Tag Archives: incentives

Recording speaking time to prevent meetings from running over

To prevent meetings from running over because some people like to listen to their own voice, one way is to publish how much of others’ time each participant took. Measuring the talking time and making the results public helps participants with low self-awareness realise how long they talked, and creates social disapproval of those who go on for too long, potentially motivating them to be more concise.

A related method to prevent time overruns using current meeting rules, e.g. Robert’s Rules, is to allocate each speaker a fixed amount of time in advance. The problem with this method is the lax enforcement both during and after the meeting. If a speaker goes over and does not respond to requests to stop, then the moderator or chairperson usually does not shut the speaker up (turn off the microphone, forcefully remove the waffler from the stage, clamp a hand over their mouth). After the meeting, the possible sanctions (e.g. not inviting the speaker to future meetings, monetary fine, opposing the speaker’s proposed policy) are also infrequent or weak. Of course this enforcement problem also arises when talk time is recorded and published. However, the clear measurement removes one excuse of the speakers going over, namely their flat denial that they took more time than allocated, or more than others.

Public time-recording is especially helpful in less formal meetings that have no moderator or chairperson keeping time and notifying speakers to stop, and in meetings where a speaker is powerful enough that other participants are reluctant to interrupt with reminders of the time limit. A timekeeper is not needed to record the duration of a speech nowadays, because smartphones can identify a person based on their voice and calculate the time for which each voice spoke. There is a business opportunity in developing an app that identifies the number and timing of the speakers. The resulting data could also be used for research into social dynamics, e.g. whether some age, gender or race groups speak less, whether people in positions of power talk and interrupt more.

A smartphone app can also play a notification sound when a speaker’s time is up, eliminating the problem that the less powerful participants do not remind an important speaker to stop. In large meetings with a microphone, a computer keeping track of speech durations can force a speaker to stop by cutting power to the microphone when the time is up. A computer may be attached to other means to stop a speaker from unreasonably taking others’ time, e.g. it may draw the stage curtain, turn off the stage lights or start noise-cancelling the speech.

Spam deterrence by boycotting

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The obvious reason for spam of any kind (emails, texts, phone calls, unsolicited mail) is that it is profitable. Thus spam must raise the probability that its target buys or otherwise complies with the spammer’s wishes, e.g. leaves a review. To deter spam, the incentive for it must be reversed – the targeted people should not give in to spammers, but do the opposite (not buy, not leave a review when receiving a „reminder”). I try to follow this strategy. If I remember that a business spammed me, then I try to boycott it, unless it is by far the best option (usually not, spammers are typically shady businesses and bottom-feeders).

Incentives are created by the difference in payoffs, not their level. Thus to deter spam, the buying probability should be lower for a spamming business than for a non-spamming competitor. To create this payoff difference for non-monetary actions, e.g. reviewinig, I leave a review with positive probability when not asked to do so, but certainly avoid reviewing when spammed with reminders.

If the whole society followed the strategy of boycotting spammers, then one possible concern is that spammers would start to use reverse psychology. They would spam in the name of their competitors to make them look like spammers. If customers start boycotting the competitors as a result, then demand shifts to the spammer, which is profitable.

The reverse psychology is unlikely to become a serious problem, because there are typically many competitors and the spammer would have to make most of them look bad to increase its demand significantly. Also, the law usually punishes the use of a fake name more harshly than unsolicited contacting. The competitors whose reputation is tarnished by spam under their name have a stronger incentive to sue its source than consumers just annoyed by the spam.

Pre-selected health insurance plans for visitors

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A half-year visit to a US university under a J1 visa requires US health insurance. In the University of Pennsylvania, the website of the International Students’ and Scholars’ Office says that they have pre-selected some health insurance plans. According to their cover description and comparison websites, these plans offer significantly less cover than similarly-priced plans not pre-selected by U Penn. My spreadsheet comparing the health insurance options is public. Possibly I have missed some aspects of insurance that justify the price difference. Another explanation is that the pre-selection was done by people who do not themselves use these insurance plans (because they are not visitors to the US) and have little incentive to make an effort to choose the best plan. A more negative and less likely interpretation is that the insurance company is providing incentives (such as kickbacks) for the selectors at U Penn to direct visitors to expensive low-cover plans that are profitable for the insurer.

