IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v256y2026ipbs0304407625002167.html

Text-term selection and analysis: Frequentist and Bayesian strategies and interpretations

Author

Listed:
  • Chen, Cathy Yi-Hsuan
  • Kapetanios, George
  • Wu, Wei-Biao

Abstract

Economic analysis based on text data has expanded rapidly, yet the ultra-high dimensionality of text data presents substantial challenges for term selection and estimation. We propose the Information-Adaptive Lasso and Information-Adaptive Spike-and-Slab Lasso as novel frequentist and Bayesian approaches to address these challenges. A key theoretical contribution of this study is the establishment of the rate of convergence in term-selection consistency, which we show to be faster than those achieved in the existing Lasso literature. Applying our methods to Federal Open Market Committee (FOMC) statements, we identify and estimate high-impact terms driving fluctuations in monetary policy uncertainty.

Suggested Citation

  • Chen, Cathy Yi-Hsuan & Kapetanios, George & Wu, Wei-Biao, 2026. "Text-term selection and analysis: Frequentist and Bayesian strategies and interpretations," Journal of Econometrics, Elsevier, vol. 256(PB).
    • Handle: RePEc:eee:econom:v:256:y:2026:i:pb:s0304407625002167
    DOI: 10.1016/j.jeconom.2025.106163
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304407625002167
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jeconom.2025.106163?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:eee:econom:v:256:y:2026:i:pb:s0304407625002167. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    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.