Question

In the presence of correlated observations, the OLS estimators are unbiased, but their estimated standard errors are inappropriate. Which of the following could happen as a result?

A. The model looks better than it really is with a spuriously high R2
B. The F test may suggest that the predictor variables are individually and jointly significant when this is not true
C. All of the answers are correct
D. The t test may suggest that the predictor variables are individually and jointly significant when this is not true

Answer 1

In the presence of correlated observations, the OLS estimators are unbiased, but their estimated standard errors are inappropriate. This can lead to the model looking better than it really is, the F test suggesting significance when it's not true, and the t test also suggesting significance when it's not true.

Step-by-step explanation:

When there are correlated observations, the OLS estimators are unbiased but their estimated standard errors are inappropriate. This can lead to several consequences:

1. The model may appear better than it really is with a spuriously high R-squared value (A).
2. The F test may suggest that the predictor variables are individually and jointly significant, even when this is not true (B).
3. The t test may suggest that the predictor variables are individually and jointly significant, even when this is not true (D).

Therefore, the correct answer is C: All of the answers are correct.