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Report NEP-BIG-2021-06-14
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:
- Andrea Matranga & Joan Serrat & Jonathan Hersh & Andre Groeger & Hannes Mueller, 2021, "Monitoring War Destruction from Space Using Machine Learning," Working Papers, Barcelona School of Economics, number 1257, May.
- Victor Klockmann & Alicia von Schenk & Marie Claire Villeval, 2021, "Artificial Intelligence, Ethics, and Diffused Pivotality," Working Papers, Groupe d'Analyse et de Théorie Economique Lyon St-Etienne (GATE Lyon St-Etienne), Université de Lyon, number 2111.
- Nikoleta Anesti & Eleni Kalamara & George Kapetanios, 2021, "Forecasting UK GDP growth with large survey panels," Bank of England working papers, Bank of England, number 923, May.
- Oren Barkan & Jonathan Benchimol & Itamar Caspi & Allon Hammer & Noam Koenigstein, 2021, "Forecasting CPI Inflation Components with Hierarchical Recurrent Neural Networks," Bank of Israel Working Papers, Bank of Israel, number 2021.06, Mar.
- Saide Aránzazu Salazar & Jaime Oliver Huidobro & Alvaro Ortiz & Tomasa Rodrigo & Ignacio Tamarit, 2021, "México | Patrones de consumo de efectivo vs. tarjeta: una aproximación Big Data
[Mexico | Cash vs. Card Consumption Patterns: A Machine Learning Approach]," Working Papers, BBVA Bank, Economic Research Department, number 21/05, May. - Victor Klockmann & Alicia von Schenk & Marie Claire Villeval, 2021, "Artificial Intelligence, Ethics, and Intergenerational Responsibility," Working Papers, Groupe d'Analyse et de Théorie Economique Lyon St-Etienne (GATE Lyon St-Etienne), Université de Lyon, number 2110.
- Pierre-Philippe Combes & Laurent Gobillon & Yanos Zylberberg, 2021, "Urban economics in a historical perspective: Recovering data with machine learning," PSE Working Papers, HAL, number halshs-03231786, May.
- Combes, Pierre-Philippe & Gobillon, Laurent & Zylberberg, Yanos, 2021, "Urban Economics in a Historical Perspective: Recovering Data with Machine Learning," IZA Discussion Papers, IZA Network @ LISER, number 14392, May.
- Adams-Prassl, Abigail & Boneva, Teodora & Rauh, Christopher & Golin, Marta, 2020, "Work Tasks That Can Be Done From Home: Evidence on Variation Within & Across Occupations and Industries," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 14901, Jun.
- Jing Xiao & Ron Boschma, 2021, "The emergence of Artificial Intelligence in European regions: the role of a local ICT base," Papers in Evolutionary Economic Geography (PEEG), Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, number 2117, May, revised May 2021.
- Shen, Fei & Xia, Chuanli & Yu, Wenting & Min, Chen & Wang, Tianjiao & Wu, Yi & Ye, Qianying, 2021, "The Growth of Negative Sentiment in Post-Umbrella Movement Hong Kong: Analyzing Public Opinion Online from 2017 to 2019," SocArXiv, Center for Open Science, number tnxw4, May, DOI: 10.31219/osf.io/tnxw4.
- Kazutoshi Kan, 2021, "Security Risks of Machine Learning Systems and Taxonomy Based on the Failure Mode Approach," IMES Discussion Paper Series, Institute for Monetary and Economic Studies, Bank of Japan, number 21-E-03, May.
- Shen, Fei & Xia, Chuanli & Yu, Wenting & Min, Chen & Wang, Tianjiao & Wu, Yi & Ye, Qianying, 2021, "The Ebb and Flow of Public Sentiments in Hong Kong: Analyzing Public Opinion Online from 2000 to 2017," SocArXiv, Center for Open Science, number 52zbm, May, DOI: 10.31219/osf.io/52zbm.
- Rho Caterina & Fernández Raúl & Palma Brenda, 2021, "A Sentiment-based Risk Indicator for the Mexican Financial Sector," Working Papers, Banco de México, number 2021-04, May.
- Simone Vannuccini & Ekaterina Prytkova, 2021, "Artificial Intelligence’s New Clothes? From General Purpose Technology to Large Technical System," SPRU Working Paper Series, SPRU - Science Policy Research Unit, University of Sussex Business School, number 2021-02, May.
- Tiago Cravo Oliveira Hashiguchi & Luke Slawomirski & Jillian Oderkirk, 2021, "Laying the foundations for artificial intelligence in health," OECD Health Working Papers, OECD Publishing, number 128, Jun, DOI: 10.1787/3f62817d-en.
- Mateusz Buczyński & Marcin Chlebus, 2021, "GARCHNet - Value-at-Risk forecasting with novel approach to GARCH models based on neural networks," Working Papers, Faculty of Economic Sciences, University of Warsaw, number 2021-08.
- Johann Pfitzinger, 2021, "An Interpretable Neural Network for Parameter Inference," Papers, arXiv.org, number 2106.05536, Jun.
- Koffi, Marlene, 2021, "Innovative ideas and gender inequality," CLEF Working Paper Series, Canadian Labour Economics Forum (CLEF), University of Waterloo, number 35.
- Klaus Ackermann & Sefa Awaworyi Churchill & Russell Smyth, 2021, "Mobile phone coverage and violent conflict," SoDa Laboratories Working Paper Series, Monash University, SoDa Laboratories, number 2021-06, May.
- Bart Cockx, 2021, "Comment améliorer l’efficacité des formations pour les demandeurs d’emploi grâce aux outils du Big Data ?," Regards économiques, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES), number 160, Mar, DOI: https://doi.org/10.14428/regardseco.