Report NEP-BIG-2021-03-22

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:

• Steve J. Bickley & Alison Macintyre & Benno Torgler, 2021. "Artificial Intelligence and Big Data in Sustainable Entrepreneurship," CREMA Working Paper Series 2021-11, Center for Research in Economics, Management and the Arts (CREMA).
• Ly, Racine & Traore, Fousseini & Dia, Khadim, 2021. "Forecasting commodity prices using long-short-term memory neural networks," IFPRI discussion papers 2000, International Food Policy Research Institute (IFPRI).
• Maximilien Germain & Mathieu Laurière & Huyên Pham & Xavier Warin, 2021. "DeepSets and their derivative networks for solving symmetric PDEs ," Working Papers hal-03154116, HAL.
• Zexin Hu & Yiqi Zhao & Matloob Khushi, 2021. "A Survey of Forex and Stock Price Prediction Using Deep Learning," Papers 2103.09750, arXiv.org.
• Yusen Lin & Jinming Xue & Louiqa Raschid, 2021. "Predicting the Behavior of Dealers in Over-The-Counter Corporate Bond Markets," Papers 2103.09098, arXiv.org.
• Luigi Longo & Massimo Riccaboni & Armando Rungi, 2021. "A Neural Network Ensemble Approach for GDP Forecasting," Working Papers 02/2021, IMT School for Advanced Studies Lucca, revised Mar 2021.
• Liu, Liang & Yang, Kun & Fujii, Hidemichi & Liu, Jun, 2021. "Artificial Intelligence and Energy Intensity in China’s Industrial Sector: Effect and Transmission Channel," MPRA Paper 106333, University Library of Munich, Germany.
• J. Ignacio Conde-Ruiz & Juan José Ganuza & Manu García & Luis A. Puch, 2021. "Gender Distribution across Topics in Top 5 Economics Journals: A Machine Learning Approach," Working Papers 2021-07, FEDEA.
• Anthony Strittmatter & Conny Wunsch, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," CESifo Working Paper Series 8912, CESifo.
• Philipp Bach & Victor Chernozhukov & Malte S. Kurz & Martin Spindler & Sven Klaassen, 2021. "DoubleML -- An Object-Oriented Implementation of Double Machine Learning in R," Papers 2103.09603, arXiv.org, revised Jun 2024.
• Mengda Li & Charles-Albert Lehalle, 2021. "Do Word Embeddings Really Understand Loughran-McDonald's Polarities?," Papers 2103.09813, arXiv.org.
• Qi Tang & Tongmei Fan & Ruchen Shi & Jingyan Huang & Yidan Ma, 2021. "Prediction of financial time series using LSTM and data denoising methods," Papers 2103.03505, arXiv.org.
• Sturm, Timo & Gerlach, Jin & Pumplun, Luisa & Mesbah, Neda & Peters, Felix & Tauchert, Christoph & Nan, Ning & Buxmann, Peter, 2021. "Coordinating Human and Machine Learning for Effective Organizational Learning," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 125653, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Jin Li & Ye Luo & Xiaowei Zhang, 2021. "Causal Reinforcement Learning: An Instrumental Variable Approach," Papers 2103.04021, arXiv.org, revised Sep 2022.
• Alexander J. M. Kell & A. Stephen McGough & Matthew Forshaw, 2021. "The impact of online machine-learning methods on long-term investment decisions and generator utilization in electricity markets," Papers 2103.04327, arXiv.org.
• Michel Denuit & Arthur Charpentier & Julien Trufin, 2021. "Autocalibration and Tweedie-dominance for Insurance Pricing with Machine Learning," Papers 2103.03635, arXiv.org, revised Jul 2021.
• Kirsten Hillebrand & Lars Hornuf, 2021. "The Social Dilemma of Big Data: Donating Personal Data to Promote Social Welfare," CESifo Working Paper Series 8926, CESifo.
• Raymond C. W. Leung & Yu-Man Tam, 2021. "Statistical Arbitrage Risk Premium by Machine Learning," Papers 2103.09987, arXiv.org.
• Hou, Bohan, 2021. "A Novel Data Governance Scheme Based on the Behavioral Economics Theory," SocArXiv 2b9dc, Center for Open Science.
• Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Causal Machine-Learning Approach," Papers 2103.10251, arXiv.org, revised Sep 2021.
• Matteo Garzoli & Alberto Plazzi & Rossen I. Valkanov, 2021. "Backcasting, Nowcasting, and Forecasting Residential Repeat-Sales Returns: Big Data meets Mixed Frequency," Swiss Finance Institute Research Paper Series 21-21, Swiss Finance Institute.
• Madalina Botina & Marilena Marin, 2021. "Application of Legal Instruments of Protection in the Field of Personal Data – Human Rights between Challenges and Limits," ConScienS Conference Proceedings 032mb, Research Association for Interdisciplinary Studies.