IDEAS home Printed from
   My bibliography  Save this article

Further improving the Stein-rule estimator using the Stein variance estimator in a misspecified linear regression model


  • Ohtani, Kazuhiro


In this paper, we consider a linear regression model when relevant regressors are omitted in the specified model. We examine the MSE dominance of the pre-test Stein-rule estimator of regression coefficients using the Stein-variance estimator over the traditional Stein-rule estimator of regression coefficients.

Suggested Citation

  • Ohtani, Kazuhiro, 1996. "Further improving the Stein-rule estimator using the Stein variance estimator in a misspecified linear regression model," Statistics & Probability Letters, Elsevier, vol. 29(3), pages 191-199, September.
  • Handle: RePEc:eee:stapro:v:29:y:1996:i:3:p:191-199

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Ohtani, Kazuhiro, 1993. "A Comparison of the Stein-Rule and Positive-Part Stein-Rule Estimators in a Misspecified Linear Regression Model," Econometric Theory, Cambridge University Press, vol. 9(04), pages 668-679, August.
    2. Ohtani, Kazuhiro, 1988. "Optimal levels of significance of a pre-test in estimating the disturbance variance after the pre-test for a linear hypothesis on coefficients in a linear regression," Economics Letters, Elsevier, vol. 28(2), pages 151-156.
    3. Gelfand, Alan E. & Dey, Dipak K., 1988. "Improved estimation of the disturbance variance in a linear regression model," Journal of Econometrics, Elsevier, vol. 39(3), pages 387-395, November.
    4. Giles, Judith A., 1991. "Pre-testing for linear restrictions in a regression model with spherically symmetric disturbances," Journal of Econometrics, Elsevier, vol. 50(3), pages 377-398, December.
    5. Berry, J. Calvin, 1994. "Improving the James-Stein estimator using the Stein variance estimator," Statistics & Probability Letters, Elsevier, vol. 20(3), pages 241-245, June.
    6. Mittelhammer, R.C., 1984. "Restricted least squares, pre-test, ols and stein rule estimators: Risk comparisons under model misspecification," Journal of Econometrics, Elsevier, vol. 25(1-2), pages 151-164.
    7. Kubokawa, Tatsuya, 1991. "An approach to improving the James-Stein estimator," Journal of Multivariate Analysis, Elsevier, vol. 36(1), pages 121-126, January.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Hu, Guikai & Yu, Shenghua & Luo, Han, 2015. "Comparisons of variance estimators in a misspecified linear model with elliptically contoured errors," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 266-276.
    2. Akio Namba & Kazuhiro Ohtani, 2007. "Risk comparison of the Stein-rule estimator in a linear regression model with omitted relevant regressors and multivariatet errors under the Pitman nearness criterion," Statistical Papers, Springer, vol. 48(1), pages 151-162, January.
    3. Kazuhiro Ohtani & Alan Wan, 2002. "ON THE USE OF THE STEIN VARIANCE ESTIMATOR IN THE DOUBLE k-CLASS ESTIMATOR IN REGRESSION," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 121-134.
    4. Ohtani, Kazuhiro, 1998. "Inadmissibility of the Stein-rule estimator under the balanced loss function," Journal of Econometrics, Elsevier, vol. 88(1), pages 193-201, November.
    5. Akio Namba, 2003. "On the use of the Stein variance estimator in the double k-class estimator when each individual regression coefficient is estimated," Statistical Papers, Springer, vol. 44(1), pages 117-124, January.


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:29:y:1996:i:3:p:191-199. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.