Product Information

Description

An annual survey of the econ.GN arXiv category, covering research published from September 2025 – August 2026. Built on a close-reading set of 120 papers and organised into 44 chapters, it maps the year by the field's research sub-directions.

Book framework (share of the year's output):

Machine Learning Applications in Economic Growth and Energy Systems (17.5%) — Applies reinforcement learning and clustering techniques to model energy pathways, economic growth, and labor automation feasibility.
Global Trade, Inequality, and Socioeconomic Data Measurement (15.6%) — Analyzes global trade flows, income distribution, and socioeconomic disparities using large-scale data and panel regression methods.
Market Design, Pricing Dynamics, and Risk Management (11.4%) — Investigates price formation, competition, and risk allocation in electricity, insurance, and prediction markets through mechanism design and agent-based modeling.
Experimental and Quasi-Experimental Evidence on Labor and Welfare (11.3%) — Evaluates causal impacts of policies, globalization, and workplace conditions on job satisfaction, health, and sustainable development using field evidence.
Generative AI Adoption, Productivity, and Labor Market Transformation (10.4%) — Examines the economic effects of generative AI on work structures, productivity indices, and the displacement or augmentation of human labor.
Market Dynamics in Housing, Labor, and Energy Sectors (9.7%) — Studies market collapse, price volatility, and design challenges in housing, labor, and electricity markets using dynamic modeling and forecasting.
Structural Modeling and Statistical Methods for Economic Dynamics (8.4%) — Utilizes structural models, language models, and stochastic control to analyze fiscal capacity, inflation, and macroeconomic dynamics.
Behavioral Economics and Impact of AGI on Human-AI Collaboration (7.7%) — Explores behavioral responses, system dynamics, and the economic implications of artificial general intelligence and human-AI interaction.
Large Language Models in Economic Behavior and Policy Analysis (4.3%) — Assesses the short-term economic effects of LLMs on employment, biases in decision-making, and their application in agentic economic analysis.
AI Governance, Accounting Frameworks, and Strategic Intelligence (3.9%) — Develops frameworks for AI governance, accounting research, and strategic management in the context of intelligence-driven commerce and security risks.

Each sub-direction is covered across three chapters — how it framed its questions, the strength of its key findings, and its open debates and frontiers — so the reader gets a traceable picture of what this part of the field actually produced over the year.