Skip navigation
Skip navigation

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

Jochmann, Markus; Koop, Gary; Leon-Gonzalez, Roberto; Strachan, Rodney


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.

CollectionsANU Research Publications
Date published: 2011
Type: Journal article
Source: Journal of Applied Econometrics
DOI: 10.1002/jae.1238


File Description SizeFormat Image
01_Jochmann_Stochastic_Search_Variable_2011.pdf207.22 kBAdobe PDF    Request a copy

Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  12 November 2018/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator