Dear all,
I am struggling to understand the differences between the Stata commands xtpmg and xtdcce2 (written by Jan Ditzen). If I understand correctly, the following two commands should be equivalent (both not controlling for cross-sectional dependence):
However, I get very different results (at least regarding the p-values). Can someone explain the difference? Which model is superior in which case?
Also, if I want to control for cross-sectional dependence, my xtdcce2 command would look like this (if I understand correctly):
I understand that one can control for cross-sectional dependence using xtpmg by including averages. Would I include those in the SR or LR equation? And again: which model would be better?
Thank you very much in advance!
I am struggling to understand the differences between the Stata commands xtpmg and xtdcce2 (written by Jan Ditzen). If I understand correctly, the following two commands should be equivalent (both not controlling for cross-sectional dependence):
HTML Code:
xtpmg d.log_ResProd_short d.ResTaxRate_Infl_PPP d.log_PopDens d.log_GDP_pc, lr(l.log_ResProd_short ResTaxRate_Infl_PPP log_PopDens log_GDP_pc) ec(ec) replace pmg
HTML Code:
xtdcce2 d.log_ResProd_short d.ResTaxRate_Infl_PPP d.log_PopDens d.log_GDP_pc, lr(l.log_ResProd_short ResTaxRate_Infl_PPP log_PopDens log_GDP_pc) pooled(l.log_ResProd_short ResTaxRate_Infl_PPP log_PopDens log_GDP_pc) nocrosssectional
HTML Code:
Pooled Mean Group Regression
(Estimate results saved as pmg)
Panel Variable (i): Country_Code Number of obs = 645
Time Variable (t): Year Number of groups = 31
Obs per group: min = 11
avg = 20.8
max = 26
Log Likelihood = 911.8572
-------------------------------------------------------------------------------------
D.log_ResProd_short | Coefficient Std. err. z P>|z| [95% conf. interval]
--------------------+----------------------------------------------------------------
ec |
ResTaxRate_Infl_PPP | .0643741 .0154175 4.18 0.000 .0341563 .0945919
log_PopDens | 2.612486 .1629119 16.04 0.000 2.293185 2.931788
log_GDP_pc | .8725355 .0349202 24.99 0.000 .8040931 .9409778
--------------------+----------------------------------------------------------------
SR |
ec | -.3689291 .0535052 -6.90 0.000 -.4737974 -.2640608
|
ResTaxRate_Infl_PPP |
D1. | 1.428748 1.130847 1.26 0.206 -.7876705 3.645167
|
log_PopDens |
D1. | -2.042252 1.804974 -1.13 0.258 -5.579936 1.495432
|
log_GDP_pc |
D1. | .6399973 .0700586 9.14 0.000 .502685 .7773096
|
_cons | -7.34668 1.069888 -6.87 0.000 -9.443622 -5.249738
-------------------------------------------------------------------------------------
HTML Code:
(Dynamic) Common Correlated Effects Estimator - Pooled Mean Group (CS-ECM)
Panel Variable (i): Country_Code Number of obs = 645
Time Variable (t): Year Number of groups = 31
Degrees of freedom per group: Obs per group:
without cross-sectional avg. min = 3 min = 11
max = 18 avg = 22
with cross-sectional avg. min = 3 max = 26
max = 18
Number of F(128, 517) = 5.47
cross-sectional lags none Prob > F = 0.00
variables in mean group regression = 97 R-squared = 0.42
variables partialled out = 31 Adj. R-squared = 0.28
Root MSE = 0.10
CD Statistic = 20.59
p-value = 0.0000
--------------------------------------------------------------------------------------
D.log_ResProd_short| Coef. Std. Err. z P>|z| [95% Conf. Interval]
----------------------+---------------------------------------------------------------
Short Run Est. |
----------------------+---------------------------------------------------------------
Mean Group: |
D.ResTaxRate_Infl_PPP| 1.144401 .8314861 1.38 0.169 -.4852817 2.774084
D.log_PopDens| -1.663779 1.683031 -0.99 0.323 -4.962458 1.634901
D.log_GDP_pc| .7696895 .0380582 20.22 0.000 .6950968 .8442821
----------------------+---------------------------------------------------------------
Adjust. Term |
----------------------+---------------------------------------------------------------
Pooled: |
L.log_ResProd_short| -.2480367 .7273092 -0.34 0.733 -1.673537 1.177463
----------------------+---------------------------------------------------------------
Long Run Est. |
----------------------+---------------------------------------------------------------
Pooled: |
ResTaxRate_Infl_PPP| .0519683 .7605495 0.07 0.946 -1.438681 1.542618
log_PopDens| 2.546216 2.789462 0.91 0.361 -2.921029 8.013462
log_GDP_pc| .7305529 .8004832 0.91 0.361 -.8383653 2.299471
--------------------------------------------------------------------------------------
Pooled Variables: L.log_ResProd_short ResTaxRate_Infl_PPP log_PopDens log_GDP_pc
Mean Group Variables: D.ResTaxRate_Infl_PPP D.log_PopDens D.log_GDP_pc
Long Run Variables: ResTaxRate_Infl_PPP log_PopDens log_GDP_pc
Cointegration variable(s): L.log_ResProd_short
Heterogenous constant partialled out.
Warning:
Collinearities detected. One or more variables are dropped and set to zero.
Use estat ebistructure to display more details.
HTML Code:
xtdcce2 d.log_ResProd_short d.ResTaxRate_Infl_PPP d.log_PopDens d.log_GDP_pc, lr(l.log_ResProd_short ResTaxRate_Infl_PPP log_PopDens log_GDP_pc) pooled(l.log_ResProd_short ResTaxRate_Infl_PPP log_PopDens log_GDP_pc) crosssectional(d.log_ResProd_short d.ResTaxRate_Infl_PPP d.log_PopDens d.log_GDP_pc)
Thank you very much in advance!
