Report NEP-BIG-2018-10-01

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:

• Donna Feir & Rob Gillezeau & Maggie Jones, 2018. "Illuminating Indigenous Economic Development," Department Discussion Papers 1806, Department of Economics, University of Victoria.
• Nicolaas Johannes Odendaal & Monique Reid, 2018. "Media based sentiment indices as an alternative measure of consumer confidence," Working Papers 17/2018, Stellenbosch University, Department of Economics.
• Ifft, Jennifer E. & Kuhns, Ryan & Patrick, Kevin T., 2017. "Predicting Credit Demand with ARMS: A Machine Learning Approach," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258134, Agricultural and Applied Economics Association.
• Zhu, Manhong & Schmitz, Andrew & Schmitz, Troy G., "undated". "What are the Culprits Causing Obesity? A Machine Learning Approach in Variable Selection and Parameter Coefficient Inference," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 261220, Agricultural and Applied Economics Association.
• Michael Zimmert, 2018. "Efficient Difference-in-Differences Estimation with High-Dimensional Common Trend Confounding," Papers 1809.01643, arXiv.org, revised Aug 2020.
• Mabe, Queen Magadi & Lin, Wei, 2018. "Determinants of Corporate Failure: The Case of the Johannesburg Stock Exchange," MPRA Paper 88485, University Library of Munich, Germany.
• Larson, D., 2018. "The consequences of cyclone and seasonal crop risks for wealth and technology adoption in rural Mozambique," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275916, International Association of Agricultural Economists.
• Marian Gidea & Daniel Goldsmith & Yuri Katz & Pablo Roldan & Yonah Shmalo, 2018. "Topological recognition of critical transitions in time series of cryptocurrencies," Papers 1809.00695, arXiv.org.
• Lei Zhang, 2018. "Artificial Neural Network Based Chaotic Generator Design for The Prediction of Financial Time Series," Proceedings of International Academic Conferences 6409417, International Institute of Social and Economic Sciences.
• Philipp Grohs & Fabian Hornung & Arnulf Jentzen & Philippe von Wurstemberger, 2018. "A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations," Papers 1809.02362, arXiv.org, revised Jan 2023.
• Philipp Bach & Victor Chernozhukov & Martin Spindler, 2018. "Valid Simultaneous Inference in High-Dimensional Settings (with the hdm package for R)," Papers 1809.04951, arXiv.org.
• Prakhar Ganesh & Puneet Rakheja, 2018. "VLSTM: Very Long Short-Term Memory Networks for High-Frequency Trading," Papers 1809.01506, arXiv.org, revised Oct 2020.
• Anastasis Kratsios & Cody Hyndman, 2018. "NEU: A Meta-Algorithm for Universal UAP-Invariant Feature Representation," Papers 1809.00082, arXiv.org, revised May 2021.
• Crane-Droesch, Andrew, 2017. "Semiparametric Panel Data Using Neural Networks," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258128, Agricultural and Applied Economics Association.
• WATANABE Toshiya & HIRAI Yuri & AKUTSU Masami & HIOKI Tomomi & NAGAI Norihito, 2018. "Study on Management and Utilization of Data Generated from Industry (Japanese)," Discussion Papers (Japanese) 18028, Research Institute of Economy, Trade and Industry (RIETI).