Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/65679
Authors: 
Aßmann, Christian
Boysen-Hogrefe, Jens
Pape, Markus
Year of Publication: 
2012
Series/Report no.: 
Economics Working Paper, Christian-Albrechts-Universität Kiel, Department of Economics 2012-11
Abstract: 
Due to their well-known indeterminacies, factor models require identifying assumptions to guarantee unique parameter estimates. For Bayesian estimation, these identifying assumptions are usually implemented by imposing constraints on certain model parameters. This strategy, however, may result in posterior distributions with shapes that depend on the ordering of cross-sections in the data set. We propose an alternative approach, which relies on a sampler without the usual identifying constraints. Identification is reached ex-post based on a Procrustes transformation. Resulting posterior estimates are ordering invariant and show favorable properties with respect to convergence and statistical as well as numerical accuracy.
Subjects: 
Bayesian Estimation
Factor Models
Multimodality
Ordering Problem
Orthogonal Transformation
JEL: 
C11
C31
C38
C51
C52
Document Type: 
Working Paper

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