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A simple bivariate count data regression model

Author

Listed:
  • Shiferaw Gurmu

    (Georgia State University)

  • John Elder

    (North Dakota State University)

Abstract

This paper develops a simple bivariate count data regression model in which dependence between count variables is introduced by means of stochastically related unobserved heterogeneity components. Unlike existing commonly used bivariate models, we obtain a computationally simple closed form of the model with an unrestricted correlation pattern.

Suggested Citation

  • Shiferaw Gurmu & John Elder, 2007. "A simple bivariate count data regression model," Economics Bulletin, AccessEcon, vol. 3(11), pages 1-10.
  • Handle: RePEc:ebl:ecbull:eb-07c30029
    as

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    File URL: http://www.accessecon.com/pubs/EB/2007/Volume3/EB-07C30029A.pdf
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    References listed on IDEAS

    as
    1. Gurmu, Shiferaw, 1997. "Semi-Parametric Estimation of Hurdle Regression Models with an Application to Medicaid Utilization," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 225-243, May-June.
    2. Wang, Peiming, 2003. "A bivariate zero-inflated negative binomial regression model for count data with excess zeros," Economics Letters, Elsevier, vol. 78(3), pages 373-378, March.
    3. Jörgen Hellström, 2006. "A bivariate count data model for household tourism demand," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 213-226.
    4. Murat K. Munkin & Pravin K. Trivedi, 1999. "Simulated maximum likelihood estimation of multivariate mixed-Poisson regression models, with application," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 29-48.
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    Cited by:

    1. So, Sunha & Lee, Dong-Hee & Jung, Byoung Cheol, 2011. "An alternative bivariate zero-inflated negative binomial regression model using a copula," Economics Letters, Elsevier, vol. 113(2), pages 183-185.
    2. Gurmu, Shiferaw & Elder, John, 2008. "A bivariate zero-inflated count data regression model with unrestricted correlation," Economics Letters, Elsevier, vol. 100(2), pages 245-248, August.

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