The Directional Identification Problem in Bayesian Factor Analysis: An Ex-Post Approach

Markus Pape, Christian Aßmann and Jens Boysen-Hogrefe

VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order from Verein für Socialpolitik / German Economic Association

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. Identi cation 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.

JEL-codes: C11 C31 C38 (search for similar items in EconPapers)
Date: 2013
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Related works:
Working Paper: The directional identification problem in Bayesian factor analysis: An ex-post approach (2012)
Working Paper: The directional identification problem in Bayesian factor analysis: An ex-post approach (2012)
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