On the Performance of Some Biased Estimators in a Misspecified Model with Correlated Regressors

Chandra Shalini () and Tyagi Gargi ()
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Chandra Shalini: Department of Mathematics & Statistics, Banasthali Vidyapith, Banasthali, 304022 India
Tyagi Gargi: Department of Mathematics & Statistics, Banasthali Vidyapith, Banasthali, 304022 India

Statistics in Transition New Series, 2017, vol. 18, issue 1, 27-52

Abstract: In this paper, the effect of misspecification due to omission of relevant variables on the dominance of the r -(k,d) class estimator proposed by Özkale (2012), over the ordinary least squares (OLS) estimator and some other competing estimators when some of the regressors in the linear regression model are correlated, have been studied with respect to the mean squared error criterion. A simulation study and numerical example have been demostrated to compare the performance of the estimators for some selected values of the parameters involved.

Keywords: omission of relevant variables; multicollinearity; r -(k; d) class estimator; mean squared error (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:stintr:v:18:y:2017:i:1:p:27-52:n:4

DOI: 10.21307/stattrans-2016-056

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