Exclusion of a relevant variable from a multiple linear regression model leads to the problem of _____.
A. misspecification of the model
B. multicollinearity
C. perfect collinearity
D. homoskedasticity
When there are omitted variables in the regression, which are determinants of the dependent variable, then
A. you cannot measure the effect of the omitted variable, but the estimator of your included variable(s) is (are) unaffected.
B. this has no effect on the estimator of your included variable because the other variable is not included.
C. this will always bias the OLS estimator of the included variable.
D. the OLS estimator is biased if the omitted variable is correlated with the included variable.
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