Applying the GLM Variance Assumption to Overcome the Scale-Dependence of the Negative Binomial QGPML Estimator |
| |
Authors: | Clément Bosquet Hervé Boulhol |
| |
Institution: | 1. Spatial Economics Research Centre , London School of Economics , London , United Kingdom;2. OECD , Université Paris, Panthéon-Sorbonne , Paris , France |
| |
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. |
| |
Keywords: | Gamma PML Negative binomial estimator Pseudo-maximum likelihood methods Poisson regression |
|
|