Identify the three desirable properties of the OLS estimators assuming the full ideal conditions.
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What are the properties of an ideal estimator?
In the following table, check the boxes to indicate the correct assumptions for (1) OLS estimators to be unbiased, (2) OLS estimators to be BLUE, and (3) OLS estimators to be the minimum variance unbiased estimators: Unbiased OLS Estimators (1) BLUE OLS Estimators (2) Minimum Variance Unbiased OLS Estimators (3) Assumption MLR.1 Linear in parameters MLR.2 Random sampling MLR.3 No perfect collinearity MLR.4 Zero conditional mean (of error term) MLR.5 Homoskedasticity MLR.6 Normality (of error term) Under assumption MLR.6 (normality), Var(ε|X) = σ^2 Therefore, by assuming that MLR.6 holds, you must necessarily assume that MLR.5 holds. Under the CLM assumptions, the conditional sample values of the independent variable X are distributed normally with a mean of μ and a variance of σ^2.
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