Prediction markets predict public events such as election outcomes better than do polls or other forecasting mechanisms. Internal corporate prediction markets in events such as sales forecasts, product launch times, and product feature demand have been less well studied. Internal corporate markets tend to have fewer participants than public markets and the participants often have strategic interests and biases. Thus, it has been an open question how well these markets operate.

Cowgill and Zitzewitz report on a number of different types of prediction markets run by Google, Ford and Firm X and although they find evidence for some biases they also find that corporate prediction markets also work better than alternative forecasting methods.

Despite large differences in market design, operation, participation, and incentives, we find that prediction market prices at our three companies are well calibrated to probabilities and improve upon alternative forecasting methods. Ford employs experts to forecast weekly vehicle sales, and we show that contemporaneous prediction market forecasts outperform the expert forecast, achieving a 25% lower mean-squared error (p = 0.104). …The strong relative predictive performance of the Google and Ford markets is achieved despite several pricing inefficiencies. Google’s markets exhibit an optimism bias. Both Google and Ford’s markets exhibit a bias away from a naive prior (1/N, where N is the number of bins, for Google and prior sales for Ford). However, we find that these inefficiencies disappear by the end of the sample. Improvement over time is driven by two mechanisms: first, more experienced traders trade against the identified inefficiencies and earn higher returns, suggesting that traders become better calibrated with experience. Secondly, traders (of a given experience level) with higher past returns earn higher future returns, trade against identified inefficiencies, and trade more in the future. These results together suggest that traders differ in their skill levels, they learn about their ability over time, and self-selection causes the average skill level in the market to rise over time.

Addendum: It’s an interesting commentary on academic publishing that Marginal Revolution first covered this paper in a working version in 2008! An extended version was received by the Review of Economic Studies in 2010 which accepted a final version in 2014 and then published the paper in 2015.