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, Rodney W. Strachan

Research output: Contribution to journalArticle

7 Citations (Scopus)


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.
Original languageEnglish
Number of pages20
JournalJournal of Applied Econometrics
Early online date28 Mar 2011
Publication statusPublished - 2012


  • stochastic search
  • vector error correction models
  • macroeconomics
  • United Kingdom

Cite this