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A Note on Student's t Test in Multiple Regression

Published online by Cambridge University Press:  19 October 2009

Extract

Recently, Cohen and Gujarati [2] have suggested that when multicollinearity is present there is “ …danger involved in mechanically dropping variables from multiple regression equations by t tests because t values of the regression coefficients may not be significantly different from zero when the true (population) values of these coefficients are in fact not zero…” The problem they discuss is not a new one and has been extensively treated in the existing literature. However, their approach is straightforward and will certainly aid the practitioner in his understanding of the problems associated with multicollinearity.

Type
Communications
Copyright
Copyright © School of Business Administration, University of Washington 1971

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References

[1]Bartlett, M.S. “A Note on the Multiplying Factors for Various x2 Approximations.” Journal of the Royal Statistical Society (B), 1954.CrossRefGoogle Scholar
[2]Cohen, Bruce, and Gujarati, Damodar. “The Student's t Test in Multiple Regression under Simple Collinearity.” Journal of Financial and Quantitative Analysis, September 1970.CrossRefGoogle Scholar
[3]Cragg, J.G. “Some Effects of Incorrect Specification on the Small Sample Properties of Several Simultaneous Equation Estimators.” International Economic Review, February 1968.CrossRefGoogle Scholar
[4]Farrar, D.E., and Glauber, R.R.. “Multicollinearity in Regression Analysis: The Problem Revisited.” Review of Economics and Statistics, February 1967.CrossRefGoogle Scholar
[5]Fisher, F.M. “On the Cost of Approximate Specification in Simultaneous Equation Estimation.” Econometrica, April 1961.CrossRefGoogle Scholar
[6]Haitovsky, Y. “Multicollinearity in Regression Analysis: A Comment.” Review of Economics and Statistics, November 1969.CrossRefGoogle Scholar
[7]Klein, L.R., and Nakamura, M.. “Singularity in the Equation Systems of Econometrics: Some Aspects of the Problem of Multicollinearity.” International Economic Review, September 1962.CrossRefGoogle Scholar
[8]Klein, L.R.An Introduction to Econometrics. Englewood Cliffs, N.J.: Prentice Hall, Inc., 1962.Google Scholar
[9]Ramsey, J.B. “Tests for Specification Errors in Classical Linear Least Squares Regression Analysis.” Journal of the Royal Statistical Society (B), 1969.CrossRefGoogle Scholar