Multicollinearity in Regression Analysis the Problem Revisited

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Multicollinearity in Regression Analysis the Problem Revisited
Donald Eugene Farrar
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These forecasts could have been improved mar- ginally, perhaps, by more fortunate choices of sample, computing algorithm, direction of minimization, functional form, etc. But their basic shortcoming consists of a failure to recognize the importance of liquid assets to consumer behavior. No matter how cleverly a consumption function's coefficients are estimated, if it does not include liquid assets it cannot provide a satis- * Lest we should be too easy on Cobb and Douglas it must be reiterated ...that their model embodies a two dimensional — not a one dimensional -- hypothesis.
-13- factory representation of postwar United States consumer behavior. Multicollinearity, unfortunately, contributes to difficulty in the specification as well as in the estimation of economic relationships.
Model specification ordinarily begins in the model builder's mind. From a combination of theory, prior information, and just plain hunch, variables are chosen to explain the be- havior of a given dependent variable.


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