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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‘‡ = 1500 observations, with āˆ‘ š‘” = 1 š‘‡ š‘„ š‘” = 3019.7575 , āˆ‘ š‘” = 1 š‘‡ š‘„ š‘” 2 = 6459.6242 āˆ‘ š‘” = 1 š‘‡ š‘„ š‘” 3 = 14522.2308 āˆ‘ š‘” = 1 š‘‡ š‘„ š‘” 4 = 34073.8192 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:

Options
A.š›¤ Ģ‚ 21 = āˆ’ 9.6815
B.There is not enough information to compute š›¤ Ģ‚ 21 .
C.š›¤ Ģ‚ 21 = āˆ’ 22.7159
D.š›¤ Ģ‚ 21 = 9.6815
E.š›¤ Ģ‚ 21 = āˆ’ 2.0132
F.š›¤ Ģ‚ 21 = 4.3064
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We start by restating the problem in our own words to ensure clarity about what is being asked. The model is y_t = α x_t^β + ε_t with i.i.d. data and E[ε_t | x_t] = 0. The moment conditions used for GMM are: 1) E[y_t āˆ’ α x_t^β] = 0 2) E[(y_t āˆ’ α x_t^β) x_t] = 0 Given a sample of size T = 1500 and the provided sums of powers of x_t, the point estimates are α̂ = āˆ’1 and β̂ = 3. We want Γ̂21, the (2,1) entry of the variance-covariance matrix of the moment conditions, which in a basic GMM setup corresponds to the derivative of the second moment condition with respect to β, evaluated at the estimates, i.e., Ī“21 = E[āˆ‚m2/āˆ‚Ī²], where m2 = (y_t āˆ’......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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