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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
Markus Jochmann () (Department of Economics, University of Strathclyde)
Gary Koop () (Department of Economics, University of Strathclyde)
Roberto Leon-Gonzalez () (National Graduate Institute for Policy Studies)
Rodney W. Strachan () (University of Queensland)

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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://www.strath.ac.uk/media/departments/economics/researchdiscussionpapers/2009/09-19.pdf
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Publisher Info
Paper provided by University of Strathclyde Business School, Department of Economics in its series Working Papers with number 09-19.

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Length: 47 pages
Date of creation: Oct 2009
Date of revision:
Handle: RePEc:str:wpaper:0919

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

Find related papers by JEL classification:
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing

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This page was last updated on 2009-11-12.


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