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Your Textbook States That an Implication of the Gauss-Markov Theorem Yˉ\bar { Y }

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Your textbook states that an implication of the Gauss-Markov theorem is that the sample average, Yˉ\bar { Y } , is the most efficient linear estimator of E(Yi)E \left( Y _ { i } \right) when Y1,,YnY _ { 1 } , \ldots , Y _ { n } are i.i.d. with E(Yi)=μYE \left( Y _ { i } \right) = \mu _ { Y } and var(Yi)=σY2\operatorname { var } \left( Y _ { i } \right) = \sigma _ { Y } ^ { 2 } . This follows from the regression model with no slope and the fact that the OLS estimator is BLUE.
Provide a proof by assuming a linear estimator in the YY 's, μ~=i=1naiYi\tilde { \mu } = \sum _ { i = 1 } ^ { n } a _ { i } Y _ { i } . (a)State the condition under which this estimator is unbiased.


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