IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2504.09736.html
   My bibliography  Save this paper

Agentic Workflows for Economic Research: Design and Implementation

Author

Listed:
  • Herbert Dawid
  • Philipp Harting
  • Hankui Wang
  • Zhongli Wang
  • Jiachen Yi

Abstract

This paper introduces a methodology based on agentic workflows for economic research that leverages Large Language Models (LLMs) and multimodal AI to enhance research efficiency and reproducibility. Our approach features autonomous and iterative processes covering the entire research lifecycle--from ideation and literature review to economic modeling and data processing, empirical analysis and result interpretation--with strategic human oversight. The workflow architecture comprises specialized agents with clearly defined roles, structured inter-agent communication protocols, systematic error escalation pathways, and adaptive mechanisms that respond to changing research demand. Human-in-the-loop (HITL) checkpoints are strategically integrated to ensure methodological validity and ethical compliance. We demonstrate the practical implementation of our framework using Microsoft's open-source platform, AutoGen, presenting experimental examples that highlight both the current capabilities and future potential of agentic workflows in improving economic research.

Suggested Citation

  • Herbert Dawid & Philipp Harting & Hankui Wang & Zhongli Wang & Jiachen Yi, 2025. "Agentic Workflows for Economic Research: Design and Implementation," Papers 2504.09736, arXiv.org.
    • Handle: RePEc:arx:papers:2504.09736
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2504.09736
    File Function: Latest version
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2504.09736. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.