Confidence Contours For 2 Test Statistics For Non-nested Regression-models

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dc.contributor.author Hall, Tony en_US
dc.contributor.editor en_US
dc.date.accessioned 2011-02-07T06:26:12Z
dc.date.available 2011-02-07T06:26:12Z
dc.date.issued 1983 en_US
dc.identifier 2006014939 en_US
dc.identifier.citation Hall Anthony 1983, 'Confidence Contours For 2 Test Statistics For Non-nested Regression-models', Elsevier Science Sa Lausanne, vol. 21, no. 1, pp. 155-160. en_US
dc.identifier.issn 0304-4076 en_US
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/13942
dc.description.abstract In this note we use the concept of implicit null hypotheses introduced by Mizon and Richard (1982) to clarify the relationship between the two test procedures discussed by Pesaran (1974) for testing non-nested regression models. These procedures are, firstly, Pesaran?s version of the Cox (1961,1962) modified likelihood ratio test statistic and, secondly, the `comprehensive test? which is the usual classical test obtained from combining the two competing models. In particular, we suggest that the two testing procedures have markedly different confidence contours as a result of having different implicit null hypotheses, en_US
dc.language en_US
dc.publisher Elsevier Science Sa Lausanne en_US
dc.relation.isbasedon http://dx.doi.org/10.1016/0304-4076(83)90124-0 en_US
dc.title Confidence Contours For 2 Test Statistics For Non-nested Regression-models en_US
dc.parent Journal Of Econometrics en_US
dc.journal.volume 21 en_US
dc.journal.number 1 en_US
dc.publocation Lausanne 1 en_US
dc.identifier.startpage 155 en_US
dc.identifier.endpage 160 en_US
dc.cauo.name BUS.School of Finance and Economics en_US
dc.conference Verified OK en_US
dc.for 140302 en_US
dc.personcode 970384 en_US
dc.percentage 100 en_US
dc.classification.name Econometric and Statistical Methods 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 ISI:A1983QF49800009 en_US
dc.description.keywords NA en_US
dc.staffid en_US
dc.staffid 970384 en_US


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