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.
prediction markets
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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.
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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).
Voters in Oregon and the Dakotas should remember what their Senators said about the DARPA project to create a futures market designed to provide information about terrorism. Ask yourself whether our presidential election would be decided more intelligently if we had a futures contract that predicted how many people would die in terrorist attacks over the next four year if Bush stays, and a similar one for a Kerry presidency. Many press reports that describe the reactions of Ron Wyden (Oregon), Byron Dorgan (North Dakota), and Tom Daschle (South Dakota) to the DARPA project are available here.
Alex Tabarrok writes about the apparent attempts to manipulate the Bush re-elected contract at Tradesports.com (which just dropped to exactly 50!), and CNBC has mentioned the same report today (with a denial from George Soros that he is responsible).
I want to warn people not to treat the failure of this manipulation as strong evidence that manipulation won’t have much effect on the reliability of the prices. If an experienced trader such as Soros tried to engage in this kind of manipulation, he would use a much more patient and cost-effective strategy than quickly driving the price down from 55 to 10.
To estimate the harm done by manipulation, we need to look at careful studies of how accurate markets have been, plus experiments such as the one Robin Hanson arranged. Note also that Robin’s attempt at a theoretical argument on this subject is unconvincing because it unrealistically assumes that traders aren’t risk-averse.
I attended a fairly interesting talk at PARC last week by Bernardo Huberman. He claimed to have created something that sounds like a hybrid between a survey and an idea futures market.
It involves selecting a small group of people (the minimum for it to work well is about 9 people). It includes some market-like trading between participants, but the results are apparently better than what markets would produce under similar conditions, because it does additional calculations such as adjusting for measured risk aversion of each participant, and has something that treats private information (i.e knowledge available to only one participant) differently from public information. At least some of the time Huberman gives participants monetary incentives to get the right answer.
This approach has an advantage over idea futures markets that bad guys are less likely to be able to manipulate it by spending money to produce inefficient prices, because the organization running the system exercises more control over who participates and how much influence each one has. Not that I think idea futures markets suffer any significant problems due to forms of manipulation like this that require the manipulator to transfer unbounded amounts of money to those who are trying to make the market prices accurate, but the difficulty of analyzing the problem has made such markets susceptible to criticism by demagogues. Also, markets tend to foster some secrecy (as traders want to maintain their advantage), while a more survey-like approach makes people less likely to have a stake in having better information than others, since they’re less likely to be involved in future surveys.
Huberman’s approach does have some disadvantages. It presumably requires the person who wants the accurate information to pay for it (with some associated public goods problems in many cases), whereas idea futures markets can often be financed by small commissions on trades. Also, Huberman’s approach probably fails to select the most informed participants in a number of circumstances, thereby failing to extract information that an open market would be able to extract.
A paper covering the most interesting parts of Huberman’s work is available here.
You might also want to see a related criticism of idea futures markets by Manski at http://www.faculty.econ.northwestern.edu/faculty/manski/prediction_markets.pdf, although that paper doesn’t do a very good job of analyzing whether any alternative is better.