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dc.contributor.author Wallace, Dudley en_US
dc.date.accessioned 2010-03-09T15:27:00Z
dc.date.available 2010-03-09T15:27:00Z
dc.date.issued 1972 en_US
dc.identifier.uri http://hdl.handle.net/10161/1870
dc.description.abstract The standard F test for linear restrictions in regression is relevant as a criterion but fails to capture the notion of tradeoff between bias and variance. Average squared distance criteria yield operational tests that are more appropriate, depending upon objectives. In the present paper two alternative criteria are developed. The first allows testing of the hypothesis that the average squared distance of a restricted estimator from the parameter point in k space is less than the average squared distance of the unrestricted, ordinary least squares estimator from the same parameter point. The second sets up a test of betterness of the restricted estimator over the unrestricted estimator of E(Y/X), where betterness is again defined in average squared distance. en_US
dc.format.extent 180419 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.publisher Econometrica en_US
dc.subject criteria en_US
dc.subject estimators en_US
dc.subject linear restrictions en_US
dc.title Weaker Criteria and Tests for Linear Restrictions in Regression en_US
dc.type Journal Article en_US
dc.department Economics

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