Printed from https://ideas.repec.org/n/nep-big/2021-03-01.html
Report NEP-BIG-2021-03-01
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:
- Cristina Angelico & Juri Marcucci & Marcello Miccoli & Filippo Quarta, 2021, "Can we measure inflation expectations using Twitter?," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area, number 1318, Feb.
- Strittmatter, Anthony & Wunsch, Conny, 2021, "The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?," Working papers, Faculty of Business and Economics - University of Basel, number 2021/05.
- McBride, Linden & Barrett, Christopher B. & Browne, Christopher & Hu, Leiqiu & Liu, Yanyan & Matteson, David S. & Sun, Ying & Wen, Jiaming, 2021, "Predicting poverty and malnutrition for targeting, mapping, monitoring, and early warning," 2021 Allied Social Sciences Association (ASSA) Annual Meeting (Virtual), January 3-5, 2021, San Diego, California, Agricultural and Applied Economics Association, number 309060, Jan, DOI: 10.22004/ag.econ.309060.
- Jean-Franc{c}ois Chassagneux & Junchao Chen & Noufel Frikha & Chao Zhou, 2021, "A learning scheme by sparse grids and Picard approximations for semilinear parabolic PDEs," Papers, arXiv.org, number 2102.12051, Feb.
- Luisa Roa & Andr'es Rodr'iguez-Rey & Alejandro Correa-Bahnsen & Carlos Valencia, 2021, "Supporting Financial Inclusion with Graph Machine Learning and Super-App Alternative Data," Papers, arXiv.org, number 2102.09974, Feb.
- Carlos Arana, 2021, "Modelos de Aprendizaje Automático Mediante Árboles de Decisión," CEMA Working Papers: Serie Documentos de Trabajo., Universidad del CEMA, number 778, Feb.
- Steven J. Davis & Stephen Hansen & Cristhian Seminario-Amez, 2020, "Firm-Level Risk Exposures and Stock Returns in the Wake of COVID-19," Working Papers, Becker Friedman Institute for Research In Economics, number 2020-139.
- Karaman Örsal, Deniz Dilan & Sturm, Silke, 2021, "Computing Consumer Sentiment in Germany via Social Media Data," Hamburg Discussion Papers in International Economics, University of Hamburg, Department of Economics, number 7.
- Jeffrey Grogger & Sean Gupta & Ria Ivandic & Tom Kirchmaier, 2021, "Comparing Conventional and Machine-Learning Approaches to Risk Assessment in Domestic Abuse Cases," Working Papers, Becker Friedman Institute for Research In Economics, number 2021-01.
- Zhiguo He & Jing Huang & Jidong Zhou, 2020, "Open Banking: Credit Market Competition When Borrowers Own the Data," Working Papers, Becker Friedman Institute for Research In Economics, number 2020-168.
- Zhen Zeng & Tucker Balch & Manuela Veloso, 2021, "Deep Video Prediction for Time Series Forecasting," Papers, arXiv.org, number 2102.12061, Feb, revised Nov 2021.
- Aina Gallego & Nikolas Schöll & Gaël Le Mens, 2021, "Politician-Citizen Interactions and Dynamic Representation: Evidence from Twitter," Working Papers, Barcelona School of Economics, number 1238, Feb.
- Aina Gallego & Nikolas Schöll & Gaël Le Mens, 2021, "Politician-citizen interactions and dynamic representation: Evidence from Twitter," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra, number 1769, Jan.
- Bandiera, Oriana & Prat, Andrea & Hansen, Stephen & Sadun, Raffaella, 2020, "CEO behavior and firm performance," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 101423, Apr.
- Müller, Henrik & Hornig, Nico & Rieger, Jonas, 2021, ""For the times they are a-changin": Gauging Uncertainty Perception over Time," DoCMA Working Papers, TU Dortmund University, Dortmund Center for Data-based Media Analysis (DoCMA), number 3, DOI: 10.17877/DE290R-21878.
- Ferman, Bruno & Lima, Lycia & Riva, Flávio, 2021, "Artificial Intelligence, Teacher Tasks and Individualized Pedagogy," SocArXiv, Center for Open Science, number qw249, Feb, DOI: 10.31219/osf.io/qw249.
- Graef, Inge & Prüfer, Jens, 2021, "Governance of Data Sharing : A Law & Economics Proposal," Discussion Paper, Tilburg University, Tilburg Law and Economic Center, number 2021-001.
- Bernard Fallery, 2020, "Données de santé : l'arbre StopCovid qui cache la forêt Health Data Hub," Post-Print, HAL, number hal-03125892, May.