Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/56184
Authors: 
Salabasis, Mickael
Year of Publication: 
2004
Series/Report no.: 
SSE/EFI Working Paper Series in Economics and Finance 565
Abstract: 
The full Bayesian treatment of error component models typically relies on data augmentation to produce the required inference. Never stricly necessary a direct approach is always possible though not necessarily practical. The mechanics of direct sampling are outlined and a template for including model uncertainty is described. The needed tools, relying on various Markov chain Monte Carlo techniques, are developed and direct sampling, with and without effect selection, is illustrated.
Subjects: 
Bayesian panel regression
parametric covariance
model selection
JEL: 
C11
C33
C63
Document Type: 
Working Paper

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