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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 (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:
- Masayuki MORIKAWA, 2020, "Use of AI, Work Style Reform, and Productivity: Evidence from an Individual-Level Survey (Japanese)," Discussion Papers (Japanese), Research Institute of Economy, Trade and Industry (RIETI), number 20016, Mar.
- Stéphan Vincent-Lancrin & Reyer van der Vlies, 2020, "Trustworthy artificial intelligence (AI) in education: Promises and challenges," OECD Education Working Papers, OECD Publishing, number 218, Apr, DOI: 10.1787/a6c90fa9-en.
- Item repec:esm:wpaper:esmt-20-01 is not listed on IDEAS anymore
- 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, Faculty of Business and Economics - University of Basel, number 2020/03.
- Romit Maulik & Junghwa Choi & Wesley Wehde & Prasanna Balaprakash, 2020, "Determining feature importance for actionable climate change mitigation policies," Papers, arXiv.org, number 2003.10234, Mar.
- Carmine de Franco & Christophe Geissler & Vincent Margot & Bruno Monnier, 2018, "ESG investments: Filtering versus machine learning approaches," Post-Print, HAL, number hal-02481891, Oct.
- Aurelio F. Bariviera & Ignasi Merediz-Sol`a, 2020, "Where do we stand in cryptocurrencies economic research? A survey based on hybrid analysis," Papers, arXiv.org, number 2003.09723, Mar.
- Saeed Nosratabadi & Amir Mosavi & Puhong Duan & Pedram Ghamisi, 2020, "Data Science in Economics," Papers, arXiv.org, number 2003.13422, Mar.
- 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 processing in times of global viral pandemic]," MPRA Paper, University Library of Munich, Germany, number 99546, Apr. - Knaus, Michael C., 2020, "Double Machine Learning Based Program Evaluation under Unconfoundedness," IZA Discussion Papers, IZA Network @ LISER, number 13051, Mar.
- Kevin Kuo & Daniel Lupton, 2020, "Towards Explainability of Machine Learning Models in Insurance Pricing," Papers, arXiv.org, number 2003.10674, Mar.
- Kyle Colangelo & Ying-Ying Lee, 2020, "Double Debiased Machine Learning Nonparametric Inference with Continuous Treatments," Papers, arXiv.org, number 2004.03036, Apr, revised Sep 2023.
- Pak, Anton & Gannon, Brenda & Staib, Andrew, 2020, "Forecasting Waiting Time to Treatment for Emergency Department Patients," OSF Preprints, Center for Open Science, number d25se, Mar, DOI: 10.31219/osf.io/d25se.
- Samir Wadhwa & Roy Dong, 2020, "Equilibrium Selection in Data Markets: Multiple-Principal, Multiple-Agent Problems with Non-Rivalrous Goods," Papers, arXiv.org, number 2004.00196, Mar, revised Mar 2023.
- Yoshizumi TOJO, 2020, "Regulation of Data Localization Measures in WTO Law (Japanese)," Discussion Papers (Japanese), Research Institute of Economy, Trade and Industry (RIETI), number 20011, Feb.
- Adriano Koshiyama & Sebastian Flennerhag & Stefano B. Blumberg & Nick Firoozye & Philip Treleaven, 2020, "QuantNet: Transferring Learning Across Systematic Trading Strategies," Papers, arXiv.org, number 2004.03445, Apr, revised Jun 2020.
- Chong, Terence Tai Leung & Li, Chen, 2020, "Search of Attention in Financial Market," MPRA Paper, University Library of Munich, Germany, number 99003, Jan.
- Xingwei Hu, 2020, "Sorting Big Data by Revealed Preference with Application to College Ranking," Papers, arXiv.org, number 2003.12198, Mar.
- Arthur Charpentier & Romuald Elie & Carl Remlinger, 2020, "Reinforcement Learning in Economics and Finance," Papers, arXiv.org, number 2003.10014, Mar.
- Noboru KAWAHAMA & Kuninobu TAKEDA, 2020, "Analyzing the Online Advertising Market from the Perspective of Competition Policy (Japanese)," Discussion Papers (Japanese), Research Institute of Economy, Trade and Industry (RIETI), number 20013, Feb.
- Oshan, Taylor M., 2020, "Potential and pitfalls of big transport data for spatial interaction models of urban mobility," OSF Preprints, Center for Open Science, number gwumt, Mar, DOI: 10.31219/osf.io/gwumt.