Report NEP-CMP-2022-11-28

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:

• Andrew Caplin & Daniel J. Martin & Philip Marx, 2022. "Modeling Machine Learning: A Cognitive Economic Approach," NBER Working Papers 30600, National Bureau of Economic Research, Inc.
• Beckmeyer, Heiner & Wiedemann, Timo, 2022. "Recovering Missing Firm Characteristics with Attention-Based Machine Learning," VfS Annual Conference 2022 (Basel): Big Data in Economics 264135, Verein für Socialpolitik / German Economic Association.
• Lukas Gonon, 2022. "Deep neural network expressivity for optimal stopping problems," Papers 2210.10443, arXiv.org.
• Gallego, Jorge & Prem, Mounu & Vargas, Juan F., 2022. "Predicting Politicians' Misconduct: Evidence from Colombia," SocArXiv 5dp8t, Center for Open Science.
• Daisuke Fujii & Taisuke Nakata & Takeshi Ojima, 2022. "Heterogeneous Risk Attitudes and Waves of Infection," CARF F-Series CARF-F-546, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
• Karl Naumann-Woleske & Max Sina Knicker & Michael Benzaquen & Jean-Philippe Bouchaud, 2022. "Exploration of the Parameter Space in Macroeconomic Models," Post-Print hal-03797418, HAL.
• Lockhart, Jeffrey W, 2022. "Gender, Sex, and the Constraints of Machine Learning Methods," SocArXiv zj468, Center for Open Science.
• Giovanni Ballarin & Petros Dellaportas & Lyudmila Grigoryeva & Marcel Hirt & Sophie van Huellen & Juan-Pablo Ortega, 2022. "Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data," Papers 2211.00363, arXiv.org, revised Jan 2024.
• Florenta Teodoridis & Jino Lu & Jeffrey L. Furman, 2022. "Mapping the Knowledge Space: Exploiting Unassisted Machine Learning Tools," NBER Working Papers 30603, National Bureau of Economic Research, Inc.
• Qiang Gao & Xinzhu Zhou & Kunpeng Zhang & Li Huang & Siyuan Liu & Fan Zhou, 2022. "Incorporating Interactive Facts for Stock Selection via Neural Recursive ODEs," Papers 2210.15925, arXiv.org.
• Bradrania, Reza & Pirayesh Neghab, Davood, 2021. "State-dependent asset allocation using neural networks," MPRA Paper 115254, University Library of Munich, Germany.
• Gallego, J & Prem, M & Vargas, J. F., 2022. "Predicting Politicians Misconduct: Evidence From Colombia," Documentos de Trabajo 20504, Universidad del Rosario.
• Kevin Kamm & Michelle Muniz, 2022. "Rating Triggers for Collateral-Inclusive XVA via Machine Learning and SDEs on Lie Groups," Papers 2211.00326, arXiv.org.
• Max Nendel & Alessandro Sgarabottolo, 2022. "A parametric approach to the estimation of convex risk functionals based on Wasserstein distance," Papers 2210.14340, arXiv.org, revised Aug 2024.
• Oecd, 2022. "Measuring the environmental impacts of artificial intelligence compute and applications: The AI footprint," OECD Digital Economy Papers 341, OECD Publishing.
• Kevin Hu & Retsef Levi & Raphael Yahalom & El Ghali Zerhouni, 2022. "Supply Chain Characteristics as Predictors of Cyber Risk: A Machine-Learning Assessment," Papers 2210.15785, arXiv.org, revised Nov 2023.
• Geon Lee & Tae-Kyoung Kim & Hyun-Gyoon Kim & Jeonggyu Huh, 2022. "Newton Raphson Emulation Network for Highly Efficient Computation of Numerous Implied Volatilities," Papers 2210.15969, arXiv.org.
• Daniel Borup & Philippe Goulet Coulombe & Erik Christian Montes Schütte & David E. Rapach & Sander Schwenk-Nebbe, 2022. "The Anatomy of Out-of-Sample Forecasting Accuracy," FRB Atlanta Working Paper 2022-16, Federal Reserve Bank of Atlanta.
• Régis MARODON & Jean-Baptiste Jacouton & Adeline LAULANIE, 2022. "The Proof is in the Pudding. Revealing the SDGs with Artificial Intelligence," Working Paper 85f81dba-c8e2-4255-878a-0, Agence française de développement.
• Michele Battisti & Ilpo Kauppinen & Britta Rude, 2022. "Twitter and Crime: The Effect of Social Movements on GenderBased Violence," ifo Working Paper Series 381, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
• Henri Bussink & Bas ter Weel, 2022. "Costs and benefits of an Individual Learning Account (ILA): A simulation analysis for the Netherlands," Tinbergen Institute Discussion Papers 22-077/V, Tinbergen Institute.
• Hilmar, Till & Paolillo, Rocco & Sachweh, Patrick, 2022. "Contagious economic failure? Discourses around “zombie firms” in Covid-19 ridden Germany and Italy," SocArXiv wypmf, Center for Open Science.