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Authors = Gianluca Cubadda

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16 pages, 353 KiB  
Article
Detecting Common Bubbles in Multivariate Mixed Causal–Noncausal Models
by Gianluca Cubadda, Alain Hecq and Elisa Voisin
Econometrics 2023, 11(1), 9; https://doi.org/10.3390/econometrics11010009 - 9 Mar 2023
Cited by 6 | Viewed by 2839
Abstract
This paper proposes concepts and methods to investigate whether the bubble patterns observed in individual time series are common among them. Having established the conditions under which common bubbles are present within the class of mixed causal–noncausal vector autoregressive models, we suggest statistical [...] Read more.
This paper proposes concepts and methods to investigate whether the bubble patterns observed in individual time series are common among them. Having established the conditions under which common bubbles are present within the class of mixed causal–noncausal vector autoregressive models, we suggest statistical tools to detect the common locally explosive dynamics in a Student t-distribution maximum likelihood framework. The performances of both likelihood ratio tests and information criteria were investigated in a Monte Carlo study. Finally, we evaluated the practical value of our approach via an empirical application on three commodity prices. Full article
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