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Count network autoregression

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  • Mirko Armillotta
  • Konstantinos Fokianos

Abstract

We consider network autoregressive models for count data with a non‐random neighborhood structure. The main methodological contribution is the development of conditions that guarantee stability and valid statistical inference for such models. We consider both cases of fixed and increasing network dimension and we show that quasi‐likelihood inference provides consistent and asymptotically normally distributed estimators. The article is complemented by simulation results and a data example.

Suggested Citation

  • Mirko Armillotta & Konstantinos Fokianos, 2024. "Count network autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(4), pages 584-612, July.
    • Handle: RePEc:bla:jtsera:v:45:y:2024:i:4:p:584-612
    DOI: 10.1111/jtsa.12728
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    References listed on IDEAS

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