Multivariate Count Time Series Modelling

Konstantinos Fokianos

Econometrics and Statistics, 2024, vol. 31, issue C, 100-116

Abstract: Autoregressive models are reviewed for the analysis of multivariate count time series. A particular topic of interest which is discussed in detail is that of the choice of a suitable distribution for a vectors of count random variables. The focus is on three main approaches taken for multivariate count time series analysis: (a) integer autoregressive processes, (b) parameter-driven models and (c) observation-driven models. The aim is to highlight some recent methodological developments and propose some potentially useful research topics.

Keywords: auto-correlation; covariates; copula; estimation; multivariate count distribution; prediction (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosta:v:31:y:2024:i:c:p:100-116

DOI: 10.1016/j.ecosta.2021.11.006

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