Avoiding an animal on the road

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When a bike or car heads towards a squirrel, the squirrel first dodges to one side and then runs away in the other direction. Birds fly directly away from the oncoming vehicle, so stay in front of the vehicle for a few seconds. These behaviours are presumably evolutionary adaptations to avoid predators. For example, the squirrel’s dodge probably misleads a predator to alter course in the direction of the dodge. The larger predator then has more difficulty than a small agile squirrel in switching direction to the opposite side of the dodge.
In avoiding vehicles, these escape patterns are counterproductive. A predator tries to collide with the prey, but a vehicle tries to avoid collision. A squirrel’s dodge confuses the driver or cyclist, who then tries to pass the animal on the opposite side of the initial feint, which is exactly the direction the animal ends up running in. The best way to avoid collision may be to just keep going in a straight line and let the animal dodge out of the way. A constant direction and speed is easy to predict, which lets the animal avoid being in the same place at the same time as the vehicle. Keeping one’s course and speed also avoids accident-prone sharp turns and sudden stopping.
If a predator was smart and knew about the dodging behaviour, then it would go opposite the initial dodge. But then the squirrel would benefit from not switching direction. In response to the squirrel just running in one direction, the predator should run in the direction of the squirrel’s initial movement, etc. This game only has a mixed strategy equilibrium where the squirrel randomises its direction and whether it dodges or not, and the predator randomises its response to the squirrel’s initial movement direction. Dodging takes more energy than just running to one side, so the dodge must have a benefit that outweighs the energy cost, which means that the predator must be less successful when the squirrel dodges. Some factor must make it difficult for the predator to swerve opposite the squirrel’s initial direction. For example, if most prey keep running in one direction instead of feinting, then the predator may be on average more successful when following the initial movement of the prey. The cognitive cost of distinguishing squirrels from other prey must be too large to develop a different strategy for chasing squirrels.
The same game describes dribbling in soccer to avoid a defender. It would be interesting to look at data on what proportion of the time the attacker feints to one side and then moves to the other, as opposed to just trying to pass around the defender in the initial movement direction. It is more difficult for both players to switch than to keep moving in one direction, but presumably the player with the ball finds it relatively more complicated than the defender. In this case, to keep the other player indifferent, each player only has to switch direction less than half of the time, but the defender relatively less frequently. If the attacker feints and the defender does not switch direction, then the defender looks clumsy and the attacker a good dribbler. Reputation concerns of soccer players (who are after all entertainers) may make them switch direction more often than a pure winning motive would dictate.
Similarly, soccer players may use flashy moves like scissor kicks more often than is optimal for winning, because the flashiness makes the player popular with fans.

Neighbourhood coordinating to keep houses small and prices high

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If apartment buildings are built in a neighbourhood of detached houses, then the house prices fall, especially next to the new apartment buildings. There is less privacy in the garden if many windows overlook it, and there is more congestion and crime if more people live nearby. The neighbourhood’s common interest may be to block the development of large buildings in it. However, an individual homeowner finds it profitable to sell to a property developer who will replace the detached house with a large apartment building, because the cost of reduced house prices is borne by the neighbours, not by the seller.
One way that neighbourhoods try to prevent this tragedy of the commons is to require all homeowners to join an association and agree to be bound by the rule that the association can prohibit new buildings or expansions. Such rule-based solutions are usually vulnerable to legal loopholes and changes in government policy that invalidate the restrictions. Game theory offers a solution without requiring any external enforcement: if one homeowner extends her house or replaces it with a bigger building, or sells to someone who will, then the neighbours respond by building apartment buildings around the property of the first breaker of the social norm of non-expansion. Then the view from the first expanded building is only the walls of the others, which makes the expansion unprofitable and deters enlargement in the first place.
The punishment for the first extension has to be certain enough to deter it. In particular, the homeowners next to the violator of the norm must be incentivised to build even at a loss. This incentive can be provided by requiring the neighbours of the homeowners next to the violator to punish those who do not punish the violator. This punishment can again be the development of large buildings next to their property. Those who refuse to punish the non-punishers can be punished the same way, etc, in concentric circles around the original violator.
The incentives provided by dynamic games such as this one may seem strange, but can be easily coordinated by a homeowners’ association without any legal power. The association simply publishes the rule that (a) enlargement of current buildings or the construction of new ones is forbidden and (b) if someone breaks the rule, then any new construction in a specified radius around the first rule-breaker is allowed. If one enlargement or new building is profitable, then typically a few extensions next to it are also profitable. The fewer neighbours of the first rule-breaker that build bigger houses as punishment, the more profitable an extension is for any neighbour. So some neighbours will punish the first violator. This will make the house prices of other neighbours fall, which reduces the cost to them of selling their houses to property developers for apartment building construction, i.e. reduces the cost of punishing the original rule-breaker.

