This is a bit outside the normal bailiwick of this blog, but is the sort of off-the-wall, half-baked idea that seems to fit here at least in that way.
Police work, at least as done in modern America, requires special authority, sometimes including the authority to use force in ways that wouldn't be allowed to a private citizen; sometimes the police make mistakes, and it is important to create systems that reduce the likelihood of that, but allowances also need to be made that they are human beings put in situations where they are likely to believe they lawfully have certain authority; if a police officer arrests an innocent man, the officer will face no legal repercussions, while a private citizen would, even if the private citizen had "reasonable cause" to suspect the victim. It is appropriate that this leeway be made, at least as for legal repercussions; if a particular police officer shows a pattern of making serious mistakes, even if they are clearly well-intended, it is just common sense[1] that that officer should be directed to more suitable employment, but being an officer trying to carry out the job in good faith should be a legal defense to criminal charges.
That extra authority, though, comes — morally if not legally — with a special duty not to intentionally abuse it. This is the case not least because the task of police work is much more feasible where the citizens largely trust that an order appearing to come from a police officer is lawful than where they don't. A police officer in Alabama was reported, not long ago, to have sexually assaulted someone he had detained, and in a situation like that the initial crime is additional to the societal cost of eroding trust people have that the officer is at least trying to be on the side of law. This erosion of trust is also the primary reason that impersonating a police officer is a serious crime.[2] I propose, then, upon the showing of mens rea in the commission of a serious crime by a police officer while using that office to facilitate the crime, that the officer be fired retroactively --- and brought up additionally on the impersonation charges.[3]
[1] I mean, it should be. My impression is that it is too difficult to remove bad cops, but that's not an especially well-informed impression.
[2] Pressed to give secondary reasons, they would also line up pretty well between impersonating an officer and abusing the office.
[3] This policy would have an interesting relationship to the "no true Scotsman fallacy"; no true police officer would intentionally commit a heinous crime, and we'll redefine who was an officer when if we have to to make it true.
Wednesday, July 27, 2016
Tuesday, July 26, 2016
liquidity and efficiency of goods and services
Years ago, I went to a barber and got a haircut that took no more than five minutes. I go with simple haircuts, and he had basically run some clippers over my head and used scissors to blend what was left. At first, I was a bit taken aback, and thought that perhaps I should tip less than usual (and indeed wondered whether I should be charged less than usual altogether), but very quickly realized that this was perverse; the haircut I had received was not, in the context of my preferences, inferior in any way to other haircuts I have received, and I'm better off having the other (say) 15 minutes of my time to (say) squander writing blog posts on the internet. Ceteris paribus, we both benefit from his having finished more quickly; I left my usual tip, leaving the pecuniary terms of trade unchanged from those in which we both lose more time.
Liquidity, like speed, is a benefit to both the buyer and the seller; both are a bit hard to analyze with supply and demand for this reason. (My go-to deep neoclassical model, from Arrow-Debreu, treats a quick haircut as a different service from a slow haircut, and as such treats them as different markets, but they are such close substitutes that it's obviously useful to treat them as in some sense "almost" the same market.) There may well be other ways in which different instances of a good or service differ in ways such that the quality that is better for the buyer is naturally better for the seller as well. My interest especially is in market liquidity, and I wonder whether distilling out this aspect provides useful models for some of the important phenomenology around that.
Liquidity, like speed, is a benefit to both the buyer and the seller; both are a bit hard to analyze with supply and demand for this reason. (My go-to deep neoclassical model, from Arrow-Debreu, treats a quick haircut as a different service from a slow haircut, and as such treats them as different markets, but they are such close substitutes that it's obviously useful to treat them as in some sense "almost" the same market.) There may well be other ways in which different instances of a good or service differ in ways such that the quality that is better for the buyer is naturally better for the seller as well. My interest especially is in market liquidity, and I wonder whether distilling out this aspect provides useful models for some of the important phenomenology around that.
Tuesday, July 12, 2016
risk and uncertainty
A century ago, an economist named Frank Knight wrote a book on "Risk and Uncertainty", where by "risk" he meant what economists generally alternate between calling "risk" and "uncertainty" today and by "uncertainty" he meant something economists haven't given as much attention in the past seventy years, but have tended to call "ambiguity" when they do.[1] The distinction is how well the relevant ignorance can be quantified; a coin toss is "risky", rather than "ambiguous", because we have pretty high confidence that the "right" probability is 50%, while the possibility of a civil war in a developed nation in the next ten years is perhaps better described as "ambiguous". Here is a link to the wikipedia page on the Ellsberg paradox. Weather in the next few days would have been "ambiguous" when Knight wrote, but was becoming risky, and is well quantifiable these days.
