ZERO-INFLATED POISSON REGRESSION MODELS: APPLICATIONS in the SCIENCES and SOCIAL SCIENCES

Buu Chau Truong, Kim Hung Pho, Cong Chanh Dinh, Michael McAleer

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)

Abstract

This paper makes a theoretical contribution by presenting a detailed derivation of a zero-inflated Poisson (ZIP) model, and then deriving the parameters of the ZIP model using a fishing data set. This model has several practical applications, and is largely performed to model count data that have an excess number of zero counts. In the scope of the paper, we introduce the complete formulae, the likelihood and log-likelihood functions and the estimating equation of the ZIP model. We then investigate the theory of large sample properties of this model under some regularity conditions. A simulation study and a fishing data set are studied for the ZIP model. The results in the actual application in this work are meaningful, useful and crucial in reality. The results also provide reliable evidence for obtaining the largest number of fish while fishing. This is the contribution of this research in terms of applications. Finally, the important applications of this model in practice, some conclusions, and future work is also presented for consideration.

Original languageEnglish
Article number2150006
JournalAnnals of Financial Economics
Volume16
Issue number2
DOIs
Publication statusPublished - Jun 2021

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