Buildings replaced quickly, so built badly

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In a fast-growing city, many buildings will be replaced by larger ones in a decade or two. Property developers probably take this into account, thus do not hesitate to build low-quality non-durable housing. If the city growth stops at some point and buildings are no longer quickly replaced, then the owners of such housing will get an unpleasant surprise.
People buying or building detached houses do not seem to take city growth into account, because at least in Canberra, I see the erection of large expensive mansions in districts where the house will in 20-30 years be surrounded by high apartment buildings. Tall structures around a mansion tend to reduce its value, and certainly make the garden less private. The investment in fancy gardens, backyard swimming pools, etc, seems a bit short-sighted in locations close to the centre of a growing city.
The mansions also fill most of the plot of land on which they stand, so from an energy efficiency point of view, they might as well join walls with neighbours, as I have written before.

Spam call deterrence

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Time-wasting marketing calls to my cellphone are a bit of a problem. I have developed the habit of checking any new number against online spam call reporting websites, and if the number turns out to be a spammer, then saving it under “Spam call” in my phone. Then in the future, any call from the same number shows up on the phone as Spam call. There are probably apps for blocking numbers, but as an economist, I would prefer a tax to a ban. I would like to make callers pay me for calling me, to compensate for my time spent answering or blocking, and also to deter spam calls. In principle, charging a fee for receiving a call is possible, because there are already 1-800 numbers and others that are pricier to call than an ordinary phone.
If it was costlier to call me than most numbers, then I would refund the extra calling fee to my friends and other legitimate callers, so they would not be deterred from calling me. This is easy, because I can see the list of calls, their durations and numbers online, so can calculate how much extra each caller paid to call me. Spammers of course would not get a refund.

Unfortunately, imposing a monetary cost on spammers is infeasible for most individuals. There are now apps that block spam numbers automatically, and the user can specify additional numbers to blacklist. However, a better version of spam call deterrence is not to block the call, but to impose as large a cost on the caller as possible. A non-monetary way to punish spammers is to waste their time. If the person called pretends to be a gullible customer and keeps the spammer talking for a long time, but in the end does not buy what is being sold, then the spammer loses more than by just being blocked. Unfortunately, this also wastes time for the victim of spam, and that time is usually more valuable than the spammer’s, especially with modern robocalls and auto-dialling.

To fight fire with fire, victims of spam could have an AI on their phone respond in their stead. The time of the AI costs little, so the AI could play the part of a gullible customer, keeping the caller hopeful. The AI could say: „Tell me more,” „How much does it cost?” and other encouraging things, agree to buy what the caller is selling, provide a fake credit card number and other data. Only after a long call, entering the fake data to process the order, confirming the address, etc, would the spammer learn that no profit is forthcoming.

Similarly, AI could produce written responses to email spam to deter it. For example, provide (fake) account numbers and passwords to the self-proclaimed Nigerian prince, after asking for various confirmations and documentation.

Spam call deterrence of course is just a part of general spam deterrence, for which one way is boycotting. However, boycotts may backfire if firms spam on behalf of competitors to make them look bad, as in a false flag attack.

