IDEAS home Printed from https://ideas.repec.org/a/kqi/journl/2025-12-1-1.html
   My bibliography  Save this article

The Effect of Height on Earnings: A Probit Model Analysis

Author

Listed:
  • Julianne Emberger

    (Commonwealth University – Bloomsburg, PA, USA)

  • Rajendra Dulal

    (Commonwealth University – Bloomsburg, PA, USA)

Abstract

This study investigates the relationship between an individual's height and their probability of earning above the median income using a probit regression model. Drawing on a sample of working-age adults from the 1994 U.S. National Health Interview Survey, the paper examines whether physical stature provides measurable advantages in labor market outcomes after controlling for education, age, and gender. We hypothesize that, conditional on these characteristics, taller individuals are more likely to earn above the median income. The findings show that height significantly predicts higher income status, which aligns with the broader literature linking physical appearance to labor productivity and social perception. The results highlight the importance of examining how childhood health and hidden biases can affect a person's chances of moving up economically.

Suggested Citation

  • Julianne Emberger & Rajendra Dulal, 2025. "The Effect of Height on Earnings: A Probit Model Analysis," Journal of Development Innovations, KarmaQuest International, vol. 9(1), pages 1-5, December.
    • Handle: RePEc:kqi:journl:2025-12-1-1
    as

    Download full text from publisher

    File URL: https://www.karmaquest.org/journal/index.php/journal/article/view/125/72
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • J10 - Labor and Demographic Economics - - Demographic Economics - - - General
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

    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:kqi:journl:2025-12-1-1. 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: Bamadev Paudel (email available below). General contact details of provider: https://edirc.repec.org/data/sneeeea.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.