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“If you don’t have something nice to say, don’t say anything at all.” That is usually bad advice. Because then when you say nothing at all it is understood that you have only unkind things to say.
If you are trying to maximize pleasantry then your policy should depend on your listener’s preferences. Based on what you say she is going to revise her beliefs over what you think about her. What matters is her preferences over these beliefs.
A key fact is that you have only limited control over those beliefs. Some of the time you will say something kind and some of the time you will say something unkind. These will move her beliefs up and down but by the law of total probability the average value of her beliefs is equal to her prior. You control only the variance.
If good feelings help at the margin more than bad feelings hurt then she is effectively risk-loving. You should go to extremes and maximize variance. Here the old adage applies: you should say something nice when you have something nice to say and you should not say anything nice when you don’t. In terms of her beliefs, it makes no difference whether you say the unkind thing or just keep quiet and allow her to infer it. But perhaps politeness gets a lexicographic kick here and you should not say anything at all.
(On thing the standard policy ignores is the ambiguity. Since there are potentially many unkind things you might be witholding, if she is pessimistic you might worry that she will assume the worst. Then you should consider saying slightly-unkind things in order to prevent the pessimistic inference. Still there is the danger of unraveling because then when you say nothing at all she will know that what is on your mind is even worse than that.)
If she is risk-averse in beliefs then you want to go to the opposite extreme and never say anything. She never updates her beliefs.
But prospect theory suggests that her preferences are S-shaped around the prior: risk-averse on the upside but risk-loving on the downside. Then often it is optimal to generate some variance but not to go to extremes. You do this by dithering. Your never give outright compliments or insults. Your statements are always noisy and subject to interpretation. But the signal to noise ratio is not zero.
A full analysis of this problem would combine the tools of psychological game theory with persuasion mechanisms a’ la Gentzkow and Kamenica.
A primer in the New York Times.
Kit is a freegan. He maintains that our society wastes far too much. Freeganism is a bubbling stew of various ideologies, drawing on elements of communism, radical environmentalism, a zealous do-it-yourself work ethic and an old-fashioned frugality of the sock-darning sort. Freegans are not revolutionaries. Rather, they aim to challenge the status quo by their lifestyle choices. Above all, freegans are dedicated to salvaging what others waste and — when possible — living without the use of currency. “I really dislike spending money,” Kit told me. “It doesn’t feel natural.”
Its kinda like composting as a lifestyle, only with someone else’s waste and instead of making fertilizer you either eat it or live in it. An entertaining read from start to finish with cameos by roadkill, frozen toilets and even property rights.
Afghan security firms provide armed escorts for NATO convoys. Some firms lost their employment because of violent incidents where they killed civilians. But NATO Convoys them suffered greater attacks and the security firms were re-employed. There is an obvious incentive problem:
“The officials suspect that the security companies may also engage in fake fighting to increase the sense of risk on the roads, and that they may sometimes stage attacks against competitors.
The suspicions raise fundamental questions about the conduct of operations here, since the convoys, and the supplies they deliver, are the lifeblood of the war effort.
“We’re funding both sides of the war,” a NATO official in Kabul said. The official, who spoke on the condition of anonymity because the investigation was incomplete, said he believed millions of dollars were making their way to the Taliban.”
This is a Mafia tactic: To get people to pay from protection, you have to create the demand for protection. Supply creates its own demand. There is also a reverse effect: The security firms sometimes bribe the Taliban to keep away from the convoys. With this source of steady income, the Taliban have no incentive to disband and may even have an incentive to expand. Demand creates its own supply.
The second circle seems less pathological than the first. If we cannot find the Taliban ourselves and kill them or bribe them then to stay away from the convoys, we have to use a local security firm. The security firm is an intermediary, adding value and generating surplus. The first circle is destroying surplus, like the Mafia. It is creating a public bad, a security problem, to generate a transfer.
