Chris Hibbert writes (in a post that is partly about the mess resulting from Tradesports’ contract on North Korean missile launches):
The fact that pay-outs are limited to the amount spent to purchase claims is integral to the institution of prediction markets. If market operators ever pay off both sides of a claim, that is likely to encourage investors to protest many more close calls.
I disagree. Having pay-outs equal to claim purchases is integral to the normal function of well-written claims, but there’s little reason to stick to that rule with a claim written as poorly as the North Korean missile claim was.
Paying off both sides was the most reasonable suggestion I’ve heard for what Tradesports should have done to limit the damage to their reputation. Experience with similar disputes (such as those on FX) suggests that traders already have sufficient motive to protest questionable decisions that it’s hard to see how disputes produced only by additional incentives could bear much resemblance to reasonable disputes. The increased incentive on Tradesports to word their claims so that fewer people misunderstand how they will be judged is likely to have some desirable effects on how Tradesports explains the meaning of their contracts.
Disputed judgments might be inevitable for exchanges that cover subjects as ambitious as Tradesports does, but there’s nothing inevitable about confusion about whether a contract was about DoD confirmation of where the missiles landed, or whether it was about what the missiles did, with DoD statements merely being used if needed to resolve any uncertainty.
(I didn’t trade any of the North Korean missile contracts).
I’ve been slowly working my way through a book by Richard Zacks called An Underground Education. I’ve found one section that deserves a blog entry of it’s own (I’ll discuss the rest of the book when I’ve finished reading it).
It describes a fairly popular betting-style market that ran from 1771 to 1776 in London about whether a diplomat named Chevalier D’Eon was male or female. D’Eon apparently acted and dressed at times as a man, and at other times as a woman, and refused to help the bettors settle their bets (even when D’Eon was offered a large amount of money to provide evidence of his/her sex). Eventually bettors got tired of waiting for an outcome and resorted to at least one lawsuit. The judge decided that D’Eon was a woman based on testimony from both sides of the lawsuit. Why did the side who had bet D’Eon was a man produce testimony that D’Eon was a woman? It was part of an accusation that the other side traded on what the SEC would call inside information. After D’Eon’s death, mortuary attendants said D’Eon was a man.
Aside from the obvious implications for how idea future style markets need to word claims so as to assure a practical means of observing whether a claim is true or not within a practical time period, this report also says some odd things about gender stereotyping. Lots of people probably think prior generations mostly had Victorian attitudes toward gender confusion, but it seems that D’Eon was sufficiently respectable in 1792 to have a dinner party thrown to honor both Thomas Paine and D’Eon.
Here are a few comments from Friday’s Prediction Markets Summit.
Chris Hibbert described a way that a market with multiple outcomes (such as for supreme court nominees, which list contracts for a number of people, plus one for the rest of the field) could improve liquidity with a modest software change. The system could generate bids and asks for a given contract by aggregating the opposite side of all the other contracts in that market, and generate a synthetic order which would sometimes be within the bid/ask range of regular orders.
Google’s Bo Cowgill reported that one legal problem that Google faces in implementing internal prediction markets is that they might sometimes spread information around the company that might make the people with that information insiders in a way that would complicate those employees’ ability to trade in Google stock. It sounds like the insider trading laws are onerous enough to create a nontrivial barrier to spreading information.
Newsfutures’ Emile Servan-Schreiber said that Newsfutures was supporting the use of internal corporate markets for some fairly big corporate decisions.
Mike Knesevitch of Intrade / Tradesports seems to have lots of experience in traditional financial markets. He said a good deal about the liquidity and accuracy of his exchange’s political markets. The Howard Dean contract went from 33 to 9 within about 5 minutes following Dean’s “implosion” speech. Part of Tradesports’ reluctance to make it’s prices easy to link to is the possibility that they will charge money for those prices much like traditional stock and futures exchanges do. I wish there were a good way for users to persuade new exchanges to commit to keeping information free, but I don’t see a practical way to do that.
HedgeStreet’s Russell Andersson reported that CFTC approval for new contracts was easier than I expected. It takes about 24 hours for contracts dealing with things that the CFTC normally deals with, but weeks to months for other topics. (Why so much variation??)
Microsoft Todd Proebsting is surprisingly enthusiastic about most (all?) of Robin Hanson’s vision of what prediction markets might do. He reported a case where a market did a much better job of predicting when a product would ship than the manager did, although there was some confusion when the market fluctuated when it’s prediction created some uncertainty over whether features would be cut to make the deadline (the contract didn’t adequately specify how it would be judged if the product changed significantly). He reported that there was no resistance to prediction markets from upper management (middle management resisted, since the markets are designed to indicate failings of middle management). He mentioned that laws regulating sweepstakes created some obstacles to implementing internal corporate markets (they’re designed to prevent a sweepstakes game from rewarding the people who control the sweepstakes). He inadvertently(?) promoted the use of open source licenses by mentioning that legal concerns deterred him from looking at Robin’s market scoring Lisp code, which has no license granting any permission to use it.
