Here’s an article by Bob Erikson and Chris Wlezien on why the political markets have been inferior to the polls as election predictors. Erikson and Wlezien write,
Election markets have been praised for their ability to forecast election outcomes, and to forecast better than trial-heat polls. This paper challenges that optimistic assessment of election markets, based on an analysis of Iowa Electronic Market (IEM) data from presidential elections between 1988 and 2004. We argue that it is inappropriate to naively compare market forecasts of an election outcome with exact poll results on the day prices are recorded, that is, market prices reflect forecasts of what will happen on Election Day whereas trial-heat polls register preferences on the day of the poll. We then show that when poll leads are properly discounted, poll-based forecasts outperform vote-share market prices. Moreover, we show that win-projections based on the polls dominate prices from winner-take-all markets. Traders in these markets generally see more uncertainty ahead in the campaign than the polling numbers warrant—in effect, they overestimate the role of election campaigns. Reasons for the performance of the IEM election markets are considered in concluding sections.
I was motivated to post this after reading Justin Wolfers’s Wall Street Journal article, “Best Bet for Next President: Prediction Markets,” where he writes, “Experimental prediction markets were established at the University of Iowa in 1988, and they have since amassed a very impressive record, repeatedly outperforming the polls.”
As I wrote a couple of years ago,
Prediction markets do a good job at making use of the information and analyses that are already out there–for elections, this includes polls and also the information such as economic indicators and past election results, which are used in good forecasting models. The market doesn’t produce the forecast so much as it motivates investors to find the good forecasts that are already out there.
As an aside, people sometimes talk about a forecasting model, or a prediction market, “outperforming the polls.” This is misleading, because a poll is a snapshot, not a forecast. It makes sense to use polls, even early polls, as an ingredient in a forecast (weighted appropriately, as estimated using linear regression, for example) but not to just use them raw.
But . . .
That said, I like Justin’s work a lot, including his paper with Zitzewitz on prediction markets. (And I’m a big fan of the idea of betting–we have an example of football point spreads in chapter 1 of Bayesian Data Analysis.) I think Justin’s Wall Street Journal article is just fine–I understand that it’s necessary to simplify a bit to reach a general audience amid space limitations. I’m just wary of overselling them or of misunderstanding of what is learned from polls.