Original Paper

AStA Advances in Statistical Analysis

, Volume 95, Issue 1, pp 59-91

First online:

Useful models for time series of counts or simply wrong ones?

  • Robert C. JungAffiliated withStaatswissenschaftliche Fakultät, Universität Erfurt Email author 
  • , A. R. TremayneAffiliated withSchool of Economics, University of New South WalesUniversity of York

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There has been a considerable and growing interest in low integer-valued time series data leading to a diversification of modelling approaches. In addition to static regression models, both observation-driven and parameter-driven models are considered here. We compare and contrast a variety of time series models for counts using two very different data sets as a testbed. A range of diagnostic devices is employed to help inform model adequacy. Special attention is paid to dynamic structure and underlying distributional assumptions including associated dispersion properties. Competing models show attractive features, but overall no one modelling approach is seen to dominate.


Count time series Parameter-driven Observation-driven Autocorrelation Overdispersion Diagnostics