On the performance of some biased estimators in a  misspecified model with correlated regressors

Shalini  Chandra; Gargi  Tyagi

doi:https://doi.org/10.59170/stattrans-2017-002

On the performance of some biased estimators in a misspecified model with correlated regressors

Shalini Chandra Department of Mathematics & Statistics, Banasthali Vidyapith, Banasthali - 304022 India. , Gargi Tyagi Department of Mathematics & Statistics, Banasthali Vidyapith, Banasthali - 304022 India. Statistics in Transition new series, vol. 18, 2017, 1, pages: 27-52 Published online: 1 March 2017 https://doi.org/10.59170/stattrans-2017-002

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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

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