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True or False? WLS is preferred to OLS when an important variable has been omitted from the model.
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- When the regression error is heteroskedastic, all of the following statements are false, with the exception of: a. the conditional variance of the error term is not constant. b. the OLS estimator is unbiased but not consistent. C. the OLS estimator is still BLUE.Comment on why there exists a trade-off between variance and bias of of OLS estimators when considering the choice of including a particular explanatory variable in your underlying model. Please keep your answer precise.Estimate the following model: purchase = β0 + β1traditional + β2aggregator + β3substack
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- In the model Y = Bo +B 1X 1 + B 2X 2 + 8, which of these parameters represents a coefficient of an independent variable? the Y the X1 the B1 the eDescribe the recommended approach towards determining model specification.How does the R2 help in determining an appropriate model? Is theideal model the one with the highest R2? Should a regressor be included in the model if it increases the model R2?In the linear model ,E (X*u) = a)X*u b) 0 c) u d) none of tha above