Bayesian analysis of dynamic factor models: An ex-post approach towards the rotation problem

Arbeitspapier

Due to their indeterminacies, static and dynamic factor models require identifying assumptions to guarantee uniqueness of the parameter estimates. The indeterminacy of the parameter estimates with respect to orthogonal transformations is known as the rotation problem. The typical strategy in Bayesian factor analysis to solve the rotation problem is to introduce ex-ante constraints on certain model parameters via degenerate and truncated prior distributions. This strategy, however, results in posterior distributions whose shapes depend on the ordering of the variables in the data set. We propose an alternative approach where the rotation problem is solved ex-post using Procrustean postprocessing. The resulting order invariance of the posterior estimates is illustrated in a simulation study and an empirical application using a well-known data set containing 120 macroeconomic time series. Favorable properties of the ex-post approach with respect to convergence, statistical and numerical accuracy are revealed.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Kiel Working Paper ; No. 1902

Classification and Topics

• Classification: Wirtschaft ; Bayesian Analysis: General ; Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models ; Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models ; Model Construction and Estimation ; Model Evaluation, Validation, and Selection
• Subject: Bayesian Estimation ; Factor Models ; Multimodality ; Rotation Problem ; Ordering Problem ; Orthogonal Transformation

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Aßmann, Christian ; Boysen-Hogrefe, Jens ; Pape, Markus
• Event: Veröffentlichung
• (who): Kiel Institute for the World Economy (IfW)
• (where): Kiel
• (when): 2014

Further information

• Handle: http://hdl.handle.net/10419/92369
• Last update: 10.03.2025, 11:43 AM CET