You are currently browsing the monthly archive for May 2011.
Do you get annoyed when someone boards the elevator with you only to ride up one floor? The stairs are right there, could they not just walk up a single flight? Well, consider this. Someone boards the elevator on the first floor with a 3rd floor destination, but instead of getting off at floor 2 and walking the last flight of stairs, they ride all the way to 3.
Doesn’t seem as annoying, right? So what explains the difference? It can’t be that you are just appalled at their laziness. Because riding to floor N rather than getting of at N-1 is just as lazy. It must be the externality.
Getting on the elevator only to ride up a single floor delays everybody else. The decision to ride to the second floor rather than the third isn’t the same because whichever he chooses the elevator is going to have to stop once.
Ah, but what if he gets on, floor 2 is already pushed but 3 is not. Then the tradeoff is the same. Because if he were to get off at floor 2 and walk he would spare everyone else the additional stop at 3. So you get annoyed at a single-floor rider you if and only if you get annoyed at this marginal-floor rider.
Well, not quite. Becuase there is one more difference. After he makes the sunk decision to get on the elevator, but before he makes the marginal decision, the problem changes. In particular, as he is riding he gains some new information: he can observe how many other people get on the elevator and are going to be affected by his decision.
This puts the marginal-floor rider in a different position than the single-floor rider in terms of social welfare. Because the single-floor rider’s decision whether to board at all is made without knowing how many other riders will be on the elevator. The marginal-floor rider can condition his decision on the number of riders.
Indeed, this means that you may even have cause to forgive Mr. Single-Floor and yet be annoyed at Ms. Marginal-Floor. He may have reasonably expected that few people, if any, were going to be inconvenienced. But if it turns out that the elevator is nearly full then the sum total of their delay due to Mr. SF’s decision to board is a sunk cost, but it’s an avoidable cost for Ms. MF. If she doesn’t get off at 2 and walk an extra flight, you all have plenty of reason to be annoyed.
This is all very important.
Also, this explains the otherwise inexplicable glass elevators, and raises the puzzle of why we don’t see them in office buildings.
Via Eli Dourado, an article in Slate by Ray Fisman on how counterfeit handbags are the gateway to the real thing.
Yet a preliminary studyfocused on counterfeit sales in China—the source of all those fake handbags in Chinatown and just about everywhere else—suggests that in many cases the sale of fakes may not be so bad for legitimate brands. The study, by Northwestern economist Yi Qian, examined the counterfeit market in the wake of well-publicized cases of food poisoning and exploding gas tanks in China, when enforcement efforts were diverted from policing fashion copycats and toward monitoring drugs, food, and gas. Counterfeit factories flourished, but surprisingly, this led to an increase in sales for high-end products in the years that followed.
Here’s one model. A fake raises your status among everyone who’s fooled. How much is that boost in status worth? Reducing enforcement makes it cheaper to buy a fake and find out. Some will learn that it’s worth more than they thought. But since not everyone is fooled by a fake they are nowwilling to pay more for the real thing to increase status on the extensive margin. These people would not have bought Prada without having first experimented with the cheap fake.
Clearly the reason that sex is so pleasurable is because that motivates us to have a lot of it. It is evolutionarily advantageous to desire the things that make us more fit. Sex feels good, we seek that feeling, we have a lot of sex, we reproduce more.
But that is not the only way to get motivated. It is also advantageous to derive pleasure directly from having children. We see children, we sense the joy we would derive from our own children and we are motivated to do what’s necessary to produce them, even if we had no particular desire for the intermediate act of sex.
And certainly both sources of motivation operate on us, but in different proportions. So it is interesting to ask what determines the optimal mix of these incentives. One alternative is to reward an intermediate act which has no direct effect on fitness but can, subject to idiosyncratic conditions together with randomness, produce a successful outcome which directly increases fitness. Sex is such an act. The other alternative is to confer rewards upon a successful outcome (or penalties for a failure.) That would mean programming us with a desire and love for children.
The tradeoff can be understood using standard intuitions from incentive theory. The rewards are designed to motivate us to take the right action at the right time. The drawback of rewarding only the final outcome is that it may be too noisy a signal of whether he acted. For example, not every encounter results in offspring. If so, then a more efficient use of rewards to motivate an act of sex is to make sex directly pleasurable. But the drawback of rewarding sex directly is that whether it is desirable to have sex right now depends on how likely it is to produce valuable offspring. If we are made to care only about the (value of) offspring we are more likely to make the right decision under the right circumstances.
