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

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dc.contributor.authorJochmann, Markus
dc.contributor.authorKoop, Gary
dc.contributor.authorLeon-Gonzalez, Roberto
dc.contributor.authorStrachan, Rodney
dc.date.accessioned2015-12-07T22:46:02Z
dc.date.issued2011
dc.date.updated2015-12-07T11:36:50Z
dc.description.abstractThis 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.
dc.identifier.issn0883-7252
dc.identifier.urihttp://hdl.handle.net/1885/25605
dc.publisherJohn Wiley & Sons Inc
dc.sourceJournal of Applied Econometrics
dc.titleStochastic Search Variable Selection in Vector Error Correction Models with an Application to the Model of the UK Macroeconomy
dc.typeJournal article
local.contributor.affiliationJochmann, Markus, Univeristy of Strathclyde
local.contributor.affiliationKoop, Gary, University of Strathclyde
local.contributor.affiliationLeon-Gonzalez, Roberto, National Graduate Institute of Policy Studies
local.contributor.affiliationStrachan, Rodney, College of Business and Economics, ANU
local.contributor.authoruidStrachan, Rodney, u4823922
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor140302 - Econometric and Statistical Methods
local.identifier.absfor010406 - Stochastic Analysis and Modelling
local.identifier.absseo910101 - Balance of Payments
local.identifier.ariespublicationu4602557xPUB39
local.identifier.citationvolumeonline: 28 MAR 2011
local.identifier.doi10.1002/jae.1238
local.identifier.scopusID2-s2.0-84872683965
local.identifier.thomsonID000313881100003
local.type.statusPublished Version

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