AI Agents and Large Language Models for Economic Research with Python : Automating Causal Discovery, Model Building, Policy Simulation, and Real-Time Decision Support

Hayden van der Post

ISBN 13: 9798199473729

Published by Independently Published Mai 2026, 2026

About this Item

Neuware.

Seller Inventory # 9798199473729

Bibliographic Details

• Title: AI Agents and Large Language Models for Economic Research with Python : Automating Causal Discovery, Model Building, Policy Simulation, and Real-Time Decision Support
• Publisher: Independently Published Mai 2026
• Publication Date: 2026
• Language: English
• ISBN 13: 9798199473729
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 229W x 152H x 31D millimeters 229 millimeters width by 152 millimeters height by 31 millimeters depth
• Weight: 599 grams

About this title

Synopsis

Reactive Publishing

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.

What You'll Find Inside:

• 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.