IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/20840.html

Deliberation and Policy Outcomes: Evidence from the Textual Analysis of FOMC Transcripts

Author

Listed:
  • Riboni, Alessandro
  • Ruge-Murcia, Francisco
  • Tran, Linh

Abstract

Natural language processing is used to extract information from FOMC transcripts and construct quantitative text-based measures of voiced policy stance, emotions, and collaboration. These measures are inputs in an econometric model of deliberation where members interact with one another across rounds of a meeting and over time across meetings. Evidence shows that members learn from one another during within-meeting deliberation and exert influence across meetings. Although emotional tone has limited effects on policy stances and decisions, it has strong predictive power for dissent behavior.

Suggested Citation

  • Riboni, Alessandro & Ruge-Murcia, Francisco & Tran, Linh, 2025. "Deliberation and Policy Outcomes: Evidence from the Textual Analysis of FOMC Transcripts," CEPR Discussion Papers 20840, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:20840
    as

    Download full text from publisher

    File URL: https://cepr.org/publications/DP20840
    Download Restriction: no
    ---><---

    More about this item

    JEL classification:

    • D7 - Microeconomics - - Analysis of Collective Decision-Making
    • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

    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:cpr:ceprdp:20840. 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: CEPR (email available below). General contact details of provider: https://cepr.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.