European Business Schools Librarian's Group

SSE/EFI Working Paper Series in Economics and Finance,
Stockholm School of Economics

No 565: Parametric covariance matrix modeling in Bayesian panel regression

Mickael Salabasis ()
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Mickael Salabasis: UC AB, Postal: Analyssektionen, SE-117 88 Stockholm, Sweden

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.

Keywords: Bayesian panel regression; parametric covariance; model selection

JEL-codes: C11; C33; C63

23 pages, First version: September 17, 2004. Revised: February 16, 2005.

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