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Bayesian Inference in a Cointegrating Panel Data Model Author info | Abstract | Publisher info | Download info | Related research | Statistics Gary Koop () (University of Strathclyde, UK and Rimini Centre for Economic Analysis, Rimini, Italy)
Roberto Leon-Gonzalez () (University of Leicester, UK and University of Queensland)
Rodney Strachan () (University of Queensland)
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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.
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Paper provided by Rimini Centre for Economic Analysis in its series Working Paper Series with number
02-07.
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Date of creation: Jul 2007Date of revision:
Jul 2007Handle: RePEc:rim:rimwps:02-07Contact details of provider: Web page: http://www.rcfea.org More information through EDIRC
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Keywords: Bayesian ; panel data cointegration ; error correction model ; reduced rank regression ; Markov Chain Monte Carlo. ; Other versions of this item:
Find related papers by JEL classification: C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data
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