Report NEP-BIG-2025-06-30

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

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-BIG

The following items were announced in this report:

• Fabio Gatti & Joel Huesler, 2025, "Text Analysis Methods for Historical Letters, The case of Michelangelo Buonarrotti," Working Papers, European Historical Economics Society (EHES), number 0279, Jun.
• Tobias Schmidt & Kai-Robin Lange & Matthias Reccius & Henrik Muller & Michael Roos & Carsten Jentsch, 2025, "Identifying economic narratives in large text corpora -- An integrated approach using Large Language Models," Papers, arXiv.org, number 2506.15041, Jun.
• Liexin Cheng & Xue Cheng & Shuaiqiang Liu, 2025, "Fast Learning in Quantitative Finance with Extreme Learning Machine," Papers, arXiv.org, number 2505.09551, May, revised May 2025.
• Timoth'ee Hornek Amir Sartipi & Igor Tchappi & Gilbert Fridgen, 2025, "Benchmarking Pre-Trained Time Series Models for Electricity Price Forecasting," Papers, arXiv.org, number 2506.08113, Jun, revised Aug 2025.
• Mihai Cucuringu & Kang Li & Chao Zhang, 2025, "Forecasting Intraday Volume in Equity Markets with Machine Learning," Papers, arXiv.org, number 2505.08180, May.
• Sukru Selim Calik & Andac Akyuz & Zeynep Hilal Kilimci & Kerem Colak, 2025, "Explainable-AI powered stock price prediction using time series transformers: A Case Study on BIST100," Papers, arXiv.org, number 2506.06345, Jun.
• Yang Qiang, 2025, "The impact of extracurricular education on socioeconomic mobility in Japan: an application of causal machine learning," Papers, arXiv.org, number 2506.07421, Jun.
• Marcus Buckmann & Ed Hill, 2025, "Improving text classification: logistic regression makes small LLMs strong and explainable ‘tens-of-shot’ classifiers," Bank of England working papers, Bank of England, number 1127, May.
• Paolo Verme, 2025, "Predicting Poverty," Papers, arXiv.org, number 2505.05958, May.
• Mateusz Wilinski & Anubha Goel & Alexandros Iosifidis & Juho Kanniainen, 2025, "Classifying and Clustering Trading Agents," Papers, arXiv.org, number 2505.21662, May.
• Réka Juhász & Nathan J. Lane & Emily Oehlsen & Veronica C. Perez, 2025, "Measuring Industrial Policy: A Text-Based Approach," NBER Working Papers, National Bureau of Economic Research, Inc, number 33895, Jun.
• Austin Pollok, 2025, "Predicting Realized Variance Out of Sample: Can Anything Beat The Benchmark?," Papers, arXiv.org, number 2506.07928, Jun.
• Marcus Buckmann & Quynh Anh Nguyen & Edward Hill, 2025, "Revealing economic facts: LLMs know more than they say," Papers, arXiv.org, number 2505.08662, May, revised Dec 2025.
• Dangxing Chen, 2025, "Explaining Risks: Axiomatic Risk Attributions for Financial Models," Papers, arXiv.org, number 2506.06653, Jun.
• Guanhao Zhou & Yuefeng Han & Xiufan Yu, 2025, "Covariate-Adjusted Deep Causal Learning for Heterogeneous Panel Data Models," Papers, arXiv.org, number 2505.20536, May.
• Emily Aiken & Anik Ashraf & Joshua Blumenstock & Raymond Guiteras & Ahmed Mushfiq Mobarak, 2025, "Scalable Targeting of Social Protection: When Do Algorithms Out-Perform Surveys and Community Knowledge?," NBER Working Papers, National Bureau of Economic Research, Inc, number 33919, Jun.
• Shu Wang & Zijun Yao & Shuhuai Zhang & Jianuo Gai & Tracy Xiao Liu & Songfa Zhong, 2025, "When Experimental Economics Meets Large Language Models: Evidence-based Tactics," Papers, arXiv.org, number 2505.21371, May, revised Jul 2025.
• Zonghan Wu & Congyuan Zou & Junlin Wang & Chenhan Wang & Hangjing Yang & Yilei Shao, 2025, "Towards Competent AI for Fundamental Analysis in Finance: A Benchmark Dataset and Evaluation," Papers, arXiv.org, number 2506.07315, May, revised Nov 2025.
• Nofal, Bastián Castro & Flores, Ignacio & Cubillos, Pablo Gutiérrez, 2025, "From Housing Gains to Pension Losses: New Methods to Reveal Wealth Inequality Dynamics in Chile," SocArXiv, Center for Open Science, number b8zve_v1, Jun, DOI: 10.31219/osf.io/b8zve_v1.
• Zheng Cao & Wanchaloem Wunkaew & Helyette Geman, 2025, "The Hype Index: an NLP-driven Measure of Market News Attention," Papers, arXiv.org, number 2506.06329, May.
• Falck-Zepeda, José B. & Zambrano, Patricia & Sanders, Arie & Trabanino, Carlos Rogelio, 2025, "Parametric and machine learning approaches to examine yield differences between control and treatment considering outliers and statistical biases: The case of insect resistant/herbicide tolerant (IR/HT) maize in Honduras," IFPRI discussion papers, International Food Policy Research Institute (IFPRI), number 2334, Apr.
• Item repec:fpr:gsspwp:158180 is not listed on IDEAS anymore

