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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. 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:
- Ioannis Nasios & Konstantinos Vogklis, 2023, "Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series," Papers, arXiv.org, number 2310.13029, Oct.
- Emmet Hall-Hoffarth, 2023, "Non-linear approximations of DSGE models with neural-networks and hard-constraints," Papers, arXiv.org, number 2310.13436, Oct.
- Patrick Rehill & Nicholas Biddle, 2023, "Transparency challenges in policy evaluation with causal machine learning -- improving usability and accountability," Papers, arXiv.org, number 2310.13240, Oct, revised Mar 2024.
- Xin Du & Kai Moriyama & Kumiko Tanaka-Ishii, 2023, "Co-Training Realized Volatility Prediction Model with Neural Distributional Transformation," Papers, arXiv.org, number 2310.14536, Oct.
- Nicolás Forteza & Sandra García-Uribe, 2023, "A Score Function to Prioritize Editing in Household Survey Data: A Machine Learning Approach," Working Papers, Banco de España, number 2330, Oct, DOI: https://doi.org/10.53479/34613.
- Jakob Kozak & Maximilian Nagl & Cathrine Nagl & Eli Beracha & Wolfgang Schäfers, 2023, "Determinants of U.S. REIT Bond Risk Premia with Explainable Machine Learning," ERES, European Real Estate Society (ERES), number eres2023_146, Jan.
- Juan Tenorio & Wilder Pérez, 2023, "GDP nowcasting with Machine Learning and Unstructured Data to Peru," Working Papers, Peruvian Economic Association, number 197, Nov.
- Nino Paulus & Lukas Lautenschlaeger & Wolfgang Schäfers, 2023, "Social Media and Real Estate: Do Twitter users predict REIT performance?," ERES, European Real Estate Society (ERES), number eres2023_200, Jan.
- Edson Pindza & Jules Clement Mba & Sutene Mwambi & Nneka Umeorah, 2023, "Neural Network for valuing Bitcoin options under jump-diffusion and market sentiment model," Papers, arXiv.org, number 2310.09622, Oct.
- George Loewenstein & Zachary Wojtowicz, 2023, "The Economics of Attention," CESifo Working Paper Series, CESifo, number 10712.
- Item repec:ces:ceswps:_10695 is not listed on IDEAS anymore
- 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, National Bureau of Economic Research, Inc, number 31788, Oct.
- Eric Ghysels & Jack Morgan & Hamed Mohammadbagherpoor, 2023, "Quantum Computational Algorithms for Derivative Pricing and Credit Risk in a Regime Switching Economy," Papers, arXiv.org, number 2311.00825, Nov.
- Michael Barnett & William Brock & Lars Peter Hansen & Ruimeng Hu & Joseph Huang, 2023, "A Deep Learning Analysis of Climate Change, Innovation, and Uncertainty," Papers, arXiv.org, number 2310.13200, Oct.
- 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, arXiv.org, number 2311.01901, Nov, revised Nov 2023.
- Anubha Goel & Puneet Pasricha & Juho Kanniainen, 2023, "Sparse Index Tracking via Topological Learning," Papers, arXiv.org, number 2310.09578, Oct.
- Thomas R. Cook & Nathan M. Palmer, 2023, "Understanding Models and Model Bias with Gaussian Processes," Research Working Paper, Federal Reserve Bank of Kansas City, number RWP 23-07, Jun, DOI: 10.18651/RWP2023-07.
- Julia Hatamyar & Noemi Kreif & Rudi Rocha & Martin Huber, 2023, "Machine Learning for Staggered Difference-in-Differences and Dynamic Treatment Effect Heterogeneity," Papers, arXiv.org, number 2310.11962, Oct.
- 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, arXiv.org, number 2310.12428, Oct, revised Aug 2024.
- Giulio Cornelli & Jon Frost & Saurabh Mishra, 2023, "Artificial intelligence, services globalisation and income inequality," BIS Working Papers, Bank for International Settlements, number 1135, Oct.
- Jean-Marie John-Mathews, 2022, "Some critical and ethical perspectives on the empirical turn of AI interpretability," Post-Print, HAL, number hal-03395823, Jan, DOI: 10.1016/j.techfore.2021.121209.
- 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, World Institute for Development Economic Research (UNU-WIDER), number wp-2023-125.
- 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, arXiv.org, number 2310.11249, Oct.
- Gaetan de Rassenfosse & Adam Jaffe & Melissa Wasserman, 2023, "AI-Generated Inventions: Implications for the Patent System," Working Papers, Chair of Science, Technology, and Innovation Policy, number 22, May.
- 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, arXiv.org, number 2310.15505, Oct.
- Bhaskarjit Sarmah & Tianjie Zhu & Dhagash Mehta & Stefano Pasquali, 2023, "Towards reducing hallucination in extracting information from financial reports using Large Language Models," Papers, arXiv.org, number 2310.10760, Oct.