Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy

Markus Jochmann (), Gary Koop, Roberto Leon-Gonzalez and Rodney Strachan

No 2009-44, SIRE Discussion Papers from Scottish Institute for Research in Economics (SIRE)

Abstract: This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.

Keywords: Bayesian; cointegration; model averaging; model selection; Markov chain Monte Carlo (search for similar items in EconPapers)
Date: 2009
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http://hdl.handle.net/10943/89
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Related works:
Journal Article: Stochastic search variable selection in vector error correction models with an application to a model of the UK macroeconomy (2013)
Working Paper: Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy (2009)
Working Paper: Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:edn:sirdps:89

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