Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Based on the approach developed by Elliott <italic>et al</italic>. (2005), we found that the loss function of a sample of oil price forecasters is asymmetric in the forecast error. Our findings indicate that the loss oil price forecasters incurred when their forecasts exceeded the price of oil tended to be larger than the loss they incurred when their forecast fell short of the price of oil. Accounting for the asymmetry of the loss function does not necessarily make forecasts look rational.