What would be the consequences for the OLS estimator heteroscedasticity is present in a regression model but ignored?
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.
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