Beyond punishing anyone who is caught planning a deliberate attack, it is hard to see any simple solution. Fewer and fewer countries want to be involved in Afghanistan and so using our own troops is difficult. The Taliban might prefer to be employed in the real economy. But the main alternative to attacking NATO convoys is growing opium. Is that any better than attack and theft?
The entire episode signals that Afghanistan is a Mafia state with leaders acting an profit maximizers, destroying surplus to capture a bigger slice of what’s left of the economic pie. A depressing state of affairs after eight years of war.
Here is a good metaphor for a problem Mother Nature has to solve. A small child is playing on the equipment at the playground. The child knows what she is physically capable of but doesn’t know what is safe. If Nature knew about swings and see-saws and monkey bars she would just encode their riskiness into the genes of the child and let the child do the optimization.
But these things came along much too recently for Nature to know about them. Fortunately Nature knows that whatever is in the child’s world was pretty likely also in the parents’ world and by now the parents have learned what is safe. So Nature can employ the parent as her agent.
But in this family-firm, the child is a specialist too. For one thing she has up-to-the-minute information about her physical abilities which change too quickly for the parents to keep track of. But just as importantly the child is the cheapest source of information about what’s in front of her. Nature could press the parent into service again to investigate the set of possible activities available to the child, but this would be costly to the parent (for whom this carrier of only half of his genes is just one of many priorities) and so would require extra incentives and anyway that information is more directly accessible to the child.
So Nature’s organizational structure utilizes a tidy division of labor. The child’s job is to identify the feasible set and the parent’s job is to veto all the alternatives that are too dangerous. One last constraint explains the reckless kid. The child cannot communicate the feasible set to the parent. This leads to the third-best solution. The child just picks something nearby, say the rope bridge, and starts climbing on it. The parent is stationed nearby ready to intervene whenever the child’s first choice is too dangerous.
And thus the seeds of much later conflict are sown.
Heather Christle tweeted:
Pacifico beer tastes like it’s mad at me.
On the other hand, Elk Cove 2007 Wilamette Valley Pinot Noir tastes like it’s embarrassed by me. Almost as if we met once before on chatroullette and sensed immediately that we were bound by some primitive psychic traction and for the briefest instant we realized how all of history had in fact led us to this seemingly random moment, face to digitized face; only to be stopped, not more than an instant later by the simultaneous fear that our common epiphany could not be real but instead just a projection of our own deep sense of unfulfillment which now was out in the open plainly readable on our faces, the shame of which brought an end, by synchronized Nexting, to our only chance at untying life’s eternal knot, and as if now we have bumped into each other again at a party, introduced by mutual friends, and Elk Cove 2007 Wilamette Valley Pinot Noir glanced at its watch and escaped, avoiding eye contact and stammering about late hours and lost sleep.
While we are on the subject, you would be well-advised not to follow me on Twitter. Here is the link not to follow. Here are the kinds of things you are better off avoiding.
The big news is that AT&T will be discontinuing its unlimited use data plans effective next week which happens to coincide with Steve Jobs worst-kept-secret announcement of the next-generation iPhone. People are up in arms.
Unlimited, all-you-can-eat wireless data was a beautiful thing for Apple devices on AT&T, delivering streams of Pandora, YouTube videos, a million tweets, and hundreds of webpages without worry. And now it’s dead.
AT&T’s new, completely restructured mobile data plans for both iPhones and iPads have officially launched the era of pay-per-byte data, which we’ve known was coming. We just hoped it would take a little longer. It’s the anti-Christmas.
One thing to keep in mind is that unlimited use tariffs are not part of an efficient or profit-maximizing pricing policy whether you consider monopoly or perfect competition. It is hard to imagine a model under which unlimited use makes sense unless there is zero marginal cost. (If marginal cost is positive then under unlimited use your usage will typically go beyond the point where your marginal value exceeds marginal cost. Whatever the market structure, this would be replaced by marginal cost pricing possibly with a reduced fixed fee.)
