it may be a concern that market value and assets are highly correlated and hence
ID: 3176949 • Letter: I
Question
it may be a concern that market value and assets are highly correlated and hence there may be a problem with including them both as explanatory variable. the followng set of output is for the regression that excludes assets from the regression above. based on this set of output, doet is seem like ly that assets and market value are highly correlated and hence does it appear that multicollinearity is a problem? Explain how you know?
Regression Statistics
ANOVA
3.89E-30
Multiple R 0.490 R Square 0.240 adjusted R square 0.236 standard Error 3981 observations 1000Explanation / Answer
For detecting multicollinearity, we need to calculate the VIF i.e. Variance inflation factor. For any predictor variable, the square root of the VIF indicates the degree to which the confidence interval for that variable’s regression parameter is expanded relative to a model with uncorrelated predictors. VIF values are provided by the vif() function in the car package. As a general rule, sqrt(vif) >2 indicates a multicollinearity problem.
So we need to calculate the vif of a model which includes both market value and assets variables and check if its square root value is >2. If yes, multicollinearity problem exists and we need to drop one of the variables.
The vif calculation needs to be done for concluding multicollinearity. Please let me know if you have doubts.
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