Multiple Choice
If the errors are heteroskedastic, then
A) the OLS estimator is still BLUE as long as the regressors are nonrandom.
B) the usual formula cannot be used for the OLS estimator.
C) your model becomes overidentified.
D) the OLS estimator is not BLUE.
Correct Answer:
Verified
Correct Answer:
Verified
Q1: Your textbook states that an implication
Q3: The large-sample distribution of <span
Q4: "One should never bother with WLS. Using
Q5: For this question you may assume
Q6: The advantage of using heteroskedasticity-robust standard errors
Q7: The extended least squares assumptions are of
Q8: If, in addition to the least squares
Q9: Assume that var(u<sub>i</sub>|X<sub>i</sub>)= ?<sub>0</sub>+?<sub>1</sub> <sub> </sub>
Q10: (Requires Appendix material)Your textbook considers various
Q11: In practice, you may want to use