AI Agents and Large Language Models for Economic Research with Python: Automating Causal Discovery, Model Building, Policy Simulation, and Real-Time Decision Support
English | May 31, 2026 | ASIN: B0H3J7ZS5H | 439 pages | Epub | 537.03 KB
Reactive PublishingAI 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.What You'll Find Inside:Fundamentals of using LLMs for economic literature review, data interpretation, and hypothesis generationBuilding and deploying AI agents capable of executing multi-step economic research tasksPractical Python implementations for causal inference automationTechniques for constructing, validating, and simulating economic models at scaleMethods for creating real-time policy analysis and decision support toolsCode examples using current open-source libraries and frameworksBest practices for ensuring transparency, reproducibility, and robustness in AI-assisted economic researchWritten 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.
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