Perhaps one of the reasons the study of ambiguity fell out of favor, and has largely stayed there for more than half a century since then,[2] is that a strong normative case for the assignment of probabilities to events was developed around World War II; in short, there is a set of appealing assumptions about how a person would behave that imply that they would act so as to maximize "expected utility", where "utility" is a real-valued function of the outcome of the individual's actions and "expected" means some kind of weighted average over possible outcomes. In perhaps simpler terms, if a reasonably intelligent person who understands the theorem were presented with actions that person had taken that were not all consistent with expected utility maximization, that person would probably say, "Yeah, I must have made a mistake in one of those decisions," though it would probably still be a matter of taste as to which of the decisions was wrong.
To be a bit more concrete, suppose an entrepreneur is deciding whether or not to build a factory. The factory is likely to be profitable under some scenarios and unprofitable under others, and the entrepreneur will not know for sure which will obtain; if certain risks are likelier than some threshold, though, building the factory will have been a bad idea, and if they're less likely, than it will have been a good idea. Whether or not the factory is built, then, implies at least a range of probabilities that the entrepreneur must impute to the risks; an entrepreneur making other decisions that are bad for any of those probabilities is making a mistake somewhere, such that changing multiple decisions guarantees a better outcome, though which decision(s) should be changed may still be up for debate (or reasoned assessment). The rejoinder, then, to the assertion that a probability can't be put on a particular event, is that often probabilities are, at least implicitly, being put on unquantifiable events; it is certainly not necessarily the case that the best way to make those decisions is to start by trying to put probabilities on the risks, but it probably is worth trying to make sure that there is some probabilistic outlook that is consistent with the entire schedule of decisions, and, if there isn't, to consider which decisions are likely to be in error.[3]
There is a class of situations, though, in which something that resembles "ambiguity aversion" makes a lot of sense, and that is being asked to (in some sense) quote a price for a good in the face of adverse selection. If, half an hour after a horse race, you remark to someone "the favored horse probably won," and she says, "You want to bet?", then, no, you don't. In general, I should suppose that other people have some information that I don't, and if I expect that they have a lot of information that I don't, then my assessment of the value of an item or the probability of an event may be very different if I condition on some of their information than if I don't; if I set a price at which I'm willing to sell, and can figure out from the fact that someone is willing to buy at that price that I shouldn't have sold at that price, I'm setting the price too low, even if it's higher than I initially think is "correct".
In a lot of contexts in which people seem to be avoiding "ambiguity", this may well fit a model of a certain willingness to accept other's probability assessments; e.g. I'm not willing to bet at any price on a given proposition, because, conditional on others' assessments, my assessment is very close to theirs.
[1] There's a nonzero chance that I have his terms backward, but that nonzero chance is hard to quantify; in any case, the concepts here are what they are, and I'll try to keep my own terminology mostly consistent with itself.
[2] I'm pretty sure Pesendorfer and/or Gul, both of whom I believe are or were at Princeton, have produced some models since the turn of the millennium attempting to model "ambiguity aversion", and I should probably read Stauber (2014): "A framework for robustness to ambiguity of higher-order beliefs," International Journal of Game Theory, 43(3): 525--550. This isn't quite my field.
[3] In certain institutional settings, certain seemingly unquantifiable events may be very narrowly pinned down; I mostly have in mind events that are tied to options markets. If a company has access to options markets on a particular event, it is likely that there is a probability above which not buying (more) options is a mistake, and another below which not selling (more) options is a mistake, and those probabilities may well be very close to each other. If you think you should build a factory, and the options-implied probability suggests you shouldn't, buying the options instead might strictly dominate building the factory; if you think you shouldn't and the market thinks you should, your best plan might be to build the factory and sell the options.
Perhaps one of the reasons the study of ambiguity fell out of favor, and has largely stayed there for more than half a century since then,[2] is that a strong normative case for the assignment of probabilities to events was developed around World War II; in short, there is a set of appealing assumptions about how a person would behave that imply that they would act so as to maximize "expected utility", where "utility" is a real-valued function of the outcome of the individual's actions and "expected" means some kind of weighted average over possible outcomes. In perhaps simpler terms, if a reasonably intelligent person who understands the theorem were presented with actions that person had taken that were not all consistent with expected utility maximization, that person would probably say, "Yeah, I must have made a mistake in one of those decisions," though it would probably still be a matter of taste as to which of the decisions was wrong.