Now these balance out differently for males than for females. Because when the female becomes pregnant and gives birth that is a very strong signal that she had sex at an opportune time but conveys noisier information about him.That is because, of course, this child could belong to any one of her (potentially numerous) mates. Instilling a love for children is therefore a relatively more effective incentive instrument for her than for him.
As for love of sex, note that the evolutionary value of offspring is different for males than for females because females have a significant opportunity cost given that they get pregnant with one mate at a time. This means that the circumstances are nearly always right for males to have sex, but much more rarely so for females. It is therefore efficient for males to derive greater pleasure from sex.
(It is a testament to my steadfastness as a theorist that I stand firmly by the logic of this argument despite the fact that, at least in my personal experience, females derive immense pleasure from sex.)
Drawing: Misread Trajectory from www.f1me.net
In time for Memorial Day I am here to share with you the results of painstaking research. You come to Cheap Talk for Economic Theology, existentially challenged theater reviews, and poetry, and today you are getting the instruction manual for summer. (Let’s hope it stops raining in time.)
I’m talking about those rugged paper bags of hardwood charcoal that are bound at the top with a zipper-like string seam that looks as if it was made to cleanly unravel. Sometimes it doesn’t and then you can yank and yank to no avail. And even when it does there seems to be some magic involved, like the gods of charcoal are smiling down on you. Well, I’m telling you its all science and you can make it happen every time with three simple steps.
Step 1: Orient yourself. There is a front and a back. The front side has clean loops, the back side string is ragged and knotted at the end. Pictures:
Front Side
Back Side
You have to pull the string from the back side. It unravels from left to right.
Step 2: Understand what you are doing. There are really two strings here woven together. There is a string on the front side which is pushed through in loops through each of the little holes in the bag. Then a string on the back side is threaded through them also in a looping fashion. The end of the string on the left side is then knotted onto the leftmost loop. What you need to do is remove that knot and free up the end of the backside string so that you can pull it.
Unraveling
Step 3: The endgame. Once you have the end of the backside string all there is left to do is pull and the whole apparatus becomes unraveled. You can then extract the frontside string leaving you with two strings in your hand, a flap of paper to lift off the bag (and recycle) and finally a wide open bag of non-fossil fuel. No hassle, no pointless yanking, no scissors. Works every time.
How does the additional length of a 5 set match help the stronger player? Commenters to my previous post point out the direct way: it lowers the chance of a fluke in which the weaker player wins with a streak of luck. But there’s another way and it can in principle be identified in data.
To illustrate the idea, take an extreme example. Suppose that the stronger player, in addition to having a greater baseline probability of winning each set, also has the ability to raise his game to a higher level. Suppose that he can do this once in the match and (here’s the extreme part) it guarantees that he will win that set. Finally, suppose that the additional effort is costly so other things equal he would like to avoid it. When will he use his freebie?
Somewhat surprisingly, he will always wait until the last set to use it. For example, in a three set match, suppose he loses the first set. He can spend his freebie in the second set but then he has to win the third set. If he waits until the third set, his odds of winning the match are exactly the same. Either way he needs to win one set at the baseline odds.
The advantage of waiting until the third set is that this allows him to avoid spending the effort in a losing cause. If he uses his freebie in the second set, he will have wasted the effort if he loses the third set. Since the odds of winning are independent of when he spends his effort, it is unambiguously better to wait as long as possible.
This strategy has the following implications which would show up in data.
- In a five set match, the score after three sets will not be the same (statistically) as the score in a three set match.
- In particular, in a five-set match the stronger player has a lower chance of winning a third set when the match is tied 1-1 than he would in a three set match.
- The odds that a higher seeded player wins a fifth set is higher than the odds that he wins, say, the second set. (This may be hard to identify because, conditional on the match going to 5 sets, it may reveal that the stronger player is not having a good day.)
- If the baseline probability is close to 50-50, then a 5 set match can actually lower the probability that the stronger player wins, compared to a 3 set match.
This “freebie” example is extreme but the general theme would always be in effect if stronger players have a greater ability to raise their level of play. That ability is an option which can be more flexibly exercised in a longer match.
