Report NEP-CMP-2020-05-25

This is the archive for NEP-CMP, a report on new working papers in the area of Computational Economics. Stan Miles issued this report. It is usually issued weekly.

Subscribe to this report: email, RSS, or Mastodon, or Bluesky.

Other reports in NEP-CMP

The following items were announced in this report:

• Lilit Popoyan & Mauro Napoletano & Andrea Roventini, 2020. "Winter is possibly not coming: Mitigating financial instability in an agent-based model with interbank market," Documents de Travail de l'OFCE 2020-14, Observatoire Francais des Conjonctures Economiques (OFCE).
• 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.
• Dimitris Korobilis & Davide Pettenuzzo, 2020. "Machine Learning Econometrics: Bayesian algorithms and methods," Working Papers 2020_09, Business School - Economics, University of Glasgow.
• Spiegel, Alisa & Severini, Simone & Britz, Wolfgang & Coletta, Attilio, 2020. "Step-by-step development of a model simulating returns on farm from investments: the example of hazelnut plantation in Italy," Discussion Papers 303668, University of Bonn, Institute for Food and Resource Economics.
• 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.
• Emir Zunic & Kemal Korjenic & Kerim Hodzic & Dzenana Donko, 2020. "Application of Facebook's Prophet Algorithm for Successful Sales Forecasting Based on Real-world Data," Papers 2005.07575, arXiv.org.
• 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.
• Gary Koop & Dimitris Korobilis, 2020. "Bayesian dynamic variable selection in high dimensions," Working Papers 2020_11, Business School - Economics, University of Glasgow.
• 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.
• 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.
• 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.
• Ikuya Takao & Shota Chikayama & Takashi Kaburagi & Satoshi Kumagai & Toshiyuki Matsumoto & Yosuke Kurihara, 2020. "After fall motion discrimination system using autoencoder," Proceedings of International Academic Conferences 10012518, International Institute of Social and Economic Sciences.
• 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).
• Antoine Bozio & Simon Rabaté & Audrey Rain & Maxime Tô, 2019. "How should a points pension system be managed?," PSE-Ecole d'économie de Paris (Postprint) halshs-02516413, HAL.