Orthogonality tests with de-trended data: Interpreting Monte-Carlo results using Nagar expansions

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dc.contributor.author Dolado, Juan José
dc.contributor.author Banerjee, Anindya
dc.contributor.author Galbraith, John W.
dc.date.accessioned 2012-12-19T17:00:57Z
dc.date.available 2012-12-19T17:00:57Z
dc.date.issued 1990-01
dc.identifier.bibliographicCitation Economics Letters, 1990, 32, 1, p. 19-24
dc.identifier.issn 0165-1765
dc.identifier.uri http://hdl.handle.net/10016/3322
dc.description.abstract We extend previous results concerning the behaviour of a finite-sample approximation to the distribution of the t-statistic used in testing orthogonality of a variable to a given information set. In particular, we look at the case in which the data are de-trended, innovations in the explanatory variable are correlated with the regressand, and the explanatory variable is substantially autocorrelated.
dc.format.mimetype text/plain
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Elsevier
dc.rights © Elsevier
dc.subject.other Estadística matemática
dc.subject.other Método de Monte Carlo
dc.title Orthogonality tests with de-trended data: Interpreting Monte-Carlo results using Nagar expansions
dc.type article
dc.type.review PeerReviewed
dc.description.status Publicado
dc.relation.publisherversion http://dx.doi.org/10.1016/0165-1765(90)90044-2
dc.subject.eciencia Economía
dc.identifier.doi 10.1016/0165-1765(90)90044-2
dc.rights.accessRights openAccess
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 19
dc.identifier.publicationissue 1
dc.identifier.publicationlastpage 24
dc.identifier.publicationtitle Economic Letters
dc.identifier.publicationvolume 32
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