Eric Zitzewitz responded to Manski’s theoretical criticisms of prediction market accuracy (see his paper on Interpreting Prediction Market Prices as Probabilities), and described some problems with inferring causality from markets and how to structure markets to minimize those problems (see his paper on Five Open Questions About Prediction Markets). He showed an amusing graph indicating that Tradesports prices implied Osama was twice as likely to be captured in October 2004 as in November 2004 (implying some connection with the U.S. elections).
The CFTC has reacted to Tradesports‘ futures-like contracts that many U.S. residents have been trading without CFTC regulation.
It is surprising how closely the contracts that they objected to coincide with contracts traded under CFTC regulation – they apparently have prohibited Tradesports from offering to U.S. residents contracts on the results of the next Fed meeting (which Hedgestreet trades under CFTC regulation; Tradesports stopped offering these in May, possibly due to negotiations with the CFTC) but as far as I can tell Tradesports is still able to offer contracts on where the Fed Funds rate will be at the end of the year.
I am also surprised that the CFTC classified the contracts as futures options rather than futures. They do have something resembling as strike price, but otherwise resemble a futures contract more than they resemble an option.
Two years ago a DARPA project was canceled after some demagogues attacked a straw man which bore a superficial resemblance to the actual project. Now Robin Hanson (who had some involvement with the project) has written a defense of the straw man, i.e. an argument that futures markets might be of some value a predicting specific features of terrorist attacks (although not nearly as valuable as more natural uses of futures markets such as predicting the effects of changes in Homeland Security budgets on the harm done by terrorism).
He has a somewhat plausible argument that there is useful information out there that might be elicited by markets, particularly concerning the terrorist choice of method and targets. An important part of his argument is that in order to be useful, the markets might only need to distinguish one-in-a-thousand risks from one-in-a-million risks. One weakness in this argument is that it makes mildly optimistic assumptions about how reasonably people will respond to the information. There is clear evidence much spending that is advertised as defense against terrorism is spent on pork instead. Markets that provide a few bits of information about which targets need defending will raise the cost of that pork-barrel spending, but I can’t tell whether the effect will be enough to meet whatever threshold is needed to have some effect.
The section on moral hazard seems to contain a rather strange assumption about the default level of trader anonymity. The “reduced” level he talks about seems to be about as much as the U.S. government would allow. It isn’t clear to me whether any anonymity helps make the prices more informative (does anyone know of empirical tests of this?). The optimal level of anonymity might vary from issue to issue according to what kind of trader has the best information.
The proposal to hide some prices is more difficult than it sounds (not to mention that it’s far from clear that the problems it would solve are real). Not only would the exchange need to delay notifying traders of the relevant trades, but it would need to delay notifying them of how the trades affected the traders’ cash/credit available for trading other futures. Which would often deter traders from trying to trade when prices are hidden (it’s also unclear whether the trades that would be deterred would add useful information). In addition, I expect many of the futures that would be traded would be about targets and/or methods covering some broad range of time; it’s unclear how to apply a condition about “attacks to occur within the next week” to those.
The proposals to deal with decision selection bias sound politically difficult to implement (unless maybe Futarchy has been substantially implemented). But there isn’t much risk to experimenting with them, and elected officials probably don’t have the attention span to understand the problem, so there probably isn’t much reason to worry about this.
In the latest issue of Econ Journal Watch, Bryan Caplan and Donald Wittman hold an inconclusive debate on whether democracy produces results that are sensibly related to voters’ interests. They come much closer than most such discussions to using the right criteria for answering that question.
But they fail because they implicitly assume that inaccuracies in voters’ beliefs are random mistakes. If that were the case, Wittman’s replies to Caplan would convince me that Caplan’s evidence of voter irrationality is as weak as the arguments that consumer irrationality prevents markets from working, and that Wittman’s proposed experiments might tell us a good deal about how well democracy works.
On the other hand, if you ask whether voters have incentives to hold beliefs that differ from the truth in nonrandom ways, you will see a fairly strong argument that voters’ inadequate incentive to hold accurate beliefs causes systematic problems with democracy.
Imagine that you live near a steel mill. This means that believing that steel import restrictions are bad will increase the risk that your acquaintances will dislike you (because you views endanger their jobs or their friends’ jobs), and will probably bias you toward supporting protectionism.
Or take the issue of how gun control affects crime rates. There are some obvious patterns of beliefs about this which the random-mistake hypothesis fails to predict. Whereas the theory that people adopt beliefs in order to indicate that they think like their friends and neighbors (combined with some regional variations in gun ownership that created some bias before people started thinking about the issue) does a much better job of predicting the observed patterns of belief.
