We consider state-space representation of a multivariate dynamic process with Markov switching in both measurement and transition equations. Under appropriate moment conditions, we show that the autocovariance structure of such a process coincides with that of a stable VARMA model. This is potentially useful for statistical applications and for model selection as, for example, the identification of the regime number. Applications for classical Markov switching models and some numerical illustrations complete the paper.

Weak VARMA Representations of Regime-Switching State-Space Models / Cavicchioli, Maddalena. - In: STATISTICAL PAPERS. - ISSN 0932-5026. - STAMPA. - 57(3):(2016), pp. 705-720. [10.1007/s00362-015-0675-1]

Weak VARMA Representations of Regime-Switching State-Space Models

CAVICCHIOLI, MADDALENA
2016

Abstract

We consider state-space representation of a multivariate dynamic process with Markov switching in both measurement and transition equations. Under appropriate moment conditions, we show that the autocovariance structure of such a process coincides with that of a stable VARMA model. This is potentially useful for statistical applications and for model selection as, for example, the identification of the regime number. Applications for classical Markov switching models and some numerical illustrations complete the paper.
2016
57(3)
705
720
Weak VARMA Representations of Regime-Switching State-Space Models / Cavicchioli, Maddalena. - In: STATISTICAL PAPERS. - ISSN 0932-5026. - STAMPA. - 57(3):(2016), pp. 705-720. [10.1007/s00362-015-0675-1]
Cavicchioli, Maddalena
File in questo prodotto:
File Dimensione Formato  
publication_STPA.pdf

Accesso riservato

Tipologia: Versione pubblicata dall'editore
Dimensione 465.47 kB
Formato Adobe PDF
465.47 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1111123
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 7
  • ???jsp.display-item.citation.isi??? 6
social impact