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Consider the following nonlinear regression model: 𝑦 𝑡 = 𝛼 𝑥 𝑡 𝛽 + 𝜀 𝑡 Assume i.i.d. data and 𝔼 [ 𝜀 𝑡 | 𝑥 𝑡 ] = 0 . To estimate 𝛼 and 𝛽 by GMM, we use the following moment conditions: 𝔼 [ 𝑦 𝑡 − 𝛼 𝑥 𝑡 𝛽 ] = 0 𝔼 [ ( 𝑦 𝑡 − 𝛼 𝑥 𝑡 𝛽 ) 𝑥 𝑡 ] = 0 We have an i.i.d. sample with 𝑇 = 8000 observations, with ∑ 𝑡 = 1 𝑇 𝑥 𝑡 = 2000 , ∑ 𝑡 = 1 𝑇 𝑥 𝑡 2 = 4000 and ∑ 𝑡 = 1 𝑇 𝑥 𝑡 3 = 8000 . We obtain point estimates 𝛼 ̂ = − 5 and 𝛽 ̂ = 3 . To compute the variance of the estimates, we need to estimate the matrix 𝛤 0 , 𝛤 ̂ 0 = [ 𝛤 ̂ 11 𝛤 ̂ 12 𝛤 ̂ 21 𝛤 ̂ 22 ] Then, the value 𝛤 ̂ 11 is:

Options
A.𝛤 ̂ 11 = 4000
B.𝛤 ̂ 11 = 0.5
C.𝛤 ̂ 11 = − 1
D.There is not enough information to compute 𝛤 ̂ 11 .
E.𝛤 ̂ 11 = − 0.25
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We start by restating the essential pieces of the problem and the candidate answers, so each option can be assessed in context. - The nonlinear regression model is y_t = α x_t^β, with i.i.d. data and E[ε_t|x_t] = 0. The GMM moment conditions given are: E[y_t − α x_t^β] = 0 E[(y_t − α x_t^β) x_t] = 0 - The problem provides a sample of size T = 8000, and the sample sums: ∑ x_t = 2000, ∑ x_t^2 = 4000, ∑ x_t^3 = 8000. The point estimates obtained are α̂ = −5 and β̂ = 3. The task asks for the estimated value of Γ̂11, the (1,1) entry of the matrix Γ̂0, which is the expectation ......Login to view full explanation

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