IDEAS home Printed from https://ideas.repec.org/p/boc/bocoec/1080.html
   My bibliography  Save this paper

The macroeconomic implications of the Gen-AI economy

Author

Listed:
  • Pablo Guerron-Quintana

    (Boston College)

  • Tomoaki Mikami

    (Boston College)

  • Jaromir Nosal

    (Boston College)

Abstract

We study the potential impact of the generative artificial intelligence (Gen-AI) revolution on the US economy through the lens of a multi-sector model in which we explicitly model the role of Gen-AI services in customer base management. In our model with carefully calibrated input-output linkages and the size of the Gen-AI sector, we find large spillovers of the Gen-AI productivity gains into the overall economy. A 10% increase in productivity in the Gen-AI sector over a 10 year horizon implies a 6% increase in aggregate GDP, despite the AI sector representing only 14% of the overall economy. That shock also implies a significant reallocation of labor away from the AI sector and into non-AI sectors. We decompose these effects into parts coming from the input-output structure and customer base management and find that they each contribute equally to the rise in GDP. In the absence of either channels, real GDP essentially does not respond to the increase in productivity in the AI sector.

Suggested Citation

  • Pablo Guerron-Quintana & Tomoaki Mikami & Jaromir Nosal, 2024. "The macroeconomic implications of the Gen-AI economy," Boston College Working Papers in Economics 1080, Boston College Department of Economics.
    • Handle: RePEc:boc:bocoec:1080
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/EC-P/wp1080.pdf
    File Function: main text
    Download Restriction: no
    ---><---

    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:boc:bocoec:1080. 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: Christopher F Baum (email available below). General contact details of provider: https://edirc.repec.org/data/debocus.html .

    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.