In this work we derive the Beveridge-Nelson decomposition and the state space representation for multivariate (co)integrated time series subject to Markov switching in regime. Then we provide explicit matrix expressions for the trend and cyclical components which improve computational performance since they are readily programmable. Further we develop impulse-response function analysis. Applications illustrate the feasibility of the proposed approach.
Trend and cycle decomposition in nonlinear time series / Cavicchioli, Maddalena. - (2022), pp. 1171-1176. (Intervento presentato al convegno SIS 2022 - 51th Scientific Meeting of the Italian Statistical Society tenutosi a Caserta, Italy nel 22-24 giugno 2022).
Trend and cycle decomposition in nonlinear time series
Cavicchioli maddalena
2022
Abstract
In this work we derive the Beveridge-Nelson decomposition and the state space representation for multivariate (co)integrated time series subject to Markov switching in regime. Then we provide explicit matrix expressions for the trend and cyclical components which improve computational performance since they are readily programmable. Further we develop impulse-response function analysis. Applications illustrate the feasibility of the proposed approach.
| File | Dimensione | Formato | |
|---|---|---|---|
|
3088-9597-1-DR.pdf
Accesso riservato
Tipologia:
Versione pubblicata dall'editore
Dimensione
169.94 kB
Formato
Adobe PDF
|
169.94 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
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
