Hello,
Could you please help me how I can find pvalue for Jstatistics in simulataneous equation with GMM?
Specifically, I am looking "the degrees of freedom (df)" number for simulatneous equation with GMM method. I could not find how to calculate it.
IF I know that, I think I can find pvalue by using
the p value: pval=chisq(jstatistics,df).
Thanks in advance
p value for Jstatistics for simultaneous equation (gmm)
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 Fe ddaethom, fe welon, fe amcangyfrifon
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Re: p value for Jstatistics for simultaneous equation (gmm)
In general the degrees of freedom are equal to the number of moment conditions (instruments) minus the number of coefficients.
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Re: p value for Jstatistics for simultaneous equation (gmm)
Gareth,
Thanks for reply and your help.
I am using Eviews system GMMHac
For eviews systemgmm HAC, for the following model , total moment conditions is just total instrument number?
Could you please help me for it?
In 2 equations, I have total 12 instruments (including constant), so total moments condition is just 12? and
thus degree of freedom: 129 =3 ?
Thanks
The result is in below
System: SYSTEM1
Estimation Method: Generalized Method of Moments
Date: 09/07/10 Time: 08:46
Sample: 1971 2007
Included observations: 37
Total system (balanced) observations 74
Kernel: Bartlett, Bandwidth: Fixed (4), No prewhitening
Linear estimation after onestep weighting matrix
Coefficient Std. Error tStatistic Prob.
C(1) 2472.962 553.9893 4.463917 0.0000
C(2) 1.190021 0.180319 6.599544 0.0000
C(3) 147.1880 43.58633 3.376929 0.0012
C(4) 21.72342 9.186045 2.364828 0.0210
C(5) 97.10365 19.77433 4.910591 0.0000
C(6) 2332.957 498.0215 4.684450 0.0000
C(7) 0.008666 0.122840 0.070548 0.9440
C(8) 4.058377 0.323720 12.53668 0.0000
C(9) 1.344488 0.803866 1.672528 0.0992
Determinant residual covariance 1.20E+12
Jstatistic 0.182100
Equation: FDI = C(1) + C(2)*GDP + C(3)*OPEN + C(4)*EXCH +C(5)
*INF
Instruments: OPEN EXCH INF GFCF TB C
Observations: 37
Rsquared 0.863444 Mean dependent var 1764.658
Adjusted Rsquared 0.846375 S.D. dependent var 4127.667
S.E. of regression 1617.842 Sum squared resid 83757200
DurbinWatson stat 1.046572
Equation: GDP = C(6) + C(7)*FDI + C(8)*GFCF + C(9)*TB
Instruments: OPEN EXCH INF GFCF TB C
Observations: 37
Rsquared 0.971717 Mean dependent var 9670.406
Adjusted Rsquared 0.969146 S.D. dependent var 4395.521
S.E. of regression 772.0905 Sum squared resid 19672084
DurbinWatson stat 0.756237
Thanks for reply and your help.
I am using Eviews system GMMHac
For eviews systemgmm HAC, for the following model , total moment conditions is just total instrument number?
Could you please help me for it?
In 2 equations, I have total 12 instruments (including constant), so total moments condition is just 12? and
thus degree of freedom: 129 =3 ?
Thanks
The result is in below
System: SYSTEM1
Estimation Method: Generalized Method of Moments
Date: 09/07/10 Time: 08:46
Sample: 1971 2007
Included observations: 37
Total system (balanced) observations 74
Kernel: Bartlett, Bandwidth: Fixed (4), No prewhitening
Linear estimation after onestep weighting matrix
Coefficient Std. Error tStatistic Prob.
C(1) 2472.962 553.9893 4.463917 0.0000
C(2) 1.190021 0.180319 6.599544 0.0000
C(3) 147.1880 43.58633 3.376929 0.0012
C(4) 21.72342 9.186045 2.364828 0.0210
C(5) 97.10365 19.77433 4.910591 0.0000
C(6) 2332.957 498.0215 4.684450 0.0000
C(7) 0.008666 0.122840 0.070548 0.9440
C(8) 4.058377 0.323720 12.53668 0.0000
C(9) 1.344488 0.803866 1.672528 0.0992
Determinant residual covariance 1.20E+12
Jstatistic 0.182100
Equation: FDI = C(1) + C(2)*GDP + C(3)*OPEN + C(4)*EXCH +C(5)
*INF
Instruments: OPEN EXCH INF GFCF TB C
Observations: 37
Rsquared 0.863444 Mean dependent var 1764.658
Adjusted Rsquared 0.846375 S.D. dependent var 4127.667
S.E. of regression 1617.842 Sum squared resid 83757200
DurbinWatson stat 1.046572
Equation: GDP = C(6) + C(7)*FDI + C(8)*GFCF + C(9)*TB
Instruments: OPEN EXCH INF GFCF TB C
Observations: 37
Rsquared 0.971717 Mean dependent var 9670.406
Adjusted Rsquared 0.969146 S.D. dependent var 4395.521
S.E. of regression 772.0905 Sum squared resid 19672084
DurbinWatson stat 0.756237

 Posts: 1
 Joined: Sat Jul 07, 2012 3:08 am
Re: p value for Jstatistics for simultaneous equation (gmm)
Dear Gareth and Kelaynak,
I also have a problem in calculating Degree of freedom in GMM methods for the system of equations. I have 4 equations with 4 endogenous variables with 36 total exogenous variables in the system (4 variables and 32 fixed effect dummies). I use all the exogenous variables for the instrumental variables. Total of parameters to be estimated in system of equations are 15 parameters including intercept (excluding 32 dummies).
Another important questions is that how you calculate the HansenJstatistic in this system of equations? (Do you calculate Hansen Jstatistic for every equation and then make all of the Hansen Jstatistic from every equation as an average?)
I am really looking forward to hearing your response.
Thank you very much
Best regards,
Maman
I also have a problem in calculating Degree of freedom in GMM methods for the system of equations. I have 4 equations with 4 endogenous variables with 36 total exogenous variables in the system (4 variables and 32 fixed effect dummies). I use all the exogenous variables for the instrumental variables. Total of parameters to be estimated in system of equations are 15 parameters including intercept (excluding 32 dummies).
Another important questions is that how you calculate the HansenJstatistic in this system of equations? (Do you calculate Hansen Jstatistic for every equation and then make all of the Hansen Jstatistic from every equation as an average?)
I am really looking forward to hearing your response.
Thank you very much
Best regards,
Maman
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