Koop, G.M. and Leon-Gonzalez, Roberto and Strachan, Rodney W. (2005) Efficient posterior simulation in cointegration models with priors on the cointegration space. Working paper. University of Leicester.
Download (296kB) | Preview
A message coming out of the recent Bayesian literature on cointegration is that it is important to elicit a prior on the space spanned by the cointegrating vectors (as opposed to a particular identi�ed choice for these vectors). In this note, we discuss a sensible way of eliciting such a prior. Furthermore, we develop a collapsed Gibbs sampling algorithm to carry out e¢ cient posterior simulation in cointegration models. The computational advantages of our algorithm are most pronounced with our model, since the form of our prior precludes simple posterior simulation using conventional methods (e.g. a Gibbs sampler involves non-standard posterior conditionals). However, the theory we draw upon implies our algorithm will be more e¢ cient even than the posterior simulation methods which are used with identi�ed versions of cointegration models.
|Item type:||Monograph (Working paper)|
|Notes:||New revised version including the parameter augmented Gibbs sampler, forthcoming Econometric Reviews.|
|Keywords:||posterior simulation, cointegration models, cointegration space, bayesian, economics, statistics, Economic Theory, Statistics|
|Subjects:||Social Sciences > Economic Theory
Social Sciences > Statistics
|Department:||Strathclyde Business School > Economics|
|Depositing user:||Strathprints Administrator|
|Date Deposited:||19 Mar 2009 15:40|
|Last modified:||22 May 2015 08:50|
Actions (login required)