Still the specific form of the tariff– zero per-MB cost up to some limit and then a steep price after that– annoys many people. In fact, there are theories that show that this kind of pricing is the best way to exploit consumers who don’t accurately forecast their own usage.
But this brings me to the second thing to keep in mind. Those exploits take advantage of people who underestimate their usage. But here is the actual pricing menu.
I bet that you actually overestimate your usage. I use my phone a lot for browsing the web, maps, etc. and I average under 200 MB per month. Because some months I do go above 200MB, I will buy the 2GB plan for $25 (I don’t need tethering.) My wife on the other hand never goes above 200MB. So the new plan is a better deal for us.
Here’s how to check your usage.
Neil is a great businessman as well as a popular songwriter (though he’s unlucky in love and that cost him). In an earlier post, I wondered why artists do not simply price discriminate and not let scalpers get the rents. If they do not want to look exploitative, then can try to use some other instruments (e.g. a refund to loyal fans) to avoid just letting scalpers exploit the fans.
Another answer is that artists actually do perform price discrimination using the scalper as the intermediary:
Less than a minute after tickets for last August’s Neil Diamond concerts at New York’s Madison Square Garden went on sale, more than 100 seats were available for hundreds of dollars more than their normal face value on premium-ticket site TicketExchange.com. The seller? Neil Diamond.
Ticket reselling — also known as scalping — is an estimated $3 billion-a-year business in which professional brokers buy seats with the hope of flipping them to the public at a hefty markup.
In the case of the Neil Diamond concerts, however, the source of the higher-priced tickets was the singer, working with Ticketmaster Entertainment Inc., which owns TicketExchange, and concert promoter AEG Live. Ticketmaster’s former and current chief executives, one of whom is Mr. Diamond’s personal manager, have acknowledged the arrangement, as has a person familiar with AEG Live, which is owned by Denver-based Anschutz Corp.
Selling premium-priced tickets on TicketExchange, priced and presented as resales by fans, is a practice used by many other top performers, according to people in the industry. Joseph Freeman, Ticketmaster’s senior vice president for legal affairs, says that the company’s “Marketplace” pages only rarely list tickets offered by fans.
According to the lead singer of Nine Inch Nails:
the true market value of some tickets for some concerts is much higher than what the act wants to be perceived as charging. For example, there are some people who would be willing to pay $1,000 and up to be in the best seats for various shows, but MOST acts in the rock / pop world don’t want to come off as greedy pricks asking that much, even though the market says its value is that high. The acts know this, the venue knows this, the promoters know this, the ticketing company knows this and the scalpers really know this. So…
The venue, the promoter, the ticketing agency and often the artist camp (artist, management and agent) take tickets from the pool of available seats and feed them directly to the re-seller (which from this point on will be referred to by their true name: SCALPER). I am not saying every one of the above entities all do this, nor am I saying they do it for all shows but this is a very common practice that happens more often than not. There is money to be made and they feel they should participate in it. There are a number of scams they employ to pull this off which is beyond the scope of this note.
StubHub.com is an example of a re-seller / scalper. So is TicketsNow.com.
Of course, the danger is that the fans find out what the artist is doing – e.g. Neil Diamond’s strategy has been fully revealed thanks to the WSJ. Either this leads to a counter-reaction or fans just get used to it and accept the new norms. Hard to say what is happening but the Bon Jovi VIP pricing without using a scalper as a middleman suggests more fans are accepting direct price discrimination by the artist.
(Hat Tip: Troy Kravitz and Mallesh Pai)
Jonah Lehrer has a post
about why those poor BP engineers should take a break. They should step away from the dry-erase board and go for a walk. They should take a long shower. They should think about anything but the thousands of barrels of toxic black sludge oozing from the pipe.
He weaves together a few stories illustrating why creativity flows best when it is not rushed. This is something I generally agree with and his post is good read but I think one of his examples needs a second look.
