51. What would be the consequences for the OLS estimator heteroscedasticity is present in a regression model but ignored?
- A. It will be ignored
- B. All of A, B and C will be true
- C. It will be inconsistent
- D. It will be inefficient
Check answer and explanation
Answer: It will be inefficient
Explanation If heteroscedasticity is present in a regression model but ignored , the Ordinary Least Squares (OLS) estimator will still be unbiased , but it will not be efficient. This means that the estimator will not have the smallest possible variance, and the estimates may not be precise.