Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
The U.S. Survey of Professional Forecasters produces precise and timely point forecasts for key macro‐economic variables. However, the accompanying density forecasts are mostly conducted for “fixed events.” For example, in each quarter, panelists predict output growth and inflation for the current calendar year and the next, hence the forecast horizon changes with each survey round. This limits the forecasts' usefulness to policymakers, researchers, and market participants. We propose a density combination approach that weights fixed‐event density forecasts, aiming at obtaining a correctly calibrated fixed‐horizon density forecast. We show that our method produces competitive density forecasts relative to widely used alternatives.