Report NEP-CMP-2019-11-18

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:

• Aubry, Mathieu & Kräussl, Roman & Manso, Gustavo & Spaenjers, Christophe, 2019. "Machine learning, human experts, and the valuation of real assets," CFS Working Paper Series 635, Center for Financial Studies (CFS).
• Johann Pfitzinger & Nico Katzke, 2019. "A constrained hierarchical risk parity algorithm with cluster-based capital allocation," Working Papers 14/2019, Stellenbosch University, Department of Economics.
• Suss, Joel & Treitel, Henry, 2019. "Predicting bank distress in the UK with machine learning," Bank of England working papers 831, Bank of England.
• Xiao, Tim, 2018. "Incremental Risk Charge Methodology," FrenXiv 6b3hu, Center for Open Science.
• Correia, Isabel & Melo, Teresa, 2019. "Dynamic facility location problem with modular capacity adjustments under uncertainty," Technical Reports on Logistics of the Saarland Business School 17, Saarland University of Applied Sciences (htw saar), Saarland Business School.
• Marco Taboga, 2019. "Cross-country differences in the size of venture capital financing rounds: a machine learning approach," Temi di discussione (Economic working papers) 1243, Bank of Italy, Economic Research and International Relations Area.
• Veale, Michael & Binns, Reuben & Van Kleek, Max, 2018. "Some HCI Priorities for GDPR-Compliant Machine Learning," LawArXiv wm6yk, Center for Open Science.
• Kambale Kavese & Andrew Phiri, 2019. "Microsimulations of a dynamic SUT economy-wide Leontief-based model for the South African economy," Working Papers 1910, Department of Economics, Nelson Mandela University, revised Nov 2019.
• Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2019. "Factor-Driven Two-Regime Regression," Working Paper Series no128, Institute of Economic Research, Seoul National University.
• Daniel Jacob, 2019. "Group Average Treatment Effects for Observational Studies," Papers 1911.02688, arXiv.org, revised Mar 2020.
• Gogas, Periklis & Papadimitriou, Theophilos & Sofianos, Emmanouil, 2019. "Money Neutrality, Monetary Aggregates and Machine Learning," DUTH Research Papers in Economics 4-2016, Democritus University of Thrace, Department of Economics.