IDEAS home Printed from https://ideas.repec.org/a/wly/iecrev/v66y2025i3p1341-1362.html
   My bibliography  Save this article

A Simple Quantile Regression Model Linking Micro Outcomes to Macro Covariates

Author

Listed:
  • Xiaohong Chen
  • Gaosheng Ju
  • Qi Li

Abstract

This paper introduces a new location‐scale quantile regression model aimed at examining the effects of macroeconomic variables on the distribution of microeconomic outcomes using repeated cross‐sectional data. The model can be converted into an equivalent mean regression, enabling quantile coefficient estimation through least squares. This transformation improves computational efficiency, simplifies statistical inference for large data sets, and maintains robustness against model misspecification. We establish the asymptotic properties of the estimator and investigate several extensions. Our applications demonstrate that stock returns and household large‐scale expenditure growth rates respond differently across quantiles to expansionary monetary shocks and macroeconomic conditions, respectively.

Suggested Citation

  • Xiaohong Chen & Gaosheng Ju & Qi Li, 2025. "A Simple Quantile Regression Model Linking Micro Outcomes to Macro Covariates," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 66(3), pages 1341-1362, August.
  • Handle: RePEc:wly:iecrev:v:66:y:2025:i:3:p:1341-1362
    DOI: 10.1111/iere.12765
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/iere.12765
    Download Restriction: no

    File URL: https://libkey.io/10.1111/iere.12765?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
    ---><---

    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:wly:iecrev:v:66:y:2025:i:3:p:1341-1362. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/deupaus.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.