Testing for zero inflation and overdispersion in INAR(1) models

Christian H. Weiß, Annika Homburg, Pedro Puig

Research output: Contribution to journalArticleResearch

20 Citations (Scopus)


© 2016, Springer-Verlag Berlin Heidelberg. The marginal distribution of count data processes rarely follows a simple Poisson model in practice. Instead, one commonly observes deviations such as overdispersion or zero inflation. To express the extend of such deviations from a Poisson model, one can compute an appropriately defined dispersion index or zero index. In this article, we develop several tests based on such indexes, including joint tests being based on an index combination. The asymptotic distribution of the resulting test statistics under the null hypothesis of a Poisson INAR(1) model is derived, and the finite-sample performance of the resulting tests is analyzed. Real data examples illustrate the application of these tests in practice.
Original languageEnglish
Pages (from-to)473-498
JournalStatistical Papers
Publication statusPublished - 15 Jun 2019


  • Count data time series
  • Discrete data models
  • Dispersion index
  • Overdispersion
  • Zero indexes
  • Zero-inflation


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