Report NEP-CMP-2016-04-04This 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.
The following items were announced in this report:
- Ghosh, Diptesh, "undated". "Comparing Genetic Algorithm Crossover and Mutation Operators for the Indexing Problem," IIMA Working Papers WP2016-03-29, Indian Institute of Management Ahmedabad, Research and Publication Department.
- Jochen Lüdering & Peter Winker, 2016. "Forward or Backward Looking? The Economic Discourse and the Observed Reality," MAGKS Papers on Economics 201607, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
- Foster, John & Wagner, Liam & Liebman, Ariel, 2015. "Modelling the Electricity and Natural Gas Sectors for the Future Grid: Developing Co-Optimisation Platforms for Market Redesign," MPRA Paper 70114, University Library of Munich, Germany.
- Britz, Wolfgang & Drud, Arne & van der Mensbrugghe, Dominique, 2015. "Reducing unwanted consequences of aggregation in large-scale economic models - a systematic empirical evaluation with the GTAP model," Discussion Papers 232876, University of Bonn, Institute for Food and Resource Economics.
- Goldsmith-Pinkham, Paul & Hirtle, Beverly & Lucca, David O., 2016. "Parsing the content of bank supervision," Staff Reports 770, Federal Reserve Bank of New York.
- Cardaci, Alberto & Saraceno, Francesco, 2016. "Inequality, Financialisation and Credit Booms - a Model of Two Crises," SEP Working Papers 2016/2, LUISS School of European Political Economy.
- Viktor Pirmana & Armida Alisjahbana & Irlan Adiyatma Rum, 2015. "Boosting National Infrastructure Investment in West Java: An Analysis Using TERM CGE Model," Working Papers in Economics and Development Studies (WoPEDS) 201507, Department of Economics, Padjadjaran University, revised Dec 2015.
- Samuel R\"onnqvist & Peter Sarlin, 2016. "Bank distress in the news: Describing events through deep learning," Papers 1603.05670, arXiv.org, revised Dec 2016.