In the early 1960s, Glucksberg gave subjects a standard test of creativity known as the Duncker candle problem. The problem has a simple premise: a subject is given a cardboard box containing a few thumbtacks, a book of matches, and a waxy candle. They are told to determine how to attach the candle to piece of corkboard so that it can burn properly and no wax drips onto the floor.
Oversimplifying a bit, to solve this problem there is one quick-and-dirty method that is likely to fail and then another less-obvious solution that works every time. (The answer is in Jonah’s post so think first before clicking through.)
Now here is where Glucksberg’s study gets interesting. Some subjects were randomly assigned to a “high drive” group, which was told that those who solved the task in the shortest amount of time would receive $20.
These subjects, it turned out, solved the problem on average 3.5 minutes later than the control subjects who were given no incentives. This is taken to be an example of the perverse effect of incentives on creative output.
The high drive subjects were playing a game. This generates different incentives than if the subjects were simply paid for speed. They are being paid to be faster than the others. To see the difference, suppose that the obvious solution works with probability p and in that case it takes only 3.5 minutes. The creative solution always works but it takes 5 minutes to come up with it. If p is small then someone who is just paid for speed will not try the obvious solution because it is very likely to fail. He would then have to come up with the creative solution and his total time will be 8.5 minutes.
But if he is competing to be the fastest then he is not trying to maximize his expected speed. As a matter of fact, if he expects everyone else to try the obvious solution and there are N others competing, then the probability is 
So it is an equilibrium for everyone to try the quick-and-dirty solution, and when they do so, almost all of them (on average a fraction 1-p of them) will fail and take 3.5 minutes longer than those in the control group.
Consider the game among a couple and their male marriage counselor. The problem for the marriage counselor is to prove that he is unbiased. It is common-knowledge at the outset that the wife worries that a male marriage counselor is biased and will always blame the wife.
Indeed if 10 weeks in a row they come in for counseling and talk about the week’s petty argument (how to stack dishes in the dishwasher, whether it matters that the towels are not folded corner-to-corner, etc.) he everytime sides with the husband, eventually the wife will want to find a new counselor.
So what happens after 9 weeks of deciding for the husband? Now all parties know that the counselor is on his last leg. He must start siding with the wife in order to keep his job, even if the husband is actually in the right (i.e. even if throwing out the 3-day old soggy quesadilla in the refrigerator was the right thing to do.) But that means that he’s now biased in favor of the wife and so the husband will fire him.
We have just concluded that if he decides for the husband 9 times in a row he will be fired. So what happens on week 9 in the rare event that he has decided for the husband 8 times in a row. Same thing, he is strategically biased in favor of the wife and he will be fired.
By induction he is biased even on week 1.
(NB: my marriage is beautiful (no counseling) and there is nobody who can fold a towel faster than me.)
David Leonhardt had an interesting column on underestimation of risk. BP’s possible underinvestment in protecting against a gross accident is exhibit one.:
The people running BP did a dreadful job of estimating the true chances of events that seemed unlikely — and may even have been unlikely — but that would bring enormous costs.
Perhaps the easiest way to see this is to consider what BP executives must be thinking today. Surely, given the expense of the clean-up and the hit to BP’s reputation, the executives wish they could go back and spend the extra money to make Deepwater Horizon safer. That they did not suggests that they figured the rig would be fine as it was.
But this does not prove the case. You may buy a stock given the odds of it going up or down. If it goes down you will regret your investment. This does not prove it was wrong to invest in the first place. It might have been right given your initial assessment. The same logic applies to BP.
This is a simple point: regret does not imply that the ex ante decision was bad. Leonhardt is a great economics commentator and journalist. The fact that he makes this elementary mistake shows how easy it is to make.
But there is another factor at work. It is impossible to determine BP’s probability assessment after the fact. They can always claim the chance of a disaster was low. There is no historical data against which to measure their assessment. All we are left with is the option to blame them even if their decision was perfect from an ex ante perspective. Blame involves saying them made a bad decision and holding them to account. This was the key element in Jeff’s earlier post on the Blame Game.
