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Report NEP-CMP-2026-03-23
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:
- Hauck, Florian & Güth, Albrecht & Kliewer, Natalia & Rößler-von Saß, David, 2026, "Applying generative adversarial networks to generate synthetic train trip data for train delay prediction," Discussion Papers, Free University Berlin, School of Business & Economics, number 2026/7, DOI: 10.17169/refubium-51427.
- Douglas KG. Araujo & Harald Uhlig, 2026, "How does AI Distribute the pie? Large Language Models and the Ultimatum Game," NBER Working Papers, National Bureau of Economic Research, Inc, number 34919, Mar.
- Ahrens, Achim & Chernozhukov, Victor & Hansen, Christian & Kozbur, Damian & Schaffer, Mark & Wiemann, Thomas, 2026, "An Introduction to Double/Debiased Machine Learning," IZA Discussion Papers, IZA Network @ LISER, number 18438, Mar.
- Chen Zhu & Xiaolu Wang, 2026, "HLER: Human-in-the-Loop Economic Research via Multi-Agent Pipelines for Empirical Discovery," Papers, arXiv.org, number 2603.07444, Mar.
- Srikumar Nayak, 2026, "Calibrated Credit Intelligence: Shift-Robust and Fair Risk Scoring with Bayesian Uncertainty and Gradient Boosting," Papers, arXiv.org, number 2603.06733, Mar.
- Yizhi Liu & Balaji Padmanabhan & Siva Viswanathan, 2026, "Estimating Visual Attribute Effects in Advertising from Observational Data: A Deepfake-Informed Double Machine Learning Approach," Papers, arXiv.org, number 2603.02359, Mar.
- Fuchs, Anna & Haensch, Anna-Carolina & Weber, Wiebke, 2026, "AI for Survey Design: Generating and Evaluating Survey Questions with Large Language Models," SocArXiv, Center for Open Science, number fzn7t_v1, Mar, DOI: 10.31219/osf.io/fzn7t_v1.
- Hui Chen & Antoine Didisheim & Luciano A. Somoza, 2026, "Out of the Black Box: Uncertainty Quantification for LLMs via Conditional Probabilities," NBER Working Papers, National Bureau of Economic Research, Inc, number 34965, Mar.
- Alexander Erlei & Lukas Meub, 2026, "LLM-Agent Interactions on Markets with Information Asymmetries," Papers, arXiv.org, number 2603.08853, Mar.
- Marina Azzimonti & David Wiczer & Yang Xuan, 2026, "Estimating Demand Shocks from Foot Traffic: A Big-Data Approach," Working Paper, Federal Reserve Bank of Richmond, number 26-05, Mar.
- Sebastien Lleo & Wolfgang Runggaldier, 2026, "Exploratory Randomization for Discrete-Time Risk-Sensitive Benchmarked Investment Management with Reinforcement Learning," Papers, arXiv.org, number 2603.00738, Feb.
- Cicilia Anggadewi Harun & Safari Kasiyanto & Camila Amalia & Shinta Fitrianti & Esha Gianne Poetry & Nilasari & Rina Megasari & Naura Pradipta Khairunnis, 2025, "The Algorithmic Alchemy: Synthesizing Global Legal Frameworks For Artificial Intelligence In Financial Services," Working Papers, Bank Indonesia, number WP/20/2025.
- Renardi Ardiya Bimantoro & Rudy Hardiyanto & Irfan Sampe & Agung Bayu Purwoko & Imam Dwi Kuncoro & Irvan Fadjar R. & Devima Christi M. & Anugerah Mohamad Setiawan & Moh. Mashudi Arif & Mahanani Margan, 2025, "Identification Of Illegal Transaction Patterns In Payment System Data Using Ai/Ml: A Case Study On Online Gambling," Working Papers, Bank Indonesia, number WP/14/2025.
- Liang, Xiaofan, 2026, "What and How Should Urban Planners Learn in the AI Era? Exploring Urban AI Pedagogy from a Pilot Course in Urban Planning Education," SocArXiv, Center for Open Science, number g9cps_v1, Mar, DOI: 10.31219/osf.io/g9cps_v1.
- Martin Huber & Sarina Joy Oberhansli, 2026, "Difference-in-differences for mediation analysis using double machine learning," Papers, arXiv.org, number 2602.23877, Feb.
- Soria, Chris, 2026, "Scaling Open-Ended Survey Coding: An LLM Pipeline Where Definitions Do the Heavy Lifting," SocArXiv, Center for Open Science, number gjvcf_v1, Mar, DOI: 10.31219/osf.io/gjvcf_v1.
- Nikolai Cook, František Bartoš, Pedro R. D. Bom, Sebastian Gechert, Klára Kantová, Jerome Geyer-Klingeberg, Tomáš Havránek, Zuzana Irsova, Martina Luskova, Matěj Opatrný, Franz Prante, Heiko , 2026, "Guidance for the Use of AI in the Meta-Analysis of Economics Research," LCERPA Working Papers, Laurier Centre for Economic Research and Policy Analysis, number jc0161, Mar, revised Mar 2026.
- Epper, Thomas & Ibsen, Kristoffer & Koch, Alexander & Nafziger, Julia, 2026, "Predicting University Dropouts: Evidence on the Value of Student Expectations and Motivation," IZA Discussion Papers, IZA Network @ LISER, number 18439, Mar.
- Batuhan Koyuncu & Byeungchun Kwon & Marco Jacopo Lombardi & Fernando Perez-Cruz & Hyun Song Shin, 2026, "Introducing BISTRO: a foundational model for unconditional and conditional forecasting of macroeconomic time series," BIS Working Papers, Bank for International Settlements, number 1337, Mar.
- Hait, Subir, 2026, "A Monte Carlo Simulation Framework for University Enrollment Strategy Under Marketing Uncertainty," SocArXiv, Center for Open Science, number 4kjb9_v1, Mar, DOI: 10.31219/osf.io/4kjb9_v1.