IDEAS home Printed from https://ideas.repec.org/p/ecb/ecbwps/20253063.html
   My bibliography  Save this paper

Enhancing GDP nowcasts with ChatGPT: a novel application of PMI news releases

Author

Listed:
  • Sun, Yiqiao
  • de Bondt, Gabe

Abstract

This study involves tasking ChatGPT with classifying an “activity sentiment score” based on PMI news releases. It explores the predictive power of this score for euro area GDP nowcasting. We find that the PMI text scores enhance GDP nowcasts beyond what is embedded in ECB/Eurosystem Staff projections and Eurostat’s first GDP estimate. The ChatGPT-derived activity score retains its significance in regressions that also include the composite output PMI diffusion index. GDP nowcasts are significantly enhanced with PMI text scores even when accounting for methodological variations, excluding extraordinary economic events like the pandemic, and for different GDP growth quantiles. However, the forecast gains from the enhancement of GDP nowcasts with ChatGPT scores are time dependent, varying by calendar years. Sizeable forecast gains of on average about 20% were obtained apart from the two most recent years due to exceptionally low forecast errors of the two benchmarks, especially the first GDP estimate. JEL Classification: C8, E32, C22

Suggested Citation

  • Sun, Yiqiao & de Bondt, Gabe, 2025. "Enhancing GDP nowcasts with ChatGPT: a novel application of PMI news releases," Working Paper Series 3063, European Central Bank.
    • Handle: RePEc:ecb:ecbwps:20253063
    Note: 2759141
    as

    Download full text from publisher

    File URL: https://www.ecb.europa.eu//pub/pdf/scpwps/ecb.wp3063~f88c1b73fc.en.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    chat generative pre-training transformer; nowcasting GDP; purchasing managers’ index (PMI); text analysis; zero-shot sentiment analysis;
    All these keywords.

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    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:ecb:ecbwps:20253063. 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: Official Publications (email available below). General contact details of provider: https://edirc.repec.org/data/emieude.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.