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

Yinuo Ren; Jue Wang

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arXiv · 2506.23154

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

Yinuo Ren·Jue Wang

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Abstract

This study explores the potential of large language models (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.

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Yinuo Ren, Jue Wang. 2025-06-29. Can LLM Improve for Expert Forecast Combination? Evidence from the European Central Bank Survey. https://arxiv.org/abs/2506.23154

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