To be a bit more concrete, suppose an entrepreneur is deciding whether or not to build a factory. The factory is likely to be profitable under some scenarios and unprofitable under others, and the entrepreneur will not know for sure which will obtain; if certain risks are likelier than some threshold, though, building the factory will have been a bad idea, and if they're less likely, than it will have been a good idea. Whether or not the factory is built, then, implies at least a range of probabilities that the entrepreneur must impute to the risks; an entrepreneur making other decisions that are bad for any of those probabilities is making a mistake somewhere, such that changing multiple decisions guarantees a better outcome, though which decision(s) should be changed may still be up for debate (or reasoned assessment). The rejoinder, then, to the assertion that a probability can't be put on a particular event, is that often probabilities are, at least implicitly, being put on unquantifiable events; it is certainly not necessarily the case that the best way to make those decisions is to start by trying to put probabilities on the risks, but it probably is worth trying to make sure that there is some probabilistic outlook that is consistent with the entire schedule of decisions, and, if there isn't, to consider which decisions are likely to be in error.[3]
There is a class of situations, though, in which something that resembles "ambiguity aversion" makes a lot of sense, and that is being asked to (in some sense) quote a price for a good in the face of adverse selection. If, half an hour after a horse race, you remark to someone "the favored horse probably won," and she says, "You want to bet?", then, no, you don't. In general, I should suppose that other people have some information that I don't, and if I expect that they have a lot of information that I don't, then my assessment of the value of an item or the probability of an event may be very different if I condition on some of their information than if I don't; if I set a price at which I'm willing to sell, and can figure out from the fact that someone is willing to buy at that price that I shouldn't have sold at that price, I'm setting the price too low, even if it's higher than I initially think is "correct".
In a lot of contexts in which people seem to be avoiding "ambiguity", this may well fit a model of a certain willingness to accept other's probability assessments; e.g. I'm not willing to bet at any price on a given proposition, because, conditional on others' assessments, my assessment is very close to theirs.
[1] There's a nonzero chance that I have his terms backward, but that nonzero chance is hard to quantify; in any case, the concepts here are what they are, and I'll try to keep my own terminology mostly consistent with itself.
[2] I'm pretty sure Pesendorfer and/or Gul, both of whom I believe are or were at Princeton, have produced some models since the turn of the millennium attempting to model "ambiguity aversion", and I should probably read Stauber (2014): "A framework for robustness to ambiguity of higher-order beliefs," International Journal of Game Theory, 43(3): 525--550. This isn't quite my field.
[3] In certain institutional settings, certain seemingly unquantifiable events may be very narrowly pinned down; I mostly have in mind events that are tied to options markets. If a company has access to options markets on a particular event, it is likely that there is a probability above which not buying (more) options is a mistake, and another below which not selling (more) options is a mistake, and those probabilities may well be very close to each other. If you think you should build a factory, and the options-implied probability suggests you shouldn't, buying the options instead might strictly dominate building the factory; if you think you shouldn't and the market thinks you should, your best plan might be to build the factory and sell the options.
liquidity and coordination
A kind of longish article from three years ago tells the story of a wire-basket maker adapting his company in response to foreign competition. One of the responses is to serve clientele with specific, urgent needs:
"The German vendor had made this style of product for them for over 20 years," says Greenblatt, "and quoted them four months to make the new version." Marlin said it could do the job in four weeks. And it delivered. "If a car company doing a model-year changeover can get the assembly line going faster, the value of that extra three months of production is enormous," says Greenblatt. "The baskets are paid for in a couple hours."I've described a "liquidity shock" as a sudden spike in a person's idiosyncratic short-term discount rate: a dollar today is suddenly a lot more valuable than a dollar a month or two from now. In this case, there's an incredibly steep discount rate for a real good: a basket in four weeks is a lot more valuable than a basket in four months. Drilling in just a bit more, the origin of this is a problem of coordinating different elements of the production process: while it could have been anticipated a year earlier that some kind of basket would be needed, by the time the specifications are available, the other parts of the production plan are being implemented as well, and you need them all (with the same specifications) to come together as quickly as possible. So here we have something of a liquidity shock created by something of a coordination problem (though neither of those words is being used exactly as I usually use them), combining two of my favorite phenomena.
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