- One implication of a theory I have written about before is that a best of 5 set match confers a greater advantage on the stronger player than a best of 3 set match. (The basic idea is that the 5 sets gives the stronger player more flexibility in timing his bursts of effort.) Here are some data that would shed light: compare men’s versus women’s Grand Slam matches in terms of the probability that a higher-seeded player will win. Even better: divide the data into non-Grand Slam and Grand Slam matches. Ask how much more likely a higher-seeded player wins a Grand Slam match versus a non-Grand Slam match. Do this for both women and men. Then do the difference-in-differences. This gives you a nice control because women play 3 sets whether its a Grand Slam or not. Men play 5 sets in Grand Slams and 3 sets in almost all non-Grand-Slam events.
- Four Grand Slams, only three surfaces. It’s time the US Open switched to ice. (with skates.)
- In honor of de Balzac.
- Photolog of dinner at Next, with gripe about ticketing.
- Mashable Big Mac.
- Did the dopamine spike before or at the moment of reward? Science needs to know.
- Man milk.
- Beautiful card trick.
Step 1: Show me the money.
Given the differential between federal reimbursements and the cost of the meals, the breakfast plan “has the potential to create $8.9 million of new revenue,” according to an internal document. C.P.S. gets as much as $1.76 per student for a meal costing about a buck.
Step 2: Maximize volume via food offerings
One classic—a sausage wrapped inside a pancake on a stick, to be dipped into syrup—was likely filled with saturated fat and calories, [a nutritionist] said. A cold alternative was Rice Krispies, Cheerios and Kellogg’s Frosted Mini-Wheats—all of which she found benign—and skim milk.
For the four days, there was not a piece of fresh fruit, there was insufficient whole grains and the orange juice was 100 percent juice but included apple and pear juice (“a money saver”), she said.
Step 3: Parents Revolt.
Meredith Crowley, a CPS parent, said she is upset that the district is serving dessert for breakfast, citing menu items such as chocolate cereal and Rice Krispie bars. She said the district implemented the program largely to generate revenue and plug a budget hole.
“Please give someone at CPS a red pen and ask them to go through the menu at Chartwell’s, ditch the desserts, red-line the Rice Krispie bars, freeze the Frosted Mini-Wheats,” Crowley said. “I will not stand back and let CPS balance the budget on the backs of poor children.”
From Jonah Lehrer:
One week later, all the subjects were quizzed about their memory of the product. Here’s where things get disturbing: While students who saw the low-imagery ad were extremely unlikely to report having tried the popcorn, those who watched the slick commercial were just as likely to have said they tried the popcorn as those who actually did. Furthermore, their ratings of the product were as favorable as those who sampled the salty, buttery treat. Most troubling, perhaps, is that these subjects were extremely confident in these made-up memories. The delusion felt true. They didn’t like the popcorn because they’d seen a good ad. They liked the popcorn because it was delicious.
The article is interesting, you should check it out. These stories always sound impossible to believe. It just doesn’t seem so easy to manipulate memories. But it’s not all that surprising when you think about it.
- You have dreams where impossible things happen, where people you know have changed dramatically out of the blue, or where your life is completely changed. And when you have a dream like that you say “this is strange” and then you accept it as true and go on. It’s incredibly easy for you to believe in impossible things. And often you do it by convincing yourself that in fact its been like this all along.
- False memories sound impossible, but on the other hand we forget things all the time. Forgetting something is not all that different from a false memory. “Where did you put your keys?” ”I didn’t put them anywhere. Somebody else must have put them somewhere.” And then you find the keys and remember that in fact you did put them there. You have not just forgotten something but you have believed in the false memory that the thing never happened.
You go into a restaurant and ask them the wait time for a table for two. The hostess says 45 minutes. Is she making it up off the top of her head?
I have always wondered about this. It turns out that some restaurants have a more sophisticated approach. They use software sold to them by opentable to estimate wait time. There is one employee whose job it is to wander round going table to table eyeballing the state of the meal. How many people are eating dessert? Have they paid or are they waiting for the check? This information and more is inputted into the software. The software then churns out an estimated wait time by size of table. This much I know.
What I don’t know is whether the hostess then adds or subtracts a fudge factor as a function of wait time. For example, if there is excess demand but the queue is short do you underestimate the wait time to encourage people to stay? The paradigmic incentives in the Crawford-Sobel Cheap Talk model arise for the restaurant.
There’s a good reason to fear regulation even if you can imagine beneficial regulation. You may be suspicious of government agencies’ motives or competence to implement it. Giving power to an agent when we can’t rely on her to use it in a beneficial way is often a bad idea.
But the same kind of fear, viewed through a mirror, often argues in favor of regulation. Take for example financial regulation. We may understand that if investors, managers, or insurers could be assumed to act reliably in ways that are consistent with their self-interest then markets would work well and there would be no rationale for regulation.
