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Report NEP-CMP-2025-06-09
This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stanley Miles issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-CMP
The following items were announced in this report:
- Jędrzej Maskiewicz & Paweł Sakowski, 2025, "Can Artificial Intelligence Trade the Stock Market?," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2025-14.
- Lutfu Sua & Haibo Wang & Jun Huang, 2025, "Deep Learning in Renewable Energy Forecasting: A Cross-Dataset Evaluation of Temporal and Spatial Models," Papers, arXiv.org, number 2505.03109, May.
- Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2025, "Panel Machine Learning with Mixed-Frequency Data: Monitoring State-Level Fiscal Variables," Working Papers, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, number 25-04, May, revised May 2025.
- Nikolaos Giannakis & Periklis Gogas & Theophilos Papadimitriou & Jamel Saadaoui & Emmanouil Sofianos, 2025, "Do International Reserve Holdings Still Predict Economic Crises? Insights from Recent Machine Learning Techniques," Working Papers, International Network for Economic Research - INFER, number 2025.6.
- Anton Korinek & Jai Vipra, 2024, "Concentrating Intelligence:Scaling and Market Structure in Artificial Intelligence," Working Papers Series, Institute for New Economic Thinking, number inetwp228, Oct, DOI: 10.36687/inetwp228.
- Elliot Beck & Michael Wolf, 2025, "Forecasting inflation with the hedged random forest," Working Papers, Swiss National Bank, number 2025-07.
- Antonicelli, Margareth & Drago, Carlo & Costantiello, Alberto & Leogrande, Angelo, 2025, "Analyzing Income Inequalities across Italian regions: Instrumental Variable Panel Data, K-Means Clustering and Machine Learning Algorithms," MPRA Paper, University Library of Munich, Germany, number 124910, May.
- Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2025, "Panel Machine Learning with Mixed-Frequency Data: Monitoring State-Level Fiscal Variables," CIRANO Working Papers, CIRANO, number 2025s-15, May.
- Sona Benecka, 2025, "Forecasting Disaggregated Producer Prices: A Fusion of Machine Learning and Econometric Techniques," Working Papers, Czech National Bank, Research and Statistics Department, number 2025/2, Mar.
- Bachoc, François & Bolte, Jérôme & Boustany, Ryan & Loubes, Jean-Michel, 2025, "When majority rules, minority loses: bias amplification of gradient descent," TSE Working Papers, Toulouse School of Economics (TSE), number 25-1641, May.
- Juan Jos√© Rinc√≥n Brice√±o, 2025, "Colombian economic activity nowcasting: addressing nonlinearities and high dimensionality through machine-learning," Documentos CEDE, Universidad de los Andes, Facultad de Economía, CEDE, number 21388, Jun.
- Nurbanu Bursa, 2025, "Stock Market Telepathy: Graph Neural Networks Predicting the Secret Conversations between MINT and G7 Countries," Papers, arXiv.org, number 2506.01945, Jun.
- Qiang Chen & Tianyang Han & Jin Li & Ye Luo & Zigan Wang & Yuxiao Wu & Xiaowei Zhang & Tuo Zhou, 2025, "Can AI Master Econometrics? Evidence from Econometrics AI Agent on Expert-Level Tasks," Papers, arXiv.org, number 2506.00856, Jun, revised Jan 2026.
- Shovon Sengupta & Tanujit Chakraborty & Sunny Kumar Singh, 2024, "Forecasting CPI inflation under economic policy and geopolitical uncertainties," Post-Print, HAL, number hal-05056934, Sep, DOI: 10.1016/j.ijforecast.2024.08.005.
- Walenta, Danilo C. & Sturm, Timo & Scholz, Yven & Buxmann, Peter, 2025, "Make Up Your Mind! Habit Engineering With Artificial Intelligence in the Context of Trading," Publications of Darmstadt Technical University, Institute for Business Studies (BWL), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 154893.
- Kyungsu Kim, 2025, "Unemployment Dynamics Forecasting with Machine Learning Regression Models," Papers, arXiv.org, number 2505.01933, May.
