What is the tradeoff researchers face when deciding how to deal with heteroskedasticity?
A) Goldfeld-Quandt overstates heteroskedasticity but LM leads to more Type I errors
B) White's robust estimator should be used for hypothesis testing,but GLS is better for interval estimation
C) GLS gives minimum variance,but results are more difficult to interpret
D) White's robust estimator requires no assumptions about the structure of the variance,but it is not as efficient as GLS estimates when the right structure is imposed on the variance
Correct Answer:
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Q1: How should you estimate a model with
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Q5: A linear probability model is likely
Q6: If you run a LM test
Q7: (See graphs of Model A - D)The
Q8: Which test for heteroskedasticity should you use
Q9: When using WLS to correct for heteroskedasticity,what
Q10: (See graphs of Model A -
Q11: If your initial econometric model has heteroskedastic
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