But should we predicate laissez faire on the assumption that they don’t make mistakes, that they perfectly fathom the complex path to their self-interest? If we can’t be sure, then giving them the power to do damage is often a bad idea.
(Drawing: Negative Space from www.f1me.net)
She wrote this convincing essay on happiness and parenting. Parents seem to be less happy but we shouldn’t read too much into that. She brings together all kinds of economic theory and data and along the way she cites a paper I like very much by Luis Rayo and Gary Becker:
Nobel Prize–winning economist Gary Becker, writing with Luis Rayo, has argued this contrary position. In their view, while “happiness and life satisfaction may be related to utility, they are no more measures of utility than are other dimensions of well-being, such as health or consumption of material goods.”[5] Or having kids. Children may make you less happy, but still raise your utility. Devout neoclassical reasoning leads Becker and Rayo to infer from the fact that we are having kids that they raise your utility (or at least they raise the utility of those who make this choice).
Rayo and Becker argued that happiness should be thought of as the carrot that gets us to make good decisions. But happiness is a scarce resource. There’s a limit to how happy you can be. So it has to be used in the most economical way. In their theory the most economical way to use happiness is to give an immediate, and completely transitory boost of happiness to reward good outcomes. You have sex, you get rewarded. It results in conception, that’s another reward. But then you are back to the baseline so as to maximize the range available for further rewards (and penalties) motivating behavior going forward. Bygones are bygones.
With that theory it makes no sense to look at a cross section of the population, compare how happy are people who did X relative to people who didn’t do X, and conclude on the basis of that whether its good to do X.
And by the way, if there is anything we can expect evolutionary incentives to have a good handle on, its whether or not to have kids. That’s the whole ballgame. If happiness is there to motivate us to succeed evolutionarily then you better have a good argument why Nature got it wrong. One place to look might be on the quantity/quality tradeoff. Perhaps the relative price of quality versus quantity has declined in modern times and Nature’s mechanism is tuned to an obsolete tradeoff. If so, then people feel a motivation to have more kids than they should. The prescription then would be to resist the temptation you feel to have another kid and instead invest more in the ones you have. Unless you want to be happy.
Browser bookmarklet that inserts a real-time third-party auction into the checkout screen of an online retailer.
So here’s the basic premise behind Gilt-ii. Everyday at noon ET, Gilt releases daily price cuts on luxury goods. There are limited quantities of these goods, and most of these items become unavailable within in minutes fo the sale opening. That’s why many shoppers on the site put things in their cart, where they have ten minutes to decide if they want to purchase the item, even if they aren’t necessarily sold on the idea of buying the item.
Gilt-ii’s bookmarklet allows those who have the items in their carts to transform into risk-free auctioneers, selling items to any Gilt shoppers who are accessing a “Sold Out – Item in Members’ Carts” message. When a user running “Gilt-ii” opens their shopping cart, their items are automatically registered for auction and displayed to out of luck buyers in the “Gilt-ii Auctions” box right into the item details page. From the auctions box, buyers submit bids on their desired items. As bids are made, they are displayed to the auctioneers right inside their shopping cart — if they see a price that they like, they can accept the bid and Gilt-ii will automatically handle the money transfer between users and change the shipping information at check out to that of the bidder. Auctioneers spend nothing until someone agrees to purchase the item from them.
As a Gilt shopper, I have experienced the letdown of not being able to purchase a coveted item (at a pretty good deal) because I didn’t act fast enough or I wasn’t able to check the site exactly when the sale started. Not only does Gilt-ii give shoppers a chance to purchase these already sold items, but it gives other Gilt shoppers the opportunity to make a few bucks off of purchases on the site by auctioning off items.
Pith helmet pitch: Mallesh Pai
A fitting end to the conflict conference organized by Joan Esteban:
Andrew Caplin told us about a new experiment that adds to the debate about “nudges.”
We have initiated experiments to study this tradeoff experimentally in a setting where imperfect perception seems highly likely and choice quality is easy to measure. In each round, subjects are presented with three options, each of which is composed of 20 numbers. The value of each option is the sum of the 20 numbers, and subjects are incentivized to select the object with the highest value. In the baseline treatment (“33%, 33%, 33%”), subjects were informed that all three options were equally likely to be the highest valued option, but in two other treatments, they were nudged towards the first option. In one of the nudge treatments (“40%, 30%, 30%”), subject were informed that the first option was 40% likely to be the highest valued option (the other two were both 30% likely). In the other nudge treament (“45%, 27.5%, 27.5%”), subjects were told that the first option was 45% likely to be the highest valued option (the other two were both 27.5% likely). Subjects completed 12 rounds of each treatment, which were presented in a random order.
