Report NEP-CMP-2022-04-25

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.

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Other reports in NEP-CMP

The following items were announced in this report:

• Massaro, Alessandro & Magaletti, Nicola & Giardinelli, Vito O. M. & Cosoli, Gabriele & Leogrande, Angelo & Cannone, Francesco, 2022. "Original Data Vs High Performance Augmented Data for ANN Prediction of Glycemic Status in Diabetes Patients," MPRA Paper 112638, University Library of Munich, Germany.
• Mr. Jean-Francois Dauphin & Mr. Kamil Dybczak & Morgan Maneely & Marzie Taheri Sanjani & Mrs. Nujin Suphaphiphat & Yifei Wang & Hanqi Zhang, 2022. "Nowcasting GDP - A Scalable Approach Using DFM, Machine Learning and Novel Data, Applied to European Economies," IMF Working Papers 2022/052, International Monetary Fund.
• Leogrande, Angelo & Magaletti, Nicola & Cosoli, Gabriele & Massaro, Alessandro, 2022. "e-Government in Europe. A Machine Learning Approach," MPRA Paper 112242, University Library of Munich, Germany.
• Leogrande, Angelo & Magaletti, Nicola & Cosoli, Gabriele & Giardinelli, Vito & Massaro, Alessandro, 2022. "ICT Specialists in Europe," MPRA Paper 112241, University Library of Munich, Germany.
• Cigdem Gedikli & Robert Hill & Oleksandr Talavera & Okan Yilmaz, 2022. "The Hidden Cost of Smoking: Rent Premia in the Housing Market," Discussion Papers 22-06, Department of Economics, University of Birmingham.
• Breinlich, Holger & Corradi, Valentina & Rocha, Nadia & Ruta, Michele & Silva, J.M.C. Santos & Zylkin, Tom, 2021. "Machine learning in international trade research - evaluating the impact of trade agreements," LSE Research Online Documents on Economics 114379, London School of Economics and Political Science, LSE Library.
• Ruan Pretorius & Terence van Zyl, 2022. "Deep Reinforcement Learning and Convex Mean-Variance Optimisation for Portfolio Management," Papers 2203.11318, arXiv.org.
• Bongers, Anelí & Molinari, Benedetto & Torres, José L., 2022. "Computers, Programming and Dynamic General Equilibrium Macroeconomic Modeling," MPRA Paper 112505, University Library of Munich, Germany.
• Hao Wu & David Levinson, 2022. "The Ensemble Approach to Forecasting: A Review and Synthesis," Working Papers 2021-10, University of Minnesota: Nexus Research Group.
• Abbasi, A & DiTraglia, F & Gazze, L & Pals, B, 2022. "Hidden hazards and Screening Policy: Predicting Undetected Lead Exposure in Illinois Using Machine Learning," CAGE Online Working Paper Series 612, Competitive Advantage in the Global Economy (CAGE).
• Jose Antonio Leon & Mario Ordaz & Eduardo A Haddad & Inacio F. Araujo, 2022. "Riesgo Causado por la Propagación de las Pérdidas por Terremoto a través de la Economía Mediante el uso de Modelos CGE Espaciales," Working Papers, Department of Economics 2022_11, University of São Paulo (FEA-USP).
• Catherine Taylor & Robert Waschik, 2022. "Evaluating the impact of automation in long-haul trucking using USAGE-Hwy," Centre of Policy Studies/IMPACT Centre Working Papers g-326, Victoria University, Centre of Policy Studies/IMPACT Centre.
• Karim Amzile & Rajaa Amzile, 2022. "The application of techniques derived from artificial intelligence to the prediction of the solvency of bank customers: case of the application of the cart type decision tree (dt)," Papers 2203.13001, arXiv.org.
• Otero Gomez, Daniel & Agudelo, Santiago Cartagena & Patiño, Andres Ospina & Lopez-Rojas, Edgar, 2021. "Anomaly Detection applied to Money Laundering Detecion using Ensemble Learning," OSF Preprints f84ht, Center for Open Science.
• Rocco, Salvatore, 2022. "Implementing and managing Algorithmic Decision-Making in the public sector," SocArXiv ex93w, Center for Open Science.