The power of cointegration tests versus data frequency and time spans.
Using Monte Carlo methods, this study illustrates the potential benefits of using high frequency data series to conduct cointegration analysis. The study also provides an account of why the results are different from those reported by Hakkio and Rush (1991). The simulation results show that when the...
| Publicado en: | Southern Economic Journal Vol. 67; no. 4; pp. 906 - 922 |
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| Formato: | Artículo |
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Southern Economic Association
April 2001
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=510141010&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 510141010 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00384038 SEJ jtl: Southern Economic Journal issn: 00384038 maglogo: N pubinfo: dt: April 2001 vid: 67 iid: 4 pid: 1482 pub: Southern Economic Association artinfo: ui: 510141010 10.2307/1061577 ppf: 906 ppct: 16 formats: fmt: @attributes: type: T tig: atl: The power of cointegration tests versus data frequency and time spans. aug: au: Zhou, Su su: Monte Carlo method Econometric models sug: subj: Monte Carlo method Econometric models ab: Using Monte Carlo methods, this study illustrates the potential benefits of using high frequency data series to conduct cointegration analysis. The study also provides an account of why the results are different from those reported by Hakkio and Rush (1991). The simulation results show that when the studies are restricted by relatively short time spans of 30 to 50 years, increasing data frequency may yield considerable power gain and less size distortion, especially when the cointegrating residual is not nearly nonstationary, and/or when the models with nonzero lag orders are required for testing cointegration. The study may help clarify some misconceptions and misinterpretations surrounding the role of data frequency and sample size in cointegration analysis. Reprinted by permission of the publisher. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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