Report NEP-BIG-2021-10-04

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:

• Nguyen, Phong Thanh, 2020. "Application Machine Learning in Construction Management," MPRA Paper 109899, University Library of Munich, Germany, revised 01 Aug 2021.
• Bali, Turan G. & Beckmeyer, Heiner & Moerke, Mathis & Weigert, Florian, 2021. "Option return predictability with machine learning and big data," CFR Working Papers 21-08, University of Cologne, Centre for Financial Research (CFR).
• Xingzuo Zhou & Yiang Li, 2021. "Forecasting the COVID-19 vaccine uptake rate: An infodemiological study in the US," Papers 2109.13971, arXiv.org, revised Dec 2021.
• Eduardo Ramos-P'erez & Pablo J. Alonso-Gonz'alez & Jos'e Javier N'u~nez-Vel'azquez, 2021. "Multi-Transformer: A New Neural Network-Based Architecture for Forecasting S&P Volatility," Papers 2109.12621, arXiv.org.
• Roland Tricot, 2021. "Venture capital investments in artificial intelligence: Analysing trends in VC in AI companies from 2012 through 2020," OECD Digital Economy Papers 319, OECD Publishing.
• Fatime Barbara Hegyi & Manran Zhu & Milan Janosov, 2021. "Measuring the Impact of Urban Innovation Districts," JRC Research Reports JRC125559, Joint Research Centre.
• Gharad T. Bryan & Dean Karlan & Adam Osman, 2021. "Big Loans to Small Businesses: Predicting Winners and Losers in an Entrepreneurial Lending Experiment," NBER Working Papers 29311, National Bureau of Economic Research, Inc.
• Ioanna Arkoudi & Carlos Lima Azevedo & Francisco C. Pereira, 2021. "Combining Discrete Choice Models and Neural Networks through Embeddings: Formulation, Interpretability and Performance," Papers 2109.12042, arXiv.org, revised Sep 2021.
• Angell, Mintaka & Gold, Samantha & Hastings, Justine S. & Howison, Mark & Jensen, Scott & Keleher, Niall & Molitor, Daniel & Roberts, Amelia, 2021. "Estimating value-added returns to labor training programs with causal machine learning," OSF Preprints thg23, Center for Open Science.
• Pengzhou Wu & Kenji Fukumizu, 2021. "Towards Principled Causal Effect Estimation by Deep Identifiable Models," Papers 2109.15062, arXiv.org, revised Nov 2021.
• Genz, Sabrina & Gregory, Terry & Janser, Markus & Lehmer, Florian & Matthes, Britta, 2021. "How do workers adjust when firms adopt new technologies?," ZEW Discussion Papers 21-073, ZEW - Leibniz Centre for European Economic Research.
• Jaeyoung Cheong & Heejoon Lee & Minjung Kang, 2021. "Stock Index Prediction using Cointegration test and Quantile Loss," Papers 2109.15045, arXiv.org.
• Olubusoye, Olusanya E & Akintande, Olalekan J. & Yaya, OlaOluwa S. & Ogbonna, Ahamuefula & Adenikinju, Adeola F., 2021. "Energy Pricing during the COVID-19 Pandemic: Predictive Information-Based Uncertainty Indexes with Machine Learning Algorithm," MPRA Paper 109838, University Library of Munich, Germany.
• Nicolas Gavoille & Anna Zasova, 2021. "What we pay in the shadow: Labor tax evasion, minimum wage hike and employment," Working Papers CEB 21-017, ULB -- Universite Libre de Bruxelles.
• Shuo Sun & Rundong Wang & Bo An, 2021. "Reinforcement Learning for Quantitative Trading," Papers 2109.13851, arXiv.org.
• Nicolas Gavoille & Anna Zasova, 2021. "What we pay in the shadows: Labor tax evasion, minimum wage hike and employment," SSE Riga/BICEPS Research Papers 6, Baltic International Centre for Economic Policy Studies (BICEPS);Stockholm School of Economics in Riga (SSE Riga).
• Kea BARET, 2021. "Fiscal rules’ compliance and Social Welfare," Working Papers of BETA 2021-38, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
• Wurm, Daniel & Zielinski, Oliver & Lübben, Neeske & Jansen, Maike & Ramesohl, Stephan, 2021. "Wege in eine ökologische Machine Economy: Wir brauchen eine 'Grüne Governance der Machine Economy', um das Zusammenspiel von Internet of Things, Künstlicher Intelligenz und Distributed Ledger Technolo," Wuppertal Reports 22, Wuppertal Institute for Climate, Environment and Energy.
• Claude Crampes & Yassine Lefouili, 2021. "Green energy pricing for digital europe," Post-Print hal-03352748, HAL.
• Pedro Garcia-del-Bario & J. James Reade, 2021. "Does Certainty on the Winner Diminish the Interest in Sport Competitions? The Case of Formula One," Economics Discussion Papers em-dp2021-18, Department of Economics, University of Reading.
• Hélia Costa & Giuseppe Nicoletti & Mauro Pisu & Christina von Rueden, 2021. "Welcome to the (digital) jungle: Measuring online platform diffusion," OECD Economics Department Working Papers 1683, OECD Publishing.
• G. Mazzei & F. G. Bellora & J. A. Serur, 2021. "Delta Hedging with Transaction Costs: Dynamic Multiscale Strategy using Neural Nets," Papers 2109.12337, arXiv.org.
• Prem, Mounu & Purroy, Miguel E. & Vargas, Juan F., 2021. "Landmines: The Local Effects of Demining," SocArXiv 3jzk6, Center for Open Science.
• Chongwoo Choe & Jiajia Cong & Chengsi Wang, 2021. "Softening Competition through Unilateral Sharing of Customer Data," Monash Economics Working Papers 2021-10, Monash University, Department of Economics.