Question: Consider the simple regression y i = x i + i where E[ | x] = 0 and E[ 2 | x] =

Consider the simple regression yi= βxi+ εiwhere E[ε | x] = 0 and E[ε2| x] = σ2

a. What is the minimum mean squared error linear estimator of β?

b. For the estimator in part a, show that ratio of the mean squared error of β to that of the ordinary least squares estimator b is

MSE [B] MSE [b] where t2: (1+7?)' [o?/x'x]

τ is the square of the population analog to the ??t ratio?? for testing the hypothesis that β = 0, which is given in (5-11). How do you interpret the behavior of this ratio as τ ?????

MSE [B] MSE [b] where t2: (1+7?)' [o?/x'x]

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First c y c x c So E c x and Var 2 c c Therefore MSE 2 c x 1 2 s 2 c c To minimize this we set MSE c ... View full answer

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