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

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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)

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.

Suggested Citation

  • Chandra Shalini & Tyagi Gargi, 2017. "On the Performance of Some Biased Estimators in a Misspecified Model with Correlated Regressors," Statistics in Transition New Series, Polish Statistical Association, vol. 18(1), pages 27-52, March.
    • Handle: RePEc:vrs:stintr:v:18:y:2017:i:1:p:27-52:n:4
    DOI: 10.21307/stattrans-2016-056
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    References listed on IDEAS

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    1. M. Özkale & Selahattin Kaçıranlar, 2008. "Comparisons of the r − k class estimator to the ordinary least squares estimator under the Pitman’s closeness criterion," Statistical Papers, Springer, vol. 49(3), pages 503-512, July.
    2. Wijekoon, P. & Trenkler, G., 1989. "Mean square error matrix superiority of estimators under linear restrictions and misspecification," Economics Letters, Elsevier, vol. 30(2), pages 141-149, August.
    3. Nityananda Sarkar, 1989. "Comparisons among some estimators in misspecified linear models with multicollinearity," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 41(4), pages 717-724, December.
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    5. Sarkar, Nityananda, 1996. "Mean square error matrix comparison of some estimators in linear regressions with multicollinearity," Statistics & Probability Letters, Elsevier, vol. 30(2), pages 133-138, October.
    6. Kadiyala, Krishna, 1986. "Mixed regression estimator under misspecification," Economics Letters, Elsevier, vol. 21(1), pages 27-30.
    7. Shalini Chandra & Nityananda Sarkar, 2015. "Comparison of the r - (k, d) Class Estimator with some Estimators for Multicollinearity under the Mahalanobis Loss Function," International Econometric Review (IER), Econometric Research Association, vol. 7(1), pages 1-12, April.
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