On the Identification of Multivariate Correlated Unobserved Components Models
نویسندگان
چکیده
This paper analyses identification for multivariate unobserved components models in which the innovations to trend and cycle are correlated. We address order and rank criteria as well as potential non-uniqueness of the reduced-form VARMA model. Identification is shown for lag lengths larger than one in case of a diagonal vector autoregressive cycle. We also discuss UC models with common features and with cycles that allow for dynamic spillovers.
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تاریخ انتشار 2015