Tests for the null hypothesis of cointegration: a Monte Carlo comparison

Detalhes bibliográficos
Autor(a) principal: Gabriel, Vasco J.
Data de Publicação: 2001
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/1439
Resumo: The aim of this paper is to compare the relative performance of several tests for the null hypothesis of cointegration, in terms of size and power in finite samples. This is carried out resorting to Monte Carlo simulations, considering a range of plausible data-generating processes. As of this writing, there is no study providing guidance on the use of this type of procedures in empirical situations, with the exception of the limited studies of McCabe et al. (1997) and Haug (1996). We also analyse the impact on size and power of choosing different procedures to estimate the long-run variance of the errors. we found that the parametrically adjusted test of McCabe et al. (1997) is the most well-balanced test in terms of power and size distrortions.
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spelling Tests for the null hypothesis of cointegration: a Monte Carlo comparisonCointegrationTestsMonte CarloThe aim of this paper is to compare the relative performance of several tests for the null hypothesis of cointegration, in terms of size and power in finite samples. This is carried out resorting to Monte Carlo simulations, considering a range of plausible data-generating processes. As of this writing, there is no study providing guidance on the use of this type of procedures in empirical situations, with the exception of the limited studies of McCabe et al. (1997) and Haug (1996). We also analyse the impact on size and power of choosing different procedures to estimate the long-run variance of the errors. we found that the parametrically adjusted test of McCabe et al. (1997) is the most well-balanced test in terms of power and size distrortions.Universidade do Minho. Núcleo de Investigação em Políticas Económicas (NIPE)Universidade do MinhoGabriel, Vasco J.2001-022001-02-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/1439enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:32:16Zoai:repositorium.sdum.uminho.pt:1822/1439Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:27:34.856780Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Tests for the null hypothesis of cointegration: a Monte Carlo comparison
title Tests for the null hypothesis of cointegration: a Monte Carlo comparison
spellingShingle Tests for the null hypothesis of cointegration: a Monte Carlo comparison
Gabriel, Vasco J.
Cointegration
Tests
Monte Carlo
title_short Tests for the null hypothesis of cointegration: a Monte Carlo comparison
title_full Tests for the null hypothesis of cointegration: a Monte Carlo comparison
title_fullStr Tests for the null hypothesis of cointegration: a Monte Carlo comparison
title_full_unstemmed Tests for the null hypothesis of cointegration: a Monte Carlo comparison
title_sort Tests for the null hypothesis of cointegration: a Monte Carlo comparison
author Gabriel, Vasco J.
author_facet Gabriel, Vasco J.
author_role author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Gabriel, Vasco J.
dc.subject.por.fl_str_mv Cointegration
Tests
Monte Carlo
topic Cointegration
Tests
Monte Carlo
description The aim of this paper is to compare the relative performance of several tests for the null hypothesis of cointegration, in terms of size and power in finite samples. This is carried out resorting to Monte Carlo simulations, considering a range of plausible data-generating processes. As of this writing, there is no study providing guidance on the use of this type of procedures in empirical situations, with the exception of the limited studies of McCabe et al. (1997) and Haug (1996). We also analyse the impact on size and power of choosing different procedures to estimate the long-run variance of the errors. we found that the parametrically adjusted test of McCabe et al. (1997) is the most well-balanced test in terms of power and size distrortions.
publishDate 2001
dc.date.none.fl_str_mv 2001-02
2001-02-01T00:00:00Z
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dc.language.iso.fl_str_mv eng
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dc.publisher.none.fl_str_mv Universidade do Minho. Núcleo de Investigação em Políticas Económicas (NIPE)
publisher.none.fl_str_mv Universidade do Minho. Núcleo de Investigação em Políticas Económicas (NIPE)
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