Report NEP-CMP-2020-11-02

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.

Other reports in NEP-CMP

The following items were announced in this report:

• Mellacher, Patrick, 2020. "COVID-Town: An Integrated Economic-Epidemiological Agent-Based Model," MPRA Paper 103661, University Library of Munich, Germany.
• João Amador & Tiago Alves, 2020. "Assessing the Scoreboard of the EU Macroeconomic Imbalances Procedure: (Machine) Learning from Decisions," Working Papers w202016, Banco de Portugal, Economics and Research Department.
• Harmenberg, Karl, 2020. "Aggregating Heterogeneous-Agent Models with Permanent Income Shocks," Working Papers 13-2020, Copenhagen Business School, Department of Economics.
• Nosratabadi, Saeed & Mosavi, Amir & Duan, Puhong & Ghamisi, Pedram & Filip, Ferdinand & Band, Shahab S. & Reuter, Uwe & Gama, Joao & Gandomi, Amir H., 2020. "Data science in economics: comprehensive review of advanced machine learning and deep learning methods," SocArXiv 9vdwf, Center for Open Science.
• Martin Spielauer & Thomas Horvath & Marian Fink & Gemma Abio & Guadalupe Souto Nieves & Concepció Patxot & Tanja Istenič, 2020. "microWELT: Microsimulation Projection of Indicators of the Economic Effects of Population Ageing Based on Disaggregated National Transfer Accounts," WIFO Working Papers 612, WIFO.
• Eric Benhamou & David Saltiel & Sandrine Ungari & Abhishek Mukhopadhyay & Jamal Atif, 2020. "AAMDRL: Augmented Asset Management with Deep Reinforcement Learning," Papers 2010.08497, arXiv.org.
• Martin Spielauer & Thomas Horvath & Walter Hyll & Marian Fink, 2020. "microWELT: Socio-Demographic Parameters and Projections for Austria, Spain, Finland, and the UK," WIFO Working Papers 611, WIFO.
• Roland Hodler & Michael Lechner & Paul A. Raschky, 2020. "Reassessing the Resource Curse using Causal Machine Learning," SoDa Laboratories Working Paper Series 2020-01, Monash University, SoDa Laboratories.