Posted by: Paul Hewitt | November 25, 2009

Use and Abuse of Public Policy Prediction Markets

Robin Hanson and others have suggested that prediction markets be used to help shape the direction of public policy.  The current hot issue is how to combat global warming and its effects on the environment. 

Matt Yglesias has argued that big money can manipulate markets.  So, we should not use prediction markets for this purpose.  On paper, prediction markets provide monetary or ego-related rewards for truthfully revealing private information by trading.  In this sense, prediction markets are said to “incentivize accuracy”.  When the incentives for manipulating the market price are greater than the incentives for not doing so, it is obvious how traders will act.  Matt argues that prediction markets that are prone to manipulation, such as climate change futures, will make inaccurate predictions, and any policy that is based on these will be inappropriate.  I agree.

Robin Hanson, on the other hand, believes that big money manipulators can only improve the accuracy of prediction markets.  He goes so far as to say that prediction markets are “especially incorruptible”.  I need to read all of his papers on this subject in their entirety, however, based on his own summary of the findings, I will make a few comments, now.  [I promise I will read them, fully, and update this post if necessary]

Robin (and others) argue that prediction market accuracy improves “as more big money powers are known to want to manipulate them.”  Manipulators are in essence noise traders.  Markets with more noise traders are more accurate, because informed traders are attracted to the possibility of profiting by trading with the noise traders. 

He qualifies his conclusion by stating that “this isn’t an absolute guarantee.”  Then, he suggests that we try it before we condemn it.  However, before we do so, I suggest we look at the theory more closely.  We may find that it works as well as the neoclassical economic framework in economics.  It works fine in a hypothetical, assumption-simplified world, but fails miserably in practice. 

Let’s look at some of the simplifying assumptions in Robin Hanson’s application of prediction market theory.  One, the informed traders are more powerful than the manipulators, or noise traders.  In Hanson’s experiments, the manipulators are able to affect the market price, but the informed traders quickly bring prices back to an accurate level. 

What if informed traders aren’t wealthier (than the manipulators)?

In a typical prediction market, greater trader wealth is accumulated by being better informed than other traders and making trades that payoff more frequently.  By virtue of their greater wealth, informed traders have more power to influence the market than uninformed traders.  This is a necessary condition to mitigate against manipulative behaviour.

In a public, real money market, trader wealth may have nothing at all to do with knowledge about that, or any other, outcome.  Manipulative traders can simply bring wealth to the market.  Furthermore, if such wealth is known to other traders, it may send a false signal to all traders about the manipulator’s “expert” status.  That is, rather than being viewed as a manipulator, the trader may be seen as an expert.  This is especially likely in markets where it is difficult (or impossible) for any individual to have enough knowledge to make an “informed” trade.  Even if you place restrictions on wealth that may be traded, so as to prevent a small group of traders from manipulating the market, if the stakes are high enough, the big money manipulator will simply finance a large number of other traders to carry out the manipulation.  I think many big money players would find the incentives large enough in the global warming debate.

What if most (or all) of the traders are uninformed? 

I would argue that as long as the collective information set is sufficiently complete, the market could obtain a reasonably accurate prediction.  If this is not the case, we will likely see a very flat distribution of predictions, reflecting the high degree of uncertainty.  Such a result would be practically useless for policy decision-making, other than to indicate that we need much more information about the subject.  Unfortunately, for an extremely complex issue, like climate change, it is highly unlikely that the market participants will have a “complete” set of information.  It is doubtful whether any of the participants would be able to properly weigh and assess all of the information, in order to make a truly accurate prediction of any climate change metric.  There are simply no, known frameworks for making such assessments, which leads us to…

Another possibility is that if traders have very little personal information about the subject, they will instinctively look to the others (the market) for guidance.  The prediction market principle of independence begins to break down.  If the market price has been manipulated, there is a good chance that the non-manipulative traders (notice I didn’t say “informed”) may “read” information in the price that isn’t true and place their trades accordingly. 

Public vs. Enterprise Prediction Market Manipulation

One of the reasons I haven’t looked into the issue of market manipulation is that it isn’t much of a problem in enterprise prediction markets.  Generally, we expect EPMs to have a sufficient number of informed traders, who tend to be “wealthier” than manipulators.  There are some noise traders, but not too many.  I agree with Robin Hanson’s assessment that manipulation will be overcome in enterprise markets.  Consequently, I’ve had little interest in looking at this issue.

However, prediction markets on public policy issues are different.  Apart from the market participants, there are many groups that have vested interests in the implications that might flow from a public policy prediction market outcome, and they will seek to influence the market prediction, by trading or by other means.  For example, big business may try to influence the information available to all traders to achieve the desired prediction.  This may take the form of advertising, public announcements, privately funded research, and all forms of lobbying activity.  Governments issue their own propaganda.  This information may be corroborated with price changes in the prediction market, lending credibility to inaccurate information.  Unless these prediction markets can be insulated from the manipulative influence of non-trading interest groups, they will not be able to prevent or eliminate manipulation of the market predictions.

How Manipulation is Nullified (or not)

Robin Hanson states that the informed traders must know that the noise traders want to manipulate the market.  In order to profit from this knowledge, they also need to know which way they wish to manipulate the market price. 

