IDEAS home Printed from https://ideas.repec.org/a/taf/jnlbes/v37y2019i2p248-259.html
   My bibliography  Save this article

M-Estimators of U-Processes With a Change-Point Due to a Covariate Threshold

Author

Listed:
  • Lili Tan
  • Yichong Zhang

Abstract

Economic theory often predicts a “tipping point” effect due to multiple equilibria. Linear threshold regressions estimate the “tipping point” by assuming at the same time that the response variable is linear in an index of covariates. However, economic theory rarely imposes a specific functional form, but rather predicts a monotonic relationship between the response variable and the index. We propose new, rank-based, estimators for both the “tipping point” and other regression coefficients, exploiting only the monotonicity condition. We derive the asymptotic properties of these estimators by establishing a more general result for M-estimators of U-processes with a change-point due to a covariate threshold. We finally apply our method to provide new estimates of the “tipping point” of social segregation in four major cities in the United States. Supplementary materials for this article are available online.

Suggested Citation

  • Lili Tan & Yichong Zhang, 2019. "M-Estimators of U-Processes With a Change-Point Due to a Covariate Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 248-259, April.
  • Handle: RePEc:taf:jnlbes:v:37:y:2019:i:2:p:248-259
    DOI: 10.1080/07350015.2017.1319373
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/07350015.2017.1319373
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/07350015.2017.1319373?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 search for a different version of it.

    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:taf:jnlbes:v:37:y:2019:i:2:p:248-259. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UBES20 .

    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.