Testing the compounding structure of the CP-INARCH model

Christian H. Weiß (), Esmeralda Gonçalves () and Nazaré Mendes Lopes ()
Additional contact information
Christian H. Weiß: Helmut Schmidt University
Esmeralda Gonçalves: Universidade de Coimbra
Nazaré Mendes Lopes: Universidade de Coimbra

Metrika: International Journal for Theoretical and Applied Statistics, 2017, vol. 80, issue 5, No 3, 603 pages

Abstract: Abstract A statistical test to distinguish between a Poisson INARCH model and a Compound Poisson INARCH model is proposed, based on the form of the probability generating function of the compounding distribution of the conditional law of the model. For first-order autoregression, the normality of the test statistics’ asymptotic distribution is established, either in the case where the model parameters are specified, or when such parameters are consistently estimated. As the test statistics’ law involves the moments of inverse conditional means of the Compound Poisson INARCH process, the analysis of their existence and calculation is performed by two approaches. For higher-order autoregressions, we use a bootstrap implementation of the test. A simulation study illustrating the finite-sample performance of this test methodology in what concerns its size and power concludes the paper.

Keywords: Count-data time series; Compound Poisson distribution; INGARCH model; Diagnostic tests; Inverse moments; 60J10; 62M02; 62M10 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s00184-017-0617-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:metrik:v:80:y:2017:i:5:d:10.1007_s00184-017-0617-0

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/184/PS2

DOI: 10.1007/s00184-017-0617-0

Access Statistics for this article

Metrika: International Journal for Theoretical and Applied Statistics is currently edited by U. Kamps and Norbert Henze

More articles in Metrika: International Journal for Theoretical and Applied Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().