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Report NEP-BIG-2025-01-20
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:
- Katsafados, Apostolos G. & Leledakis, George N. & Panagiotou, Nikolaos P. & Pyrgiotakis, Emmanouil G., 2024, "Can central bankers’ talk predict bank stock returns? A machine learning approach," MPRA Paper, University Library of Munich, Germany, number 122899, Oct.
- Abbate Nicolás Francisco & Gasparini Leonardo & Ronchetti Franco & Quiroga Facundo, 2024, "High-Resolution Income Estimates Using Satellite Imagery: A Deep Learning Approach applied in Buenos Aires," Asociación Argentina de Economía Política: Working Papers, Asociación Argentina de Economía Política, number 4701, Nov.
- Jairo Flores & Bruno Gonzaga & Walter Ruelas-Huanca & Juan Tang, 2024, "Nowcasting Peruvian GDP with Machine Learning Methods," Working Papers, Banco Central de Reserva del Perú, number 2024-019, Dec.
- Dyakonova, Ludmila & Konstantinov, Alexey, 2024, "Approaches to risk analysis in the financial sector based on machine learning and artificial intelligence methods," MPRA Paper, University Library of Munich, Germany, number 122941, Dec.
- Nuttapol Lertmethaphat & Nuarpear Lekfuangfu & Pucktada Treeratpituk, 2025, "Exploring the Thai Job Market Through the Lens of Natural Language Processing and Machine Learning," PIER Discussion Papers, Puey Ungphakorn Institute for Economic Research, number 228, Jan.
- Li, Chao & Keeley, Alexander Ryota & Takeda, Shutaro & Seki, Daikichi & Managi, Shunsuke, 2024, "ESG Tendencies from News - Investigated by AI Trained by Human Intelligence," MPRA Paper, University Library of Munich, Germany, number 122757, Nov.
- Caravaggio, Nicola & Resce, Giuliano & Idola Francesca, Spanò, 2024, "Is Local Taxation Predictable? A Machine Learning Approach," Economics & Statistics Discussion Papers, University of Molise, Department of Economics, number esdp24098, Sep.
- Coco, Giuseppe & Monturano, Gianluca & Resce, Giuliano, 2025, "Predicting Delays in Cohesion Infrastructure Projects," Economics & Statistics Discussion Papers, University of Molise, Department of Economics, number esdp25099, Jan.
- Aguilar Rafael, 2024, "Predicción de inflación en Argentina con métodos econométricos clásicos y machine learning," Asociación Argentina de Economía Política: Working Papers, Asociación Argentina de Economía Política, number 4704, Nov.
- Chaohua Dong & Jiti Gao & Bin Peng & Yayi Yan, 2024, "Estimation and Inference for a Class of Generalized Hierarchical Models," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 7/24.
- Koukopoulos, Anastasios & Farmakis, Timoleon & Katiaj, Pavlina & Fraidaki, Katerina & Kavatha, Marina, 2024, "Apple Vision Pro: A Reddit-Based Sentiment Analysis," MPRA Paper, University Library of Munich, Germany, number 123180.
- Angela C. Lyons & Josephine Kass-Hanna & Deepika Pingali & Aiman Soliman & David Zhu & Yifang Zhang & Alejandro Montoya Castano, 2024, "A Geospatial Analysis of Food Insecurity Among Refugee Households in Lebanon Using Machine Learning Techniques," Working Papers, Economic Research Forum, number 1729, Sep, revised 20 Sep 2024.
- Guhan Sivakumar, 2025, "HMM-LSTM Fusion Model for Economic Forecasting," Papers, arXiv.org, number 2501.02002, Jan.
- Wonseong Kim & Christina Niklaus & Choong Lyol Lee & Siegfried Handschuh, 2025, "DisSim-FinBERT: Text Simplification for Core Message Extraction in Complex Financial Texts," Papers, arXiv.org, number 2501.04959, Jan, revised Mar 2026.
- Li, Chao & Keeley, Alexander Ryota & Takeda, Shutaro & Seki, Daikichi & Managi, Shunsuke, 2024, "Investor’s ESG Tendency Probed by Pre-trained Transformers," MPRA Paper, University Library of Munich, Germany, number 122756, Nov.
- Niousha Bagheri & Milad Ghasri & Michael Barlow, 2025, "RUM-NN: A Neural Network Model Compatible with Random Utility Maximisation for Discrete Choice Setups," Papers, arXiv.org, number 2501.05221, Jan.
- Lennart Ante & Aman Saggu, 2025, "Quantifying A Firm's AI Engagement: Constructing Objective, Data-Driven, AI Stock Indices Using 10-K Filings," Papers, arXiv.org, number 2501.01763, Jan.
- Vogel, Justus & Cordier, Johannes & Filipovic, Miodrag, 2025, "Causal Effects and Optimal Policy Learning for Intensive Care Unit Discharge Decisions to Solve Hospital Process Bottlenecks: Approach, Methods, and First Results," Working Paper Series in Health Economics, Management and Policy, University of St.Gallen, School of Medicine, Chair of Health Economics, Policy and Management, number 2025-01, revised 2025.
- Aromí J. Daniel & Heymann Daniel, 2024, "Synthetic surveys of monetary policymakers: perceptions, narratives and transparency," Asociación Argentina de Economía Política: Working Papers, Asociación Argentina de Economía Política, number 4707, Nov.
- Leogrande, Angelo & Drago, Carlo & Mallardi, Giulio & Costantiello, Alberto & Magaletti, Nicola, 2024, "Patenting Propensity in Italy: A Machine Learning Approach to Regional Clustering," MPRA Paper, University Library of Munich, Germany, number 123081, Dec.
- Cova, Joshua & Schmitz, Luuk, 2024, "A primer for the use of classifier and generative large language models in social science research," OSF Preprints, Center for Open Science, number r3qng, Dec, DOI: 10.31219/osf.io/r3qng.
- Galasso, Vincenzo & Nannicini, Tommaso & Nozza, Debora, 2024, "We Need to Talk: Audio Surveys and Information Extraction," IZA Discussion Papers, IZA Network @ LISER, number 17488, Nov.
- Leek, Lauren Caroline & Bischl, Simeon, 2024, "How Central Bank Independence Shapes Monetary Policy Communication: A Large Language Model Application," SocArXiv, Center for Open Science, number yrhka, Nov, DOI: 10.31219/osf.io/yrhka.