Multivariate mixed Poisson Generalized Inverse Gaussian INAR(1) regression

Zezhun Chen, Angelos Dassios and George Tzougas

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: In this paper, we present a novel family of multivariate mixed Poisson-Generalized Inverse Gaussian INAR(1), MMPGIG-INAR(1), regression models for modelling time series of overdispersed count response variables in a versatile manner. The statistical properties associated with the proposed family of models are discussed and we derive the joint distribution of innovations across all the sequences. Finally, for illustrative purposes different members of the MMPGIG-INAR(1) class are fitted to Local Government Property Insurance Fund data from the state of Wisconsin via maximum likelihood estimation.

Keywords: count data time series; multivariate INAR(1) regression models; multivariate mixed Poisson- Generalized Inverse Gaussian; correlated time series; maximum likelihood estimation (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Pages: 23 pages
Date: 2022-07-09
New Economics Papers: this item is included in nep-ecm
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Published in Computational Statistics, 9, July, 2022. ISSN: 0943-4062

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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:115369

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