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Semi-Parametric Models for Negative Binomial Panel Data

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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.

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Authors and Affiliations

  1. Memorial University, St. John’s, Canada

    Brajendra C. Sutradhar

  2. University of Mauritius, Moka, Mauritius

    Vandna Jowaheer

  3. Sri Sathya Sai Institute of Higher Learning, Anantapur, India

    R. Prabhakar Rao

Authors
  1. Brajendra C. Sutradhar
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  2. Vandna Jowaheer
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  3. R. Prabhakar Rao
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Correspondence to Brajendra C. Sutradhar.

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Sutradhar, B.C., Jowaheer, V. & Rao, R.P. Semi-Parametric Models for Negative Binomial Panel Data. Sankhya A 78, 269–303 (2016). https://doi.org/10.1007/s13171-016-0089-8

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  • DOI: https://doi.org/10.1007/s13171-016-0089-8

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