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We use information from higher order moments to achieve identification of non-Gaussian structural vector autoregressive moving average (SVARMA) models, possibly nonfundamental or noncausal, through a frequency domain criterion based on spectral densities. This allows us identify the location roots determinantal lag matrix polynomials and rotation model errors leading shocks up sign permutation....

We provide a closed-form estimator based on the VARMA representation for the unrestricted multivariate GARCH(1,1). We show that all parameters can be derived using basic linear algebra tools. We show that the estimator is consistent and asymptotically normal distributed. Our results allow also to derive a closed form for the parameters in the context of temporal aggregation of multivariate GARC...

Fig3. Quantitative Asymr and ihMTr values as a function of fc values, in IC, GM and Mu Fig2. Asymr and ihMTr as a function of fc values Magnetization Transfer from Inhomogeneously Broadened Lines (ihMT): Effect of MT Asymmetry on the ihMT Signal Guillaume Duhamel, Valentin Prevost, Gopal Varma, David C Alsop, and Olivier Girard CRMBM, CNRS 7339, Aix-Marseille Université, Marseille, 13005, Franc...

Estimation of dynamic stochastic general equilibrium (DSGE) models using state space methods implies vector autoregressive moving average (VARMA) representations of the observables. Following Lippi and Reichlin’s (1994) analysis of nonfundamentalness, this note highlights the potential dangers of non-uniqueness, both of estimates of deep parameters and of structural innovations. ∗Department of ...

The basic assumption of a structural VARMA model (SVARMA) is that it is driven by a white noise whose components are independent and can be interpreted as economic shocks, called “structural” shocks. When the errors are Gaussian, independence is equivalent to noncorrelation and these models have to face two kinds of identification issues. The first identification problem is “static” and is due ...

NEWS FOCUS 24 Chasing the Money The Vulnerable: Talene Yacoubian The Veteran: Russ Hille The Adapter: Rachel Brewster The Administrator: Jay Walsh The Well-Heeled: Donald Bowden The Crowd-Funder: Heidi Moretti Anatomy of a Grant: Michael Imperiale >> Editorial p. 9; Policy Forum p. 41; Science Careers features by T. Gura and G. B. S. N. P. Varma at http://scim.ag/1dUhSB2; Science Podcast LETTER...