Report NEP-BIG-2025-09-08

This is the archive for NEP-BIG, a report on new working papers in the area of Big Data. Tom Coupé issued this report. It is usually issued weekly.

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Other reports in NEP-BIG

The following items were announced in this report:

• Annie Liang, 2025. "Using Machine Learning to Generate, Clarify, and Improve Economic Models," Papers 2508.19136, arXiv.org.
• Nicholas Gray & Finn Lattimore & Kate McLoughlin & Callan Windsor, 2025. "An AI-powered Tool for Central Bank Business Liaisons: Quantitative Indicators and On-demand Insights from Firms," RBA Research Discussion Papers rdp2025-06, Reserve Bank of Australia.
• Haojie Liu & Zihan Lin & Randall R. Rojas, 2025. "Enhancing Trading Performance Through Sentiment Analysis with Large Language Models: Evidence from the S&P 500," Papers 2507.09739, arXiv.org.
• Nikolaos Askitas, 2025. "The Behavioral Signature of GenAI in Scientific Communication," CESifo Working Paper Series 12069, CESifo.
• Hui Chen & Antoine Didisheim & Luciano Somoza & Hanqing Tian, 2025. "A Financial Brain Scan of the LLM," Papers 2508.21285, arXiv.org.
• Zehra Usta & Martin Andersson & Katarzyna Kopczewska & Maria Kubara, 2025. "Identifying Catalyst Technologies in Clusters with Unsupervised Machine Learning. An application on patent clusters in the UK," Papers in Evolutionary Economic Geography (PEEG) 2528, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Aug 2025.
• Mohammed-Khalil Ghali & Cecil Pang & Oscar Molina & Carlos Gershenson-Garcia & Daehan Won, 2025. "Forecasting Commodity Price Shocks Using Temporal and Semantic Fusion of Prices Signals and Agentic Generative AI Extracted Economic News," Papers 2508.06497, arXiv.org.
• Jonathan Benchimol & Sophia Kazinnik & Yossi Saadon, 2025. "Federal Reserve Communication and the COVID-19 Pandemic," Working Papers 2025.10, International Network for Economic Research - INFER.
• Tianyi Li & Yu Qin & Olivia R. Liu Sheng, 2025. "A Multi-Task Evaluation of LLMs' Processing of Academic Text Input," Papers 2508.11779, arXiv.org.
• Shanyan Lai, 2025. "Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models," Papers 2508.19006, arXiv.org.
• Maxim Chupilkin, 2025. "Left Leaning Models: AI Assumptions on Economic Policy," Papers 2507.15771, arXiv.org.
• Manel Labidi & Ying Zhang & Matthieu Petit Guillaume & Aurélien Krauth, 2025. "Stock Market Performance Prediction: A Comparative Study Between Econometric Models and Artificial Intelligence-Based Models [Prédiction de la performance boursière, une étude comparative entre mod," Post-Print hal-05168124, HAL.
• Bonacina, Monica & Demir, Mert & Sileo, Antonio & Zanoni, Angela, 2025. "What Hinders Electric Vehicle Diffusion? Insights from a Neural Network Approach," FEEM Working Papers 369002, Fondazione Eni Enrico Mattei (FEEM).
• Zhuohang Zhu & Haodong Chen & Qiang Qu & Vera Chung, 2025. "FinCast: A Foundation Model for Financial Time-Series Forecasting," Papers 2508.19609, arXiv.org.
• Sudheer Chava & Wendi Du & Indrajit Mitra & Agam Shah & Linghang Zeng, 2025. "Firm-Level Input Price Changes and Their Effects: A Deep Learning Approach," FRB Atlanta Working Paper 2025-7, Federal Reserve Bank of Atlanta.
• Bingyang Wang & Grant Johnson & Maria Hybinette & Tucker Balch, 2025. "Is All the Information in the Price? LLM Embeddings versus the EMH in Stock Clustering," Papers 2509.01590, arXiv.org.
• Andrew Blair-Stanek & Nils Holzenberger & Benjamin Van Durme, 2025. "Can LLMs Identify Tax Abuse?," Papers 2508.20097, arXiv.org.