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A Seemingly Unrelated Poisson Regression Model

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  • GARY KING

    (Harvard University)

Abstract

This article introduces a new estimator for the analysis of two contemporaneously correlated endogenous event count variables. This seemingly unrelated Poisson regression model (SUPREME) estimator combines the efficiencies created by single equation Poisson regression model estimators and insights from “seemingly unrelated†linear regression models.

Suggested Citation

  • Gary King, 1989. "A Seemingly Unrelated Poisson Regression Model," Sociological Methods & Research, , vol. 17(3), pages 235-255, February.
  • Handle: RePEc:sae:somere:v:17:y:1989:i:3:p:235-255
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    Cited by:

    1. Sitienei, Isaac & Gillespie, Jeffrey & Scaglia, Guillermo, 2017. "Adoption of Beef Care Management Practices and Its Determinants: Analysis of the U.S. Grass-Fed Beef Industry," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252712, Southern Agricultural Economics Association.
    2. Lazkano, Itziar & Nøstbakken, Linda & Pelli, Martino, 2017. "From fossil fuels to renewables: The role of electricity storage," European Economic Review, Elsevier, vol. 99(C), pages 113-129.
    3. A. Colin Cameron & Per Johansson, 2004. "Bivariate Count Data Regression Using Series Expansions: With Applications," Working Papers 9815, University of California, Davis, Department of Economics.
    4. repec:bla:stratm:v:40:y:2019:i:6:p:865-893 is not listed on IDEAS
    5. Michael R Ransom & C. Arden Pope Iii, 1995. "External Health Costs Of A Steel Mill," Contemporary Economic Policy, Western Economic Association International, vol. 13(2), pages 86-97, April.
    6. Bruce Mcwilliams & Yacov Tsur & Eithan Hochman & David Zilberman, 1998. "Count-data regression models of the time to adopt new technologies," Applied Economics Letters, Taylor & Francis Journals, vol. 5(6), pages 369-373.

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