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Report NEP-BIG-2021-03-08
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:
- Tom Coupé, 2021, "Who is the Most Sought-After Economist? Ranking Economists Using Google Trends," Working Papers in Economics, University of Canterbury, Department of Economics and Finance, number 21/02, Feb.
- Manu García & J. Ignacio Conde-Ruiz & Luis A. Puch & Juan-José Ganuza, 2021, "Gender Distribution across Topics in Top 5 Economics Journals: A Machine Learning Approach," Working Papers, Barcelona School of Economics, number 1241, Mar.
- Philippe Goulet Coulombe & Massimiliano Marcellino & Dalibor Stevanovic, 2021, "Can Machine Learning Catch the COVID-19 Recession?," CIRANO Working Papers, CIRANO, number 2021s-09, Mar.
- Strittmatter, Anthony & Wunsch, Conny, 2021, "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," IZA Discussion Papers, IZA Network @ LISER, number 14128, Feb.
- Alexandre Bonnet R. Costa & Pedro Cavalcanti G. Ferreira & Wagner P. Gaglianone & Osmani Teixeira C. Guillén & João Victor Issler & Yihao Lin, 2021, "Machine Learning and Oil Price Point and Density Forecasting," Working Papers Series, Central Bank of Brazil, Research Department, number 544, Feb.
- Michael Danquah & Abdul Malik Iddrisu & Ernest Owusu Boakye & Solomon Owusu, 2021, "Do gender wage differences within households influence women's empowerment and welfare?: Evidence from Ghana," WIDER Working Paper Series, World Institute for Development Economic Research (UNU-WIDER), number wp-2021-40.
- Gründler, Klaus & Krieger, Tommy, 2021, "Using machine learning for measuring democracy: An update," ZEW Discussion Papers, ZEW - Leibniz Centre for European Economic Research, number 21-012.
- Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2021, "Investor Confidence and Forecastability of US Stock Market Realized Volatility : Evidence from Machine Learning," Working Papers, University of Pretoria, Department of Economics, number 202118, Feb.
- Alessandro Bitetto & Paola Cerchiello & Stefano Filomeni & Alessandra Tanda & Barbara Tarantino, 2021, "Machine Learning and Credit Risk: Empirical Evidence from SMEs," DEM Working Papers Series, University of Pavia, Department of Economics and Management, number 201, Feb.
- Cécile Godé & Amandine Pascal, 2021, "Big (Et) Data Dans Toute Sa Complexite," Post-Print, HAL, number hal-03134526, Feb, DOI: 10.36863/mds.a.15696.
- Jacob, Daniel, 2020, "Cross-Fitting and Averaging for Machine Learning Estimation of Heterogeneous Treatment Effects," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2020-014.
- Maria Dimakopoulou & Zhimei Ren & Zhengyuan Zhou, 2021, "Online Multi-Armed Bandits with Adaptive Inference," Papers, arXiv.org, number 2102.13202, Feb, revised Jun 2021.
- Marcelle Chauvet & Rafael R. S. Guimaraes, 2021, "Transfer Learning for Business Cycle Identification," Working Papers Series, Central Bank of Brazil, Research Department, number 545, Feb.
- Abhiroop Mukherjee & George Panayotov & Janghoon Shon, 2019, "Eye in the sky: private satellites and government macro data," HKUST IEMS Working Paper Series, HKUST Institute for Emerging Market Studies, number 2019-68, Oct, revised Oct 2019.
- Craja, Patricia & Kim, Alisa & Lessmann, Stefan, 2020, "Deep Learning application for fraud detection in financial statements," IRTG 1792 Discussion Papers, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", number 2020-007.
- Alexis Marchal, 2021, "Risk & Returns around Fomc Press Conferences: A Novel Perspective from Computer Vision," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 21-18, Mar.
- Andrea Fronzetti Colladon & Stefano Grassi & Francesco Ravazzolo & Francesco Violante, 2021, "Forecasting financial markets with semantic network analysis in the COVID—19 crisis," Working Papers, Center for Research in Economics and Statistics, number 2021-06, Mar.
- Graef, Inge & Prüfer, Jens, 2021, "Governance of Data Sharing : a Law & Economics Proposal," Discussion Paper, Tilburg University, Center for Economic Research, number 2021-004.
- Massimo Ferrari & Frederik Kurcz & Maria Sole Pagliari, 2021, "Do Words Hurt More Than Actions? The Impact of Trade Tensions on Financial Markets," Working papers, Banque de France, number 802.