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Report NEP-BIG-2024-02-19
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:
- Patrick Rehill & Nicholas Biddle, 2024, "Heterogeneous treatment effect estimation with high-dimensional data in public policy evaluation -- an application to the conditioning of cash transfers in Morocco using causal machine learning," Papers, arXiv.org, number 2401.07075, Jan, revised Mar 2024.
- Michele Leonardo Bianchi, 2024, "Text mining arXiv: a look through quantitative finance papers," Papers, arXiv.org, number 2401.01751, Jan, revised Apr 2024.
- Robin Jarry & Marc Chaumont & Laure Berti-Équille & Gérard Subsol, 2023, "Comparing spatial and spatio-temporal paradigms to estimate the evolution of socio-economical indicators from satellite images," Post-Print, HAL, number hal-04268542, Jul, DOI: 10.1109/IGARSS52108.2023.10282306.
- Jin, Keyan & Zhong, Ziqi & Zhao, Elena Yifei, 2024, "Sustainable digital marketing under big data: an AI random forest model approach," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 121402, Jan.
- Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E & Wiemann, Thomas, 2024, "Model Averaging and Double Machine Learning," IZA Discussion Papers, IZA Network @ LISER, number 16714, Jan.
- Bloom, Nicholas & Davis, Steven J. & Hansen, Stephen & Lambert, Peter John & Sadun, Raffaella & Taska, Bledi, 2023, "Remote work across jobs, companies and space," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 121302, Jul.
- Rui KATO & Daisuke MIYAKAWA & Masaki YANAOKA & Shinji YUKIMOTO, 2024, "Using Supply Chain Network Information and High-frequency Mobility Data to Forecast Firm Dynamics (Japanese)," Discussion Papers (Japanese), Research Institute of Economy, Trade and Industry (RIETI), number 24005, Jan.
- F. Bolivar & Miguel A. Duran & A. Lozano-Vivas, 2024, "Business Model Contributions to Bank Profit Performance: A Machine Learning Approach," Papers, arXiv.org, number 2401.12334, Jan.
- Zan Yu & Lianzeng Zhang, 2024, "Computing the Gerber-Shiu function with interest and a constant dividend barrier by physics-informed neural networks," Papers, arXiv.org, number 2401.04378, Jan.
- Bohan Ma & Yushan Xue & Yuan Lu & Jing Chen, 2023, "Stockformer: A Price-Volume Factor Stock Selection Model Based on Wavelet Transform and Multi-Task Self-Attention Networks," Papers, arXiv.org, number 2401.06139, Nov, revised Jun 2024.
- Sourabh Balgi & Adel Daoud & Jose M. Pe~na & Geoffrey T. Wodtke & Jesse Zhou, 2024, "Deep Learning With DAGs," Papers, arXiv.org, number 2401.06864, Jan.
- Lezhi Li & Ting-Yu Chang & Hai Wang, 2023, "Multimodal Gen-AI for Fundamental Investment Research," Papers, arXiv.org, number 2401.06164, Dec.
- G. Arbia & V. Nardelli & N. Salvini & I. Valentini, 2024, "New accessibility measures based on unconventional big data sources," Papers, arXiv.org, number 2401.13370, Jan.
- Albert, Jose Ramon G. & Siar, Sheila V. & Vizmanos, Jana Flor V. & Hernandez,Angelo C. & Sarmiento,JaninaLuz C., 2023, "Like, Comment, and Share: Analyzing Public Sentiments of Government Policies in Social Media," Discussion Papers, Philippine Institute for Development Studies, number DP 2023-33, DOI: https://doi.org/10.62986/dp2023.33.
- Jeongbin Kim & Matthew Kovach & Kyu-Min Lee & Euncheol Shin & Hector Tzavellas, 2024, "Can an LLM Learn Preferences from Choice Data?," Papers, arXiv.org, number 2401.07345, Jan, revised Apr 2026.
- Tetiana Yukhymenko & Oleh Sorochan, 2024, "Impact of the central bank's communication on macro financial outcomes," IHEID Working Papers, Economics Section, The Graduate Institute of International Studies, number 01-2024, Feb.
- Lembregts, Christophe & Cadario, Romain, 2024, "Consumer-Driven Climate Mitigation: Exploring Barriers and Solutions in Studying Higher Mitigation Potential Behaviors," OSF Preprints, Center for Open Science, number ywus6, Jan, DOI: 10.31219/osf.io/ywus6.