At about 9 AM CST on the morning of election day I made a snap shot of the map for a Discovery Channel Website article.
Every state colored blue was won by a democrat and every state colored red went to a republican. But also note the 69% given to GOP (Republican) Senate control although this election will give control to the democrats. No outcome would have made all the states and senate control agree with the 9 AM map.
Were the markets inconsistent? No, because the markets predict not absolutely but probabilistically. For example, the markets gave a probability of winning 60% for each of Virginia and Missouri and the democrats needed both to take the senate. If these races were independent events, the probability that the democrats take both is 36% or a 64% chance of GOP senate control assuming no other surprises.
Of course the races were not independent events and there are other states involved making it more difficult to compare the probabilities of the individual races with that of senate control.
So how did the markets do as predictors? Quite well as the outcome seems quite reasonable given the markets. Other outcomes would have also been reasonable such as the Democrats losing Virginia and the senate remaining in republican hands, a possibility that came very close to happening.
We plan a map with a better design and more features for the 2008 Electoral College and Senate races. Stay tuned.
But what about 24 hours before your snapshot? Or 48 hours? In other words, at what point did the map settle on the actual outcome in terms of blue v. red?ReplyDelete
A prediction is more powerful the larger the gap in time, it would seem. And if the map is essentially showing the same thing that the polls at the same time showed, then it would seem much less useful.
So I'd really like to see this kind of analysis.
So how did the markets do for the governors?ReplyDelete
I understand that combinatorial markets have been proposed as a way out of this - however the complexity of that (taken over 50 states) would be mind-boggling at best.ReplyDelete
Would it not be best to identify (Bayesian?) parameters that help predict the races? Something like a basis set of outcomes - and the predictions on the individual races could be made out of combinations of those basis functions?