Report NEP-BIG-2020-04-13
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.Subscribe to this report: email, RSS, or Mastodon.
Other reports in NEP-BIG
The following items were announced in this report:
- MORIKAWA Masayuki, 2020. "Use of AI, Work Style Reform, and Productivity: Evidence from an Individual-Level Survey (Japanese)," Discussion Papers (Japanese) 20016, Research Institute of Economy, Trade and Industry (RIETI).
- Stéphan Vincent-Lancrin & Reyer van der Vlies, 2020. "Trustworthy artificial intelligence (AI) in education: Promises and challenges," OECD Education Working Papers 218, OECD Publishing.
- Francis de Véricourt, & Huseyin Gurkan,, 2020. "Contracting, pricing, and data collection under the AI flywheel effect," ESMT Research Working Papers ESMT-20-01, ESMT European School of Management and Technology.
- Rutzer, Christian & Niggli, Matthias & Weder, Rolf, 2020. "Estimating the Green Potential of Occupations: A New Approach Applied to the U.S. Labor Market," Working papers 2020/03, Faculty of Business and Economics - University of Basel.
- Romit Maulik & Junghwa Choi & Wesley Wehde & Prasanna Balaprakash, 2020. "Determining feature importance for actionable climate change mitigation policies," Papers 2003.10234, arXiv.org.
- Carmine de Franco & Christophe Geissler & Vincent Margot & Bruno Monnier, 2018. "ESG investments: Filtering versus machine learning approaches," Post-Print hal-02481891, HAL.
- Aurelio F. Bariviera & Ignasi Merediz-Sol`a, 2020. "Where do we stand in cryptocurrencies economic research? A survey based on hybrid analysis," Papers 2003.09723, arXiv.org.
- Saeed Nosratabadi & Amir Mosavi & Puhong Duan & Pedram Ghamisi, 2020. "Data Science in Economics," Papers 2003.13422, arXiv.org.
- Herrera, Pablo Matías & Garcia Fronti, Javier, 2020. "Tecnologías de Big data y biopolítica: mecanismos relacionales de procesamiento de datos en época de pandemia mundial viral [Big data technologies and biopolitics: relational mechanisms of data pro," MPRA Paper 99546, University Library of Munich, Germany.
- Knaus, Michael C., 2020. "Double Machine Learning Based Program Evaluation under Unconfoundedness," IZA Discussion Papers 13051, Institute of Labor Economics (IZA).
- Kevin Kuo & Daniel Lupton, 2020. "Towards Explainability of Machine Learning Models in Insurance Pricing," Papers 2003.10674, arXiv.org.
- Kyle Colangelo & Ying-Ying Lee, 2020. "Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments," Papers 2004.03036, arXiv.org, revised Sep 2023.
- Pak, Anton & Gannon, Brenda & Staib, Andrew, 2020. "Forecasting Waiting Time to Treatment for Emergency Department Patients," OSF Preprints d25se, Center for Open Science.
- Samir Wadhwa & Roy Dong, 2020. "Equilibrium Selection in Data Markets: Multiple-Principal, Multiple-Agent Problems with Non-Rivalrous Goods," Papers 2004.00196, arXiv.org, revised Mar 2023.
- TOJO Yoshizumi, 2020. "Regulation of Data Localization Measures in WTO Law (Japanese)," Discussion Papers (Japanese) 20011, Research Institute of Economy, Trade and Industry (RIETI).
- Adriano Koshiyama & Sebastian Flennerhag & Stefano B. Blumberg & Nick Firoozye & Philip Treleaven, 2020. "QuantNet: Transferring Learning Across Systematic Trading Strategies," Papers 2004.03445, arXiv.org, revised Jun 2020.
- Chong, Terence Tai Leung & Li, Chen, 2020. "Search of Attention in Financial Market," MPRA Paper 99003, University Library of Munich, Germany.
- Xingwei Hu, 2020. "Sorting Big Data by Revealed Preference with Application to College Ranking," Papers 2003.12198, arXiv.org.
- Arthur Charpentier & Romuald Elie & Carl Remlinger, 2020. "Reinforcement Learning in Economics and Finance," Papers 2003.10014, arXiv.org.
- KAWAHAMA Noboru & TAKEDA Kuninobu, 2020. "Analyzing the Online Advertising Market from the Perspective of Competition Policy (Japanese)," Discussion Papers (Japanese) 20013, Research Institute of Economy, Trade and Industry (RIETI).
- Oshan, Taylor M., 2020. "Potential and pitfalls of big transport data for spatial interaction models of urban mobility," OSF Preprints gwumt, Center for Open Science.