The subjects got the best option only 54% of the time revealing that effort was required to add up all 20 numbers three times to find the largest sum. The nudges gave them hints but notice that the hints also lower the return to search effort. So in theory there will be both income and substitution effects. And in the experiment you see evidence of both. Their choices reveal that they utilized the hints: they more often chose the highlighted alternative. But, the interesting finding is that their chances of getting the best alternative did not increase. In essence, the hint perfectly crowded out their own search effort.
You could take a pessimistic view based on this: nudges don’t improve outcomes, they just make people lazier. But in fact the experiment suggests a nuanced interpretation of nudges. Even if we don’t see any evidence that, say published calorie counts improve the quality of decisions, that doesn’t imply that they have no welfare effects. Information is a fungible resource. If you give people information, they can save the effort of gathering it themselves. Given that information is a public good, these are potentially large welfare gains that would be hard to measure directly.
I once wrote about height and speed in tennis arguing that negative correlation appears at the highest level simply because they are substitutes and the athletes are selected to be the very best. At the blog MickeyMouseModels.blogspot.com, there is a post which shows very nicely the effect using simulated data. Quoting:
Suppose that, in the general population, the distribution of height and speed looks roughly like this:
Where did I get this data? It’s entirely hypothetical. I made it up! That said, I did try to keep it semi-realistic: the heights are generated as H = 4 + U1 + U2 + U3 feet, where the U are independently uniform on (0, 1); the result is a bell curve on (4, 7) feet, which I prefer to the (-Inf, +Inf) of an actual normal distribution. (I’ve created something similar to the N=3 frame in this animation.)
The next step is to give individuals a maximum footspeed S = 10 + U4 + U5 + U6 mph, with the U independently uniform on (0, 5). By construction, speed is independent from height, and falls more or less in a bell curve from 10 to 25 mph. Fun anecdote: my population is too slow to include Usain Bolt, whose top footspeed is close to 28 mph.
Back to tennis. Let’s imagine that tennis ability increases with both height and speed — and, moreover, that those two attributes are substitutable: if you’re short (and have a weak serve), you can make up for it by being fast. With that in mind, let’s revisit the scatterplot:
There it is: height and speed are independent in the general population, but very much dependent — and negatively correlated — among tennis players. The plot really drives the point home: top athletes will be either very tall, very fast, or nearly both; and excluding everyone else creates a downward slope.
That was the title of a very interesting talk at the Biology and Economics conference I attended over the weekend at USC. The authors are Juan Carillo, Isabelle Brocas and Ricardo Alonso. It’s basically a model of how multitasking is accomplished when different modules in the brain are responsible for specialized tasks and those modules require scarce resources like oxygen in order to do their job. (I cannot find a copy of the paper online.)
The brain is modeled as a kludgy organization. Imagine that the listening-to-your-wife division and the watching-the-French-Open division of YourBrainINC operate independently of one another and care about nothing but completing their individual tasks. What happens when both tasks are presented at the same time? In the model there is a central administrator in charge of deciding how to ration energy between the two divisions. What makes this non-trivial is that only the individual divisions know how much juice they are going to need based on the level of difficulty of this particular instance of the task.
Here’s the key perspective of the model. It is assumed that the divisions are greedy: they want all the resources they need to accomplish their task and only the central administrator internalizes the tradeoffs across the two tasks. This friction imposes limits on efficient resource allocation. And these limits can be understood via a mechanism design problem which is novel in that there are no monetary transfers available. (If only the brain had currency.)
The optimal scheme has a quota structure which has some rigidity. There is a cap on the amount of resources a given division can utilize and that cap is determined solely by the needs of the other division. (This is a familiar theme from economic incentive mechanisms.) An implication is that there is too little flexibility in re-allocating resources to difficult tasks. Holding fixed the difficulty of task A, as the difficulty of task B increases, eventually the cap binds. The easy task is still accomplished perfectly but errors start to creep in on the difficult task.
(Drawing: Our team is non-hierarchical from www.f1me.net)
- A 60 Minutes interview of Sleeper-era Woody Allen. It’s interesting how little Woody Allen changed but how much 60 Minutes changed.
