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BIVPOISSON: Stata module to perform seemingly unrelated count regression


  • Abbie Zhang

    (Henan University)

  • James Fisher
  • Joseph Terza

    (Indiana University-Purdue University (IUPUI))

Programming Language



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, 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 ( Windows users should not attempt to download these files with a web browser.

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