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Consider the following nonlinear regression model: š¦ š” = š¼ š„ š” š½ + š š” Assume i.i.d. data and š¼ [ š š” | š„ š” ] = 0 . To estimate š¼ and š½ by GMM, we use the following moment conditions: š¼ [ š¦ š” ā š¼ š„ š” š½ ] = 0 š¼ [ ( š¦ š” ā š¼ š„ š” š½ ) š„ š” ] = 0 We have an i.i.d. sample with š = 1000 observations, with ā š” = 1 š š„ š” = 1123.9975 , ā š” = 1 š š„ š” 2 = 5379.7163 ā š” = 1 š š„ š” 3 = 15602.875 ā š” = 1 š š„ š” 4 = 81337.6911 We obtain point estimates š¼ Ģ = ā 1 and š½ 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:
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A.š¤
Ģ
21
=
ā
81.3377
B.š¤
Ģ
21
=
5.3797
C.There is not enough information to compute
š¤
Ģ
21
.
D.š¤
Ģ
21
=
ā
1.124
E.š¤
Ģ
21
=
ā
15.6029
F.š¤
Ģ
21
=
15.6029
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Before judging any option, Iāll outline what ĪĢ21 represents in this GMM setup. The second moment condition is E[(y_t ā α x_t^β) x_t] = 0, and the first moment condition is E[y_t ā α x_t^β] = 0. When forming the Ī matrix, its entry Ī21 is the expectation of the derivative of the first moment condition with respect to β, i.e. Ī21 = E[ ā/āβ (y_t ā α x_t^β) ]. Since ā/āβ of y_t ā α x_t^β equals āα x_t^β ln x_t, we get Ī21 = E[ āα x_t^β ln x_t ].
Now, with the given parameter values α = ā1 and β = 3, this simplifies to Ī21 = ā(ā1) E[ x_t^3 ln x_t ] = ......Login to view full explanationē»å½å³åÆę„ēå®ę“ēę”
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Consider the following nonlinear regression model: yi=α+eβxi+εi, Assume i.i.d. data and š¼[εi|xi]=0. To estimate α and β by GMM, we use the two theoretical moment conditions š¼[yiāαāeβxi]=0 š¼[(yiāαāeβxi)xi]=0 To compute the variance of the GMM estimator we need the matrices Ī0 and Φ0.
Consider the following nonlinear regression model: yi=α+eβxi+εi, Assume i.i.d. data and š¼[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” = š¼ š„ š” š½ + š š” Assume i.i.d. data and š¼ [ š š” | š„ š” ] = 0 . To estimate š¼ and š½ by GMM, we use the following moment conditions: š¼ [ š¦ š” ā š¼ š„ š” š½ ] = 0 š¼ [ ( š¦ š” ā š¼ š„ š” š½ ) š„ š” ] = 0 We have an i.i.d. sample with š = 8000 observations, with ā š” = 1 š š„ š” = 2000 , ā š” = 1 š š„ š” 2 = 4000 and ā š” = 1 š š„ š” 3 = 8000 . We obtain point estimates š¼ Ģ = ā 5 and š½ 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 = š¼ + š½ š„ š + š š , Assume i.i.d. data and š¼ [ š š | š„ š ] = 0 . To estimate š¼ and š½ by GMM, we use the two theoretical moment conditions š¼ [ š¦ š ā š¼ ā š½ š„ š ] = 0 š¼ [ ( š¦ š ā š¼ ā š½ 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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