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Bayesian Analysis of Stochastic and Deterministic Processes in The Error Correction Model

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Author Info
Strachan, Rodney (University of Liverpool)
Brett Inder

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Abstract

In this article a method for joint estimation of the number of stochastic trends and the deterministic processes in a multivariate error correction model is presented. This approach takes advantage of the Laplace method of approximating integrals and, the second important contribution of the paper, careful elicitation of the prior for the cointegrating vectors from a prior on the cointegrating space. The approach follows the classical approaches of James (1969), Anderson (1951) and Johansen (1988 and 1991) and performs well when used to estimate the number of stochastic trends compared with information criteria in finite samples in Monte Carlo experiments.

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File URL: http://repec.org/res2003/Strachan.pdf
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Publisher Info
Paper provided by Royal Economic Society in its series Royal Economic Society Annual Conference 2003 with number 197.

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Date of creation: 04 Jun 2003
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Handle: RePEc:ecj:ac2003:197

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Web page: http://www.res.org.uk/society/annualconf.asp
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Related research
Keywords: stochastic trend; deterministic trend; posterior probability; Grassman manifold; Stiefel manifold;

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

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