IDEAS home Printed from https://ideas.repec.org/c/boc/bocode/s459104.html
 

BIVPOISSON: Stata module to perform seemingly unrelated count regression

Author

Listed:
  • Abbie Zhang

    (Henan University)

  • James Fisher
  • Joseph Terza

    (Indiana University-Purdue University (IUPUI))

Programming Language

Stata

Abstract

bivpoisson implements the count-valued seemingly unrelated regression (count SUR) estimator proposed in Terza and Zhang (2021). This paper shows that bivpoisson affords greater precision and accuracy than Linear Seemingly Unrelated Regression (sureg) when the underlying data are correlated and count-valued; see Terza and Zhang (2021, https://doi.org/10.7912/C2/2873) for details and illustrations. Post-Estimation command (in development) associated with this package will support predictions and causal effects parameter estimation (i.e., Average Treatment Effects).

Suggested Citation

  • Abbie Zhang & James Fisher & Joseph Terza, 2022. "BIVPOISSON: Stata module to perform seemingly unrelated count regression," Statistical Software Components S459104, Boston College Department of Economics, revised 16 Aug 2022.
    • Handle: RePEc:boc:bocode:s459104
    Note: This module should be installed from within Stata by typing "ssc install bivpoisson". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/bocode/b/bivpoisson.sthlp
    File Function: help file
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/b/bivpoisson.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/b/bivpoisson-example-code.do
    File Function: sample code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/h/Health_Data.dta
    File Function: sample data file
    Download Restriction: no
    ---><---

    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:boc:bocode:s459104. 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 (email available below). General contact details of provider: https://edirc.repec.org/data/debocus.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.