Mixing properties of non-stationary INGARCH(1, 1) processes





Faculty/Professorship: Mathematics for Business and Economics  
Author(s): Doukhan, Paul; Leucht, Anne  ; Neumann, Michael H.
Title of the Journal: Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability
ISSN: 1573-9759
Publisher Information: Aarhus
Year of publication: 2021
Issue: Version: April 8, 2021
Pages: 663–688
Language(s): English
DOI: 10.3150/21-BEJ1362
Abstract: 
We derive mixing properties for a broad class of Poisson count time series satisfying a certain contraction condition. Using specific coupling techniques, we prove absolute regularity at a geometric rate not only for stationary Poisson-GARCH processes but also for models with an explosive trend. We provide easily verifiable sufficient conditions for absolute regularity for a variety of models including classical (log-)linear models. Finally, we illustrate the practical use of our results for hypothesis testing.
GND Keywords: Poisson-Prozess; GARCH-Prozess; Lineares Modell; Regelmäßigkeit; Zeitreihe
Keywords: Absolute regularity, INGARCH
DDC Classification: 330 Economics  
RVK Classification: QH 170   
Peer Reviewed: Ja
International Distribution: Ja
Type: Article
URI: https://fis.uni-bamberg.de/handle/uniba/52082
Release Date: 16. November 2021