Applying the GLM Variance Assumption to Overcome the Scale-Dependence of the Negative Binomial QGPML Estimator

Clement Bosquet and Herve Boulhol

Econometric Reviews, 2014, vol. 33, issue 7, 772-784

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.

Date: 2014
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Related works:
Working Paper: Applying the GLM variance assumption to overcome the scale-dependence of the Negative Binomial QGPML Estimator (2014)
Working Paper: Scale-dependence of the Negative Binomial Pseudo-Maximum Likelihood Estimator (2010)
Working Paper: Scale-dependence of the Negative Binomial Pseudo-Maximum Likelihood Estimator (2010)
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DOI: 10.1080/07474938.2013.806102

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