Overconfidence in Private Information Explains Biases in Professional Forecasts

We observe a rich set of public information signals available to participants in the Survey of Professional Forecasters (SPF) and decompose individual forecast revisions into those due to public information and a remainder due to residual information. We find that SPF forecasters overreact to residual information at almost all forecast horizons and for almost all forecast variables. In addition, forecasts are overly anchored to prior beliefs for all variables at all forecast horizons. We show analytically that overconfidence in private information qualitatively generates both of these features. It also implies that forecast errors correlate positively with past forecast revisions at the consensus level, but negatively at the individual level, as documented previously in the literature. Estimating Bayesian updating models on SPF data, we show that overconfidence in private information also replicates the observed patterns quantitatively. All estimated models display strong and statistically significant overconfidence in private information.