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Applying the GLM variance assumption to overcome the scale-dependence of the Negative Binomial QGPML Estimator

Author

Listed:
  • Clément Bosquet

    (THEMA - Théorie économique, modélisation et applications - CNRS - Centre National de la Recherche Scientifique - CY - CY Cergy Paris Université)

  • Hervé Boulhol

    (THEMA - Théorie économique, modélisation et applications - CNRS - Centre National de la Recherche Scientifique - CY - CY Cergy Paris Université)

Abstract

Recently, various studies have used the Poisson Pseudo-Maximal Likehood (PML) to estimate gravity specifications of trade flows and non-count data models more generally. Some papers also report results based on the Negative Binomial Quasi-Generalised Pseudo-Maximum Likelihood (NB QGPML) estimator, which encompasses the Poisson assumption as a special case. This note shows that the NB QGPML estimators that have been used so far are unappealing when applied to a continuous dependent variable which unit choice is arbitrary, because estimates artificially depend on that choice. A new NB QGPML estimator is introduced to overcome this shortcoming.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Clément Bosquet & Hervé Boulhol, 2014. "Applying the GLM variance assumption to overcome the scale-dependence of the Negative Binomial QGPML Estimator," Post-Print hal-02979749, HAL.
    • Handle: RePEc:hal:journl:hal-02979749
    DOI: 10.1080/07474938.2013.806102
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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • F10 - International Economics - - Trade - - - General

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