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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 = 1500 observations, with ā š” = 1 š š„ š” = 3019.7575 , ā š” = 1 š š„ š” 2 = 6459.6242 ā š” = 1 š š„ š” 3 = 14522.2308 ā š” = 1 š š„ š” 4 = 34073.8192 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
9.6815
B.There is not enough information to compute
š¤
Ģ
21
.
C.š¤
Ģ
21
=
ā
22.7159
D.š¤
Ģ
21
=
9.6815
E.š¤
Ģ
21
=
ā
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 ā α x_t^β] = 0
2) E[(y_t ā 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 Ī±Ģ = ā1 and Ī²Ģ = 3. We want ĪĢ21, 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., Ī21 = E[ām2/āβ], where m2 = (y_t ā......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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