What are the limitations of the Gauss-Markov theorem? (Check all that apply.) A. If the error...

Transcribed Image Text:

What are the limitations of the Gauss-Markov theorem? (Check all that apply.) A. If the error term is heteroskedastic, then the OLS estimator is not BLUE. B. Even if the conditions of the theorem hold, it is possible that under some conditions, other estimators that are not linear or conditionally unbiased may be more efficient than OLS. c. The Gauss-Markov theorem does not provide a theoretical justification for using OLS. D. If the error term is heteroskedastic, then the OLS estimator may or may not be BLUE. In which of the following cases would the weighted least squares estimator (WLS) or the least absolute deviations estimator (LAD) be preferred to the OLS estimator? (Check all that apply.) A. LAD is preferred to OLS if extreme outliers are not rare in the data. B. WLS is preffered to OLS if the least squares estimator is biased. C. LAD is preferred to OLS if the least square estimator is inconsistent. D. WLS is preffered to OLS if the errors are heteroskedastic. What are the limitations of the Gauss-Markov theorem? (Check all that apply.) A. If the error term is heteroskedastic, then the OLS estimator is not BLUE. B. Even if the conditions of the theorem hold, it is possible that under some conditions, other estimators that are not linear or conditionally unbiased may be more efficient than OLS. c. The Gauss-Markov theorem does not provide a theoretical justification for using OLS. D. If the error term is heteroskedastic, then the OLS estimator may or may not be BLUE. In which of the following cases would the weighted least squares estimator (WLS) or the least absolute deviations estimator (LAD) be preferred to the OLS estimator? (Check all that apply.) A. LAD is preferred to OLS if extreme outliers are not rare in the data. B. WLS is preffered to OLS if the least squares estimator is biased. C. LAD is preferred to OLS if the least square estimator is inconsistent. D. WLS is preffered to OLS if the errors are heteroskedastic.

Answer rating: 100% (QA)

Answer There are five Gauss Markov assumptions also called conditions Linearity the parameters w... View the full answer