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. 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:

• Hakan Pabuccu & Adrian Barbu, 2023, "Feature Selection with Annealing for Forecasting Financial Time Series," Papers, arXiv.org, number 2303.02223, Mar, revised Feb 2024.
• Aggarwal, Sakshi, 2023, "Machine Learning algorithms, perspectives, and real-world application: Empirical evidence from United States trade data," MPRA Paper, University Library of Munich, Germany, number 116579, Mar.
• Sobin Joseph & Shashi Jain, 2023, "A neural network based model for multi-dimensional nonlinear Hawkes processes," Papers, arXiv.org, number 2303.03073, Mar.
• Tohid Atashbar & Rui Aruhan Shi, 2023, "AI and Macroeconomic Modeling: Deep Reinforcement Learning in an RBC model," IMF Working Papers, International Monetary Fund, number 2023/040, Feb.
• Konstantin Boss & Finja Krueger & Conghan Zheng & Tobias Heidland & Andre Groeger, 2023, "Forecasting Bilateral Refugee Flows with High-dimensional Data and Machine Learning Techniques," Working Papers, Barcelona School of Economics, number 1387, Mar.
• Dylan Brewer & Alyssa Carlson, 2023, "Addressing Sample Selection Bias for Machine Learning Methods," Working Papers, Department of Economics, University of Missouri, number 2302, Mar.
• Muhammad Hamza Amjad, 2023, "Artificial Intelligence (AI) and Policy in Developing Countries," PIDE Webinar Brief, Pakistan Institute of Development Economics, number 2023:115.
• 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, International Monetary Fund, number 2023/041, Feb.
• 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), Bank of Italy, Economic Research and International Relations Area, number 1405, Mar.
• Martin Vesely, 2023, "Finding the Optimal Currency Composition of Foreign Exchange Reserves with a Quantum Computer," Papers, arXiv.org, number 2303.01909, Mar.
• Anastasis Kratsios & Cody Hyndman, 2023, "Generative Ornstein-Uhlenbeck Markets via Geometric Deep Learning," Papers, arXiv.org, number 2302.09176, Feb.
• Sam Dannels, 2023, "Creating Disasters: Recession Forecasting with GAN-Generated Synthetic Time Series Data," Papers, arXiv.org, number 2302.10490, Feb.
• Aldo Glielmo & Marco Favorito & Debmallya Chanda & Domenico Delli Gatti, 2023, "Reinforcement Learning for Combining Search Methods in the Calibration of Economic ABMs," Papers, arXiv.org, number 2302.11835, Feb, revised Dec 2023.
• Seoyun Hong, 2023, "Censored Quantile Regression with Many Controls," Papers, arXiv.org, number 2303.02784, Mar.
• Lett, Elle & La Cava, William, 2023, "Translating Intersectionality to Fair Machine Learning in Health Sciences," SocArXiv, Center for Open Science, number gu7yh, Feb, DOI: 10.31219/osf.io/gu7yh.
• Lucila Porto, 2022, "Q-Learning algorithms in a Hotelling model," Asociación Argentina de Economía Política: Working Papers, Asociación Argentina de Economía Política, number 4587, Nov.
• Luca Badolato & Ari Gabriel Decter-Frain & Nicolas Irons & Maria L. Miranda & Erin Walk & Elnura Zhalieva & Monica J. Alexander & Ugofilippo Basellini & Emilio Zagheni, 2023, "The limits of predicting individual-level longevity," MPIDR Working Papers, Max Planck Institute for Demographic Research, Rostock, Germany, number WP-2023-008, DOI: 10.4054/MPIDR-WP-2023-008.
• 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), Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL), number 137083.
• Ali Fathi & Bernhard Hientzsch, 2023, "A Comparison of Reinforcement Learning and Deep Trajectory Based Stochastic Control Agents for Stepwise Mean-Variance Hedging," Papers, arXiv.org, number 2302.07996, Feb, revised Nov 2023.
• Yasar, Alperen, 2023, "Power struggles and gender discrimination in the workplace," SocArXiv, Center for Open Science, number t4g83, Feb, DOI: 10.31219/osf.io/t4g83.
• Frederico Dutilh Novaes & Gabriel de Abreu Madeira & Aurimar Cerqueira, 2023, "The Economics of the DeLend Project: Agent-based Simulations," Papers, arXiv.org, number 2303.03214, Mar, revised Apr 2023.
• Yuan Gao & Biao Jiang & Jietong Zhou, 2023, "Financial Distress Prediction For Small And Medium Enterprises Using Machine Learning Techniques," Papers, arXiv.org, number 2302.12118, Feb.
• Norbäck, Pehr-Johan & Persson, Lars, 2023, "Why Big Data Can Make Creative Destruction More Creative – But Less Destructive," Working Paper Series, Research Institute of Industrial Economics, number 1454, Feb.
• Moez Kilani & Ousmane Diop & Ngagne Diop, 2023, "Using Transport Activity-Based Model to Simulate the Pandemic," Post-Print, HAL, number hal-03946166, Feb, DOI: 10.3390/su1010000.
• 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, Global Labor Organization (GLO), number 1250.
• Daniel Ciganda & Julia Hellstrand & Mikko Myrskylä, 2023, "Future fertility scenarios in Finland: a computational forecasting approach," MPIDR Working Papers, Max Planck Institute for Demographic Research, Rostock, Germany, number WP-2023-010, DOI: 10.4054/MPIDR-WP-2023-010.
• 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, European Central Bank, number 2795, Mar.
• Jiahua Xu & Yebo Feng & Daniel Perez & Benjamin Livshits, 2023, "Auto.gov: Learning-based Governance for Decentralized Finance (DeFi)," Papers, arXiv.org, number 2302.09551, Feb, revised May 2025.
• 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, Center for Open Science, number b75fr, Feb, DOI: 10.31219/osf.io/b75fr.

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. 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: