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dc.contributor.author Geweke, J
dc.date.accessioned 2012-02-02T11:14:01Z
dc.date.issued 2010-04
dc.identifier.citation International Journal of Forecasting, 2010, 26 (2), pp. 435 - 438
dc.identifier.issn 0169-2070
dc.identifier.other C2 en_US
dc.identifier.uri http://hdl.handle.net/10453/16823
dc.description.abstract The article by Zellner and Ando proposes methods for coping with the excess kurtosis that is often observed in disturbances in applications of the seemingly unrelated regressions (SUR) model. This is an important topic which is of particular relevance in forecasting. However, the proposed methods do not address the problem: the direct Monte Carlo (DMC) algorithm is incorrect and the proposed variant of the Student-t distribution cannot account for thick tails in the distribution of disturbances in the SUR model. © 2010 International Institute of Forecasters.
dc.language eng
dc.relation.isbasedon 10.1016/j.ijforecast.2010.01.006
dc.title Comment
dc.type Journal Article
dc.parent International Journal of Forecasting
dc.journal.volume 2
dc.journal.volume 26
dc.journal.number 2 en_US
dc.publocation Netherlands, United States en_US
dc.identifier.startpage 435 en_US
dc.identifier.endpage 438 en_US
dc.cauo.name BUS.Faculty of Business en_US
dc.conference Verified OK en_US
dc.for 1403 Econometrics
dc.personcode 101228
dc.percentage 100 en_US
dc.classification.name Econometrics en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Business
pubs.organisational-group /University of Technology Sydney/Faculty of Business/Economics
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
pubs.consider-herdc false
utslib.collection.history Closed (ID: 3)


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