• Giuseppe Arbia & Luca Morandini & Vincenzo Nardelli, 2025, "Evaluating Large Language Model Capabilities in Assessing Spatial Econometrics Research," Papers, arXiv.org, number 2506.06377, Jun.
• Weber, Isabella & Wasner, Evan & Lang, Markus & Braun, Benjamin & Klooster, Jens van’t, 2025, "Implicit coordination in sellers’ inflation: how cost shocks facilitate price hikes," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 128231, Sep.
• R. Maria del Rio-Chanona & Marco Pangallo & Cars Hommes, 2025, "Can Generative AI agents behave like humans? Evidence from laboratory market experiments," Papers, arXiv.org, number 2505.07457, May.
• Fabian Muny, 2025, "Evaluating Program Sequences with Double Machine Learning: An Application to Labor Market Policies," Papers, arXiv.org, number 2506.11960, Jun.
• Thiago Christiano Silva & Kei Moriya & Mr. Romain M Veyrune, 2025, "From Text to Quantified Insights: A Large-Scale LLM Analysis of Central Bank Communication," IMF Working Papers, International Monetary Fund, number 2025/109, Jun.
• Weixian Waylon Li & Hyeonjun Kim & Mihai Cucuringu & Tiejun Ma, 2025, "Can LLM-based Financial Investing Strategies Outperform the Market in Long Run?," Papers, arXiv.org, number 2505.07078, May, revised Feb 2026.
• Gabriel Nova & Stephane Hess & Sander van Cranenburgh, 2025, "Delphos: A reinforcement learning framework for assisting discrete choice model specification," Papers, arXiv.org, number 2506.06410, Jun, revised Mar 2026.
• Mindy L. Mallory & Rundong Peng & Meilin Ma & H. Holly Wang, 2025, "High-Dimensional Spatial-Plus-Vertical Price Relationships and Price Transmission: A Machine Learning Approach," Papers, arXiv.org, number 2506.13967, Jun.
• Xueying Ding & Aakriti Mittal & Achintya Gopal, 2025, "DELPHYNE: A Pre-Trained Model for General and Financial Time Series," Papers, arXiv.org, number 2506.06288, May.
• Yu Li & Yuhan Wu & Shuhua Zhang, 2025, "The Exploratory Multi-Asset Mean-Variance Portfolio Selection using Reinforcement Learning," Papers, arXiv.org, number 2505.07537, May.
• James Cussens & Julia Hatamyar & Vishalie Shah & Noemi Kreif, 2025, "Fast Learning of Optimal Policy Trees," Papers, arXiv.org, number 2506.15435, Jun.
• Qirui Mi & Qipeng Yang & Zijun Fan & Wentian Fan & Heyang Ma & Chengdong Ma & Siyu Xia & Bo An & Jun Wang & Haifeng Zhang, 2025, "EconGym: A Scalable AI Testbed with Diverse Economic Tasks," Papers, arXiv.org, number 2506.12110, Jun.
• Weiyao Meng & John Harvey & James Goulding & Chris James Carter & Evgeniya Lukinova & Andrew Smith & Paul Frobisher & Mina Forrest & Georgiana Nica-Avram, 2025, "Large Language Models as 'Hidden Persuaders': Fake Product Reviews are Indistinguishable to Humans and Machines," Papers, arXiv.org, number 2506.13313, Jun.

Report NEP-BIG-2025-06-30

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

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-BIG

The following items were announced in this report: