Report NEP-BIG-2021-05-10

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 & Amstad, Marlene & He, Chao & XIA, Fan Dora, 2021. "Trade sentiment and the stock market: new evidence based on big data textual analysis of Chinese media," CEPR Discussion Papers 15682, C.E.P.R. Discussion Papers.
• Qingfeng Liu & Yang Feng, 2021. "Machine Collaboration," Papers 2105.02569, arXiv.org, revised Feb 2024.
• Martin Huber & Jonas Meier & Hannes Wallimann, 2021. "Business analytics meets artificial intelligence: Assessing the demand effects of discounts on Swiss train tickets," Papers 2105.01426, arXiv.org, revised Jun 2022.
• David Imhof & Hannes Wallimann, 2021. "Detecting bid-rigging coalitions in different countries and auction formats," Papers 2105.00337, arXiv.org.
• Nekoei, Arash & Sinn, Fabian, 2021. "Human Biographical Record (HBR)," CEPR Discussion Papers 15825, C.E.P.R. Discussion Papers.
• Riccardo Aiolfi & Nicola Moreni & Marco Bianchetti & Marco Scaringi & Filippo Fogliani, 2021. "Learning Bermudans," Papers 2105.00655, arXiv.org.
• Yusuke Narita & Kohei Yata, 2021. "Algorithm is Experiment: Machine Learning, Market Design, and Policy Eligibility Rules," Cowles Foundation Discussion Papers 2283, Cowles Foundation for Research in Economics, Yale University.
• Wunsch, Conny & Strittmatter, Anthony, 2021. "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," CEPR Discussion Papers 15840, C.E.P.R. Discussion Papers.
• Navid Mottaghi & Sara Farhangdoost, 2021. "Stock Price Forecasting in Presence of Covid-19 Pandemic and Evaluating Performances of Machine Learning Models for Time-Series Forecasting," Papers 2105.02785, arXiv.org.
• Yusuke Narita & Kohei Yata, 2021. "Algorithm is Experiment: Machine Learning, Market Design, and Policy Eligibility Rules," Working Papers 2021-022, Human Capital and Economic Opportunity Working Group.
• Victor Chernozhukov & Whitney K. Newey & Victor Quintas-Martinez & Vasilis Syrgkanis, 2021. "Automatic Debiased Machine Learning via Riesz Regression," Papers 2104.14737, arXiv.org, revised Mar 2024.
• Rovetta, Alessandro, 2021. "The Impact of COVID-19 on Conspiracy Attitudes and Risk Perception in Italy: an Infodemiological Survey through Google Trends," SocArXiv 83f9g, Center for Open Science.
• Gorodnichenko, Yuriy & Maliar, Serguei & Naubert, Christopher, 2020. "Household Savings and Monetary Policy under Individual and Aggregate Stochastic Volatility," CEPR Discussion Papers 15614, C.E.P.R. Discussion Papers.
• Wilson, Thomas & Grossman, Irina & Alexander, Monica & Rees, Philip & Temple, Jeromey, 2021. "Methods for small area population forecasts: state-of-the-art and research needs," SocArXiv sp6me, Center for Open Science.
• Jayachandran, Seema & Biradavolu, Monica & Cooper, Jan, 2021. "Using machine learning and qualitative interviews to design a five-question women's agency index," CEPR Discussion Papers 15961, C.E.P.R. Discussion Papers.
• Marcellino, Massimiliano & Stevanovic, Dalibor & Goulet Coulombe, Philippe, 2021. "Can Machine Learning Catch the COVID-19 Recession?," CEPR Discussion Papers 15867, C.E.P.R. Discussion Papers.
• Qiutong Guo & Shun Lei & Qing Ye & Zhiyang Fang, 2021. "MRC-LSTM: A Hybrid Approach of Multi-scale Residual CNN and LSTM to Predict Bitcoin Price," Papers 2105.00707, arXiv.org.
• Kulkarni, Shruti, 2020. "Using Machine Learning to Analyze Climate Change Technology Transfer (CCTT)," SocArXiv zyb3j, Center for Open Science.
• Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Machine-Learning Approach," Economics working papers 2021-08, Department of Economics, Johannes Kepler University Linz, Austria.
• Montserrat Lopez-Cobo & Riccardo Righi & Sofia Samoili & Miguel Vazquez-Prada Baillet & Melisande Cardona & Giuditta De-Prato, 2021. "AI Watch Index. Policy relevant dimensions to assess Europe’s performance in artificial intelligence," JRC Research Reports JRC124424, Joint Research Centre.
• Wehrheim, Lino & Jopp, Tobias Alexander & Spoerer, Mark, 2021. "Turn, turn, turn: A digital history of German historiography, 1950-2019," Working Papers 31, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
• Gorodnichenko, Yuriy & Pham, Tho & Talavera, Oleksandr, 2021. "The Voice of Monetary Policy," CEPR Discussion Papers 15932, C.E.P.R. Discussion Papers.
• Lenza, Michele & Cimadomo, Jacopo & Giannone, Domenico & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
• Korinek, Anton & Stiglitz, Joseph, 2021. "Artificial Intelligence, Globalization, and Strategies for Economic Development," CEPR Discussion Papers 15772, C.E.P.R. Discussion Papers.