Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We compare a Global VAR model of actual and expected outputs with alternative models for assessing the roles of cross-country interdependencies and confidence in forecasting. Forecast performances are judged on point and density forecasts of growth, on probability forecasts of the occurrence of national and global recessionary events, and, through a novel ‘fair bet’ exercise, on decision-making using probability forecasts. We find that multi-country and survey data are required in order to capture the influence of global interactions and expectations in forecasts fully. We argue that output predictions should avoid simple point forecasts and focus on densities and events that are relevant to decision-makers.