The Wisdom of Competitive Crowds

Abstract:     
When several individuals are asked to forecast an uncertain quantity, they often face implicit or explicit incentives to be the most accurate. Despite the desire to elicit honest forecasts, such competition induces forecasters to report strategically and non-truthfully. The question we address is whether the competitive crowd's forecast (the average of strategic forecasts) is more accurate than the truthful crowd's forecast (the average of truthful forecasts from the same forecasters). We analyze a forecasting competition in which a prize is awarded to the forecaster whose point forecast is closest to the actual outcome. Before reporting a forecast, we assume each forecaster receives two signals: one common and one private. These signals represent the forecasters' past shared and personal experiences relevant for forecasting the uncertain quantity of interest. In a set of equilibrium results, we characterize the nature of the strategic forecasts in this game. As the correlation among the forecasters' private signals increases, the forecasters switch from using a pure to a mixed strategy. In both cases, forecasters exaggerate their private information and thereby make the competitive crowd's forecast more accurate than the truthful crowd's forecast. These findings suggest that forecasting competitions may be attractive alternatives to prediction markets because they are easy to implement and may be more accurate.

Number of Pages in PDF File: 39

Keywords: forecasting competitions, strategic forecasting, expert opinion, averaging opinions, combining forecasts.

JEL Classification: D41, D82

working papers series