Report NEP-CMP-2023-11-20

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:

• Ioannis Nasios & Konstantinos Vogklis, 2023. "Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series," Papers 2310.13029, arXiv.org.
• Emmet Hall-Hoffarth, 2023. "Non-linear approximations of DSGE models with neural-networks and hard-constraints," Papers 2310.13436, arXiv.org.
• Patrick Rehill & Nicholas Biddle, 2023. "Transparency challenges in policy evaluation with causal machine learning -- improving usability and accountability," Papers 2310.13240, arXiv.org, revised Mar 2024.
• Xin Du & Kai Moriyama & Kumiko Tanaka-Ishii, 2023. "Co-Training Realized Volatility Prediction Model with Neural Distributional Transformation," Papers 2310.14536, arXiv.org.
• Nicolás Forteza & Sandra García-Uribe, 2023. "A Score Function to Prioritize Editing in Household Survey Data: A Machine Learning Approach," Working Papers 2330, Banco de España.
• Jakob Kozak & Maximilian Nagl & Cathrine Nagl & Eli Beracha & Wolfgang Schäfers, 2023. "Determinants of U.S. REIT Bond Risk Premia with Explainable Machine Learning," ERES eres2023_146, European Real Estate Society (ERES).
• Juan Tenorio & Wilder Pérez, 2023. "GDP nowcasting with Machine Learning and Unstructured Data to Peru," Working Papers 197, Peruvian Economic Association.
• Nino Paulus & Lukas Lautenschlaeger & Wolfgang Schäfers, 2023. "Social Media and Real Estate: Do Twitter users predict REIT performance?," ERES eres2023_200, European Real Estate Society (ERES).
• Edson Pindza & Jules Clement Mba & Sutene Mwambi & Nneka Umeorah, 2023. "Neural Network for valuing Bitcoin options under jump-diffusion and market sentiment model," Papers 2310.09622, arXiv.org.
• George Loewenstein & Zachary Wojtowicz, 2023. "The Economics of Attention," CESifo Working Paper Series 10712, CESifo.
• Giovanni Compiani & Ilya Morozov & Stephan Seiler, 2023. "Demand Estimation with Text and Image Data," CESifo Working Paper Series 10695, CESifo.
• Kristina McElheran & J. Frank Li & Erik Brynjolfsson & Zachary Kroff & Emin Dinlersoz & Lucia S. Foster & Nikolas Zolas, 2023. "AI Adoption in America: Who, What, and Where," NBER Working Papers 31788, National Bureau of Economic Research, Inc.
• Eric Ghysels & Jack Morgan & Hamed Mohammadbagherpoor, 2023. "Quantum Computational Algorithms for Derivative Pricing and Credit Risk in a Regime Switching Economy," Papers 2311.00825, arXiv.org.
• Michael Barnett & William Brock & Lars Peter Hansen & Ruimeng Hu & Joseph Huang, 2023. "A Deep Learning Analysis of Climate Change, Innovation, and Uncertainty," Papers 2310.13200, arXiv.org.
• Conor B. Hamill & Raad Khraishi & Simona Gherghel & Jerrard Lawrence & Salvatore Mercuri & Ramin Okhrati & Greig A. Cowan, 2023. "Agent-based Modelling of Credit Card Promotions," Papers 2311.01901, arXiv.org, revised Nov 2023.
• Anubha Goel & Puneet Pasricha & Juho Kanniainen, 2023. "Sparse Index Tracking via Topological Learning," Papers 2310.09578, arXiv.org.
• Thomas R. Cook & Nathan M. Palmer, 2023. "Understanding Models and Model Bias with Gaussian Processes," Research Working Paper RWP 23-07, Federal Reserve Bank of Kansas City.
• Julia Hatamyar & Noemi Kreif & Rudi Rocha & Martin Huber, 2023. "Machine Learning for Staggered Difference-in-Differences and Dynamic Treatment Effect Heterogeneity," Papers 2310.11962, arXiv.org.
• Joshua Rosaler & Dhruv Desai & Bhaskarjit Sarmah & Dimitrios Vamvourellis & Deran Onay & Dhagash Mehta & Stefano Pasquali, 2023. "Enhanced Local Explainability and Trust Scores with Random Forest Proximities," Papers 2310.12428, arXiv.org, revised Aug 2024.
• Giulio Cornelli & Jon Frost & Saurabh Mishra, 2023. "Artificial intelligence, services globalisation and income inequality," BIS Working Papers 1135, Bank for International Settlements.
• Jean-Marie John-Mathews, 2022. "Some critical and ethical perspectives on the empirical turn of AI interpretability," Post-Print hal-03395823, HAL.
• Harouna Kinda & Abrams M.E. Tagem, 2023. "Double taxation treaties and resource revenue mobilization in developing countries: A neural network approach," WIDER Working Paper Series wp-2023-125, World Institute for Development Economic Research (UNU-WIDER).
• Xu Yang & Xiao Yang & Weiqing Liu & Jinhui Li & Peng Yu & Zeqi Ye & Jiang Bian, 2023. "Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle," Papers 2310.11249, arXiv.org.
• Gaetan de Rassenfosse & Adam Jaffe & Melissa Wasserman, 2023. "AI-Generated Inventions: Implications for the Patent System," Working Papers 22, Chair of Science, Technology, and Innovation Policy.
• Sukwoong Choi & William S. Moses & Neil Thompson, 2023. "The Quantum Tortoise and the Classical Hare: A simple framework for understanding which problems quantum computing will accelerate (and which it will not)," Papers 2310.15505, arXiv.org.
• Bhaskarjit Sarmah & Tianjie Zhu & Dhagash Mehta & Stefano Pasquali, 2023. "Towards reducing hallucination in extracting information from financial reports using Large Language Models," Papers 2310.10760, arXiv.org.