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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 ()
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Rodney Strachan: University of Queensland

No 919, Working Papers from University of Strathclyde Business School, Department of Economics

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)
JEL-codes: C11 C32 C52 (search for similar items in EconPapers)
Pages: 47 pages
Date: 2009-10
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
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Citations: View citations in EconPapers (4)

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http://www.strath.ac.uk/media/1newwebsite/departme ... apers/2009/09-19.pdf (application/pdf)

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) Downloads
Working Paper: Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy (2009) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:str:wpaper:0919

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