Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/195466
Authors: 
Yang, Yukai
Bauwens, Luc
Year of Publication: 
2018
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 6 [Year:] 2018 [Issue:] 4 [Pages:] 1-22
Abstract: 
We develop novel multivariate state-space models wherein the latent states evolve on the Stiefel manifold and follow a conditional matrix Langevin distribution. The latent states correspond to time-varying reduced rank parameter matrices, like the loadings in dynamic factor models and the parameters of cointegrating relations in vector error-correction models. The corresponding nonlinear filtering algorithms are developed and evaluated by means of simulation experiments.
Subjects: 
state-space models
Stiefel manifold
matrix Langevin distribution
filtering
smoothing
Laplace method
dynamic factor model
cointegration
JEL: 
C32
C51
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article
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