Gender equity either on paper or by forcing people to change research fields

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Suppose that a university employs roughly equal numbers of men and women overall, but the proportions of the genders differ across research fields, or across research and administration, and the university wants gender equality within each subfield. Using the narrowest definition of a research field, each field has either one or zero people, so in the smallest fields, gender equality is impossible. From now on, the focus is on fields or administrative units that have at least two people.
Gender equity can be achieved on paper by redrawing the administrative boundaries or redefining research fields. A simple algorithm (not the only possible algorithm) is to form pairs of one male and one female employee and call each such pair an administrative unit. Larger units can be formed by adding many male-female pairs together. If the numbers of men and women are not exactly equal, then some single-gender pairs will be left over, but most administrative units will have perfect gender equality.
The same idea can be used less radically by reassigning people who do interdisciplinary work and could plausibly belong to multiple research fields. Each person who is „between” fields gets assigned to the field that has a smaller fraction of that person’s gender. This increases gender equality in both the field that the person joins and the field that the person left. The field with a bigger surplus of that person’s gender loses one of that gender, and the field with a smaller surplus gains one.
Other than reassigning people or redrawing administrative boundaries, gender equity requires inducing people to change their research fields. To some of my colleagues, directing researchers to change their area is ideologically unacceptable. However, if equity is the goal and people’s field change is necessary to achieve it, then several methods can be used. The inducements can be softer or harder. A hard inducement is a hiring policy (and job ads) that restrict hiring to only one gender. The same can be done with promotion and retention. If this policy was explicitly stated to everyone, then it would become more effective, and also more acceptable to people than when they are surprised with it upon applying for promotion.
Soft inducements consist of hints that one gender is preferred, which are usually stated in political doublespeak like „we are committed to equity” or „we are an equal opportunity employer”. If many more candidates of one gender apply, then giving all candidates an equal opportunity of getting hired does not result in equal proportions of men and women employed. I am in favour of clear guidelines and transparency, for example of explicitly stating in job ads and promotion policies that the underrepresented gender is preferred, and which gender is currently underrepresented. Clearly telling people that switching fields is good for their career is likely to have a bigger effect than the currently used hints.
It may be easier to shift the research areas of people who are earlier in their careers. Encouraging more young people of a given gender to go to an area where their gender is underrepresented is one way of inducing them to change their field (relative to their preference).
Current equity policies are focussing almost exclusively on the inflow of employees. Gender balance can also be improved by managing the outflow, for example by offering early retirement schemes to one gender, or expanding these to a wider age range for one gender. If there are gender differences in the propensity of accepting certain inducements to leave, then the same inducements can be offered to both genders (seemingly gender-neutrally), with the desired result that one gender exits more.

Keeping journals honest about response times

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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.

Incentivising refereeing

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To shorten the refereeing lag and improve report quality in economics, the natural solution is to incentivise academics to do a better and quicker job. Economists respond to incentives, but currently no salary or promotion consequences arise from good or bad refereeing, as far as I know. In http://sanderheinsalu.com/ajaveeb/?p=503, I wrote about incentives for authors not to submit careless papers (in the hope that a refereeing mistake gets them accepted). One such incentive is requiring refereeing for a journal as a precondition for submitting to that journal. If a submitted paper gets n referee reports on average, then before submitting, an author should referee n papers in a timely manner, which should balance the supply and demand of refereeing. This forced refereeing may lead to quick, but sloppy reports.

An additional incentive is needed for quality. Rahman’s 2010 paper on the question „who watches the watchmen” suggests an answer. The editor can insert a deliberate mistake in every paper and see whether a referee finds it. If not, then the refereeing of that person is likely of low quality. The mistake is corrected before publication. Alternatively, the editor can ask each author to insert a mistake and tell the editor about it. The author is not penalised for this mistake and is asked to correct it if the paper is accepted. The referees are again judged on whether they find the mistake.

The above scheme derives refereeing incentives from publication incentives, requiring minimal change to the current system. However, it is somewhat indirect. A more straightforward incentive for refereeing is to reward it directly, either paying for it or basing promotion decisions partly on it. The speed of refereeing is already slightly monetarily incentivised in the American Economic Journal: Microeconomics. If the referee sends the report before a deadline, then she or he is paid 100 dollars. If a good referee report takes about 10 hours, then the amount is certainly not enough to motivate quality provision, but it is a step in one of the right directions. A simple improvement on the binary „before vs after deadline” reward scheme is to reduce the payment gradually as the delay of the referee report increases.

If refereeing is incentivised, then lower-ranked journals need larger incentives to compensate for the fact that refereeing for these has less inherent prestige and the paper one has to read is of lower quality. On the other hand, lower-ranked journals are less able to motivate refereeing with the threat of not accepting submissions from those who have not refereed. There are more lower-ranked journals, and it is less important to get accepted by any particular one of them. Some of the less prestigious journals would find no referees under the system proposed above. This is good, because it removes the „peer reviewed” status of some junk journals and may force them to close. If authors know that quality journals require refereeing before submission, then they draw the obvious conclusion about a journal that does not require it.