- Heinisch, Katja & Scaramella, Fabio & Schult, Christoph, 2025, "Assumption errors and forecast accuracy: A partial linear instrumental variable and double machine learning approach," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 6/2025, DOI: 10.18717/dprpy3-ff77.
- Mohammadhossein Rashidi & Mohammad Modarres, 2025, "Predicting the Price of Gold in the Financial Markets Using Hybrid Models," Papers, arXiv.org, number 2505.01402, May.
- Amy Wenxuan Ding & Shibo Li, 2025, "Generative AI lacks the human creativity to achieve scientific discovery from scratch," Post-Print, HAL, number hal-05053017, Mar, DOI: 10.1038/s41598-025-93794-9.
- Rahil Dejkam & Reinhard Madlener, 2024, "Machine-Learning-Enhanced Measuring of Multidimensional Energy Poverty: Insights from a Pilot Survey in Portugal and Denmark," FCN Working Papers, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), number 1/2024, Oct.
- Pal, Hemendra, 2023, "The Impact of Russia-Ukraine conflict on Global Commodity Brent Crude Prices," MPRA Paper, University Library of Munich, Germany, number 124770, Aug, revised 02 Oct 2024.
- Sunyaev, Ali & Benlian, Alexander & Pfeiffer, Jella & Jussupow, Ekaterina & Thiebes, Scott & Maedche, Alexander & Gawlitza, Joshua, 2025, "High-Risk Artificial Intelligence," Publications of Darmstadt Technical University, Institute for Business Studies (BWL), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 154738, May.
- Fourie, Jurgens & Steenkamp, Daan, 2025, "Forecasting economic downturns in South Africa using leading indicators and machine learning," MPRA Paper, University Library of Munich, Germany, number 124709, May.
- Hongyang Yang & Likun Lin & Yang She & Xinyu Liao & Jiaoyang Wang & Runjia Zhang & Yuquan Mo & Christina Dan Wang, 2025, "FinRobot: Generative Business Process AI Agents for Enterprise Resource Planning in Finance," Papers, arXiv.org, number 2506.01423, Jun.
- Dreoni Ilda & Serruys Hannes & Manso Luis & Tudo Jose & Amores Antonio F, 2025, "Statistical imputation and validation of consumption microdata for EUROMOD," JRC Working Papers on Taxation & Structural Reforms, Joint Research Centre, number 2025-02, Apr.
- Förster, Maximilian & Hagn, Michael & Hambauer, Nico & Jaki, Paula & Obermeier, Andreas & Pinski, Marc & Schauer, Andreas & Schiller, Alexander & Benlian, Alexander & Heinrich, Bernd & Jussupow, Ekate, 2025, "A Taxonomy for Uncertainty-Aware Explainable AI," Publications of Darmstadt Technical University, Institute for Business Studies (BWL), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 154878.
- Ulrike Famira-Mühlberger & Thomas Horvath & Thomas Leoni & Martin Spielauer & Viktoria Szenkurök & Philipp Warum, 2025, "Demographic Change and the Future of Austria's Long-Term Care Allowance: A Dynamic Microsimulation Study," WIFO Working Papers, WIFO, number 705, May.
- Stefano Fasani & Valeria Patella & Giuseppe Pagano Giorgianni & Lorenza Rossi, 2025, "Belief Distortions and Disagreement about Inflation," Working Papers, Lancaster University Management School, Economics Department, number 423478673.
- Lin, Ziqi (Rachel), 2025, "Tax share analysis and prediction of kernel extreme Learning machine optimized by vector weighted average algorithm," OSF Preprints, Center for Open Science, number ymjw9_v1, May, DOI: 10.31219/osf.io/ymjw9_v1.
- Grebe, Leonard Nils, 2025, "Beyond the Replication Crisis: Investigating Methodological Drivers of Inconsistency in Financial Economics," Publications of Darmstadt Technical University, Institute for Business Studies (BWL), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 154892, May.