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Comment: “On the Use of Principal Components Analysis to Interpret Cross-Sectional Differences among Commercial Banks”

Published online by Cambridge University Press:  19 October 2009

Marion L. Chiattello
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Extract

Robert J. Saunders [4] has demonstrated that, because of the high degree of linear interdependence among many of the variables commonly used in banking studies, it may be necessary to interpret explanatory variables in a cross-sectional regression equation, not as representing individual influences but as representing more general factors. He attempted to demonstrate how principal component analysis might be used to isolate and identify some of these general factors.

Information

Type
Communications
Information
Journal of Financial and Quantitative Analysis , Volume 9 , Issue 6 , December 1974 , pp. 1047 - 1051
Copyright
Copyright © School of Business Administration, University of Washington 1974

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References

REFERENCES

[1]Federal Deposit Insurance Corporation. Bank Operating Statistics. Washington, D.C., April 1968.Google Scholar
[2]Rummell, R. J.Applied Factor Analysis. Evanston, Ill.: Northwestern University Press, 1970.Google Scholar
[3]Rummell, R. J. “Understanding Factor Analysis.” The Journal of Conflict Resolution, vol. 11 (December 1968), pp. 444–480.CrossRefGoogle Scholar
[4]Saunders, R. J. “On the Interpretation of Models Explaining Cross Sectional Differences among Commercial Banks.” Journal of Financial and Quantitative Analysis, vol. 4 (March 1969), pp. 25–35.CrossRefGoogle Scholar