Report NEP-BIG-2019-02-04

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:

• Artem Kochnev, 2019. "Dying Light: War and Trade of the Separatist-Controlled Areas of Ukraine," wiiw Working Papers 161, The Vienna Institute for International Economic Studies, wiiw.
• Hollenbeck, Brett, 2018. "Online Reputation Mechanisms and the Decreasing Value of Chain Affliation," MPRA Paper 91573, University Library of Munich, Germany.
• Kinne, Jan & Lenz, David, 2019. "Predicting innovative firms using web mining and deep learning," ZEW Discussion Papers 19-001, ZEW - Leibniz Centre for European Economic Research.
• Blanka Horvath & Aitor Muguruza & Mehdi Tomas, 2019. "Deep Learning Volatility," Papers 1901.09647, arXiv.org, revised Aug 2019.
• Dylan J. Foster & Vasilis Syrgkanis, 2019. "Orthogonal Statistical Learning," Papers 1901.09036, arXiv.org, revised Jun 2023.
• Nikolaos Passalis & Anastasios Tefas & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data," Papers 1901.08280, arXiv.org.
• Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2019. "lassopack: Model selection and prediction with regularized regression in Stata," Papers 1901.05397, arXiv.org.
• Lechner, Michael, 2018. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," IZA Discussion Papers 12040, Institute of Labor Economics (IZA).