Report NEP-BIG-2020-07-27

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:

• Gambacorta, Leonardo & Huang, Yiping & Qiu, Han & Wang, Jingyi, 2019. "How do machine learning and non-traditional data affect credit scoring? New evidence from a Chinese fintech firm," CEPR Discussion Papers 14259, C.E.P.R. Discussion Papers.
• Roberto Molinari & Gaetan Bakalli & Stéphane Guerrier & Cesare Miglioli & Samuel Orso & O. Scaillet, 2020. "Swag: A Wrapper Method for Sparse Learning," Swiss Finance Institute Research Paper Series 20-49, Swiss Finance Institute.
• Marijn A. Bolhuis & Brett Rayner, 2020. "Deus ex Machina? A Framework for Macro Forecasting with Machine Learning," IMF Working Papers 2020/045, International Monetary Fund.
• Marijn A. Bolhuis & Brett Rayner, 2020. "The More the Merrier? A Machine Learning Algorithm for Optimal Pooling of Panel Data," IMF Working Papers 2020/044, International Monetary Fund.
• Martin, Ian & Nagel, Stefan, 2019. "Market Efficiency in the Age of Big Data," CEPR Discussion Papers 14235, C.E.P.R. Discussion Papers.
• Azar, José & Alekseeva, Liudmila & Gine, Mireia & Samila, Sampsa & Taska, Bledi, 2020. "The Demand for AI Skills in the Labor Market," CEPR Discussion Papers 14320, C.E.P.R. Discussion Papers.
• E. Ramos-P'erez & P. J. Alonso-Gonz'alez & J. J. N'u~nez-Vel'azquez, 2020. "Forecasting volatility with a stacked model based on a hybridized Artificial Neural Network," Papers 2006.16383, arXiv.org, revised Aug 2020.
• Daniel Bartl & Samuel Drapeau & Jan Obloj & Johannes Wiesel, 2020. "Sensitivity analysis of Wasserstein distributionally robust optimization problems," Papers 2006.12022, arXiv.org, revised Nov 2021.
• Susan Ariel Aaronson, 2020. "America's uneven approach to AI and its consequences," Working Papers 2020-7, The George Washington University, Institute for International Economic Policy.
• Cyrille Lenoel & Garry Young, 2020. "Real-time turning point indicators: Review of current international practices," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-05, Economic Statistics Centre of Excellence (ESCoE).
• Ali Hirsa & Weilong Fu, 2020. "An unsupervised deep learning approach in solving partial integro-differential equations," Papers 2006.15012, arXiv.org, revised Dec 2020.
• Duso, Tomaso & Argentesi, Elena & Buccirossi, Paolo & Calvano, Emilio & Marrazzo, Alessia & Nava, Salvatore, 2019. "Merger Policy in Digital Markets: An Ex-Post Assessment," CEPR Discussion Papers 14166, C.E.P.R. Discussion Papers.
• Philippe Goulet Coulombe, 2020. "The Macroeconomy as a Random Forest," Papers 2006.12724, arXiv.org, revised Mar 2021.
• Lechner, Michael & Cockx, Bart & Bollens, Joost, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," CEPR Discussion Papers 14270, C.E.P.R. Discussion Papers.
• David Zenz, 2020. "Die Vernetzung Wiens mit den Städten Europas," wiiw Statistical Reports 9, The Vienna Institute for International Economic Studies, wiiw.
• Kwadwo Osei Bonsu & Jie Song, 2020. "Turbulence on the Global Economy influenced by Artificial Intelligence and Foreign Policy Inefficiencies," Papers 2006.16911, arXiv.org.
• Giglio, Stefano & Feng, Guanhao & Xiu, Dacheng, 2020. "Taming the Factor Zoo: A Test of New Factors," CEPR Discussion Papers 14266, C.E.P.R. Discussion Papers.
• Jungsik Hwang, 2020. "Modeling Financial Time Series using LSTM with Trainable Initial Hidden States," Papers 2007.06848, arXiv.org.
• Hassan, Tarek & Hollander, Stephan & van Lent, Laurence & Tahoun, Ahmed, 2019. "The Global Impact of Brexit Uncertainty," CEPR Discussion Papers 14253, C.E.P.R. Discussion Papers.
• Jonathan Readshaw & Stefano Giani, 2020. "Using Company Specific Headlines and Convolutional Neural Networks to Predict Stock Fluctuations," Papers 2006.12426, arXiv.org.
• Jozef Barunik & Michael Ellington, 2020. "Persistence in Financial Connectedness and Systemic Risk," Papers 2007.07842, arXiv.org, revised Nov 2023.
• Pai, Mallesh & Hansen, Karsten, 2020. "Algorithmic Collusion: Supra-competitive Prices via Independent Algorithms," CEPR Discussion Papers 14372, C.E.P.R. Discussion Papers.
• Dainis Zegners & Uwe Sunde & Anthony Strittmatter, 2020. "Decisions and Performance Under Bounded Rationality: A Computational Benchmarking Approach," CESifo Working Paper Series 8341, CESifo.
• Massimo Guidolin & Manuela Pedio, 2020. "Media Attention vs. Sentiment as Drivers of Conditional Volatility Predictions: An Application to Brexit," BAFFI CAREFIN Working Papers 20145, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
• Gorshkova, Taisiya (Горшкова, Таисия) & Turuntseva, Marina (Турунцева, Марина), 2020. "Theoretical approaches to forecasting regional macro-indicators [Теоретические Подходы К Прогнозированию Региональных Макропоказателей]," Working Papers 032042, Russian Presidential Academy of National Economy and Public Administration.
• Mr. Serhan Cevik, 2020. "Where Should We Go? Internet Searches and Tourist Arrivals," IMF Working Papers 2020/022, International Monetary Fund.
• Badr Bentalha, 2020. "Big-Data and Service Supply chain management: Challenges and opportunities [Big-Data et Service Supply chain management: Challenges et opportunités]," Post-Print hal-02680861, HAL.
• Laurent Ferrara & Anna Simoni, 2020. "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage," Papers 2007.00273, arXiv.org, revised Sep 2022.
• Osório, António (António Miguel) & Pinto, Alberto Adrego, 2019. "Information, uncertainty and the manipulability of artifcial intelligence autonomous vehicles systems," Working Papers 2072/376028, Universitat Rovira i Virgili, Department of Economics.
• Mels de Zeeuw, 2020. "Opportunity Occupations and the Future of Work," Workforce Currents 2020-01, Federal Reserve Bank of Atlanta.
• Braesemann, Fabian & Stephany, Fabian, 2020. "Measuring Digital Development with Online Data: Digital Economies in Eastern Europe and Central Asia," SocArXiv f9jqh, Center for Open Science.