- McDonalds in France.
- Stuff an old guy googles.
I learned something from reading this article about a classic experimental finding in developmental psychology:
So you keep hiding the toy in “A” and the baby keeps searching for the toy in “A.” Simple enough. But what happens if you suddenly hide the toy in “B”? Remember, you’re hiding the toy in full view of the infant. An older child or an adult would simply reach for “B” to retrieve the toy. But not the infant. But, despite having just seen the object hidden in the new “B” location, infants between 8 and 12 months of age (the age at which infants begin to have enough motor control to successfully reach for an object) frequently look for it under box “A,” where it had previously been hidden. This effect, first demonstrated by Jean Piaget, is called the perseverative search error or sometimes the A-not-B error.
The result is robust to many variations on the experiment and the full article goes through some hypotheses about the error and a new experiment that turns them on their head.
So why are these the current “market probabilities” for American Idol?
- Lauren Alaina to be eliminated tonight: 50%
- Haley Reinhart to be eliminated tonight: 58%
- Scotty McReery to be eliminated tonight: 15%
The winning percentages also add up to more than 100. Is it not possible to short them all?
Thanks to Zeke for the pointer.
Apparently it’s biology and economics week for me because after Andrew Caplin finishes his fantastic series of lectures here at NU tomorrow, I am off to LA for this conference at USC on Biology, Neuroscience, and Economic Modeling.
Today Andrew was talking about the empirical foundations of dopamine as a reward system. Along the way he reminded us of an important finding about how dopamine actually works in the brain. It’s not what you would have guessed. If you take a monkey and do a Pavlovian experiment where you ring a bell and then later give him some goodies, the dopamine neurons fire not when the actual payoff comes, but instead when the bell rings. Interestingly, when you ring the bell and then don’t come through with the goods there is a dip in dopamine activity that seems to be associated with the letdown.
The theory is that dopamine responds to changes in expectations about payoffs, and not directly to the realization of those payoffs. This raises a very interesting theoretical question: why would that be Nature’s most convenient way to incentivize us? Think of Nature as the principal, you are the agent. You have decision-making authority because you know what choices are available and Nature gives you dopamine bonuses to guide you to good decisions. Can you come up with the right set of constraints on this moral hazard problem under which the optimal contract uses immediate rewards for the expectation of a good outcome rather than rewards that come later when the outcome actually obtains?
Here’s my lame first try, based on discount factors. Depending on your idiosyncratic circumstances your survival probability fluctuates, and this changes how much you discount the expectation of future rewards. Evolution can’t react to these changes. But if Nature is going to use future rewards to motivate your behavior today she is going to have to calibrate the magnitude of those incentive payments to your discount factor. The fluctuations in your discount factor make this prone to error. Immediate payments are better because they don’t require Nature to make any guesses about discounting.
Andrew Caplin is visiting Northwestern this week to give a series of lectures on psychology and economics. Today he talked about some of his early work and briefly mentioned an intriguing paper that he wrote with Kfir Eliaz.
Too few people get themselves tested for HIV infection. Probably this is because the anxiety that would accompany the bad news overwhelms the incentive to get tested in the hopes of getting the good news (and also the benefit of acting on whatever news comes out.) For many people, if they have HIV they would much rather not know it.
How do you encourage testing when fear is the barrier? Caplin and Eliaz offer one surprisingly simple, yet surely controversial possibility: make the tests less informative. But not just any old way. Because we want to maintain the carrot of a positive result but minimize the deterrent of a negative result. Now we could try outright deception by certifying everyone who tests negative but give no information to those who test positive. But that won’t fool people for long. Anyone who is not certified will know he is positive and we are back to the anxiety deterrent.
But even when we are bound by the constraint that subjects will not be fooled there is a lot of freedom to manipulate the informativeness of the test. Here’s how to ramp down the deterrent effect of bad result without losing much of the incentive effects of a good result. A patient who is tested will receive one of two outcomes: a certification that he is negative or an inconclusive result. The key idea is that when the patient is negative the test will be designed to produce an inconclusive result with positive probability p. (This could be achieved by actually degrading the quality of the test or just withholding the result with positive probability.)
Now a patient who receives an inconclusive result won’t be fooled. He will become more pessimistic, that is inevitable. But only slightly more pessimistic. The larger we choose p (the key policy instrument) the less scary is an inconclusive result. And no matter what p is, a certification that the patient is HIV-negative is a 100% certification. There is a tradeoff that arises, of course, and that is that high p means that we get the good news less often. But it should be clear that some p, often strictly between 0 and 1, would be optimal in the sense of maximizing testing and minimizing infection.
