Report NEP-CMP-2023-04-03

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:

• Hakan Pabuccu & Adrian Barbu, 2023. "Feature Selection with Annealing for Forecasting Financial Time Series," Papers 2303.02223, arXiv.org, revised Feb 2024.
• Aggarwal, Sakshi, 2023. "Machine Learning algorithms, perspectives, and real-world application: Empirical evidence from United States trade data," MPRA Paper 116579, University Library of Munich, Germany.
• Sobin Joseph & Shashi Jain, 2023. "A neural network based model for multi-dimensional nonlinear Hawkes processes," Papers 2303.03073, arXiv.org.
• Tohid Atashbar & Rui Aruhan Shi, 2023. "AI and Macroeconomic Modeling: Deep Reinforcement Learning in an RBC model," IMF Working Papers 2023/040, International Monetary Fund.
• Konstantin Boss & Andre Groeger & Tobias Heidland & Finja Krueger & Conghan Zheng, 2023. "Forecasting Bilateral Refugee Flows with High-dimensional Data and Machine Learning Techniques," Working Papers 1387, Barcelona School of Economics.
• Dylan Brewer & Alyssa Carlson, 2023. "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers 2302, Department of Economics, University of Missouri.
• Muhammad Hamza Amjad, 2023. "Artificial Intelligence (AI) and Policy in Developing Countries," PIDE Webinar Brief 2023:115, Pakistan Institute of Development Economics.
• Mr. Jorge A Chan-Lau & Ruofei Hu & Maksym Ivanyna & Ritong Qu & Cheng Zhong, 2023. "Surrogate Data Models: Interpreting Large-scale Machine Learning Crisis Prediction Models," IMF Working Papers 2023/041, International Monetary Fund.
• Raffaele De Marchi & Alessandro Moro, 2023. "Forecasting fiscal crises in emerging markets and low-income countries with machine learning models," Temi di discussione (Economic working papers) 1405, Bank of Italy, Economic Research and International Relations Area.
• Martin Vesely, 2023. "Finding the Optimal Currency Composition of Foreign Exchange Reserves with a Quantum Computer," Papers 2303.01909, arXiv.org.
• Anastasis Kratsios & Cody Hyndman, 2023. "Generative Ornstein-Uhlenbeck Markets via Geometric Deep Learning," Papers 2302.09176, arXiv.org.
• Sam Dannels, 2023. "Creating Disasters: Recession Forecasting with GAN-Generated Synthetic Time Series Data," Papers 2302.10490, arXiv.org.
• Aldo Glielmo & Marco Favorito & Debmallya Chanda & Domenico Delli Gatti, 2023. "Reinforcement Learning for Combining Search Methods in the Calibration of Economic ABMs," Papers 2302.11835, arXiv.org, revised Dec 2023.
• Seoyun Hong, 2023. "Censored Quantile Regression with Many Controls," Papers 2303.02784, arXiv.org.
• Lett, Elle & La Cava, William, 2023. "Translating Intersectionality to Fair Machine Learning in Health Sciences," SocArXiv gu7yh, Center for Open Science.
• Lucila Porto, 2022. "Q-Learning algorithms in a Hotelling model," Asociación Argentina de Economía Política: Working Papers 4587, Asociación Argentina de Economía Política.
• Luca Badolato & Ari Gabriel Decter-Frain & Nicolas Irons & Maria Laura Miranda & Erin Walk & Elnura Zhalieva & Monica J. Alexander & Ugofilippo Basellini & Emilio Zagheni, 2023. "The limits of predicting individual-level longevity," MPIDR Working Papers WP-2023-008, Max Planck Institute for Demographic Research, Rostock, Germany.
• Sturm, Timo, 2023. "Exploring Human and Artificial Intelligence Collaboration and Its Impact on Organizational Performance: A Multi-Level Analysis," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 137083, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
• Ali Fathi & Bernhard Hientzsch, 2023. "A Comparison of Reinforcement Learning and Deep Trajectory Based Stochastic Control Agents for Stepwise Mean-Variance Hedging," Papers 2302.07996, arXiv.org, revised Nov 2023.
• Yasar, Alperen, 2023. "Power struggles and gender discrimination in the workplace," SocArXiv t4g83, Center for Open Science.
• Frederico Dutilh Novaes & Gabriel de Abreu Madeira & Aurimar Cerqueira, 2023. "The Economics of the DeLend Project: Agent-based Simulations," Papers 2303.03214, arXiv.org, revised Apr 2023.
• Yuan Gao & Biao Jiang & Jietong Zhou, 2023. "Financial Distress Prediction For Small And Medium Enterprises Using Machine Learning Techniques," Papers 2302.12118, arXiv.org.
• Norbäck, Pehr-Johan & Persson, Lars, 2023. "Why Big Data Can Make Creative Destruction More Creative – But Less Destructive," Working Paper Series 1454, Research Institute of Industrial Economics.
• Moez Kilani & Ousmane Diop & Ngagne Diop, 2023. "Using Transport Activity-Based Model to Simulate the Pandemic," Post-Print hal-03946166, HAL.
• Das, Gouranga G. & Ginting, Edimon & Horridge, Mark & Yamano, Takashi, 2023. "Growth Constraints and Structural Diversification for Kyrgyzstan Economy: Policy Analysis of Key Reforms and its Implications," GLO Discussion Paper Series 1250, Global Labor Organization (GLO).
• Daniel Ciganda & Julia Hellstrand & Mikko Myrskylä, 2023. "Future fertility scenarios in Finland: a computational forecasting approach," MPIDR Working Papers WP-2023-010, Max Planck Institute for Demographic Research, Rostock, Germany.
• Giannoulakis, Stelios & Forletta, Marco & Gross, Marco & Tereanu, Eugen, 2023. "The effectiveness of borrower-based macroprudential policies: a cross-country analysis using an integrated micro-macro simulation model," Working Paper Series 2795, European Central Bank.
• Jiahua Xu & Daniel Perez & Yebo Feng & Benjamin Livshits, 2023. "Auto.gov: Learning-based On-chain Governance for Decentralized Finance (DeFi)," Papers 2302.09551, arXiv.org, revised May 2023.
• Moore, Duncan A.Q. & Yaqub, Ohid & Sampat, Bhaven N., 2023. "Manual versus machine: An evaluation of the performance of the Medical Text Indexer (MTI) at classifying different document types by disease area," SocArXiv b75fr, Center for Open Science.