Reply to Moldbug

By Robin Hanson · May 22, 2009 6:00 am · Comments (74) · ·

A Mencius Moldbug has written a confused and rambling 7400 word critique of futarchy. But since Mencius seems to have passion and potential, let me try to communicate.  Most readers may prefer to skip this post; it will get tedious.

Prediction markets are a fine idea, whereas decision markets are… well… retarded. … Almost every conceivable application of a decision market … does not produce accurate predictions.

So if PM good, DM bad, your complaints should focus on features that distinguish decision and prediction markets, right?

For a market to produce accurate predictions, there must be genuine experts in the market, and they must be substantially better-funded than the morons.

OK, except that morons may largely cancel each other, in which case you don't need as many non-morons.  But this issue applies equally to prediction and decision markets, doesn't it?

If no one has ever seen the Emperor of China's nose, can a prediction market predict its length? … The worst case is that in which nobody has any way of actually calculating the prediction, but no one in the market is sure that this is the case. Your market signal will look exactly like that of an accurate prediction market, but predict nothing at all.

You can ask for a full probability distribution.  If speculators know they don't know anything, then they will give you a broad distribution that expresses a lot of uncertainty.  This is them telling you they don't know much.  In your nose example, they may just give you the distribution over nose sizes for elite Chinese.  And how is this issue different for prediction vs. decision markets?

In an old and healthy prediction market we would indeed expect to see accurate predictions. But only in the case in which Darwinian forces have been operating for a substantial period of time.

Trader experience does seem to improve their collective accuracy.  But this hardly means accuracy was zero initially.  By now we have a great deal of experience in field and lab prediction markets where accuracy was valuable from day one.  And how does this issue distinguish prediction vs. decision markets?

 The adaptive explanation of market efficiency tells us why prediction markets with pretend money are a complete waste of time. These just aggregate the whims of the participants.

Play money markets do often fail badly, but many of them have done very well.  All else equal I prefer real money markets, but "complete waste of time" is way too strong.  And how does this distinguish prediction vs. decision markets?

A prediction market only makes valid predictions if it can resist feedback, where feedback is any effect of the market's result on the interests of the players. … With feedback, players with a financial interest in the effect of the prediction have an interest which conflicts with the efficiency of the market.

There are several possible concerns you might have here.  First, traders might sabotage events in the real world to improve their forecast accuracy.  This can be a problem for any forecasting mechanism that rewards accurate contributions, and there are several ways to deal with it.  Also, traders might try to distort the market price because that price influences decisions.  Theory, lab data, and field data suggest this is not much of a problem.  And how do these issues distinguish prediction vs. decision markets?

A prediction market, like any other market, functions only in the general absence of asymmetrical information. It is with some pain that I absorb the realization that a member of the George Mason School is unable to correctly apply this concept. … The rational approach to a market in which other players have more information than you is not to play. … This is one of the many reasons why insider trading is illegal.

Er, in pretty much every speculative market that has ever existed, traders have had differing relevant info.  Identical info is a very rare situation.  Some traders had more total info, and the traders who had less would have been well advised to leave.  And how does this distinguish prediction vs. decision markets?

Futarchy is… retarded, … because … It must be trained. During the training period, it is an inaccurate prediction market. … But who wants to run an inaccurate futarchy for a training period? … Testing the accuracy of a prediction market … is close to impossible.

After the fact it is quite easy to test for forecast accuracy.  And even if initial accuracy was poor, why not begin if we expect accuracy to greatly improve?  And how does this distinguish prediction vs. decision markets?

In order to make an accurate bet that some policy or other will increase GDP, as opposed to no policy at all, you first need an accurate estimate of GDP assuming no policy change at all. Whose error bars are shorter than the impact you expect from the policy change.  In other words, Professor Hanson is basically expecting the AM antenna on his ghetto blaster to pick up signals from Alpha Centauri.

We can sensibly compare small differences in conditional expectations even when conditional variances are high.  For example, even when you cannot predict the date of your death well, you can reasonable expect a longer lifespan if you exercise today than if you do not exercise today.  The difference in these two expectations can be tiny compared to the variance in your realized lifespan, and yet you can have reasonable beliefs about this difference, and act on them.  See also the presidential nomination decision markets which have been run for many years by IEM and Intrade as proof that decision markets are mechanically feasible, even in situations of great uncertainty.

Professors, Hanson and Abramowicz. Their primary angle seems to be in recommending decision markets to USG.

There is now a prediction market industry, where I do a lot of consulting, most of which is to private companies.  Most of this consulting is on prediction markets, but some are decision markets. 

Consider Professor Hanson's favorite statistic – GDP. If we translate GDP into Apple terms, it is gross revenue. GDP is simply the total sales of all American companies. So suppose our man, at Apple, had access to a perfect Hansonian decision market, which for any policy could calculate whether or not that policy would increase Apple's sales. … Many bad decisions increase gross revenue. What about costs? What about quality? What about customer service and brand reputation? What about employee morale? Etc, etc, etc.

For firms I recommend forecasting profits or stock price, not revenue.  For nations I suggest a full national welfare; GDP is only a first step to such a measure.

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