Report NEP-CMP-2023-03-27

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:

• Nikhil Malik & Emaad Manzoor, 2023. "Does Machine Learning Amplify Pricing Errors in the Housing Market? -- The Economics of Machine Learning Feedback Loops," Papers 2302.09438, arXiv.org.
• Maudud Hassan Uzzal & Robert Ślepaczuk, 2023. "The performance of time series forecasting based on classical and machine learning methods for S&P 500 index," Working Papers 2023-05, Faculty of Economic Sciences, University of Warsaw.
• Sharma, Rahul, 2021. "The Effects of Artificial Intelligence on the World as a Whole from an Economic Perspective," MPRA Paper 116596, University Library of Munich, Germany.
• Ivan Guo & Nicolas Langren'e & Jiahao Wu, 2023. "Simultaneous upper and lower bounds of American-style option prices with hedging via neural networks," Papers 2302.12439, arXiv.org, revised Nov 2024.
• Martin Vesely, 2023. "Finding the Optimal Currency Composition of Foreign Exchange Reserves with a Quantum Computer," Working Papers 2023/1, Czech National Bank.
• Philippe Goulet Coulombe, 2021. "The Macroeconomy as a Random Forest," Working Papers 21-05, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
• Lorena Torres Lahoz & Francisco Camara Pereira & Georges Sfeir & Ioanna Arkoudi & Mayara Moraes Monteiro & Carlos Lima Azevedo, 2023. "Attitudes and Latent Class Choice Models using Machine learning," Papers 2302.09871, arXiv.org.
• Arun Kumar Polala & Bernhard Hientzsch, 2023. "Parametric Differential Machine Learning for Pricing and Calibration," Papers 2302.06682, arXiv.org, revised Feb 2023.
• Deniz Preil & Michael Krapp, 2023. "Genetic multi-armed bandits: a reinforcement learning approach for discrete optimization via simulation," Papers 2302.07695, arXiv.org.
• Francis X. Diebold & Maximilian Gobel & Philippe Goulet Coulombe, 2022. "Assessing and Comparing Fixed-Target Forecasts of Arctic Sea Ice: Glide Charts for Feature-Engineered Linear Regression and Machine Learning Models," Working Papers 22-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
• Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
• Shubhranshu Shekhar & Jetson Leder-Luis & Leman Akoglu, 2023. "Unsupervised Machine Learning for Explainable Health Care Fraud Detection," NBER Working Papers 30946, National Bureau of Economic Research, Inc.
• Alper Deniz Karakas, 2023. "Reevaluating the Taylor Rule with Machine Learning," Papers 2302.08323, arXiv.org.
• James Bell, 2023. "The global economic impact of AI technologies in the fight against financial crime," Papers 2302.13823, arXiv.org.
• Ganesh Iyer & T. Tony Ke, 2023. "Competitive Model Selection in Algorithmic Targeting," NBER Working Papers 31002, National Bureau of Economic Research, Inc.
• Daas, Piet & Hassink, Wolter & Klijs, Bart, 2023. "On the Validity of Using Webpage Texts to Identify the Target Population of a Survey: An Application to Detect Online Platforms," IZA Discussion Papers 15941, Institute of Labor Economics (IZA).
• Mckay Jensen & Nicholas Emery-Xu & Robert Trager, 2023. "Industrial Policy for Advanced AI: Compute Pricing and the Safety Tax," Papers 2302.11436, arXiv.org.
• Tom, Daniel, 2021. "Logistic Regression Collaborating with AI Beam Search," MPRA Paper 116592, University Library of Munich, Germany, revised 04 Mar 2023.
• Laura Nurski, 2023. "Artificial intelligence adoption in the public sector- a case study," Working Papers node_8829, Bruegel.
• Philipp Adammer & Jan Pruser & Rainer Schussler, 2023. "Forecasting Macroeconomic Tail Risk in Real Time: Do Textual Data Add Value?," Papers 2302.13999, arXiv.org, revised May 2024.
• Vasilis Syrgkanis & Ruohan Zhan, 2023. "Post Reinforcement Learning Inference," Papers 2302.08854, arXiv.org, revised May 2024.