can pay a university or other institution for access to it. The payment may be in labour (becoming an unpaid research assistant). Becoming financially independent therefore means giving oneself more than tenure. Not many academics seem to have noticed this option, because they choose a wasteful consumerist lifestyle and do not plan their finances.
Given the scarcity of tenure-track jobs in many fields, choosing the highest-paying private-sector position (to accumulate savings), may be a quicker and more certain path to the economic equivalent of tenure than completing sequential postdocs. The option of an industry job seems risky to graduate students, because unlike in academia, one can get fired. However, the chance of layoffs should be compared to failing to get a second postdoc at an institution of the same or higher prestige. When one industry job ends, there are others. Like in academia, moving downward is easier than up.
To properly compare the prospects in academia and industry, one should look at the statistics, not listen to anecdotal tales of one’s acquaintances or the promises of recruiters. If one aspires to be a researcher, then one should base one’s life decisions on properly researched facts. It is surprising how many academics do not. The relevant statistics on the percentage of graduates or postdocs who get a tenure-track job or later tenure have been published for several fields (http://www.nature.com/ncb/journal/v12/n12/full/ncb1210-1123.html, http://www.education.uw.edu/cirge/wp-content/uploads/2012/11/so-you-want-to-become-a-professor.pdf, https://www.aeaweb.org/articles?id=10.1257/jep.28.3.205). The earnings in both higher education and various industries are published as part of national labour force statistics. Objective information on job security (frequency of firing) is harder to get, but administrative data from the Nordic countries has it.
Of course, earnings are not the whole story. If one has to live in an expensive city to get a high salary, then the disposable income may be lower than with a smaller salary in a cheaper location. Non-monetary aspects of the job matter, such as hazardous or hostile work environment, the hours and flexibility. Junior academics normally work much longer than the 40 hours per week standard in most jobs, but the highest-paid private-sector positions may require even more time and effort than academia. The hours may be more flexible in academia, other than the teaching times. The work is probably of the same low danger level. There is no reason to suppose the friendliness of the colleagues to differ.
Besides higher salary, a benefit of industry jobs is that they can be started earlier in life, before the 6 years in graduate school and a few more in postdoc positions. Starting early helps with savings accumulation, due to compound interest. Some people have become financially independent in their early thirties this way (see mrmoneymustache.com).
If one likes all aspects of an academic job (teaching, research and service), then it is reasonable to choose an academic career. If some aspects are not inherently rewarding, then one should consider the alternative scenario in which the hours spent on those aspects are spent on paid employment instead. The rewarding parts of the job are done in one’s free time. Does this alternative scenario yield a higher salary? The non-monetary parts of this scenario seem comparable to academia.
Tenure is becoming more difficult to get, as evidenced by the lengthening PhD duration, the increasing average number of postdocs people do before getting tenure, and by the lengthening tenure clocks (9 years at Carnegie Mellon vs the standard 6). Senior academics (who have guarateed jobs) benefit from increased competition among junior academics, because then the juniors will do more work for the seniors for less money. So the senior academics have an incentive to lure young people into academia (to work in their labs as students and postdocs), even if this is not in the young people’s interest. The seniors do not fear competition from juniors, due to the aforementioned guaranteed jobs.
Graduate student and postdoc unions are lobbying universities and governments to give them more money. This has at best a limited impact, because in the end the jobs and salaries are determined by supply and demand. If the unions want to make current students and postdocs better off, then they should discourage new students from entering academia. If they want everyone to be better off, then they should encourage research-based decision-making by everyone. I do not mean presenting isolated facts that support their political agenda (like the unions do now), but promoting the use of the full set of labour force statistics available, asking people to think about their life goals and what jobs will help achieve those goals, and developing predictive models along the lines of “if you do a PhD in this field in this university, then your probable job and income at age 30, 40, etc is…”.

