Report NEP-CMP-2023-07-17

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:

• Zihan Chen & Lei Nico Zheng & Cheng Lu & Jialu Yuan & Di Zhu, 2023. "ChatGPT Informed Graph Neural Network for Stock Movement Prediction," Papers 2306.03763, arXiv.org, revised Sep 2023.
• Hendriks, Patrick & Sturm, Timo & Olt, Christian M. & Buxmann, Peter, 2023. "The Impact of Human-Artificial Intelligence Partnerships on Organizational Learning," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 138376, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Vetter, Oliver A. & Mehler, Maren F. & Buxmann, Peter, 2023. "As Much Art as Science - Examining the Realization of Business Models Driven by Machine Learning Through a Dynamic Capabilities Perspective," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 138319, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• von Schenk, Alicia & Klockmann, Victor & Bonnefon, Jean-François & Rahwan, Iyad & Köbis, Nils, 2023. "Lie-detection algorithms attract few users but vastly increase accusation rates," TSE Working Papers 23-1448, Toulouse School of Economics (TSE).
• von Schenk, Alicia & Klockmann, Victor & Bonnefon, Jean-François & Rahwan, Iyad & Köbis, Nils, 2023. "Lie-detection algorithms attract few users but vastly increase accusation rates," IAST Working Papers 23-155, Institute for Advanced Study in Toulouse (IAST).
• Dylan Brewer & Alyssa Carlson, 2023. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2310, Department of Economics, University of Missouri.
• Item repec:ags:aaea22:335782 is not listed on IDEAS anymore

• Shadi Haj-Yahia & Omar Mansour & Tomer Toledo, 2023. "Incorporating Domain Knowledge in Deep Neural Networks for Discrete Choice Models," Papers 2306.00016, arXiv.org.
• Jan-Peter Kucklick & Jennifer Priefer & Daniel Beverungen & Oliver Müller, 2023. "Elucidating the Predictive Power of Search and Experience Qualities for Pricing of Complex Goods – A Machine Learning-based Study on Real Estate Appraisal," Working Papers Dissertations 112, Paderborn University, Faculty of Business Administration and Economics.
• Item repec:ags:aaea22:335809 is not listed on IDEAS anymore

• Michael Cafarella & Gabriel Ehrlich & Tian Gao & John C. Haltiwanger & Matthew D. Shapiro & Laura Zhao, 2023. "Using Machine Learning to Construct Hedonic Price Indices," NBER Working Papers 31315, National Bureau of Economic Research, Inc.
• Philippe Goulet Coulombe & Maximilian Goebel, 2023. "Maximally Machine-Learnable Portfolios," Papers 2306.05568, arXiv.org, revised Apr 2024.
• Julián Alonso Cárdenas-Cárdenas & Deicy J. Cristiano-Botia & Nicolás Martínez-Cortés, 2023. "Colombian inflation forecast using Long Short-Term Memory approach," Borradores de Economia 1241, Banco de la Republica de Colombia.
• Lorenzo Bretscher & Jesús Fernández-Villaverde & Simon Scheidegger, 2023. "Ricardian Business Cycles," Swiss Finance Institute Research Paper Series 23-43, Swiss Finance Institute.
• Jesús Fernández-Villaverde & Isaiah J. Hull, 2023. "Dynamic Programming on a Quantum Annealer: Solving the RBC Model," NBER Working Papers 31326, National Bureau of Economic Research, Inc.
• Ilias Chronopoulos & Katerina Chrysikou & George Kapetanios & James Mitchell & Aristeidis Raftapostolos, 2023. "Deep Neural Network Estimation in Panel Data Models," Papers 2305.19921, arXiv.org.
• Mukherjee, Krishnendu, 2023. "Layer: An Alternative Approach To Solve Large Capacitated Vehicle Routing Problem with Time Window Using AI and Exact Method," MPRA Paper 117513, University Library of Munich, Germany, revised 12 Jun 2023.
• Mehler, Maren F. & Vetter, Oliver A., 2023. "How Much Are Machine Assistants Worth? Willingness to Pay for Machine Learning-Based Software Testing," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 138317, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Severin Reissl & Alessandro Caiani & Francesco Lamperti & Mattia Guerini & Fabio Vanni & Giorgio Fagiolo & Tommaso Ferraresi & Leonardo Ghezzi & Mauro Napoletano & Andrea Roventini, 2021. "Assessing the Economic Impact of Lockdowns in Italy: A Computational Input-Output Approach," SciencePo Working papers Main hal-04103906, HAL.
• Zazueta, Jorge & Zazueta-Hernández, Jorge & Heredia, Andrea Chavez, 2023. "Support Vector Machines and Bankruptcy Prediction," SocArXiv 7z24k, Center for Open Science.
• Jiti Gao & Fei Liu & Bin Peng & Yanrong Yang, 2023. "Localized Neural Network Modelling of Time Series: A Case Study on US Monetary Policy," Papers 2306.05593, arXiv.org, revised Jul 2024.
• Andor, Mark Andreas & Bernstein, David H. & Parmeter, Christopher F. & Sommer, Stephan, 2023. "Internal meta-analysis for Monte Carlo simulations," Ruhr Economic Papers 997, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
• Andrea Borsato & Andre Lorentz, 2023. "Open Science vs. Mission-oriented Policies and the Long-run Dynamics of Integrated Economies: An Agent-based Model with a Kaldorian Flavour," Working Papers of BETA 2023-17, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
• Marica Valente & Timm Gries & Lorenzo Trapani, 2023. "Informal employment from migration shocks," Working Papers 2023-09, Faculty of Economics and Statistics, Universität Innsbruck.
• Simon Hirsch & Florian Ziel, 2023. "Multivariate Simulation-based Forecasting for Intraday Power Markets: Modelling Cross-Product Price Effects," Papers 2306.13419, arXiv.org.