Prediction Market Based Electoral Map Forecast

Slashdot points to ElectoralMap.net, a site which aggregates the Intrade prediction market results for individual states in the fall U.S. Presidential election, to predict aggregate electoral college totals and the election winner. I’m bookmarking it as an alternative to media coverage of the race, which will put their own spin on likely outcomes. Note the arrows at the bottom of the map will allow you to track the changes in sentiment over the weeks and months leading up to the election.

A somewhat more elaborate alternative is Electoral Vote Predictor, which uses polls rather than prediction markets. However, they are almost always the same, to tell the truth. I followed this site closely in the 2004 election. Site operator Andrew Tanenbaum includes a frank discussion of the accuracy of the 2004 predictions.

Robin Hanson argued earlier that closely following the news is not that great an idea, and I have to agree. It is something of a bad habit, but I find myself doing it anyway. We have this instinct that choosing our Leader is as important to our lives as it was when we were a tribe of two dozen, and that we have similar influence over the result. Following elections and participating in politics activates these vestigial tribal instincts in much the same was as sports, with similarly futile results. It can be seen as another form of “information porn“, exciting and titillating but ultimately unproductive.

I wish they used a different algorithm in the ElectoralMap site. It appears that the methodology is to take the individual state Intrade predictions, and assign all the electoral votes for a state to the party that has a 55% or greater predicted probability of carrying the state. States with less than a 55% probability for either party are shown as undecided. What I would like to see instead is to multiply the number of electoral votes for a state times the probability that the party will carry that state, and sum those results per party. This way, states that are seen as solidly preferring one party will be given greater weight towards that party than those which are more uncertain.

Then to make it even more useful, run a Monte Carlo simulation where each state is randomly assigned to one party or the other, with the odds taken from the prediction market, to create a simulated election result. Repeat this many times to calculate the mean and standard deviation for possible outcomes. In this way, confidence intervals can be given for the predictions. It’s possible that we might see the predicted electoral votes stay roughly the same for some time, but the confidence interval might narrow or widen. I don’t know if there is some statistical trick to compute the C.I. without actually running simulated elections, just from the distribution of probability estimates, but if so, that would be even better. My suspicion is that realistic confidence intervals are going to show that the election will be too close to call and could easily go either way – at least, that would have been the case in the last few elections.

Why not do this programming myself? Well, I might have the ability to do that. Intrade has an API, but it’s not clear if it allows retrieving the necessary data. I wouldn’t know how to display it on a colorful map, but the math should be simple enough, if you can retrieve the market prices, so producing a textual result would be straightforward. Maybe I will try to work on it in my spare time.

We don’t often post these kinds of pointer articles here, although they dominate many blogs. In that earlier posting about the news, Robin wrote, “I avoid posts that should not be nearly as interesting a year before or after.” This one does not really qualify, although there may be some historical value to be able to go back and look at how market sentiment evolved over time.