Report NEP-CMP-2024-01-01

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:

• Parth Daxesh Modi & Kamyar Arshi & Pertami J. Kunz & Abdelhak M. Zoubir, 2023. "A Data-driven Deep Learning Approach for Bitcoin Price Forecasting," Papers 2311.06280, arXiv.org.
• Stempel, Daniel & Zahner, Johannes, 2023. "Whose Inflation Rates Matter Most? A DSGE Model and Machine Learning Approach to Monetary Policy in the Euro Area," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277627, Verein für Socialpolitik / German Economic Association.
• Khaled AlAjmi & Jose Deodoro & Mr. Ashraf Khan & Kei Moriya, 2023. "Predicting the Law: Artificial Intelligence Findings from the IMF’s Central Bank Legislation Database," IMF Working Papers 2023/241, International Monetary Fund.
• Holtemöller, Oliver & Kozyrev, Boris, 2023. "Forecasting Economic Activity with a Neural Network in Uncertain Times: Monte Carlo Evidence and Application to German GDP," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277688, Verein für Socialpolitik / German Economic Association.
• Ksenia E. Chistyakova & Tatiana B. Kazakova, 2023. "Grammar In Language Models: Bert Study," HSE Working papers WP BRP 115/LNG/2023, National Research University Higher School of Economics.
• Chaohua Dong & Jiti Gao & Bin Peng & Yayi Yan, 2023. "Estimation of Semiparametric Multi-Index Models Using Deep Neural Networks," Monash Econometrics and Business Statistics Working Papers 21/23, Monash University, Department of Econometrics and Business Statistics.
• Yuxi Heluo & Kexin Wang & Charles W. Robson, 2023. "Do we listen to what we are told? An empirical study on human behaviour during the COVID-19 pandemic: neural networks vs. regression analysis," Papers 2311.13046, arXiv.org.
• Jose E. Gomez-Gonzalez & Jorge M. Uribe & Oscar M. Valencia, 2023. "Sovereign Risk and Economic Complexity: Machine Learning Insights on Causality and Prediction," IREA Working Papers 202315, University of Barcelona, Research Institute of Applied Economics, revised Nov 2023.
• Antoine Jacquier & Oleksiy Kondratyev & Gordon Lee & Mugad Oumgari, 2023. "Quantum Computing for Financial Mathematics," Papers 2311.06621, arXiv.org.
• Thomas Chalaux & David Turner, 2023. "Doombot: a machine learning algorithm for predicting downturns in OECD countries," OECD Economics Department Working Papers 1780, OECD Publishing.
• Osman, Adam & Speer, Jamin D., 2023. "Stigma and Take-up of Labor Market Assistance: Evidence from Two Field Experiments," IZA Discussion Papers 16599, Institute of Labor Economics (IZA).