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Report NEP-BIG-2026-09-07
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:
- Max Ahrens & Dragos Gorduza & Micheal McMahon, 2025, "EcoFinBench – a natural language processing benchmark for economics and finance," Bank of England Staff Working Paper series, Bank of England, number 1163, Dec.
- João Anderson da Silva Felix & Michel Alexandre & Cássio da Nóbrega Besarria, 2026, "Forecasting the Cost of a Basic Basket of Goods: a comparative analysis using machine learning models and online prices," Working Papers Series, Central Bank of Brazil, Research Department, number 650, Aug.
- Tulia Gattone & Donato Romano & Luca Tiberti, 2026, "Pathways of Climate Variability, Agricultural Performance, and Conflict: A Machine Learning Approach to Complex Dependencies," Working Papers - Economics, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa, number wp2026_10.rdf.
- Joshua Elias Fred A. Suero, 2025, "Developing a Standard Strategy for Time Series Forecasting Integrating Statistical and Machine Learning Techniques Using a Meta-Model Approach and its Application in Generating External Debt Projections," BSP Discussion Paper Series, Bangko Sentral ng Pilipinas, number 202503, Apr.
- Pierri, Gastón & Fontenele, Marcelo & Nunes, Jose Luiz, 2026, "AI and Judicial Productivity: The Impact of MIDAS on the Courts of Fortaleza, Brazil," IDB Publications (Working Papers), Inter-American Development Bank, number 14700, Aug, DOI: http://dx.doi.org/10.18235/0014427.
- Jeremy Bejarano & Viren Desai & Kausthub Keshava & Arsh Kumar & Zixiao Wang & Vincent Hanyang Xu & Yangge Xu, 2026, "Do Deep Learning Methods Improve Financial Forecasts?," The OFR Blog, Office of Financial Research, US Department of the Treasury, number 26-10, Aug.
- Ryu, Jaehyeon & Yu, Jisang, 2026, "Reducing Basis Risk in Index Insurance Using Satellite-Based Vegetation Indices and Machine Learning," 2026 Annual Meeting, July 26 - 28, 2026, Kansas City, Missouri, Agricultural and Applied Economics Association, number 404414, DOI: 10.22004/ag.econ.404414.
- Jeremy Bejarano & Viren Desai & Kausthub Keshava & Arsh Kumar & Zixiao Wang & Vincent Hanyang Xu & Yangge Xu, 2026, "An Open Benchmark for Evaluating Time Series Forecasting Methods across Financial Markets," Working Papers, Office of Financial Research, US Department of the Treasury, number 26-05, Aug.
- Sahab Zandi & Noah Kostesku & Christophe Mues & Mar'ia 'Oskarsd'ottir & Cristi'an Bravo, 2026, "Communicating Credit Risk with Large Language Models: Evaluation of Explanations from Standard and Alternative Data-Based Models," Papers, arXiv.org, number 2608.17715, Aug.
- Ashwin, Julian & Beaudry, Paul & Ellison, Martin, 2024, "Neural Network Learning for Nonlinear Economies," CEPR Discussion Papers, Centre for Economic Policy Research, number 19295, Jul.
- Marcus Buckmann & Quynh Anh Nguyen & Ed Hill, 2025, "Revealing economic facts: LLMs know more than they say," Bank of England Staff Working Paper series, Bank of England, number 1150, Oct.
- Nikoleta Anesti & Edward Hill & Andreas Joseph, 2026, "Inflation attitudes of large language models," Bank of England Staff Working Paper series, Bank of England, number 1190, Jun.
- Fusheng Luo, 2026, "From Financial Sentiment Classification to Return Predictability: A QLoRA Benchmark of Large Language Models," Papers, arXiv.org, number 2608.04200, Aug.
- Penaranda, Francisco & Sentana, Enrique, 2024, "Portfolio management with big data," CEPR Discussion Papers, Centre for Economic Policy Research, number 19314, Jul.
- Julius Dobelt, 2026, "Cross-Sectional Heterogeneity in LSTM Networks for Financial Time Series," Papers, arXiv.org, number 2608.05755, Aug, revised Aug 2026.
- Rishabh Singh Chauhan & Mahdi Ghadimi & Lishun Liu, 2026, "Estimating Heterogeneity in Travel Mode Choice Shifts with Causal Forests," Papers, arXiv.org, number 2608.04208, Aug.
- Ylva Baeckström & Roman Matkovskyy, 2026, "Financial advice behaviour: humans versus AI," Post-Print, HAL, number hal-05725514, Sep, DOI: 10.1016/j.jcorpfin.2026.103044.
- Aaron L. Garavito-Acosta & Wilmer Martinez-Rivera & Juan J. Ospina-Tejeiro & Edgar Caicedo-Garcia, 2026, "Experimenting with Large Language Models for Inflation Forecasting in Colombia," IHEID Working Papers, Economics Section, The Graduate Institute of International Studies, number 23-2026, Aug, revised 01 Sep 2026.