In the New Yorker, Lawrence Wright discusses a meeting with Hamid Gul, the former head of the Pakistani secret service I.S.I. In his time as head, Gul channeled the bulk of American aid in a particular direction:
I asked Gul why, during the Afghan jihad, he had favored Gulbuddin Hekmatyar, one of the seven warlords who had been designated to receive American assistance in the fight against the Soviets. Hekmatyar was the most brutal member of the group, but, crucially, he was a Pashtun, like Gul.
But
Gul offered a more principled rationale for his choice: “I went to each of the seven, you see, and I asked them, ‘I know you are the strongest, but who is No. 2?’ ” He formed a tight, smug smile. “They all said Hekmatyar.”
Gul’s mechanism is something like the following: Each player is allowed to cast a vote for everyone but himself. The warlord who gets the most votes gets a disproportionate amount of U.S. aid.
By not allowing a warlord to vote for himself, Gul eliminates the warlord’s obvious incentive to push his own candidacy to extract U.S. aid. Such a mechanism would yield no information. With this strategy unavailable, each player must decide how to cast a vote for the others. Voting mechanisms have multiple equilibria but let us look at a “natural” one where a player conditions on the event that his vote is decisive (i.e. his vote can send the collective decision one way or the other). In this scenario, each player must decide how the allocation of U.S. aid to the player he votes for feeds back to him. Therefore, he will vote for the player who will use the money to take an action that most helps him, the voter. If fighting Soviets is such an action, he will vote for the strongest player. If instead he is worried that the money will be used to buy weapons and soldiers to attack other warlords, he will vote for the weakest warlord.
So, Gul’s mechanism does aggregate information in some circumstances even if, as Wright intimates, Gul is simply supporting a fellow Pashtun.
- There is an inverse relationship between how carefully you stack the dishes inside the dishwasher and how tidy you keep it outside in your kitchen.
- In addition to funny-haha and funny-strange there is a third category of joke where the impetus for laughter is that the comedian has made some embarrassing fact that is privately true for all of us into common knowledge.
- It would be too much of an accident for 50-50 genetic mixing to be evolutionarily optimal. So to compensate we must have a programmed taste either for mates who are similar to us or who are different.
- It is well known that in a moderately sized group of total strangers the probability is about 50% that two of them will have the same birthday. But when that group happens to be at a restaurant the probability is virtually 1.
I know of that line of apparel only because I have seen the name stenciled across the shirts and sweaters of its devotees. I infer that they are really nice clothes. Somehow I want to own some.
Which makes me wonder why they are not just giving their clothes away. We get free shirts, they get to drape their brand name across our bodies. Perhaps they would be selective about which bodies, but there must be a market opportunity here. If brand recognition drives sales then the eventual premium they could charge would seem to justify a lot of free hoodies up front. How else can we explain Abercrombie and Fitch, once a middling brand of fishing/hunting wear now international purveyors of pre-teen libido?
Normally this kind of rent seeking would be doubly inefficient. Resources wasted in a competition to corner the market, then the inefficient scarcity under the resulting monopoly. But in this case the rent seeking behavior involves giving away the stuff that’s eventually going to be so scarce. Moreover, since we apparently want to wear only the coolest clothes, the eventual monopoly may in fact be the first-best outcome. So we have firms competing to create the surplus maximizing market structure and in the process handing out all the accompanying rents in the form of euro-inscripted jeggings.
The new iPad “newspaper” the Daily profiles Next Restaurant and their fixed-price online reservation system. As we blogged before, the tickets sell out in seconds and there is a huge resale market with $85 tickets selling for thousands of dollars in the resale market. The excess demand implies the tickets are underpriced from a pure profit-maximization perspective. But Nick Kokonas, one of the partners in Next and the person responsible for the innovative pricing scheme, is reluctant to use an auction to capture the surplus Next is generating for scalpers. He is worried about price-gauging. We have suggested one solution: impose a maximum price/ticket, say $150.
There is a new idea reported in the Daily: Next will offer “season tickets” in 2012, allowing dinners to come four times/year, each time the restaurant changes theme, going from say French early twentieth century to South Indian mid-twentieth century (just a suggestion!). The usual motivation for season tickets is to offer a “volume discount” and extract more surplus from high willing to pay customers. Another is to have demand tied in. Next has no need to offer volume discounts, if anything the tables are priced too cheap. Perhaps there will be a volume premium for guests privileged enough to be able to go to four meals at Next rather that try to find four separate reservations? I guess the season tickets make it even easier to fill up the restaurant for the year and reduce the reservations hassle factor for the restaurant. Looking forward to hearing the details….