Because this seems to be a widespread problem with democracy, I’m fairly certain democracy works poorly compared to markets and compared to forms of government such as Futarchy which improve the incentives for policies to be based on accurate beliefs.
For a long time I’ve thought that the weakest part of the argument for Futarchy is the problem of choosing a good measure of national welfare. Democracy is sufficiently subject to manipulation by demagogues (e.g. convincing voters that Saddam had some responsibility for Sept. 11 or that confiscating guns will make us safer) that turning politicized disputes about factual questions over to an institution that maximizes GDP would probably be an improvement even if the flaws in using GDP cause it to do foolish things like preferring Microsoft’s commercial crap to free alternatives. But it would be hard to convince people addicted to having democratic processes decide questions of fact to ignore such flaws.
I want to propose that such a system should be designed to maximize life expectancy instead. That measure seems to correlate fairly well with a number of things we value such as wealth and happiness. I’m not sure how it correlates with equality, and suspect it is imperfect at putting the optimal weight on increasing that, so I’m not claiming it’s a utopian solution. But I doubt there’s much risk that maximizing lifespans would increase inequality.
It would create pressures to keep peoples’ hearts beating when they’re brain-dead, and to put undesirable restrictions on activities such as skiing and rock-climbing. But it’s not obvious why that would be significantly different from the biases of existing governments.
Book Review: Entrepreneurial Economics: Bright Ideas from the Dismal Science, edited by Alexander Tabarrok
This collection of papers has a bunch of very good ideas.
The patent buyouts chapter shows how most patents could be put into the public domain (fixing some problems associated with monopoly) while also increasing the incentives for innovation (at least in areas such as drugs where the patent system works moderately well). Two minor weaknesses in the paper: it ought to explain why this is a better use of money than funding research directly (I expect this could be done by analyzing the incentives and track record of small startup drug companies versus nonprofit/government researchers). The joint randomization for substitutes works well if there’s unlimited money to buy patents, but if a patentholder can make joint patents too expensive to buy by falsely claiming that its patent is a substitute, then it’s hard to analyze whether problems result (although I’m fairly sure they could be dealt with).
The chapter on decision markets (aka idea futures) provides some hints on how many of the problems with democracy could be fixed. Hopefully this will encourage readers to seek out his more thorough argument.
The time-consistent health insurance proposal describes a good free-market alternative solution to many of the problems that government-run insurance proposals claim to address.
The chapter on gene insurance would address additional problems with people born with genes that scare insurers, but only if it were possible to require buying this insurance prior before an infants genes get tested for defects. But it’s unclear how such a requirement can be enforced – it seems possible that a mother will often be able to get a fetus tested secretly before the government realizes it’s time for the child to get insured.
The section on organ shortages provides some interesting arguments that the medical establishment profits from the shortage of organs created by laws against the sale of organs.
The chapter on securities regulation is too longwinded but contains good evidence that competition between securities regulators will help investors.
Book Review: Catastrophe: Risk And Response by Richard A. Posner
This book does a very good job of arguing that humans are doing an inadequate job of minimizing the expected harm associated with improbable but major disasters such as asteroid strikes and sudden climate changes. He provides a rather thorough and unbiased summary of civilization-threatening risks, and a good set of references to the relevant literature.
I am disappointed that he gave little attention to the risks of AI. Probably his reason is that his expertise in law and economics will do little to address what is more of an engineering problem that is unlikely to be solved by better laws.
I suspect he’s overly concerned about biodiversity loss. He tries to justify his concern by noting risks to our food chain that seem to depend on our food supply being less diverse than it is.
His solutions do little to fix the bad incentives which have prevented adequate preparations. The closest he comes to fixing them is his proposal for a center for catastrophic-risk assessment and response, which would presumably have some incentive to convince people of risks in order to justify its existence.
His criticisms of information markets (aka idea futures) ignore the best arguments on this subject. He attacks the straw man of using them to predict particular terrorist attacks, and ignores possibilities such as using them to predict whether invading Iraq would reduce or increase deaths due to terrorism over many years. And his claim that scientists need no monetary incentives naively ignores their bias to dismiss concerns about harm resulting from their research (bias which he notes elsewhere as a cause of recklessness). See Robin Hanson’s Idea Futures web pages for arguments suggesting that this is a major mistake on Posner’s part.
Once again, I feel somewhat humbled for underestimating the accuracy of presidential election markets. At least I was cautious enough to mainly bet against Bush winning states where he appeared to be behind, and against him winning 400 electoral votes, which made up for what I lost betting that Kerry would win the election and popular vote.
Assuming the preliminary results are accurately indicating the final results, Tradesports did quite well at predicting the elections (except for a few hours on Tuesday afternoon when it mistakenly reacted to exit polls). It’s Monday evening prices correctly indicated which presidential candidate would win each state. And it did a good job of indicating which states were closest (saying Iowa and Ohio were the least certain).