Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/32262
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dc.contributor.authorSymeonides, SD-
dc.contributor.authorKaravias, Y-
dc.contributor.authorTzavalis, E-
dc.date.accessioned2025-10-31T19:30:59Z-
dc.date.available2025-10-31T19:30:59Z-
dc.date.issued2016-04-14-
dc.identifier.citationSymeonides, S.D., Karavias, Y. and Tzavalis, E. (2017) 'Size corrected significance tests in seemingly unrelated regressions with autocorrelated errors', Journal of Time Series Econometrics, 9 (1), pp. 1 - 39. doi: 10.1515/jtse-2015-0014.en_US
dc.identifier.issn1941-1928-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/32262-
dc.descriptionJEL Classification: CIO; C12; D24.en_US
dc.description.abstractRefined asymptotic methods are used to produce degrees-of-freedom-adjusted Edgeworth and Cornish-Fisher size corrections of the t and F testing procedures for the parameters of a S.U.R. model with serially correlated errors. The corrected tests follow the Student-t and F distributions, respectively, with an approximation error of order O(τ3), where τ = 1/√T and T is the number of time observations. Monte Carlo simulations provide evidence that the size corrections suggested hereby have better finite sample properties, compared to the asymptotic testing procedures (either standard or Edgeworth corrected), which do not adjust for the degrees of freedom.en_US
dc.format.extent1 - 41-
dc.format.mediumPrint-Electronic-
dc.language.isoen_USen_US
dc.publisherDe Gruyteren_US
dc.rightsCreative Commons Attribution-NonCommercial 4.0 International-
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/-
dc.subjectlinear regressionen_US
dc.subjectS.U.R. modelsen_US
dc.subjectstochastic expansionsen_US
dc.subjectasymptotic approximationsen_US
dc.subjectAR(1) errorsen_US
dc.titleSize corrected significance tests in seemingly unrelated regressions with autocorrelated errorsen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1515/jtse-2015-0014-
dc.relation.isPartOfJournal of Time Series Econometrics-
pubs.issue1-
pubs.publication-statusPublished-
pubs.volume9-
dc.identifier.eissn2194-6507-
dc.rights.licensehttps://creativecommons.org/licenses/by-nc/4.0/legalcode.en-
dc.rights.holderDe Gruyter-
Appears in Collections:Dept of Economics and Finance Research Papers

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