Estimation of regression coefficients of interest when other regression coefficients are of no interest : The case of non-normal errors

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Original languageEnglish
Pages (from-to)803-810
Journal / PublicationStatistics and Probability Letters
Volume77
Issue number8
Publication statusPublished - 15 Apr 2007

Abstract

This note considers the problem of estimating regression coefficients when some other coefficients in the model are of no interest. For the case of normal errors, Magnus and Durbin [1999. Estimation of regression coefficients of interest when other regression coefficients are of no interest. Econometrica 67, 639-643] and Danilov and Magnus [2004. On the harm that ignoring pretesting can cause. J. Econometrics 122, 27-46] studied this problem and established an equivalence theorem which states that the problem of estimating the coefficients of interest is equivalent to that of finding an optimal estimator of the vector of coefficients of no interest given a single observation from a normal distribution. The aim of this note is to generalize their findings to the large sample non-normal errors case. Some applications of our results are also given. © 2007 Elsevier B.V. All rights reserved.

Research Area(s)

  • Asymptotic risk, Non-normal errors, Weighted estimators

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