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Report NEP-BIG-2018-07-16
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:
- Peter Tillmann & Andreas Walter, 2018, "ECB vs Bundesbank: Diverging Tones and Policy Effectiveness," MAGKS Papers on Economics, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung), number 201820.
- Jos'e Igor Morlanes, 2018, "Non-linear Time Series and Artificial Neural Networks of Red Hat Volatility," Papers, arXiv.org, number 1806.01070, Jun.
- Papaioannou, Elias & Chiovelli, Giorgio & Michalopoulos, Stelios, 2018, "Landmines and Spatial Development," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 13021, Jun.
- Carlos Pedro Gonc{c}alves, 2018, "Financial Risk and Returns Prediction with Modular Networked Learning," Papers, arXiv.org, number 1806.05876, Jun.
- Nariyasu YAMAZAWA, 2018, "Analyzing Business Conditions by Quantitative Text Analysis–Time Series Analysis Using Appearance Rate and Principal Component," ESRI Discussion paper series, Economic and Social Research Institute (ESRI), number 345, Mar.
- Greg Kirczenow & Ali Fathi & Matt Davison, 2018, "Machine Learning for Yield Curve Feature Extraction: Application to Illiquid Corporate Bonds (Preliminary Draft)," Papers, arXiv.org, number 1806.01731, Jun.
- Akash Malhotra, 2018, "A hybrid econometric-machine learning approach for relative importance analysis: Prioritizing food policy," Papers, arXiv.org, number 1806.04517, Jun, revised Aug 2020.
- Gary Koop & Stuart McIntyre & James Mitchell, 2018, "UK Regional Nowcasting using a Mixed Frequency Vector Autoregressive Model," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers, Economic Statistics Centre of Excellence (ESCoE), number ESCoE DP-2018-07, Jun.
- Miruna Oprescu & Vasilis Syrgkanis & Zhiwei Steven Wu, 2018, "Orthogonal Random Forest for Causal Inference," Papers, arXiv.org, number 1806.03467, Jun, revised Sep 2019.
- Guilhem Fabre, 2018, "China's digital transformation. Why is artificial intelligence a priority for chinese R&D?
[La transformation numérique de la Chine : pourquoi l'intelligence artificielle est-elle devenue une priorité de la recherche et le développement chinoise ?," Working Papers, HAL, number halshs-01818508, Jun. - Zhan Gao & Zhentao Shi, 2018, "Implementing Convex Optimization in R: Two Econometric Examples," Papers, arXiv.org, number 1806.10423, Jun, revised Aug 2019.
- Tadas Limba & Aurimas Šidlauskas, 2018, "Secure personal data administration in the social networks: the case of voluntary sharing of personal data on the Facebook," Post-Print, HAL, number hal-01773973, Mar, DOI: 10.9770/jesi.2018.5.3(9).
- Ash, Elliott & Chen, Daniel L., 2018, "Mapping the Geometry of Law using Document Embeddings," IAST Working Papers, Institute for Advanced Study in Toulouse (IAST), number 18-77, Jul.
- Ash, Elliott & Chen, Daniel L., 2018, "Mapping the Geometry of Law using Document Embeddings," TSE Working Papers, Toulouse School of Economics (TSE), number 18-935, Jul.
- Benjamin W. Pugsley & Peter Sedlacek & Vincent Sterk, 2018, "The Nature of Firm Growth," Working Papers, Center for Economic Studies, U.S. Census Bureau, number 18-30, Jun.