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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. 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:
- Andrew Caplin & Daniel J. Martin & Philip Marx, 2022, "Modeling Machine Learning: A Cognitive Economic Approach," NBER Working Papers, National Bureau of Economic Research, Inc, number 30600, Oct.
- Beckmeyer, Heiner & Wiedemann, Timo, 2022, "Recovering Missing Firm Characteristics with Attention-Based Machine Learning," VfS Annual Conference 2022 (Basel): Big Data in Economics, Verein für Socialpolitik / German Economic Association, number 264135.
- Lukas Gonon, 2022, "Deep neural network expressivity for optimal stopping problems," Papers, arXiv.org, number 2210.10443, Oct.
- Gallego, Jorge & Prem, Mounu & Vargas, Juan F., 2022, "Predicting Politicians' Misconduct: Evidence from Colombia," SocArXiv, Center for Open Science, number 5dp8t, Oct, DOI: 10.31219/osf.io/5dp8t.
- Daisuke Fujii & Taisuke Nakata & Takeshi Ojima, 2022, "Heterogeneous Risk Attitudes and Waves of Infection," CARF F-Series, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo, number CARF-F-546, Nov.
- Karl Naumann-Woleske & Max Sina Knicker & Michael Benzaquen & Jean-Philippe Bouchaud, 2024, "Exploration of the Parameter Space in Macroeconomic Models," Post-Print, HAL, number hal-03797418.
- Lockhart, Jeffrey W, 2022, "Gender, Sex, and the Constraints of Machine Learning Methods," SocArXiv, Center for Open Science, number zj468, Nov, DOI: 10.31219/osf.io/zj468.
- 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, arXiv.org, number 2211.00363, Nov, revised Jan 2024.
- Florenta Teodoridis & Jino Lu & Jeffrey L. Furman, 2022, "Mapping the Knowledge Space: Exploiting Unassisted Machine Learning Tools," NBER Working Papers, National Bureau of Economic Research, Inc, number 30603, Oct.
- Qiang Gao & Xinzhu Zhou & Kunpeng Zhang & Li Huang & Siyuan Liu & Fan Zhou, 2022, "Incorporating Interactive Facts for Stock Selection via Neural Recursive ODEs," Papers, arXiv.org, number 2210.15925, Oct.
- Bradrania, Reza & Pirayesh Neghab, Davood, 2021, "State-dependent asset allocation using neural networks," MPRA Paper, University Library of Munich, Germany, number 115254, Feb.
- J Gallego & M Prem & J. F. Vargas, 2022, "Predicting Politicians Misconduct: Evidence From Colombia," Documentos de Trabajo, Universidad del Rosario, number 20504, Oct.
- Kevin Kamm & Michelle Muniz, 2022, "Rating Triggers for Collateral-Inclusive XVA via Machine Learning and SDEs on Lie Groups," Papers, arXiv.org, number 2211.00326, Nov.
- Max Nendel & Alessandro Sgarabottolo, 2022, "A parametric approach to the estimation of convex risk functionals based on Wasserstein distance," Papers, arXiv.org, number 2210.14340, Oct, revised Aug 2024.
- Oecd, 2022, "Measuring the environmental impacts of artificial intelligence compute and applications: The AI footprint," OECD Digital Economy Papers, OECD Publishing, number 341, Nov, DOI: 10.1787/7babf571-en.
- Kevin Hu & Retsef Levi & Raphael Yahalom & El Ghali Zerhouni, 2022, "Supply Chain Characteristics as Predictors of Cyber Risk: A Machine-Learning Assessment," Papers, arXiv.org, number 2210.15785, Oct, 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, arXiv.org, number 2210.15969, Oct.
- 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, Federal Reserve Bank of Atlanta, number 2022-16, Nov, DOI: 10.29338/wp2022-16.
- Régis MARODON & Jean-Baptiste Jacouton & Adeline LAULANIE, 2022, "The Proof is in the Pudding. Revealing the SDGs with Artificial Intelligence," Working Paper, Agence française de développement, number 85f81dba-c8e2-4255-878a-0, Oct.
- Michele Battisti & Ilpo Kauppinen & Britta Rude, 2022, "Twitter and Crime: The Effect of Social Movements on GenderBased Violence," ifo Working Paper Series, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 381.
- 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, Tinbergen Institute, number 22-077/V, Nov.
- Hilmar, Till & Paolillo, Rocco & Sachweh, Patrick, 2022, "Contagious economic failure? Discourses around “zombie firms” in Covid-19 ridden Germany and Italy," SocArXiv, Center for Open Science, number wypmf, Nov, DOI: 10.31219/osf.io/wypmf.