In a global warming market, big business, carbon emitters would likely exert downward pressure on any metric that shows adverse effects from their activities, so that legislators would be less likely to impose costly laws to prevent such activities or to compensate others for the effects.  On the other hand, “tree-hugging” organizations may wish to increase the market price, so that such legislation is more likely to be enacted.  In both cases, the truly informed trader must know who the trader is and the trader’s motive for trading.  Since there is no way to prevent a trader from diguising his identity, it is impossible to properly match the motive with the trader.  It also begs the following question.

How might the informed trader distinguish between a manipulative trader and a misinformed honest trader?  I don’t have that answer, but unless it can be answered,  it may be impossible to ensure that attempts at manipulation will lead to more accurate predictions, at least in complex, public policy prediction markets. 

Conclusion

In theory, it is a nice idea to try and accurately aggregate as much information as possible in order to determine the best course of action in public policy decisions.  Most public policy decisions are remarkably complex with numerous tradeoffs among competing interests.  All decision-making benefits from more information that is more accurate and more timely.  Unfortunately, simply inserting a prediction market framework into the decision-making process does not eliminate the political biases that have been, and will always be, there. 

While it may be possible to operate public policy prediction markets for some issues, their use in the climate change or global warming debate is questionable.  Not only can there be no guarantee of manipulation-free markets, we wouldn’t even know if market predictions had been manipulated.  If actual public policy were to depend on false readings from such markets, the potential for significant misallocation of resources is immense.  It is simply too great a risk to consider at this time, in my opinion.

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Responses

  1. Maybe you should actually read the literature instead of posting a whole bunch of vague concerns that just popped into your head. Here are some corrections to the above – for more, read the lit.

    To an expert user, the tool of neoclassical economics can be an enormously useful tool in practice. One doesn’t need much info to profit by correcting manipulators – you need only a good guess that manipulation is likely. No you don’t need to know the direction of manipulation, nor do you need to know which traders are manipulators. In an open market, the money available to investors meeting this description far outweighs that available to manipulators. Of course if no one can know anything, the market will at best just tell you that – what more could you expect. There is no “prediction market principle of independence” – it is fine if trader info is correlated. Yes of course propaganda might mislead some – but that will apply also to any institution one might use instead of prediction markets.

  2. […] Paul Hewitt: […]

  3. I promise you, I will read the literature. Until then, here is my response.

    Yes, neoclassical economics is enormously useful, but not so much in a practical sense. It is best used to explain basic concepts about how an economy allocates resources. When the simplifying assumptions are relaxed, the neoclassical framework is not very good at explaining real-life phenomena.

    As for being able to correct the manipulators, of course the “informed” traders must know which way the market price has been manipulated! They will know this, only if they are truly “informed”, but part of my argument is that there just aren’t enough (if any) “informed” traders in such a market. Consequently, they will have no idea whether the market price has been manipulated or not. Do you really believe there would be enough truly informed traders in a climate change market?

    Your position requires that there will be enough traders to recognize the manipulation and take advantage of it. You need to prove this, rather than blindly arguing that the money in an open market will far outweight that available to the manipulators. Just because the money is available doesn’t mean that it will be used. If the investors are ignorant, one, they won’t know the market has been manipulated, and two, they won’t risk trying to change the price.

    You say all traders need is a “good guess” that the market is being manipulated? This assumes that they have a good idea about what the market price should be. i.e. they must be “informed”.

    You mentioned that “if no one can know anything” the market will tell us this. I assume you mean that the market will tell us by revealing a very flat distribution. If so, I agree, and there’s no harm in trying (other than the cost of the market).

    I thought I implied that propaganda or political influence would be present in the existing institutional environment and that it was not something new to prediction markets.

    I’m not sure I would call my concerns “vague”. Subjective, perhaps, but not vague. My concerns are about the conceptual aspects of operating a public policy prediction market. There is no objective, established foundation for using such markets. Accordingly, it should be fair game to question the subjective concepts that are being considered. I might add that your summary of the manipulation issue is vague, too, using terms like “should”, “possibility”, “isn’t an absolute guarantee”, etc…

    I will be reading your papers and I will adjust my position as necessary.

    Thank you for your comments.

  4. I’m confused — why does an informed trader need to know that a trader betting the wrong way is dishonest and manipulative, rather than honest but arrogantly stupid? The right thing to do is to place a bet on the right side either way, and take the other side’s money.

    As far as I can see, telling an informed trader “In Prediction Market Q there are a bunch of suckers who have lots of dollars and no sense” will have similar results to telling them “In Prediction Market Q there are a bunch of stinkers who have lots of money and are trying to manipulate the results.”

    Of course, if we can tell that certain betters are trying to manipulate the market, then even someone who is uninformed about everything else will know to bet against them, but even without that, informed traders will see that there are lots of sucker bets available and will take advantage of them, without knowing or caring why the betters on the other side are lining up to lose their money . . .

  5. I stand corrected about whether an *informed* trader needs to distinguish the manipulator from the arrogantly stupid one. If the trader truly is informed, it should make no difference.

    My discussion about identifying manipulation was based on a pretty realistic assumption (at least I think so) that most traders in this type of market are *not* “informed”. Consequently, they would need to know something about the manipulator and his motive in order to determine which way the market was being manipulated. As such, I don’t agree with your comment that uninformed bettors would be able to bet against the manipulators. How would they know?

  6. […] – Robin Hanson to Paul Hewitt – #1 […]

  7. […] OR… maybe manipulators can game these markets.  I think they can, as explained here, here, here and here.  These references apply to several points that follow regarding […]


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