2018/05/01 by John Haslett, Andrew Parnell, Haslett, John +3
Decision Sciences · Economics, Econometrics and Finance · Social Sciences · #FOS: Computer and information sciences #Insurance, Mortality, Demography, Risk Management #Methodology (stat.ME) #Monetary Policy and Economic Impact #demographic modeling and climate adaptation
paper · pdf · doi:10.48550/arxiv.1805.00555
openalex publication_date 2018/05/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We propose a new framework for the modelling of count data exhibiting zero inflation (ZI). The main part of this framework includes a new and more general parameterisation for ZI models which naturally includes both over- and under-inflation. It further sheds new theoretical light on modelling and inference and permits a simpler alternative, which we term as multiplicative, in contrast to the dominant mixture and hurdle models. Our approach gives the statistician access to new types of ZI of which mixture and hurdle are special cases. We outline a simple parameterised modelling approach which can help to infer both ZI type and degree and provide an underlying treatment that shows that current ZI models are themselves typically within the exponential family, thus permitting much simpler theory, computation and classical inference. We outline some possibilities for a natural Bayesian framework for inference; and a rich basis for work on correlated ZI counts. The present paper is an incomplete report on the underlying theory. A later version will include computational issues and provide further examples.