Bayesian Inference in a Cointegrating Panel Data Model

Gary Koop, Roberto Leon-Gonzalez and Rodney Strachan

Working Paper series from Rimini Centre for Economic Analysis

Abstract: This paper develops methods of Bayesian inference in a cointegrating panel data model. This model involves each cross-sectional unit having a vector error correction representation. It is flexible in the sense that different cross-sectional units can have different cointegration ranks and cointegration spaces. Furthermore, the parameters which characterize short-run dynamics and deterministic components are allowed to vary over cross-sectional units. In addition to a noninformative prior, we introduce an informative prior which allows for information about the likely location of the cointegration space and about the degree of similarity in coefficients in different cross-sectional units. A collapsed Gibbs sampling algorithm is developed which allows for efficient posterior inference. Our methods are illustrated using real and artificial data.

Keywords: Bayesian; panel data cointegration; error correction model; reduced rank regression; Markov Chain Monte Carlo (search for similar items in EconPapers)
JEL-codes: C11 C32 C33 (search for similar items in EconPapers)
Date: 2007-07
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http://www.rcea.org/RePEc/pdf/wp02_07.pdf (application/pdf)

Related works:
Chapter: Bayesian inference in a cointegrating panel data model (2008)
Working Paper: Bayesian Inference in a Cointegrating Panel Data Model (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:rim:rimwps:02_07

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