Applications of zero-inflated count data models have proliferated in empirical economic research. There is a downside to this development, as zero-inflated Poisson or zero-inflated Negative Binomial Maximum Likelihood estimators are not robust to misspecification. In contrast, simple Poisson...

Applications of zero-inflated count data models have proliferated in health economics. However, zero-inflated Poisson or zero-inflated negative binomial maximum likelihood estimators are not robust to misspecification. This paper proposes Poisson quasi-likelihood estimators as an alternative....

Applications of zero-inflated count data models have proliferated in empirical economic research. There is a downside to this development, as zero-inflated Poisson or zero-inflated Negative Binomial Maximum Likelihood estimators are not robust to misspecification. In contrast, simple Poisson...

The book provides graduate students and researchers with an up-to-date survey of econometric and statistical techniques for the analysis of count data, with a focus on regression models. Specialised discrete data probability models are required in order to interpret results in terms of an...

The book provides graduate students and researchers with an up-to-date survey of statistical and econometric techniques for the analysis of count data, with a focus on conditional distribution models. Proper count data probability models allow for rich inferences, both with respect to the...

This book presents econometric methods for the analysis of event counts. It reviews the recent literature and introduces several new results. While the emphasis is on methods for cross-section data, the modelling of time series and panel count data is discussed as well. Topics include: dependent...