Here is a problem at has been in the back of my mind for a long time. What is the second best dominant-strategy mechanism (DSIC) in a market setting?
For some background, start with the bilateral trade problem of Myerson-Satterthwaite. We know that among all DSIC, budget-balanced mechanisms the most efficient is a fixed-price mechanism. That is, a price is fixed ex ante and the buyer and seller simply announce whether they are willing to trade at that price. Trade occurs if and only if both are willing and if so the buyer pays the fixed price to the seller. This is Hagerty and Rogerson.
Now suppose there are two buyers and two sellers. How would a fixed-price mechanism work? We fix a price p. Buyers announce their values and sellers announce their costs. We first see if there are any trades that can be made at the fixed price p. If both buyers have values above p and both sellers have values below then both units trade at price p. If two buyers have values above p and only one seller has value below p then one unit will be sold: the buyers will compete in a second-price auction and the seller will receive p (there will be a budget surplus here.) Similarly if the sellers are on the long side they will compete to sell with the buyer paying p and again a surplus.
A fixed-price mechanism is no longer optimal. The reason is that we can now use competition among buyers and sellers and “price discovery.” A simple mechanism (but not the optimal one) is a double auction. The buyers play a second-price auction between themselves, the sellers play a second-price reverse auction between themselves. The winner of the two auctions have won the right to trade. They will trade if and only if the second highest buyer value (which is what the winning buyer will pay) exceeds the second-lowest seller value (which is what the winning seller will receive.) This ensures that there will be no deficit. There might be a surplus, which would have to be burned.
This mechanism is DSIC and never runs a deficit. It is not optimal however because it only sells one unit. But it has the viture of allowing the “price” to adjust based on “supply and demand.” Still, there is no welfare ranking between this mechanism and a fixed-price mechanism because a fixed price mechanism will sometimes trade two units (if the price was chosen fortuitously) and sometimes trade no units (if the price turned out too high or low) even though the price discovery mechanism would have traded one.
But here is a mechanism that dominates both. It’s a hybrid of the two. We fix a price p and we interleave the rules of the fixed-price mechanism and the double auction in the following order
- First check if we can clear two trades at price p. If so, do it and we are done.
- If not, then check if we can sell one unit by the double auction rules. If so, do it and we are done.
- Finally, if no trades were executed using the previous two steps then return to the fixed-price and see if we can execute a single trade using it.
I believe this mechanism is DSIC (exercise for the reader, the order of execution is crucial!). It never runs a deficit and it generates more trade than either standalone mechanism: fixed-price or double auction.
Very interesting research question: is this a second-best mechanism? If not, what is? If so, how do you generalize it to markets with an arbitrary number of buyers and sellers?
- Poetry by selective transcription. (I think I will take one of her poems and add additional words to make a radio story.)
- Miley Cyrus singing Smells Like Teen Spirit.
- Expressionist urnial
- Re-assuring lack of correlation.
- This is just by way of public confession that I listened to this entire thing.
James is an alley-mechanic – he and his team of five workers repair cars in an alley behind a church on the South Side of Chicago. James rents the space from the church pastor for $50/day. James has been doing business there for twenty years or so. Then, along comes Carl, another alley mechanic. He sets up a garage close to James. Carl hires some homeless people to hand out flyers offering discounts to motorists arriving at James’ repair shop.
James is ticked, to put it mildly. James thinks he has property rights to car repairs in the area – he pays $50/day for this right. He asks the pastor to adjudicate. The pastor is well-known in the neighborhood and often acts as a mediator in contractual disputes. The pastor finds in favor of James. But Carl is not from the neighborhood and does not acknowledge the pastor’s authority. He continues to compete with James.
James turns to an informal court that has developed in the neighborhood. The court arose to settle disputes between rival gangs but it grew to act as a general arbiter of contractual disagreements in the local underground economy. Again, the court finds in favor of James. Again, Carl ignores the determination of the “court” as it has no authority over him. Finally, the pastor is forced to use old-fashioned contract enforcement – violence. He hires a gang of thugs to beat up Carl and his crew and drive them out. End of story
(Source: Talk by Sudhir Venkatesh at the Harris School, University of Chicago)
