arXiv AI By Xinyue Zhao, Ruiyi Zhang, Liqin Ye, Rui Cao, Pengtao Xie, Sudheer Chava

Can LLMs Take the Pulse of the Economy? A Real-Time Evaluation of LLM Nowcasts on Macroeconomic Indicators

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The paper introduces LiveMacroEval, a live benchmark that tests large language model (LLM) agents’ ability to produce hourly nowcasts for sixteen major U.S. macroeconomic indicators before their official release. It evaluates LLM performance against institutional nowcasts, Bloomberg ECOS consensus, and an auto-ARIMA baseline using a LiveMacro Score linked to announcement-window equity returns and a LiveBetting Score from simulated Polymarket-style trading. Over six months, state-of-the-art LLMs with web search achieved overall accuracy comparable to professional benchmarks, though performance varied across indicators.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv Machine Learning
Aug 18

Macroeconomic Forecasting with Large Language Models

arXiv:2407. 00890v5 Announce Type: replace-cross Abstract: This paper presents a comparative analysis evaluating the accuracy of Large Language Models (LLMs) against traditional macro time series forecasting approaches.

By Andrea Carriero, Davide Pettenuzzo, Shubhranshu Shekhar