Report NEP-BIG-2020-05-25

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:

• Dimitris Korobilis & Davide Pettenuzzo, 2020. "Machine Learning Econometrics: Bayesian algorithms and methods," Working Papers 2020_09, Business School - Economics, University of Glasgow.
• Budzinski, Oliver & Gruésevaja, Marina & Noskova, Victoriia, 2020. "The economics of the German investigation of Facebook's data collection," Ilmenau Economics Discussion Papers 139, Ilmenau University of Technology, Institute of Economics.
• Paola Tubaro & Antonio A. Casilli & Marion Coville, 2020. "The trainer, the verifier, the imitator: Three ways in which human platform workers support artificial intelligence," Post-Print hal-02554196, HAL.
• Wallimann, Hannes & Imhof, David & Huber, Martin, 2020. "A Machine Learning Approach for Flagging Incomplete Bid-rigging Cartels," FSES Working Papers 513, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
• Nicolaj N. Mühlbach, 2020. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," CREATES Research Papers 2020-04, Department of Economics and Business Economics, Aarhus University.
• Cockx, Bart & Lechner, Michael & Bollens, Joost, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," Research Memorandum 015, Maastricht University, Graduate School of Business and Economics (GSBE).
• Cockx, Bart & Lechner, Michael & Bollens, Joost, 2020. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," ROA Research Memorandum 006, Maastricht University, Research Centre for Education and the Labour Market (ROA).
• Farbmacher, Helmut & Huber, Martin & Langen, Henrika & Spindler, Martin, 2020. "Causal mediation analysis with double machine learning," FSES Working Papers 515, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
• Schmidt, Florian Alexander, 2019. "Crowdsourced production of AI Training Data: How human workers teach self-driving cars how to see," Working Paper Forschungsförderung 155, Hans-Böckler-Stiftung, Düsseldorf.
• Rub'en Loaiza-Maya & Michael Stanley Smith & David J. Nott & Peter J. Danaher, 2020. "Fast and Accurate Variational Inference for Models with Many Latent Variables," Papers 2005.07430, arXiv.org, revised Apr 2021.
• Kaiser, Oliver S. & Malanowski, Norbert, 2019. "Smart Data und Künstliche Intelligenz: Technologie, Arbeit, Akzeptanz," Working Paper Forschungsförderung 136, Hans-Böckler-Stiftung, Düsseldorf.
• Jorge Gallego & Mounu Prem & Juan F. Vargas, 2020. "Corruption in the times of Pandemia," Documentos de Trabajo 18164, The Latin American and Caribbean Economic Association (LACEA).
• John R. J. Thompson & Longlong Feng & R. Mark Reesor & Chuck Grace, 2020. "Know Your Clients' behaviours: a cluster analysis of financial transactions," Papers 2005.03625, arXiv.org, revised May 2020.
• Carlos Cantú & Gong Cheng & Sebastian Doerr & Jon Frost & Leonardo Gambacorta, 2020. "On health and privacy: technology to combat the pandemic," BIS Bulletins 17, Bank for International Settlements.
• Michele Costola & Matteo Iacopini & Carlo R. M. A. Santagiustina, 2020. "Public Concern and the Financial Markets during the COVID-19 outbreak," Papers 2005.06796, arXiv.org.
• Daniel Borup & Bent Jesper Christensen & Nicolaj N. Mühlbach & Mikkel S. Nielsen, 2020. "Targeting predictors in random forest regression," CREATES Research Papers 2020-03, Department of Economics and Business Economics, Aarhus University.
• Milena Djourelova, 2020. "Media persuasion through slanted language: Evidence from the coverage of immigration," Economics Working Papers 1720, Department of Economics and Business, Universitat Pompeu Fabra.
• Thonipara, Anita & Sternberg, Rolf G. & Proeger, Till & Haefner, Lukas, 2020. "Assessing the Digital Divide and its Regional Determinants: Evidence from a Web-Scraping Analysis," ifh Working Papers 25/2020, Volkswirtschaftliches Institut für Mittelstand und Handwerk an der Universität Göttingen (ifh), revised 2020.