Editor’s Note: This working paper was prepared for an upcoming book, The Handbook of Economic Forecasting, Volume 2.
Prediction markets—markets used to forecast future events—have been used to accurately forecast the outcome of political contests, sporting events, and, occasionally, economic outcomes. This chapter summarizes the latest research on prediction markets in order to further their utilization by economic forecasters. We show that prediction markets have a number of attractive features: they quickly incorporate new information, are largely efficient, and impervious to manipulation. Moreover, markets generally exhibit lower statistical errors than professional forecasters and polls. Finally, we show how markets can be used to both uncover the economic model behind forecasts, as well as test existing economic models.
Market prices, in the form of gambling odds, have been used to forecast events since at least the beginning of the sixteenth century. The use of such prices had a heyday in the early twentieth century, when gambling odds on elections were printed daily in newspapers such as The New York Times. This was followed by a decline in popularity, due largely to the advent of scienti c polling (Rhode and Strumpf, 2004, 2008). Scientific interest in market prices as tools for forecasting was kindled in the second half of the twentieth century by the efficient markets hypothesis and experimental economics (Plott and Sunder, 1982, 1988; Berg et al., 2008). This scientific foundation, coupled with advances in telecommunications—which allowed prices to be shared in real time across companies and the globe—has lead to resurgent interest in using markets for forecasting (Snowberg, Wolfers and Zitzewitz, 2007b).
Despite this long history, and markets’ proven track-record of providing accurate forecasts of uncertain events, prediction markets—markets used to forecast future events—are largely unused in economic forecasting. There are some exceptions: the difference in yields between inflation protected and standard government bonds is used to forecast inflation, and futures contracts are sometimes used to forecast commodity prices, such as the price of oil. However, as other chapters in this volume reveal, these uses are accompanied by concerns about what else, other than information about future events, may be lurking in market prices (Alquist and Vigfusson, 2012; Duffee, 2012; Wright and Faust, 2012; Zhou and Rapach, 2012).
This chapter brings together the latest research on prediction markets to further their utilization by economic forecasters. We begin by providing a description of standard types of prediction markets, and an heuristic framework useful in understanding why prediction markets do, and sometimes do not, make useful predictions. We then show that, in practice, prediction markets often have a number of attractive features: they quickly incorporate new information, are largely efficient, and impervious to manipulation. Moreover, markets generally outperform professional forecasters and polls. Finally, we argue that examining co-movement in market prices, through, for example, event studies, can be used to shed light on the underlying economic model of market participants. We conclude with a short list of open questions that may be of particular interest to economic forecasters.
There's a far greater concentration of wealth than there is a concentration of income. And that actually has quite a separate effect and impact on the economy.