Report NEP-BIG-2024-09-23

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:

• Tom Coupé, 2024. "Revealed Preferences: ChatGPT’s Opinion on Economic Issues and the Economics Profession," Working Papers in Economics 24/13, University of Canterbury, Department of Economics and Finance.
• Jean-Charles Bricongne & Baptiste Meunier & Raquel Caldeira, 2024. "Should Central Banks Care About Text Mining? A Literature Review," Working papers 950, Banque de France.
• Tarek A. Hassan & Stephan Hollander & Aakash Kalyani & Markus Schwedeler & Ahmed Tahoun & Laurence van Lent, 2024. "Economic Surveillance using Corporate Text," Working Papers 2024-022, Federal Reserve Bank of St. Louis.
• Lucas Zhang, 2024. "Continuous difference-in-differences with double/debiased machine learning," Papers 2408.10509, arXiv.org.
• Domenico Moramarco & Paolo Brunori & Pedro Salas-Rojo, 2024. "Biases in inequality of opportunity estimates: measures and solutions," Working Papers 675, ECINEQ, Society for the Study of Economic Inequality.
• Sina Montazeri & Haseebullah Jumakhan & Sonia Abrasiabian & Amir Mirzaeinia, 2024. "Gradient Reduction Convolutional Neural Network Policy for Financial Deep Reinforcement Learning," Papers 2408.11859, arXiv.org.
• Sid Bhatia & Sidharth Peri & Sam Friedman & Michelle Malen, 2024. "High-Frequency Trading Liquidity Analysis | Application of Machine Learning Classification," Papers 2408.10016, arXiv.org.
• Lijuan Wang & Yijia Hu & Yan Zhou, 2024. "Cross-border Commodity Pricing Strategy Optimization via Mixed Neural Network for Time Series Analysis," Papers 2408.12115, arXiv.org.
• Daniel Souza & Aldo Geuna & Jeff Rodr'iguez, 2024. "How Small is Big Enough? Open Labeled Datasets and the Development of Deep Learning," Papers 2408.10359, arXiv.org.
• Yuntao Wu & Jiayuan Guo & Goutham Gopalakrishna & Zisis Poulos, 2024. "Deep-MacroFin: Informed Equilibrium Neural Network for Continuous Time Economic Models," Papers 2408.10368, arXiv.org, revised Oct 2024.
• Soren Bettels & Stefan Weber, 2024. "An Integrated Approach to Importance Sampling and Machine Learning for Efficient Monte Carlo Estimation of Distortion Risk Measures in Black Box Models," Papers 2408.02401, arXiv.org, revised Jan 2025.
• Stephan Hetzenecker & Maximilian Osterhaus, 2024. "Deep Learning for the Estimation of Heterogeneous Parameters in Discrete Choice Models," Papers 2408.09560, arXiv.org.
• Zheng Cao, 2024. "Stochastic Calculus for Option Pricing with Convex Duality, Logistic Model, and Numerical Examination," Papers 2408.05672, arXiv.org.
• Domenico Moramarco & Paolo Brunori & Pedro Salas-Rojo, 2024. "Biases in inequality of opportunity estimates: measures and solutions," SERIES 02-2024, Dipartimento di Economia e Finanza - Università degli Studi di Bari "Aldo Moro", revised Aug 2024.
• Abhinandan Dalal & Patrick Blobaum & Shiva Kasiviswanathan & Aaditya Ramdas, 2024. "Anytime-Valid Inference for Double/Debiased Machine Learning of Causal Parameters," Papers 2408.09598, arXiv.org, revised Sep 2024.
• Qianqian Xie & Dong Li & Mengxi Xiao & Zihao Jiang & Ruoyu Xiang & Xiao Zhang & Zhengyu Chen & Yueru He & Weiguang Han & Yuzhe Yang & Shunian Chen & Yifei Zhang & Lihang Shen & Daniel Kim & Zhiwei Liu, 2024. "Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications," Papers 2408.11878, arXiv.org.
• Federico Daniel Forte, 2024. "Argentina | Pronóstico de inflación de corto plazo con modelos Random Forest [Argentina | Forecasting short-term inflation with Random Forest Models]," Working Papers 24/10, BBVA Bank, Economic Research Department.
• CJ Finnegan & James F. McCann & Salissou Moutari, 2024. "Less is more: AI Decision-Making using Dynamic Deep Neural Networks for Short-Term Stock Index Prediction," Papers 2408.11740, arXiv.org.
• Simon D Angus & Lachlan O'Neill, 2024. "Paired Completion: Flexible Quantification of Issue-framing at Scale with LLMs," Papers 2408.09742, arXiv.org.
• Zitian Gao & Yihao Xiao, 2024. "Enhancing Startup Success Predictions in Venture Capital: A GraphRAG Augmented Multivariate Time Series Method," Papers 2408.09420, arXiv.org, revised Dec 2024.
• Julia M. Puaschunder, 2024. "Knowledge in the 21st Century: Making Sense of Big Data," RAIS Conference Proceedings 2022-2024 0386, Research Association for Interdisciplinary Studies.
• Mathias Valla, 2024. "A Longitudinal Tree-Based Framework for Lapse Management in Life Insurance," Post-Print hal-04178278, HAL.
• Jianqing Fan & Weining Wang & Yue Zhao, 2024. "Conditional nonparametric variable screening by neural factor regression," Papers 2408.10825, arXiv.org.
• Julia Schmidt & Graham Pilgrim & Annabelle Mourougane, 2024. "Measuring the demand for AI skills in the United Kingdom," OECD Artificial Intelligence Papers 25, OECD Publishing.
• Aleksandar Arandjelovi'c & Julia Eisenberg, 2024. "Reinsurance with neural networks," Papers 2408.06168, arXiv.org.
• Aleksandar Arandjelovi'c & Pavel V. Shevchenko & Tomoko Matsui & Daisuke Murakami & Tor A. Myrvoll, 2024. "Solving stochastic climate-economy models: A deep least-squares Monte Carlo approach," Papers 2408.09642, arXiv.org.
• Julia M. Puaschunder, 2024. "Big Data Inequality," RAIS Conference Proceedings 2022-2024 0415, Research Association for Interdisciplinary Studies.
• Hamza Bennani & Davide Romelli, 2024. "Exploring the informativeness and drivers of tone during committee meetings: the case of the Federal Reserve," Post-Print hal-04670309, HAL.
• Nicolás Forteza & Elvira Prades & Marc Roca, 2024. "Analysing the VAT Cut Pass-Through in Spain Using Web Scraped Supermarket Data and Machine Learning," Working papers 951, Banque de France.