Seminar food guidelines

The food should be easy to eat from a plastic plate in one’s lap without paying attention to it. It should not require a knife, fork, spoon or chopsticks. Sandwiches fulfill these criteria. Sushi can also be eaten with one’s fingers. Sandwiches should not be so thick that they have to be disassembled to fit in the mouth. Sandwiches should not contain ingredients that are difficult to bite through, for example prosciutto, non-crispy bacon, meat with tendons in it.
The food should not drip or stain the hands, especially with a greasy or otherwise difficult-to-remove sauce. Wraps should neither have the bottom cut off nor contain a thin sauce that leaks through the bottom. Sandwiches should not have contents falling out – avoid a thick stack of many fillings between the breads. A single filling can be thicker, e.g. a chicken breast. Biting into the food should not cause the food to fall apart (rice paper rolls have this problem) or something to squirt out the other end (as happens with sandwiches with a lot of sauce or mayonnaise).
Sandwiches should not require toothpicks to hold them together, because these are annoying to remove. Sandwiches should not be cut into pieces so small that they require toothpicks or that the filling falls out of all sides. The bread should not fall apart when picking up the sandwich.
Avoid ingredients with a strong, specific taste that some people love and some hate. Sauerkraut, pickles, olives, capers, kimchi, herring, anchovies, hot spices and fungal cheese are bad ideas. The food should be like a politician – trying to please everyone, avoiding controversy. Spices and sauces can accompany the food separately, like wasabi and soy sauce with sushi – then everyone can add the amount they like.
Crunchy food (nachos, potato crisps, toast) should be avoided, because the sound of chewing them distracts the audience and the shards may cut the inside of the mouth.
Nuts and small berries (raspberries, blueberries) are difficult to eat when one’s attention is elsewhere, because these tend to roll off handheld plates. Transferring very small food items like nuts and berries to one’s plate at the start of the seminar is also annoying, because these have to be picked up one by one or only a few at a time. To help people fill their plates easily, put nuts, berries and crisps in separate bowls or at least separate piles, don’t scatter them over and among other food. Nuts and small berries in particular are difficult to chase between other foods.
In general, keep different foods separate. For example, sandwich bread touching cut-up fruit tends to soak juice from it and get unpleasantly soggy and sweet. Cheese and dessert touching on the same platter leads to a cheesy-tasting dessert. Separating foods also helps allergic people avoid the triggering ones.
Remove the leaves from strawberries.
If bananas are slightly green, then they are difficult to peel, so a small cut should be made near the stalk from which the peeling can start.
Don’t cut grapes – it makes them go bad in hours. Whole, undamaged grapes keep for days at room temperature.
Fruit should be either in bite-sized pieces (melon, papaya) if there are forks to eat with, or whole so it can be handheld without leaking or staining (apples, bananas). A bad idea is to have long slices of melon that stain hands with juice and don’t fit in the mouth in one piece. If there are no forks, then cut-up kiwis, pineapple and other wet, slippery fruits are a bad idea, because these are difficult to hold and stain the hands.
One strange thing I have seen (and that should be avoided) is salad scattered among sandwiches, without any forks or other utensils to serve or eat it with. The only way was to eat the salad with one’s hands.
Portions that are too large for the average eater (footlong subs, whole chicken breasts) lead to food waste, because people eat only a fraction of the portion and throw the rest away.
The mechanics of eating the food is as important as the taste. The ease of eating of various forms of food can be field-tested in a seminar-like situation: eating sitting, with a small plastic plate in one’s lap, no table, only occasionally glancing at the food.
Similar points apply to stand-up reception food.

The obsolete PhD degree

Let’s distinguish the knowledge from the degree first. The average skill requirement of jobs (measured in years of education for example) is rising over time, so people need more knowledge before entering the labour market. What is obsolete is the packaging of that knowledge into degrees and perhaps its teaching in universities.
The PhD takes six years on average (http://gsa.yale.edu/sites/default/files/Improving%20Graduate%20Education%20at%20Yale%20University.pdf) and during that time the student is guided by one or at most a few advisors. Working on the same topic on years is often necessary to become an expert, so unavoidable. But being tied to the same advisor is a throwback to the medieval guild system where the apprentice and journeyman work years for the master. It means seeing only one viewpoint or set of techniques. Most importantly, the topic of the thesis is limited to what the advisor is competent in (sometimes a laissez-faire advisor allows a dissertation on an unfamiliar subject, which is even worse – incompetent advising follows). Taking courses from other faculty in the same department or university broadens the horizons a bit, but there may be an institutional culture that introduces biases, or expertise in some fields may simply be missing from the university. Attending conferences again broadens the mind, but conferences are few and far between. Suggestions that run counter to the advisor’s views may be interpreted as wrong by a novice graduate student.
Ideally, a trainee researcher would be advised by the whole world’s scientific community, mostly but not exclusively by people in the same discipline. Electronic communication makes this easy. Many different viewpoints would be explained to the graduate student, interpersonal issues would be easier to resolve by changing advisors (no lock-in to one person who determines one’s career prospects). People who just use students as free labour without providing much in return would suddenly become lonely. The problem is moral hazard – if no specific person has responsibility for a student, indefinite postponement of advising effort may occur. Credit for useful advice would be spread between many people, which dilutes incentives. In short, advising is a public good.
Still, public goods are sometimes provided, despite the difficulty of explaining this with a rational agent model. People write free software, answer questions from strangers in forums, upload advice and instructions on many topics. This suggests some volunteer advisors would step forward under a shared responsibility system. The advisor pool may become more ideologically biased than now, because people who want to spread propaganda on their strong views have a greater incentive to volunteer advice. They do this on the internet, after all. Similar incentives for shrill prophets operate in universities, but if each faculty member is required to advise some students or if there is a cap on how many disciples one can take, there is less scope for indoctrinating the masses. Such restrictions can be imposed online to some extent. There could be a reputation mechanism among the advisors, so the crackpots are labelled as such. The larger pool of opinions may balance the biases.
The economies of scale in advising one student are reduced with sharing. A single advisor per student means that during most of the PhD program, the advisor is already familiar with the student’s work and only needs to read the new part each week. With many advisors, each would need to devote time to the same material. Some sharing of responsibilities (one reads the introduction, another the conclusion) is possible, but the interdependence of the parts of the research does not permit full splitting.
Another medieval aspect of the PhD is paying for the received teaching in labour, not money. Graduate students may be free from tuition and may even get a scholarship, but in return have to work as teaching assistants or do the advisor’s research in their lab. Less ethical help also occurs, such as reviewing papers the advisor is officially the referee of. Inefficiencies of a barter economy are introduced. Instead of paying for the program with money earned in the job the student is the most productive or happy in, the student is forced to work as a teaching assistant and essentially pay the difference between a fair market wage and the teaching assistant wage to the university. Further, the teaching work is restricted to the university of the PhD program, even if other universities need teachers more and offer higher wages. This gives the university market power and allows it to depress grad student salaries.
A doctoral program may lose money directly, in the sense that teaching the grad students is more expensive (due to small classes, advanced material, so more professor time per student) than their TA work. The fact that universities still keep the PhD programs suggests the existence of indirect benefits. One is reputation – attracting paying undergraduate and Master’s students. In some countries, an institution is not allowed to call itself a university if it does not teach at the doctoral level. Altruism by the higher education sector is possible, even if John Quiggin’s quote “never stand between a Vice-Chancellor and a bucket of money” suggests otherwise.
One utopic proposal is an online system where graduate students and advisors sign up and can talk over video calls, send emails etc. It keeps a record who communicated with whom and how much. Later, data on the academic achievement and job market performance of students can be added, so advisors can be rewarded for their students’ success. There may also be some popularity index, meaning students rate their advisors and vice versa. But in the end, an advisor’s contribution should matter more than popularity, so the latter is optional. Advisors may look at and rate each other’s advising sessions to limit the spread of bad advice. Students can collaborate and may decide to meet in person.
For experimental science, lab space can be rented by student cooperatives. Instruction in the use of equipment can be given via video. Classroom space can also be rented directly by groups of students if needed. The students may pay advisors. Some people may only advise conditional on payment. Students may teach other students (including TA jobs), whether for money or pro bono. The system would cut out the middlemen – university administrators – making education cheaper for society. Of course, in the lab and classroom rental business, other middlemen would appear and take their share.

Keeping journals honest about response times

Academic journals in economics commonly take 3-6 months after manuscript submission to send the first response (reject, accept or revise) to the author. The variance of this response time is large both within and across journals. Authors prefer to receive quick responses, even if these are rejections, because then the article can be submitted to the next journal sooner. The quicker an article gets published, the sooner the author can use it to get a raise, a grant or tenure. This creates an incentive for authors to preferentially submit to journals with short response times.
If more articles are submitted to a journal, then the journal has a larger pool of research to select from. If the selection is positively correlated with article quality, then a journal with a larger pool to select from publishes on average higher quality articles. Higher quality raises the prestige of a journal’s editors. So there is an incentive for a journal to claim to have short response times to attract authors. On the other hand, procrastination of the referees and the editors tends to lengthen the actual response times. Many journals publish statistics about their response times on their website, but currently nothing guarantees the journals’ honesty. There are well-known tricks (other than outright lying) to shorten the reported response time, for example considering an article submitted only when it is assigned to an editor, and counting the response time from that point. Assigning to an editor can take over two weeks in my experience.
To keep journals honest, authors who have submitted to a journal should be able to check whether their papers have been correctly included in the statistics. Some authors may be reluctant to have their name and paper title associated with a rejection from a journal. A rejection may be inferred from a paper being included in the submission statistics, but not being published after a few years. A way around this is to report the response time for each manuscript number. Each submission to a journal is already assigned a unique identifier (manuscript number), which does not contain any identifying details of the author. The submitter of a paper is informed of its manuscript number, so can check whether the response time publicly reported for that manuscript number is correct.
Currently, authors can make public claims about the response time they encountered (e.g. on https://www.econjobrumors.com/journals.php), but these claims are hard to check. An author wanting to harm a journal may claim a very long response time. If the authors’ reported response times are mostly truthful, then these provide information about a journal’s actual response time. Symmetrically, if the journals’ reported response times are accurate, then an author’s truthfulness can be statistically tested, with the power of the test depending on the number of articles for which the author reports the response time.