Printed from https://ideas.repec.org/n/nep-big/2020-02-10.html
Report NEP-BIG-2020-02-10
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:
- Sidra Mehtab & Jaydip Sen, 2020, "Stock Price Prediction Using Convolutional Neural Networks on a Multivariate Timeseries," Papers, arXiv.org, number 2001.09769, Jan.
- D. Desbois, 2019, "Tax dredger on social networks: new learning algorithms to track fraud
[Drague fiscale sur les réseaux sociaux : de nouveaux algorithmes d’apprentissage pour traquer la fraude]," Post-Print, HAL, number hal-02406386, Dec. - Wheeler, Andrew Palmer & Steenbeek, Wouter, 2020, "Mapping the risk terrain for crime using machine learning," SocArXiv, Center for Open Science, number xc538, Jan, DOI: 10.31219/osf.io/xc538.
- Krüger, Miriam & Kinne, Jan & Lenz, David & Resch, Bernd, 2020, "The digital layer: How innovative firms relate on the web," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 20-003.
- Patrick Gagliardini & Hao Ma, 2019, "Extracting Statistical Factors When Betas are Time-Varying," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-65, Jul.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018, "Economic Predictions with Big Data: The Illusion of Sparsity," Liberty Street Economics, Federal Reserve Bank of New York, number 20180521, May.
- Moore, Phoebe V., 2019, "The mirror for (artificial) intelligence: Working in whose reflection?," Discussion Papers, Research Group Globalization, Work, and Production, WZB Berlin Social Science Center, number SP III 2019-302.
- Item repec:hal:wpaper:hal-02423632 is not listed on IDEAS anymore
- Ian Martin & Stefan Nagel, 2019, "Market Efficiency in the Age of Big Data," CESifo Working Paper Series, CESifo, number 8015.
- Axenbeck, Janna & Breithaupt, Patrick, 2019, "Web-based innovation indicators: Which firm website characteristics relate to firm-level innovation activity?," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 19-063.
- Jaqueson K. Galimberti, 2020, "Forecasting GDP growth from outer space," Working Papers, Auckland University of Technology, Department of Economics, number 2020-02, Feb.
- Item repec:hal:wpaper:hal-02422378 is not listed on IDEAS anymore
- Jörg Claussen & Christian Peukert & Ananya Sen, 2019, "The Editor vs. the Algorithm: Returns to Data and Externalities in Online News," CESifo Working Paper Series, CESifo, number 8012.
- Tine Van Calster & Filip Van den Bossche & Bart Baesens & Wilfried Lemahieu, 2020, "Profit-oriented sales forecasting: a comparison of forecasting techniques from a business perspective," Papers, arXiv.org, number 2002.00949, Feb.
- Jeffrey Clemens & Parker Rogers, 2020, "Demand Shocks, Procurement Policies, and the Nature of Medical Innovation: Evidence from Wartime Prosthetic Device Patents," NBER Working Papers, National Bureau of Economic Research, Inc, number 26679, Jan.
- Susan C. Athey & Kevin A. Bryan & Joshua S. Gans, 2020, "The Allocation of Decision Authority to Human and Artificial Intelligence," NBER Working Papers, National Bureau of Economic Research, Inc, number 26673, Jan.
- Yufang Wang & Haiyan Wang, 2020, "Using Networks and Partial Differential Equations to Predict Bitcoin Price," Papers, arXiv.org, number 2001.03099, Jan.
- Boeing, Geoff, 2020, "Urban Street Network Analysis in a Computational Notebook," SocArXiv, Center for Open Science, number dxtq3, Jan, DOI: 10.31219/osf.io/dxtq3.
- PREZIOSI Nadir & FAKO Peter & HRISTOV Hristo & JONKERS Koen & GOENAGA BELDARRAIN Xabier & ALVES DIAS Patricia & AMOROSO Sara & ANNONI Alessandro & ASENSIO BERMEJO Jose Miguel & BELLIA Mario & BLAGOEVA, 2019, "China: Challenges and Prospects from an Industrial and Innovation Powerhouse," JRC Research Reports, Joint Research Centre, number JRC116516, May.
- Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2020, "Forecasting Realized Volatility of Bitcoin: The Role of the Trade War," Working Papers, University of Pretoria, Department of Economics, number 202003, Jan.
- Yafei Han & Francisco Camara Pereira & Moshe Ben-Akiva & Christopher Zegras, 2020, "A Neural-embedded Choice Model: TasteNet-MNL Modeling Taste Heterogeneity with Flexibility and Interpretability," Papers, arXiv.org, number 2002.00922, Feb, revised Jul 2022.
- Griffin, Greg Phillip & Mulhall, Megan & Simek, Chris & Riggs, William W., 2020, "Mitigating Bias in Big Data for Transportation," SocArXiv, Center for Open Science, number trbv9, Jan, DOI: 10.31219/osf.io/trbv9.
- Zhengkun Li & Minh-Ngoc Tran & Chao Wang & Richard Gerlach & Junbin Gao, 2020, "A Bayesian Long Short-Term Memory Model for Value at Risk and Expected Shortfall Joint Forecasting," Papers, arXiv.org, number 2001.08374, Jan, revised May 2021.
- Christoph Engel & Rima Maria Rahal, 2020, "What the Judge Argues is Not What the Judge Thinks - Eye Tracking Evidence about the Normative Weight of Conflicting Concerns in a Torts Case," Discussion Paper Series of the Max Planck Institute for Behavioral Economics, Max Planck Institute for Behavioral Economics, number 2020_03, Jan, revised 01 Mar 2021.
- Hans Buehler & Lukas Gonon & Josef Teichmann & Ben Wood & Baranidharan Mohan & Jonathan Kochems, 2019, "Deep Hedging: Hedging Derivatives Under Generic Market Frictions Using Reinforcement Learning," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 19-80, May.
- Timo Klein, 2020, "Event Studies in Merger Analysis: Review and an Application Using U.S. TNIC Data," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 20-005/VII, Jan, revised 31 Mar 2020.
- Leland Bybee & Bryan T. Kelly & Asaf Manela & Dacheng Xiu, 2020, "The Structure of Economic News," NBER Working Papers, National Bureau of Economic Research, Inc, number 26648, Jan.