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Geweke, J

Comment

Geweke, J

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Publication Type:: Journal Article
Citation:: International Journal of Forecasting, 2010, 26 (2), pp. 435 - 438
Issue Date:: 2010-01-01

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Field	Value	Language
dc.contributor.author	Geweke, J	en_US
dc.date.issued	2010-01-01	en_US
dc.identifier.citation	International Journal of Forecasting, 2010, 26 (2), pp. 435 - 438	en_US
dc.identifier.issn	0169-2070	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.	en_US
dc.relation.ispartof	International Journal of Forecasting	en_US
dc.relation.isbasedon	10.1016/j.ijforecast.2010.01.006	en_US
dc.subject.classification	Econometrics	en_US
dc.title	Comment	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	26	en_US
utslib.for	1403 Econometrics	en_US
utslib.for	0104 Statistics	en_US
utslib.for	1505 Marketing	en_US
pubs.embargo.period	Not known	en_US
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 Discipline
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	26	en_US

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.

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http://hdl.handle.net/10453/16823