Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

Detalhes bibliográficos
Autor(a) principal: Athanasopoulos, George
Data de Publicação: 2011
Outros Autores: Guillen, Osmani Teixeira Carvalho, Issler, João Victor, Vahid, Farshid
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
Texto Completo: http://hdl.handle.net/10438/7813
Resumo: We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. A Monte Carlo study explores the finite sample performance of this procedure and evaluates the forecasting accuracy of models selected by this procedure. Two empirical applications confirm the usefulness of the model selection procedure proposed here for forecasting.
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spelling Athanasopoulos, GeorgeGuillen, Osmani Teixeira CarvalhoIssler, João VictorVahid, FarshidEscolas::EPGEFGV2011-01-27T13:35:17Z2011-01-27T13:35:17Z2011-01-270104-8910http://hdl.handle.net/10438/7813We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. A Monte Carlo study explores the finite sample performance of this procedure and evaluates the forecasting accuracy of models selected by this procedure. Two empirical applications confirm the usefulness of the model selection procedure proposed here for forecasting.engFundação Getulio Vargas. Escola de Pós-graduação em EconomiaEnsaios Econômicos;713Reduced rank modelsModel selection criteriaForecasting accuracyEconomiaAnálise de regressãoModelos macroeconômicosPrevisão econômicaMonte Carlo, Método deMétodos de simulaçãoEconomiaModel selection, estimation and forecasting in VAR models with short-run and long-run restrictionsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlereponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVinfo:eu-repo/semantics/openAccessLICENSElicense.txtlicense.txttext/plain; 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dc.title.eng.fl_str_mv Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
title Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
spellingShingle Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
Athanasopoulos, George
Reduced rank models
Model selection criteria
Forecasting accuracy
Economia
Análise de regressão
Modelos macroeconômicos
Previsão econômica
Monte Carlo, Método de
Métodos de simulação
Economia
title_short Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
title_full Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
title_fullStr Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
title_full_unstemmed Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
title_sort Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
author Athanasopoulos, George
author_facet Athanasopoulos, George
Guillen, Osmani Teixeira Carvalho
Issler, João Victor
Vahid, Farshid
author_role author
author2 Guillen, Osmani Teixeira Carvalho
Issler, João Victor
Vahid, Farshid
author2_role author
author
author
dc.contributor.unidadefgv.por.fl_str_mv Escolas::EPGE
dc.contributor.affiliation.none.fl_str_mv FGV
dc.contributor.author.fl_str_mv Athanasopoulos, George
Guillen, Osmani Teixeira Carvalho
Issler, João Victor
Vahid, Farshid
dc.subject.eng.fl_str_mv Reduced rank models
Model selection criteria
Forecasting accuracy
topic Reduced rank models
Model selection criteria
Forecasting accuracy
Economia
Análise de regressão
Modelos macroeconômicos
Previsão econômica
Monte Carlo, Método de
Métodos de simulação
Economia
dc.subject.area.por.fl_str_mv Economia
dc.subject.bibliodata.por.fl_str_mv Análise de regressão
Modelos macroeconômicos
Previsão econômica
Monte Carlo, Método de
Métodos de simulação
Economia
description We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. A Monte Carlo study explores the finite sample performance of this procedure and evaluates the forecasting accuracy of models selected by this procedure. Two empirical applications confirm the usefulness of the model selection procedure proposed here for forecasting.
publishDate 2011
dc.date.accessioned.fl_str_mv 2011-01-27T13:35:17Z
dc.date.available.fl_str_mv 2011-01-27T13:35:17Z
dc.date.issued.fl_str_mv 2011-01-27
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10438/7813
dc.identifier.issn.none.fl_str_mv 0104-8910
identifier_str_mv 0104-8910
url http://hdl.handle.net/10438/7813
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartofseries.por.fl_str_mv Ensaios Econômicos;713
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Fundação Getulio Vargas. Escola de Pós-graduação em Economia
publisher.none.fl_str_mv Fundação Getulio Vargas. Escola de Pós-graduação em Economia
dc.source.none.fl_str_mv reponame:Repositório Institucional do FGV (FGV Repositório Digital)
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