Can LLM Improve for Expert Forecast Combination? Evidence from the European Central Bank Survey

Abstract: This study explores the potential of LLMs to enhance expert forecasting through ensemble learning. Leveraging the European Central Bank's Survey of Professional Forecasters (SPF) dataset, we propose a comprehensive framework to evaluate LLM-driven ensemble predictions under varying conditions, including the intensity of expert disagreement, dynamics of herd behavior, and limitations in attention allocation.