Hello! I'm currently running GMM tests in Stata but I keep getting both a very high number of instruments (100-200+) and an even higher Wald Chi2 score (1.71e+08).
Below is the code that I ran and its following output:
xtdpdsys PFAGDP LNGDPPcap SDGDum LNGDPPcapxSDGDum DependencyRatio Inflation CMReturns PopGrowth LFParticRate, lags(1) twostep artests(2).
System dynamic panel-data estimation Number of obs = 603
Group variable: Country Number of groups = 35
Time variable: Year
Obs per group:
min = 1
avg = 17.22857
max = 20
Number of instruments = 218 Wald chi2(9) = 1.71e+08
Prob > chi2 = 0.0000
Two-step results
----------------------------------------------------------------------------------
PFAGDP | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
PFAGDP |
L1. | . 9695742 .003495 277.42 0.000 .9627241 .9764244
|
LNGDPPcap | 35.98271 1.9354 18.59 0.000 32.18939 39.77602
SDGDum | 16.02427 5.916328 2.71 0.007 4.428483 27.62006
LNGDPPcapxSDGDum | -3.615439 1.266003 -2.86 0.004 -6.096759 -1.134119
DependencyRatio | 3.062755 .2688706 11.39 0.000 2.535778 3.589732
Inflation | -.1901946 .0337445 -5.64 0.000 -.2563326 -.1240565
CMReturns | 11.93403 .2071649 57.61 0.000 11.528 12.34007
PopGrowth | -2.534041 .3077528 -8.23 0.000 -3.137226 -1.930857
LFParticRate | -.3305291 .0430299 -7.68 0.000 -.4148661 -.246192
_cons | -152.4423 8.000879 -19.05 0.000 -168.1238 -136.7609
----------------------------------------------------------------------------------
Warning: gmm two-step standard errors are biased; robust standard
errors are recommended.
Instruments for differenced equation
GMM-type: L(2/.).PFAGDP
Standard: D.LNGDPPcap D.SDGDum D.LNGDPPcapxSDGDum D.DependencyRatio
D.Inflation D.CMReturns D.PopGrowth D.LFParticRate
Instruments for level equation
GMM-type: LD.PFAGDP
Standard: _cons
When i tried running the following code, i was able to lower the number of instruments and Wald Chi2 score, but both are still relatively high:
xtdpdsys PFAGDP LNGDPPcap SDGDum LNGDPPcapxSDGDum DependencyRatio Inflation CMReturns PopGrowth LFParticRate, lags(1) maxldep(1) maxlags(1) pre(LNGDPPcap, lagstruct(1,1)) artests(2)
xtdpdsys PFAGDP LNGDPPcap SDGDum LNGDPPcapxSDGDum DependencyRatio Inflation CMReturns PopGrowth LFParticRate, lags(1) maxldep(1) maxlags(1) pre(LNGDPPcap, lags
> truct(1,1)) artests(2)
note: LNGDPPcap dropped because of collinearity
System dynamic panel-data estimation Number of obs = 602
Group variable: Country Number of groups = 35
Time variable: Year
Obs per group:
min = 1
avg = 17.2
max = 20
Number of instruments = 85 Wald chi2(10) = 5043.31
Prob > chi2 = 0.0000
One-step results
----------------------------------------------------------------------------------
PFAGDP | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
PFAGDP |
L1. | 1.000401 .0301854 33.14 0.000 .9412387 1.059563
|
LNGDPPcap |
--. | 19.03887 27.25736 0.70 0.485 -34.38458 72.46231
L1. | -13.77005 26.78573 -0.51 0.607 -66.26912 38.72902
|
SDGDum | -8.781053 47.83211 -0.18 0.854 -102.5303 84.96817
LNGDPPcapxSDGDum | 1.667439 10.34791 0.16 0.872 -18.61409 21.94897
DependencyRatio | -1.056532 1.346547 -0.78 0.433 -3.695715 1.582651
Inflation | -.1494649 .2983697 -0.50 0.616 -.7342587 .4353289
CMReturns | 9.951293 2.3603 4.22 0.000 5.32519 14.5774
PopGrowth | -1.691797 1.676526 -1.01 0.313 -4.977727 1.594133
LFParticRate | .0269194 .3792645 0.07 0.943 -.7164253 .7702641
_cons | -18.29174 33.14363 -0.55 0.581 -83.25207 46.66859
----------------------------------------------------------------------------------
Instruments for differenced equation
GMM-type: L(2/2).PFAGDP L(1/1).L.LNGDPPcap
Standard: D.LNGDPPcap D.SDGDum D.LNGDPPcapxSDGDum D.DependencyRatio
D.Inflation D.CMReturns D.PopGrowth D.LFParticRate
Instruments for level equation
GMM-type: LD.PFAGDP LD.LNGDPPcap
Standard: _cons
Any ideas on how to fix this, and also specify the use of only 2 variables (lag of the dependent variable PFAGDP, and LNGDPPcap) as the only instruments?
