Report NEP-BIG-2019-06-17

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:

• Lukas Ryll & Sebastian Seidens, 2019. "Evaluating the Performance of Machine Learning Algorithms in Financial Market Forecasting: A Comprehensive Survey," Papers 1906.07786, arXiv.org, revised Jul 2019.
• Martin Obschonka & David B. Audretsch, 2019. "Artificial Intelligence and Big Data in Entrepreneurship: A New Era Has Begun," Papers 1906.00553, arXiv.org.
• Ehrlich, Maximilian V. & Hilber, Christian A. L. & Schöni, Olivier, 2018. "Institutional settings and urban sprawl: evidence from Europe," LSE Research Online Documents on Economics 86364, London School of Economics and Political Science, LSE Library.
• KEIDA Masayuki & TAKEDA Yosuke, 2019. "The Art of Central Bank Communication: A Topic Analysis on Words used by the Bank of Japan's Governors," Discussion papers 19038, Research Institute of Economy, Trade and Industry (RIETI).
• Majid Bazarbash, 2019. "FinTech in Financial Inclusion: Machine Learning Applications in Assessing Credit Risk," IMF Working Papers 19/109, International Monetary Fund.
• Di Wang & Qi Wu & Wen Zhang, 2019. "Neural Learning of Online Consumer Credit Risk," Papers 1906.01923, arXiv.org.
• Mueller, Hannes & Rauh, Christopher, 2019. "The Hard Problem of Prediction for Conflict Prevention," CEPR Discussion Papers 13748, C.E.P.R. Discussion Papers.
• Shanka Subhra Mondal & Sharada Prasanna Mohanty & Benjamin Harlander & Mehmet Koseoglu & Lance Rane & Kirill Romanov & Wei-Kai Liu & Pranoot Hatwar & Marcel Salathe & Joe Byrum, 2019. "Investment Ranking Challenge: Identifying the best performing stocks based on their semi-annual returns," Papers 1906.08636, arXiv.org.
• Xue Guo & Hu Zhang & Tianhai Tian, 2019. "Multi-Likelihood Methods for Developing Stock Relationship Networks Using Financial Big Data," Papers 1906.08088, arXiv.org.
• IKEUCHI Kenta & MOTOHASHI Kazuyuki, 2019. "Linkage of Patent and Design Right Data: Analysis of Industrial Design Activities in Companies at the Creator Level (Japanese)," Discussion Papers (Japanese) 19017, Research Institute of Economy, Trade and Industry (RIETI).
• Andrew Bennett & Nathan Kallus & Tobias Schnabel, 2019. "Deep Generalized Method of Moments for Instrumental Variable Analysis," Papers 1905.12495, arXiv.org, revised Apr 2020.
• Rob Donnelly & Francisco R. Ruiz & David Blei & Susan Athey, 2019. "Counterfactual Inference for Consumer Choice Across Many Product Categories," Papers 1906.02635, arXiv.org, revised Aug 2023.
• Marcin Hołda, 2019. "Newspaper-based economic uncertainty indices for Poland," NBP Working Papers 310, Narodowy Bank Polski.
• Martin Labaj & Daniel Dujava, 2019. "Economic growth and convergence during the transition to production using automation capital," Department of Economic Policy Working Paper Series 017, Department of Economic Policy, Faculty of National Economy, University of Economics in Bratislava.
• Bertani, Filippo & Ponta, Linda & Raberto, Marco & Teglio, Andrea & Cincotti, Silvano, 2019. "An economy under the digital transformation," MPRA Paper 94205, University Library of Munich, Germany.
• Goller, Daniel & Krumer, Alex, 2019. "Let’s meet as usual: Do games on non-frequent days differ? Evidence from top European soccer leagues," Economics Working Paper Series 1907, University of St. Gallen, School of Economics and Political Science.
• Isphording, Ingo E. & Raabe, Tobias, 2019. "Early Identification of College Dropouts Using Machine-Learning: Conceptual Considerations and an Empirical Example," IZA Research Reports 89, Institute of Labor Economics (IZA).
• Svitlana Vyetrenko & Shaojie Xu, 2019. "Risk-Sensitive Compact Decision Trees for Autonomous Execution in Presence of Simulated Market Response," Papers 1906.02312, arXiv.org, revised Jan 2021.