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Consider the following nonlinear regression model: š‘¦ š‘” = š›¼ š‘„ š‘” š›½ + šœ€ š‘” Assume i.i.d. data and š”¼ [ šœ€ š‘” | š‘„ š‘” ] = 0 . To estimate š›¼ and š›½ by GMM, we use the following moment conditions: š”¼ [ š‘¦ š‘” āˆ’ š›¼ š‘„ š‘” š›½ ] = 0 š”¼ [ ( š‘¦ š‘” āˆ’ š›¼ š‘„ š‘” š›½ ) š‘„ š‘” ] = 0 We have an i.i.d. sample with š‘‡ = 1000 observations, with āˆ‘ š‘” = 1 š‘‡ š‘„ š‘” = 1123.9975 , āˆ‘ š‘” = 1 š‘‡ š‘„ š‘” 2 = 5379.7163 āˆ‘ š‘” = 1 š‘‡ š‘„ š‘” 3 = 15602.875 āˆ‘ š‘” = 1 š‘‡ š‘„ š‘” 4 = 81337.6911 We obtain point estimates š›¼ Ģ‚ = āˆ’ 1 and š›½ Ģ‚ = 3 . To compute the variance of the estimates, we need to estimate the matrix š›¤ 0 , š›¤ Ģ‚ 0 = [ š›¤ Ģ‚ 11 š›¤ Ģ‚ 12 š›¤ Ģ‚ 21 š›¤ Ģ‚ 22 ] Then, the value š›¤ Ģ‚ 21 is:

选锹
A.š›¤ Ģ‚ 21 = āˆ’ 81.3377
B.š›¤ Ģ‚ 21 = 5.3797
C.There is not enough information to compute š›¤ Ģ‚ 21 .
D.š›¤ Ģ‚ 21 = āˆ’ 1.124
E.š›¤ Ģ‚ 21 = āˆ’ 15.6029
F.š›¤ Ģ‚ 21 = 15.6029
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Before judging any option, I’ll outline what Γ̂21 represents in this GMM setup. The second moment condition is E[(y_t āˆ’ α x_t^β) x_t] = 0, and the first moment condition is E[y_t āˆ’ α x_t^β] = 0. When forming the Ī“ matrix, its entry Ī“21 is the expectation of the derivative of the first moment condition with respect to β, i.e. Ī“21 = E[ āˆ‚/āˆ‚Ī² (y_t āˆ’ α x_t^β) ]. Since āˆ‚/āˆ‚Ī² of y_t āˆ’ α x_t^β equals āˆ’Ī± x_t^β ln x_t, we get Ī“21 = E[ āˆ’Ī± x_t^β ln x_t ]. Now, with the given parameter values α = āˆ’1 and β = 3, this simplifies to Ī“21 = āˆ’(āˆ’1) E[ x_t^3 ln x_t ] = ......Login to view full explanation

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Consider the following nonlinear regression model: yi=α+eβxi+εi, Assume i.i.d. data and š”¼[εi|xi]=0. To estimate α and β by GMM, we use the two theoretical moment conditions š”¼[yiāˆ’Ī±āˆ’eβxi]=0 š”¼[(yiāˆ’Ī±āˆ’eβxi)xi]=0 To compute the variance of the GMM estimator we need the matrices Ī“0 and Φ0.

Consider the following nonlinear regression model: yi=α+eβxi+εi, Assume i.i.d. data and š”¼[εi|xi]=0. To estimate α and β by GMM, we need two moment conditions. Choose the best answer below:

Consider the following nonlinear regression model: š‘¦ š‘” = š›¼ š‘„ š‘” š›½ + šœ€ š‘” Assume i.i.d. data and š”¼ [ šœ€ š‘” | š‘„ š‘” ] = 0 . To estimate š›¼ and š›½ by GMM, we use the following moment conditions: š”¼ [ š‘¦ š‘” āˆ’ š›¼ š‘„ š‘” š›½ ] = 0 š”¼ [ ( š‘¦ š‘” āˆ’ š›¼ š‘„ š‘” š›½ ) š‘„ š‘” ] = 0 We have an i.i.d. sample with š‘‡ = 8000 observations, with āˆ‘ š‘” = 1 š‘‡ š‘„ š‘” = 2000 , āˆ‘ š‘” = 1 š‘‡ š‘„ š‘” 2 = 4000 and āˆ‘ š‘” = 1 š‘‡ š‘„ š‘” 3 = 8000 . We obtain point estimates š›¼ Ģ‚ = āˆ’ 5 and š›½ Ģ‚ = 3 . To compute the variance of the estimates, we need to estimate the matrix š›¤ 0 , š›¤ Ģ‚ 0 = [ š›¤ Ģ‚ 11 š›¤ Ģ‚ 12 š›¤ Ģ‚ 21 š›¤ Ģ‚ 22 ] Then, the value š›¤ Ģ‚ 11 is:

Consider the following nonlinear regression model: š‘¦ š‘– = š›¼ + š›½ š‘„ š‘– + šœ€ š‘– , Assume i.i.d. data and š”¼ [ šœ€ š‘– | š‘„ š‘– ] = 0 . To estimate š›¼ and š›½ by GMM, we use the two theoretical moment conditions š”¼ [ š‘¦ š‘– āˆ’ š›¼ āˆ’ š›½ š‘„ š‘– ] = 0 š”¼ [ ( š‘¦ š‘– āˆ’ š›¼ āˆ’ š›½ š‘„ š‘– ) š‘„ š‘– ] = 0 To compute the variance of the GMM estimator we need the matrices š›¤ 0 and š›· 0 .

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