Hello everybody,
I have a balanced panel of 19 countries over 24 time periods. The model is
g_it= ß_0+δ*g_(it-1)+ß_1*x_it+ε_it
It is a income growth regression, where the regressor are population growth, institutions, the trade share and so on.
I used until now, the one-step system GMM estimator with robust standard errors.
xtdpd g l.g FD CL I LQ RS RF ddummy p, dgmmiv(I LQ RS FD RF ddummy l.g , lagrange(4)) lgmmiv(I LQ RS ddummy FD RF l.g, lag(4)) iv(p) vce(robust) artests(2)
Dynamic panel-data estimation Number of obs = 435
Group variable: id Number of groups = 19
Time variable: time
Obs per group: min = 21
avg = 22.89474
max = 23
Number of instruments = 470 Wald chi2(9) = 74.97
Prob > chi2 = 0.0000
One-step results
------------------------------------------------------------------------------
| Robust
g | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
g |
L1. | .1320479 .0528852 2.50 0.013 .0283948 .235701
FD | .3835768 .1107316 3.46 0.001 .1665468 .6006068
CL | -.0000431 .0019382 -0.02 0.982 -.003842 .0037557
I | -.2958265 .0795866 -3.72 0.000 -.4518134 -.1398396
LQ | -.0002257 .0090368 -0.02 0.980 -.0179375 .0174861
RS | .0107728 .0041573 2.59 0.010 .0026247 .0189209
RF | -.0195168 .0047356 -4.12 0.000 -.0287984 -.0102352
ddummy | .0054591 .0041961 1.30 0.193 -.0027651 .0136834
p | -.0006131 .0002331 -2.63 0.009 -.00107 -.0001562
_cons | .0229008 .0155701 1.47 0.141 -.007616 .0534176
------------------------------------------------------------------------------
Instruments for differenced equation
GMM-type: L(4/.).I L(4/.).LQ L(4/.).RS L(4/.).FD L(4/.).RF L(4/.).ddummy
L(4/.).L.g
Standard: D.p
Instruments for level equation
GMM-type: L4D.I L4D.LQ L4D.RS L4D.ddummy L4D.FD L4D.RF L5D.g
Standard: p _cons
To compare the results, because I think the two step estimator can better deal
with heteroskedasticity (Windmeijer robust errors), I want to employ the two step estimator.
However, all the coefficients become insignificant. How can I interpret these results?
And are the one step (with robust standard errors) estimates also robust to heteroskedasticity (across time and countries)?
xtdpd g l.g FD CL I LQ RS RF ddummy p, twostep dgmmiv(I LQ RS FD RF ddummy l.g , lagrange(4)) lgmmiv(I LQ RS ddummy FD RF l.g, lag(4)) iv(p) vce(robust) artests(2)
Dynamic panel-data estimation Number of obs = 435
Group variable: id Number of groups = 19
Time variable: time
Obs per group: min = 21
avg = 22.89474
max = 23
Number of instruments = 470 Wald chi2(8) = 3.19
Prob > chi2 = 0.9220
Two-step results
------------------------------------------------------------------------------
| WC-Robust
g | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
g |
L1. | -.1018478 3.185356 -0.03 0.974 -6.345031 6.141336
FD | .1034821 16.18238 0.01 0.995 -31.61339 31.82036
CL | -.0076123 .1367406 -0.06 0.956 -.275619 .2603944
I | -.073898 17.0281 -0.00 0.997 -33.44835 33.30056
LQ | .0169259 .6985014 0.02 0.981 -1.352112 1.385963
RS | .1058199 .7143544 0.15 0.882 -1.294289 1.505929
RF | -.1225682 .7167893 -0.17 0.864 -1.527449 1.282313
ddummy | .0806485 .2211386 0.36 0.715 -.3527752 .5140722
p | -.0019078 .0129519 -0.15 0.883 -.0272929 .0234774
_cons | .0281583 1.297514 0.02 0.983 -2.514923 2.57124
------------------------------------------------------------------------------
Instruments for differenced equation
GMM-type: L(4/.).I L(4/.).LQ L(4/.).RS L(4/.).FD L(4/.).RF L(4/.).ddummy
L(4/.).L.g
Standard: D.p
Instruments for level equation
GMM-type: L4D.I L4D.LQ L4D.RS L4D.ddummy L4D.FD L4D.RF L5D.g
Standard: p _cons
P.S. It does not matter, if I restrict the lagrange.
Hope somebody can help.
Best wishes
Markus
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