Testing unit root based on partially adaptive estimation
Autor(a) principal: | |
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Data de Publicação: | 2004 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional do FGV (FGV Repositório Digital) |
Texto Completo: | http://hdl.handle.net/10438/887 |
Resumo: | This paper proposes unit tests based on partially adaptive estimation. The proposed tests provide an intermediate class of inference procedures that are more efficient than the traditional OLS-based methods and simpler than unit root tests based on fully adptive estimation using nonparametric methods. The limiting distribution of the proposed test is a combination of standard normal and the traditional Dickey-Fuller (DF) distribution, including the traditional ADF test as a special case when using Gaussian density. Taking into a account the well documented characteristic of heavy-tail behavior in economic and financial data, we consider unit root tests coupled with a class of partially adaptive M-estimators based on the student-t distributions, wich includes te normal distribution as a limiting case. Monte Carlo Experiments indicate that, in the presence of heavy tail distributions or innovations that are contaminated by outliers, the proposed test is more powerful than the traditional ADF test. We apply the proposed test to several macroeconomic time series that have heavy-tailed distributions. The unit root hypothesis is rejected in U.S. real GNP, supporting the literature of transitory shocks in output. However, evidence against unit roots is not found in real exchange rate and nominal interest rate even haevy-tail is taken into a account. |
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Xiao, ZhijieLima, Luiz RenatoEscolas::EPGEFGV2008-05-13T15:39:13Z2008-05-13T15:39:13Z2004-03-010104-8910http://hdl.handle.net/10438/887This paper proposes unit tests based on partially adaptive estimation. The proposed tests provide an intermediate class of inference procedures that are more efficient than the traditional OLS-based methods and simpler than unit root tests based on fully adptive estimation using nonparametric methods. The limiting distribution of the proposed test is a combination of standard normal and the traditional Dickey-Fuller (DF) distribution, including the traditional ADF test as a special case when using Gaussian density. Taking into a account the well documented characteristic of heavy-tail behavior in economic and financial data, we consider unit root tests coupled with a class of partially adaptive M-estimators based on the student-t distributions, wich includes te normal distribution as a limiting case. Monte Carlo Experiments indicate that, in the presence of heavy tail distributions or innovations that are contaminated by outliers, the proposed test is more powerful than the traditional ADF test. We apply the proposed test to several macroeconomic time series that have heavy-tailed distributions. The unit root hypothesis is rejected in U.S. real GNP, supporting the literature of transitory shocks in output. However, evidence against unit roots is not found in real exchange rate and nominal interest rate even haevy-tail is taken into a account.engEscola de Pós-Graduação em Economia da FGVEnsaios Econômicos;528Testing unit root based on partially adaptive estimationinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleEconomiaEconomiaAnálise de séries temporaisEconometriareponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVinfo:eu-repo/semantics/openAccessORIGINAL1549.pdfapplication/pdf312234https://repositorio.fgv.br/bitstreams/8162494d-aa2b-41ea-9dd9-2ddc37fc625f/downloadef978ff5fff41efedbdb126a489fe191MD51TEXT1549.pdf.txt1549.pdf.txtExtracted texttext/plain132531https://repositorio.fgv.br/bitstreams/549a61ed-1d0c-4a1d-b85c-4e6b1c8b050e/download8a2b5a49ca6b15d35cc9acd7e3e6ebf7MD56THUMBNAIL1549.pdf.jpg1549.pdf.jpgGenerated Thumbnailimage/jpeg3213https://repositorio.fgv.br/bitstreams/168c0b7b-e66b-42cf-9dfb-08292b9605a0/download8efab102488d948608476310187ed487MD5710438/8872023-11-09 21:52:59.483open.accessoai:repositorio.fgv.br:10438/887https://repositorio.fgv.brRepositório InstitucionalPRIhttp://bibliotecadigital.fgv.br/dspace-oai/requestopendoar:39742023-11-09T21:52:59Repositório Institucional do FGV (FGV Repositório Digital) - Fundação Getulio Vargas (FGV)false |
dc.title.eng.fl_str_mv |
Testing unit root based on partially adaptive estimation |
title |
Testing unit root based on partially adaptive estimation |
spellingShingle |
Testing unit root based on partially adaptive estimation Xiao, Zhijie Economia Economia Análise de séries temporais Econometria |
title_short |
Testing unit root based on partially adaptive estimation |
title_full |
Testing unit root based on partially adaptive estimation |
title_fullStr |
Testing unit root based on partially adaptive estimation |
title_full_unstemmed |
Testing unit root based on partially adaptive estimation |
title_sort |
Testing unit root based on partially adaptive estimation |
author |
Xiao, Zhijie |
author_facet |
Xiao, Zhijie Lima, Luiz Renato |
author_role |
author |
author2 |
Lima, Luiz Renato |
author2_role |
author |
dc.contributor.unidadefgv.por.fl_str_mv |
Escolas::EPGE |
dc.contributor.affiliation.none.fl_str_mv |
FGV |
dc.contributor.author.fl_str_mv |
Xiao, Zhijie Lima, Luiz Renato |
dc.subject.area.por.fl_str_mv |
Economia |
topic |
Economia Economia Análise de séries temporais Econometria |
dc.subject.bibliodata.por.fl_str_mv |
Economia Análise de séries temporais Econometria |
description |
This paper proposes unit tests based on partially adaptive estimation. The proposed tests provide an intermediate class of inference procedures that are more efficient than the traditional OLS-based methods and simpler than unit root tests based on fully adptive estimation using nonparametric methods. The limiting distribution of the proposed test is a combination of standard normal and the traditional Dickey-Fuller (DF) distribution, including the traditional ADF test as a special case when using Gaussian density. Taking into a account the well documented characteristic of heavy-tail behavior in economic and financial data, we consider unit root tests coupled with a class of partially adaptive M-estimators based on the student-t distributions, wich includes te normal distribution as a limiting case. Monte Carlo Experiments indicate that, in the presence of heavy tail distributions or innovations that are contaminated by outliers, the proposed test is more powerful than the traditional ADF test. We apply the proposed test to several macroeconomic time series that have heavy-tailed distributions. The unit root hypothesis is rejected in U.S. real GNP, supporting the literature of transitory shocks in output. However, evidence against unit roots is not found in real exchange rate and nominal interest rate even haevy-tail is taken into a account. |
publishDate |
2004 |
dc.date.issued.fl_str_mv |
2004-03-01 |
dc.date.accessioned.fl_str_mv |
2008-05-13T15:39:13Z |
dc.date.available.fl_str_mv |
2008-05-13T15:39:13Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10438/887 |
dc.identifier.issn.none.fl_str_mv |
0104-8910 |
identifier_str_mv |
0104-8910 |
url |
http://hdl.handle.net/10438/887 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartofseries.por.fl_str_mv |
Ensaios Econômicos;528 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Escola de Pós-Graduação em Economia da FGV |
publisher.none.fl_str_mv |
Escola de Pós-Graduação em Economia da FGV |
dc.source.none.fl_str_mv |
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