Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-24T19:29:27.082Z Has data issue: false hasContentIssue false

A Comparison of the Stein-Rule and Positive-Part Stein-Rule Estimators in a Misspecified Linear Regression Model

Published online by Cambridge University Press:  11 February 2009

Kazuhiro Ohtani
Affiliation:
Kobe University

Abstract

In this paper, we examine the performance of the predictive risk of the Steinrule (SR) and positive-part Stein-rule (PSR) estimators when relevant regressors are omitted in the specified model. The exact formula of the predictive risk of the PSR estimator is derived, and the sufficient condition for the PSR estimator to dominate the SR estimator under a specification error is given. It is shown by numerical computation that the PSR estimator seems to be the best choice among the OLS, SR, and PSR estimators even when there are omitted variables.

Type
Miscellanea
Copyright
Copyright © Cambridge University Press 1993

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Abramowitz, M. & Stegun, I.A.. Handbook of Mathematical Functions. New York: Dover Publications, 1972.Google Scholar
2.Adkins, L.C. & Hill, R.C.. The RLS positive-part Stein estimator. American Journal of Agricultural Economics 72 (1990): 727730.CrossRefGoogle Scholar
3.Cramer, J.S.Mean and variance of R2 in small and moderate samples. Journal of Econometrics 35 (1987): 253266.Google Scholar
4.Judge, G.G. & Bock, M.E.. A comparison of traditional and Stein-rule estimators under weighted squared error loss. International Economic Review 17 (1976): 234240.Google Scholar
5.Judge, G.G. & Yancey, T. A.. Improved Methods of Inference in Econometrics. Amsterdam: North-Holland, 1986.Google Scholar
6.Kmenta, J.Elements of Econometrics, Second edition. New York: Macmillan, 1986.Google Scholar
7.Mittelhammer, R.C.Restricted least squares, pre-test, OLS and Stein rule estimators: Risk comparisons under model misspecification. Journal of Econometrics 25 (1984): 151164.Google Scholar
8.Toyoda, T. & Wallace, T.D.. Optimal critical values for pre-testing in regression. Econometrica (1976): 365375.CrossRefGoogle Scholar
9.Ullah, A., Carter, R.A.L. & Srivastava, V.K.. The sampling distribution of shrinkage estimators and their F-ratios in the regression model. Journal of Econometrics 25 (1984): 109122.Google Scholar
10.Yancey, T.A. & Judge, G.G.. A Monte Carlo comparison of traditional and Stein-rule estimators under squared error loss. Journal of Econometrics 4 (1976): 285294.CrossRefGoogle Scholar