Consider the same simple linear regression (SLR) model Gauss Markov assumptions: Y = Bo + B...

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Consider the same simple linear regression (SLR) model Gauss Markov assumptions: Y = Bo + B₁ X + u, where the error term u has an unconditional variance of o². Your friend highly recommends this specific linear estimator ₁ = ₁ Σ1 W₁Y₁, where W1 W2 = 1 x2-xX1 W₁ = 0 (a) 1 X2-X1 (b) for i= 3, 4, 5,...., n, where n is the sample size. which satisfies Is this estimator bias or unbiased? Please prove. Derive the conditional variance of this estimator P₁. Is it greater or less than the 0² conditional variance of OLS estimator P₁ derived in class, i.e. ? Σ=1(x;− x)2· Consider the same simple linear regression (SLR) model Gauss Markov assumptions: Y = Bo + B₁ X + u, where the error term u has an unconditional variance of o². Your friend highly recommends this specific linear estimator ₁ = ₁ Σ1 W₁Y₁, where W1 W2 = 1 x2-xX1 W₁ = 0 (a) 1 X2-X1 (b) for i= 3, 4, 5,...., n, where n is the sample size. which satisfies Is this estimator bias or unbiased? Please prove. Derive the conditional variance of this estimator P₁. Is it greater or less than the 0² conditional variance of OLS estimator P₁ derived in class, i.e. ? Σ=1(x;− x)2·

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a To determine whether the estimator 21WiYi is biased or unbiased we need to calculate its expectation E and compare it to the true population paramet... View the full answer