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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. Stanley 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:
- 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, University Library of Munich, Germany, number 112638, Apr.
- 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, International Monetary Fund, number 2022/052, Mar.
- Leogrande, Angelo & Magaletti, Nicola & Cosoli, Gabriele & Massaro, Alessandro, 2022, "e-Government in Europe. A Machine Learning Approach," MPRA Paper, University Library of Munich, Germany, number 112242, Mar.
- Leogrande, Angelo & Magaletti, Nicola & Cosoli, Gabriele & Giardinelli, Vito & Massaro, Alessandro, 2022, "ICT Specialists in Europe," MPRA Paper, University Library of Munich, Germany, number 112241, Mar.
- Cigdem Gedikli & Robert Hill & Oleksandr Talavera & Okan Yilmaz, 2022, "The Hidden Cost of Smoking: Rent Premia in the Housing Market," Discussion Papers, Department of Economics, University of Birmingham, number 22-06, Mar.
- 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, London School of Economics and Political Science, LSE Library, number 114379, Jun.
- Ruan Pretorius & Terence van Zyl, 2022, "Deep Reinforcement Learning and Convex Mean-Variance Optimisation for Portfolio Management," Papers, arXiv.org, number 2203.11318, Feb.
- Bongers, Anelí & Molinari, Benedetto & Torres, José L., 2022, "Computers, Programming and Dynamic General Equilibrium Macroeconomic Modeling," MPRA Paper, University Library of Munich, Germany, number 112505, Mar.
- Hao Wu & David Levinson, 2022, "The Ensemble Approach to Forecasting: A Review and Synthesis," Working Papers, University of Minnesota: Nexus Research Group, number 2021-10, DOI: 10.1016/j.trc.2021.103357.
- 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, Competitive Advantage in the Global Economy (CAGE), number 612.
- Jose Antonio Leon & Mario Ordaz & Eduardo A Haddad & Inacio F. Araujo, 2022, "Riesgo Causado por la Propagacion de las Perdidas por Terremoto a traves de la Economia Mediante el uso de Modelos CGE Espaciales," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2022_11, Mar.
- 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, Victoria University, Centre of Policy Studies/IMPACT Centre, number g-326, Apr.
- 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, arXiv.org, number 2203.13001, Mar.
- 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, Center for Open Science, number f84ht, Dec, DOI: 10.31219/osf.io/f84ht.
- Rocco, Salvatore, 2022, "Implementing and managing Algorithmic Decision-Making in the public sector," SocArXiv, Center for Open Science, number ex93w, Mar, DOI: 10.31219/osf.io/ex93w.