Exact maximum likelihood estimation of regression models with finite order moving average errors

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dc.contributor.author Pagan, AR
dc.contributor.author Nicholls, D
dc.date.accessioned 2011-02-07T06:25:52Z
dc.date.issued 1976-01
dc.identifier.citation Review of Economic Studies, 1976, 43 (135), pp. 383 - 387
dc.identifier.issn 0034-6527
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/13903
dc.description.abstract The article presents information on exact maximum likelihood estimation of regression models with finite order moving average errors. A number of procedures for the estimation of models with moving average error specifications already appear in the literature. All these methods are, basically, derived from a consideration of a function which dominates the likelihood function and which is, asymptotically, equivalent to it. Consequently these procedures are applicable to large sample situations. economist M.H. Pesaran, however, has considered the exact likelihood function and his procedure is applicable to small samples. Unfortunately his method is not one that can be easily extended to the case of moving averages of order higher than the first since, for these models, it is not a straightforward matter to set up the orthogonal transformation required to diagonalize the covariance matrix of the disturbance term. Yet, as economist K. Kang has emphasized, it is of some importance to be able to compute the exact maximum likelihood (ML) estimates, since the generalized least squares (GLS) estimates frequently imply a non-invertible process for the disturbance term, and, for identification purposes, it is necessary that the process be invertible. The article is directed at the situation arising when the GLS estimates do not satisfy invertibility whereas the ML estimates do, this lack of invertibility of the OLS estimates being brought about by the omission of the extra terms in the likelihood function
dc.format Yes
dc.publisher Wiley-Blackwell
dc.title Exact maximum likelihood estimation of regression models with finite order moving average errors
dc.type Journal Article
dc.parent Review of Economic Studies
dc.journal.volume 135
dc.journal.volume 43
dc.journal.number 135 en_US
dc.publocation USA en_US
dc.identifier.startpage 383 en_US
dc.identifier.endpage 387 en_US
dc.cauo.name BUS.School of Finance and Economics en_US
dc.conference Verified OK en_US
dc.for 1401 Economic Theory
dc.personcode 100844
dc.percentage 100 en_US
dc.classification.name Economic Theory 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
dc.description.keywords NA en_US
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Business
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
utslib.collection.history Uncategorised (ID: 363)
utslib.collection.history Closed (ID: 3)

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