estimate vector autoregressive moving average (VARMA) and state space models, which are not misspecified, using simulated data … VARMA models. However, state space algorithms can outperform SVARs. In particular, the CCA subspace method consistently … used in the literature make identification via long-run restrictions difficult for any method. …

estimate vector autoregressive moving average (VARMA) and state space models, which are not misspecified, using simulated data … VARMA models. However, state space algorithms can outperform SVARs. In particular, the CCA subspace method consistently … used in the literature make identification via long-run restrictions difficult for any method. …

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 …

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 …

The identification of a VAR requires differentiating between correlation and causation. This paper presents a method to …