Report NEP-BIG-2019-09-02
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.Subscribe to this report: email, RSS, or Mastodon.
Other reports in NEP-BIG
The following items were announced in this report:
- Bertin Martens & Songul Tolan, 2018. "Will this time be different? A review of the literature on the Impact of Artificial Intelligence on Employment, Incomes and Growth," JRC Working Papers on Digital Economy 2018-08, Joint Research Centre.
- Morelli, Massimo & Gennaro, Gloria & Lecce, Giampaolo, 2019. "Intertemporal Evidence on the Strategy of Populism," CEPR Discussion Papers 13804, C.E.P.R. Discussion Papers.
- Attia, Tarek M., 2019. "Challenges and Opportunities in the Future Applications of IoT Technology," 2nd Europe – Middle East – North African Regional ITS Conference, Aswan 2019: Leveraging Technologies For Growth 201752, International Telecommunications Society (ITS).
- Bertin Martens, 2018. "The impact of data access regimes on artificial intelligence and machine learning," JRC Working Papers on Digital Economy 2018-09, Joint Research Centre.
- Lisa-Cheree Martin, 2019. "Machine Learning vs Traditional Forecasting Methods: An Application to South African GDP," Working Papers 12/2019, Stellenbosch University, Department of Economics.
- Blattman, Christopher & Dube, Oeindrila & Bazzi, Samuel & Gudgeon, Matthew & Peck, Richard & Blair, Robert, 2019. "The Promise and Pitfalls of Conflict Prediction: Evidence from Colombia and Indonesia," CEPR Discussion Papers 13829, C.E.P.R. Discussion Papers.
- Mossad, Omar S. & ElNainay, Mustafa & Torki, Marwan, 2019. "Modulations Recognition using Deep Neural Network in Wireless Communications," 2nd Europe – Middle East – North African Regional ITS Conference, Aswan 2019: Leveraging Technologies For Growth 201750, International Telecommunications Society (ITS).
- David Byrd & Tucker Hybinette Balch, 2019. "Intra-day Equity Price Prediction using Deep Learning as a Measure of Market Efficiency," Papers 1908.08168, arXiv.org.
- Goller, Daniel & Lechner, Michael & Moczall, Andreas & Wolff, Joachim, 2019. "Does the estimation of the propensity score by machine learning improve matching estimation? The case of Germany’s programmes for long term unemployed," Economics Working Paper Series 1910, University of St. Gallen, School of Economics and Political Science.
- Christian Bayer & Blanka Horvath & Aitor Muguruza & Benjamin Stemper & Mehdi Tomas, 2019. "On deep calibration of (rough) stochastic volatility models," Papers 1908.08806, arXiv.org.
- Songul Tolan, 2018. "Fair and Unbiased Algorithmic Decision Making: Current State and Future Challenges," JRC Working Papers on Digital Economy 2018-10, Joint Research Centre.
- Jingyuan Wang & Yang Zhang & Ke Tang & Junjie Wu & Zhang Xiong, 2019. "AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks," Papers 1908.02646, arXiv.org.
- Károly Szóka & Brigitta Kovács, 2019. "Process orientation in the modern controlling," Proceedings of Business and Management Conferences 9211706, International Institute of Social and Economic Sciences.
- Michael Zimmert & Michael Lechner, 2019. "Nonparametric estimation of causal heterogeneity under high-dimensional confounding," Papers 1908.08779, arXiv.org.
- Victor Chernozhukov & Whitney Newey & Vira Semenova, 2019. "Welfare Analysis in Dynamic Models," Papers 1908.09173, arXiv.org, revised Nov 2024.
- Abdel Ghafar, Ahmed Ismail & Vazquez Castro, Ágeles & Essam Khedr, Mohamed, 2019. "Multidimensional Self-Organizing Chord-Based Networking for Internet of Things," 2nd Europe – Middle East – North African Regional ITS Conference, Aswan 2019: Leveraging Technologies For Growth 201736, International Telecommunications Society (ITS).
- Stephan B. Bruns & Alessio Moneta & David I. Stern, 2019. "Estimating the Economy-Wide Rebound Effect Using Empirically Identified Structural Vector Autoregressions," LEM Papers Series 2019/27, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
- Manel Hamdi & Walid Chkili, 2019. "An artificial neural network augmented GARCH model for Islamic stock market volatility: Do asymmetry and long memory matter?," Working Papers 13, Economic Research Forum, revised 21 Aug 2019.
- Mark Weber & Giacomo Domeniconi & Jie Chen & Daniel Karl I. Weidele & Claudio Bellei & Tom Robinson & Charles E. Leiserson, 2019. "Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics," Papers 1908.02591, arXiv.org.
- Lotfi Boudabsa & Damir Filipović, 2019. "Machine Learning With Kernels for Portfolio Valuation and Risk Management," Swiss Finance Institute Research Paper Series 19-34, Swiss Finance Institute.
- Albanesi, Stefania & Vamossy, Domonkos, 2019. "Predicting Consumer Default: A Deep Learning Approach," CEPR Discussion Papers 13914, C.E.P.R. Discussion Papers.
- Stephany, Fabian & Lorenz, Hanno, 2019. "Back to the Future - Changing Job Profiles in the Digital Age," EconStor Preprints 202035, ZBW - Leibniz Information Centre for Economics.
- Stefania Albanesi & Domonkos F. Vamossy, 2019. "Predicting Consumer Default: A Deep Learning Approach," NBER Working Papers 26165, National Bureau of Economic Research, Inc.
- Seán Kennedy, 2019. "The potential of tax microdata for tax policy," OECD Taxation Working Papers 45, OECD Publishing.
- TAMURA Suguru, 2019. "Results of a survey on standardization activities: Japanese institutions' standardization activities in 2017 (Implementation, knowledge source, organizational structure, and interest to artificial int," Policy Discussion Papers 19013, Research Institute of Economy, Trade and Industry (RIETI).