IDEAS home Printed from https://ideas.repec.org/a/tsj/stataj/v21y2021i2p430-461.html
   My bibliography  Save this article

Maximum likelihood estimation of an across-regime correlation parameter

Author

Listed:
  • Giorgio Calzolari

    (University of Firenze)

  • Maria Gabriella Campolo

    (University of Messina)

  • Antonino Di Pino

    (University of Messina)

  • Laura Magazzini

    (Sant’Anna School of Advanced Studies)

Abstract

In this article, we describe the mlcar command, which implements a maximum likelihood method to simultaneously estimate the regression coefficients of a two-regime endogenous switching model and the coefficient measuring the correlation of outcomes between the two regimes. This coefficient, known as the “across-regime” correlation parameter, is generally unidentified in the traditional estimation procedures.

Suggested Citation

  • Giorgio Calzolari & Maria Gabriella Campolo & Antonino Di Pino & Laura Magazzini, 2021. "Maximum likelihood estimation of an across-regime correlation parameter," Stata Journal, StataCorp LP, vol. 21(2), pages 430-461, June.
    • Handle: RePEc:tsj:stataj:v:21:y:2021:i:2:p:430-461
    DOI: 10.1177/1536867X211025834
    Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-2/st0642/
    as

    Download full text from publisher

    File URL: http://www.stata-journal.com/article.html?article=st0642
    File Function: link to article purchase
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1536867X211025834?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Giorgio Calzolari & Maria Gabriella Campolo & Antonino Pino & Laura Magazzini, 2023. "Assessing individual skill influence on housework time of Italian women: an endogenous-switching approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 659-679, June.

    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:tsj:stataj:v:21:y:2021:i:2:p:430-461. 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: Christopher F. Baum or Lisa Gilmore (email available below). General contact details of provider: http://www.stata-journal.com/ .

    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.