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Semi-Parametric Models for Negative Binomial Panel Data

Author

Listed:
  • Brajendra C. Sutradhar

    (Memorial University)

  • Vandna Jowaheer

    (University of Mauritius)

  • R. Prabhakar Rao

    (Sri Sathya Sai Institute of Higher Learning)

Abstract

This paper considers a semi-parametric model for longitudinal negative binomial counts under the assumption that the repeated count responses follow an ARMA type non-stationary correlation structure. A step-by-step estimation approach is developed which provides consistent estimators for the non-parametric function, the auto-correlation structure and overdispersion parameter involved in the marginal negative binomial model, subsequently yielding a consistent estimator for the main regression parameter. Proofs for the consistency properties of the estimators are given. Also the convergence rates for the estimators of the non-parametric function as well as main parameters of the model are derived.

Suggested Citation

  • Brajendra C. Sutradhar & Vandna Jowaheer & R. Prabhakar Rao, 2016. "Semi-Parametric Models for Negative Binomial Panel Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 78(2), pages 269-303, August.
    • Handle: RePEc:spr:sankha:v:78:y:2016:i:2:d:10.1007_s13171-016-0089-8
    DOI: 10.1007/s13171-016-0089-8
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    References listed on IDEAS

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    Cited by:

    1. Brajendra C. Sutradhar, 2018. "Semi-parametric Dynamic Models for Longitudinal Ordinal Categorical Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(1), pages 80-109, February.

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