AI Agents and Large Language Models for Economic Research with Python: Automating Causal Discovery, Model Building, Policy Simulation, and Real-Time D (Paperback) (ISBN-13: 9798199473729)

AI Agents and Large Language Models for Economic Research with Python offers a practical, hands-on guide to integrating modern AI technologies into economic analysis and research workflows.

This book explores how Large Language Models and autonomous AI agents can be leveraged alongside Python to enhance traditional economic research methods. It provides clear implementations for automating key tasks including causal discovery, econometric model building, policy simulation, and real-time decision support systems.

• Fundamentals of using LLMs for economic literature review, data interpretation, and hypothesis generation
• Building and deploying AI agents capable of executing multi-step economic research tasks
• Practical Python implementations for causal inference automation
• Techniques for constructing, validating, and simulating economic models at scale
• Methods for creating real-time policy analysis and decision support tools
• Code examples using current open-source libraries and frameworks
• Best practices for ensuring transparency, reproducibility, and robustness in AI-assisted economic research

Written for economists, researchers, data scientists, and graduate students, this book bridges the gap between cutting-edge AI technologies and applied economic analysis. Rather than treating AI as a black box, it emphasizes understanding the underlying methods, limitations, and responsible implementation practices.

Whether you are looking to accelerate your research pipeline, explore new analytical approaches, or incorporate AI agents into policy evaluation workflows, this guide provides the technical foundation and working code examples needed to begin.

Clear. Technical. Reproducible.

Ready to enhance your economic research capabilities with AI and Python.