Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/7101
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dc.contributor.authorCanepa, A-
dc.date.accessioned2013-01-07T15:15:11Z-
dc.date.available2013-01-07T15:15:11Z-
dc.date.issued2012-
dc.identifier.citationEconomics and Finance Working Paper, Brunel University, 12-10, Jun 2012en_US
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/7101-
dc.description.abstractJohansen's (2000) Bartlett correction factor for the LR test of linear restrictions on cointegrated vectors is derived under the i.i.d. Gaussian assumption for the innovation terms. However, the distribution of most data relating to financial variables are fat-tailed and often skewed, there is therefore a need to examine small sample inference procedures that require weaker assumptions for the innovation term. This paper suggests that using a non-parametric bootstrap to approximate a Bartlett-type correction provides a statistic that does not require specification of the innovation distribution and can be used by applied econometricians to perform a small sample inference procedure that is less computationally demanding than estimating the p-value of the observed statistic.en_US
dc.language.isoenen_US
dc.publisherBrunel Universityen_US
dc.subjectCointegrationen_US
dc.subjectBootstrapen_US
dc.subjectBartlett correctionen_US
dc.titleRobust Bartlett adjustment for hypotheses testing on cointegrating vectors: A bootstrap approachen_US
dc.typeArticleen_US
pubs.organisational-data/Brunel-
pubs.organisational-data/Brunel/Brunel Active Staff-
pubs.organisational-data/Brunel/Brunel Active Staff/School of Social Sciences-
pubs.organisational-data/Brunel/Brunel Active Staff/School of Social Sciences/Economics and Finance-
pubs.organisational-data/Brunel/Group Publication Pages-
pubs.organisational-data/Brunel/University Research Centres and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups-
pubs.organisational-data/Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups/Centre for the Analysis of Risk and Optimisation Modelling Applications-
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Dept of Economics and Finance Research Papers

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