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

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Author Info

  • Jochmann, Markus
  • Koop, Gary
  • Leon-Gonzalez
  • Strachan, Rodney W.

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.

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File URL: http://repo.sire.ac.uk/handle/10943/89
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Bibliographic Info

Paper provided by Scottish Institute for Research in Economics (SIRE) in its series SIRE Discussion Papers with number 2009-44.

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Date of creation: 2009
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Handle: RePEc:edn:sirdps:89

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Related research

Keywords: Bayesian; cointegration; model averaging; model selection; Markov chain Monte Carlo;

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Cited by:
  1. Senbeta Sisay R., 2012. "How important are external shocks in explaining growth in Sub-Saharan Africa? Evidence from a Bayesian VAR," Working Papers 2012010, University of Antwerp, Faculty of Applied Economics.
  2. Jochmann, Markus & Koop, Gary, 2011. "Regime-Switching Cointegration," SIRE Discussion Papers 2011-60, Scottish Institute for Research in Economics (SIRE).

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