I spent one year as an Associate Professor at Boston University. The doors in the economics building are strange because the key turns in the opposite way you would expect. Instead of turning the key to the right in order to pull the bolt left-to-right, you turn the key to the left. For the first month I got it wrong every morning.
Eventually I realized that I needed to do the opposite of my instinct. And so as I was just about to turn the key to the right I would stop myself and do the opposite. This worked for about a week. The problem was that as soon as I started to consistently get it right, it became second nature and then I could no longer tell what my primitive instinct was and what my second-order counter-instinct was. I would begin to turn the key to the left and then stop myself and turn the key to the right.
I have since concluded that it is basically impossible to “do the opposite” and that we are all lesser beings because of it. We could learn from experience much faster if we had the ability to remenber what our a) what our natural instinct is b) whether it works and c) to do the opposite when it doesn’t.
We could be George Castanza:
John F Kennedy was born in Brookline and attended Devotion School. Our kids are attending Devotion this year and our third-grader took part in a lovely event at JFK’s birthplace last week. There were some nice speeches, including one by the head of the JFK Presidential Library . It involved this story:
When Jack was quite young but old enough to ride a bike, he played a game of Chicken with his older brother Joe, perhaps on the very street of his birthplace. In classic fashion, they raced towards each other on their bikes. Joe expected some respect from his younger brother. Joe thought Jack would swerve and let him win the game. No such luck. They slammed into each other and had to go to hospital.
I had never heard this story before. I mentioned it to several Americans but they had never heard it either. Everyone knows the famous Chicken story: Khrushchev vs Kennedy during the Cuban Missile Crisis.
Schelling could always take commonplace strategic interactions and draw fundamental lessons from them. Similarly, it would be nice to think that JFK’s childhood experience gave him some insight into how to play Chicken when the stakes were high.
In a famous paper, Mark Walker and John Wooders tested a central hypothesis of game theory using data on serving strategy at Wimbledon. The probability of winning a point conditional on serving out wide should equal the probability conditional on serving down the middle. They find support for this in the data.
A second hypothesis doesn’t fare so well. Walker and Wooders suggest that the location of the serve should be statistically independent over time, and this is not borne out in the data. The reason for the theoretical prediction is straightforward and follows from the usual zero-sum logic. The server is trying to be unpredictable. Any serial correlation will allow the returner to improve his prediction where the serve is coming and prepare.
But this assumes there are no payoff spillovers from point to point. However it’s probably true that having served to the left on the first serve (and say faulted) is effectively “practice” and this makes the server momentarily better than average at serving to the left again. If this is important in practice, what effect would it have on the time series of serves?
It has two effects. To understand the effects it is important to remember that optimal play in these zero-sum games is equivalent to choosing a random strategy that makes your opponent indifferent between his two strategies. For the returner this means randomly favoring the forehand or backhand side in order to equalize the server’s payoffs from the two serving directions. Since the server now has a boost from serving, say, out wide again, the returner must increase his probability of guessing that direction in order to balance that out. This is a change in the returner’s behavior, but not yet any change in the serving probabilities.
The boost for the server is a temporary disadvantage for the returner. For example, if he guesses down the line, he is more likely to lose the point now than before. He may also be more likely to lose the point even if he guesses out wide, but lets say the first outweighs the second. Then the returner now prefers to guess out wide. The server has to adjust his randomization in order to restore indifference for the returner. He does this by increasing the probability of serving down the line.
Thus, a first serve fault out wide increases the probability that the next serve is down the line. In fact, this kind of “excessive negative correlation” is just what Walker and Wooders found. (Although I am not sure how things break down within-points versus across-points and things are more complicated when we consider ad-court serves to deuce-court serves.)
(lunchtime conversation with NU faculty acknowledged, especially a comment by Alessandro Pavan.)
Cheap Talk 