Report NEP-AIN-2026-06-29

This is the archive for NEP-AIN, a report on new working papers in the area of Artificial Intelligence. Ben Greiner issued this report. It is usually issued weekly.

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Other reports in NEP-AIN

The following items were announced in this report:

• Abel, Martin & Dawi, Raghad & Lenk, Tyler & Singer, Aidan, 2026, "Algorithm Aversion in Prosocial Tasks: Evidence from AI-Based Performance Evaluation," IZA Discussion Papers, IZA Network @ LISER, number 18678, May.
• Kasberger, Bernhard & Martin, Simon & Normann, Hans-Theo & Werner, Tobias, 2026, "Algorithmic cooperation: A comparison with human play in the infinitely repeated prisoner's dilemma," DICE Discussion Papers, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE), number 437.
• Pallavi Pal & Anjana Susarla, 2026, "Algorithm or Creative? A Three-Arm Experimental Design for Decomposing Algorithmic Bias in Platform A/B Tests," Papers, arXiv.org, number 2605.23706, May.
• Masahiro Kato, 2026, "AI Economist Agent: An Agentic Framework for Model-Grounded Economic Analysis with RAG, Knowledge Graphs, and Large Language Models," Papers, arXiv.org, number 2606.20041, Jun.
• Yan Dai & Maryam Farboodi & Negin Golrezaei & Sepehr Shahshahani, 2026, "Market Design for AI: Beyond the Copyright Binary," Papers, arXiv.org, number 2606.12260, Jun.
• Valerio Fedele Addis & Giuseppe Attanasi & Giovanni Di Bartolomeo & Michele Mariella & Valentina Peruzzi, 2026, "Evaluating Creative Work with Artificial Intelligence: Evidence from Constrained Innovation Tasks," CIMEO Working Paper Series, Centre for Investigation and Modelling of Experimental Observations (CIMEO), number 197.
• Shan Huang & Renke Schmacker & Hannes Ullrich, 2026, "AI Adoption by Human Experts: Evidence from Primary Care Physicians," Discussion Papers of DIW Berlin, DIW Berlin, German Institute for Economic Research, number 2168.
• Lukas Althoff & Hugo Reichardt, 2026, "Task-Specific Technical Change and Comparative Advantage," NBER Working Papers, National Bureau of Economic Research, Inc, number 35353, Jun.
• Westby, Samuel & Modestino, Alicia & Cheng, Peiran, 2026, "Generative AI and the Redefinition of Entry-Level Software Work," IZA Discussion Papers, IZA Network @ LISER, number 18723, Jun.
• Xiliu He & Haoxiang Zhao & Mingyi Ma & Edward Wen Chuan Lai & Koei Enomoto & Anni Hu & Jiatong Li & Lingyun Chu & Yuan Lai, 2026, "Generative AI impacts on intra-urban inequality and skill premium in Beijing," Papers, arXiv.org, number 2605.25505, May.
• Lindenlaub, Ilse & Oh, Ryungha & Rodriguez, Maria Alejandra & Veldkamp, Laura, 2026, "Beyond Exposure: Predicting AI Adoption Based on Comparative Advantage," CEPR Discussion Papers, Centre for Economic Policy Research, number 21589, Jun.
• Payal Malik & Nikita Jain, 2026, "Interactions of Artificial Intelligence with India's Labour Market," Indian Council for Research on International Economic Relations (ICRIER) Policy Paper, Indian Council for Research on International Economic Relations (ICRIER), New Delhi, India, number ipcide-10, Feb.
• Dennis Facius & Roberto Iacono, 2026, "Labor Market Consequences of Generative AI: Early Evidence from Norway," CESifo Working Paper Series, CESifo, number 12752.
• Krzywdzinski, Martin, 2026, "What do software developers think about the automation of their work and its limits? Findings from a large-scale international survey," Discussion Papers, Research Group Globalization, Work, and Production, WZB Berlin Social Science Center, number SP III 2026-301.
• Christopher Campos & John D. Singleton, 2026, "AI Diffusion Gaps: Unequal Integration of AI Across K-12 Schools," NBER Working Papers, National Bureau of Economic Research, Inc, number 35347, Jun.
• Strömberg, David & Lei, Victor & Wu, Yanhui, 2026, "The Generative AI Learning Penalty: Evidence from Chinese Secondary Education," CEPR Discussion Papers, Centre for Economic Policy Research, number 21577, Jun.
• Korinek, Anton & McKelvey, Patrick, 2026, "Measuring the AI Economy," CEPR Discussion Papers, Centre for Economic Policy Research, number 21571, Jun.
• John R. Graham & Campbell R. Harvey & Manish Jha, 2026, "CFOs Meet LLMs," Papers, arXiv.org, number 2606.13812, Jun.
• David R. Agrawal & William F. Fox, 2026, "The Smarter State? Artificial Intelligence and Modern State and Local Public Finance," CESifo Working Paper Series, CESifo, number 12716.
• Yiqing Wang & Dehao Dai & Ding Ma & Kerui Geng, 2026, "Macro Economists in the Machine: A Multi-Agent LLM Framework for Commodity-Related ETF Portfolio Construction," Papers, arXiv.org, number 2606.08283, Jun.
• Junyi Yao & Zihao Zheng, 2026, "Beyond Agent Architecture: Execution Assumptions and Reproducibility in LLM-Based Trading Systems," Papers, arXiv.org, number 2606.08285, Jun.
• Ruizhe Zhou & Xiaoyang Liu & Gaoyuan Du & Yi Zheng & Shouxi Ren & Deepayan Chakrabarti & Dengdu Jiang, 2026, "From Accuracy to Auditability: A Survey of Determinism in Financial AI Systems," Papers, arXiv.org, number 2605.23955, May, revised May 2026.