When does information on forecast variance improve the performance of a combined forecast?

We show that the consensus forecast can be biased if some forecasters minimize an asymmetric loss function and the DGP features conditional heteroscedasticity. The time-varying bias depends on the variance of the process. As a consequence, the information from the ex-ante variation of forecasts can be used to improve the predictive accuracy of the combined forecast. Forecast survey data from the Euro area and the U.S. confirm the implications of the theoretical model.