Thank you so much!
Below is the code that I ran and its following output:
xtdpdsys PFAGDP LNGDPPcap SDGDum LNGDPPcapxSDGDum DependencyRatio Inflation CMReturns PopGrowth LFParticRate, lags(1) twostep artests(2).
System dynamic panel-data estimation Number of obs = 603
Group variable: Country Number of groups = 35
Time variable: Year
Obs per group:
min = 1
avg = 17.22857
max = 20
Number of instruments = 218 Wald chi2(9) = 1.71e+08
Prob > chi2 = 0.0000
Two-step results
----------------------------------------------------------------------------------
PFAGDP | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
PFAGDP |
L1. | . 9695742 .003495 277.42 0.000 .9627241 .9764244
|
LNGDPPcap | 35.98271 1.9354 18.59 0.000 32.18939 39.77602
SDGDum | 16.02427 5.916328 2.71 0.007 4.428483 27.62006
LNGDPPcapxSDGDum | -3.615439 1.266003 -2.86 0.004 -6.096759 -1.134119
DependencyRatio | 3.062755 .2688706 11.39 0.000 2.535778 3.589732
Inflation | -.1901946 .0337445 -5.64 0.000 -.2563326 -.1240565
CMReturns | 11.93403 .2071649 57.61 0.000 11.528 12.34007
PopGrowth | -2.534041 .3077528 -8.23 0.000 -3.137226 -1.930857
LFParticRate | -.3305291 .0430299 -7.68 0.000 -.4148661 -.246192
_cons | -152.4423 8.000879 -19.05 0.000 -168.1238 -136.7609
----------------------------------------------------------------------------------
Warning: gmm two-step standard errors are biased; robust standard
errors are recommended.
Instruments for differenced equation
GMM-type: L(2/.).PFAGDP
Standard: D.LNGDPPcap D.SDGDum D.LNGDPPcapxSDGDum D.DependencyRatio
D.Inflation D.CMReturns D.PopGrowth D.LFParticRate
Instruments for level equation
GMM-type: LD.PFAGDP
Standard: _cons
When i tried running the following code, i was able to lower the number of instruments and Wald Chi2 score, but both are still relatively high:
xtdpdsys PFAGDP LNGDPPcap SDGDum LNGDPPcapxSDGDum DependencyRatio Inflation CMReturns PopGrowth LFParticRate, lags(1) maxldep(1) maxlags(1) pre(LNGDPPcap, lagstruct(1,1)) artests(2)
xtdpdsys PFAGDP LNGDPPcap SDGDum LNGDPPcapxSDGDum DependencyRatio Inflation CMReturns PopGrowth LFParticRate, lags(1) maxldep(1) maxlags(1) pre(LNGDPPcap, lags
> truct(1,1)) artests(2)
note: LNGDPPcap dropped because of collinearity
System dynamic panel-data estimation Number of obs = 602
Group variable: Country Number of groups = 35
Time variable: Year
Obs per group:
min = 1
avg = 17.2
max = 20
Number of instruments = 85 Wald chi2(10) = 5043.31
Prob > chi2 = 0.0000
One-step results
----------------------------------------------------------------------------------
PFAGDP | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-----------------+----------------------------------------------------------------
PFAGDP |
L1. | 1.000401 .0301854 33.14 0.000 .9412387 1.059563
|
LNGDPPcap |
--. | 19.03887 27.25736 0.70 0.485 -34.38458 72.46231
L1. | -13.77005 26.78573 -0.51 0.607 -66.26912 38.72902
|
SDGDum | -8.781053 47.83211 -0.18 0.854 -102.5303 84.96817
LNGDPPcapxSDGDum | 1.667439 10.34791 0.16 0.872 -18.61409 21.94897
DependencyRatio | -1.056532 1.346547 -0.78 0.433 -3.695715 1.582651
Inflation | -.1494649 .2983697 -0.50 0.616 -.7342587 .4353289
CMReturns | 9.951293 2.3603 4.22 0.000 5.32519 14.5774
PopGrowth | -1.691797 1.676526 -1.01 0.313 -4.977727 1.594133
LFParticRate | .0269194 .3792645 0.07 0.943 -.7164253 .7702641
_cons | -18.29174 33.14363 -0.55 0.581 -83.25207 46.66859
----------------------------------------------------------------------------------
Instruments for differenced equation
GMM-type: L(2/2).PFAGDP L(1/1).L.LNGDPPcap
Standard: D.LNGDPPcap D.SDGDum D.LNGDPPcapxSDGDum D.DependencyRatio
D.Inflation D.CMReturns D.PopGrowth D.LFParticRate
Instruments for level equation
GMM-type: LD.PFAGDP LD.LNGDPPcap
Standard: _cons
Any ideas on how to fix this, and also specify the use of only 2 variables (lag of the dependent variable PFAGDP, and LNGDPPcap) as the only instruments?
Thank you so much!
