Dear all,
I'm using xtabond2 program to run a System-GMM regression but due to my lack of experience in estimating such a kind of model I'm not sure if I'm doing this correctly.
To summarize, my dependent variable is I (co2 emissions) and my regressors are Lagged I, P (population), Arpc (per capita GDP), T (technology), Jovens (% of the young population), Urb (% of the urbanized population). I'm also controlling for time fixed effects and to do that I have manually created time dummies for each period of 11 years (year1-year11). Moreover, I'm considering P, Arpc and T as endogenous on the other hand Jovens and Urb as exogenous.
Then I've wrtitten:
Output:
Question:
1) Is my equation correctly specified in terms of what I want to estimate?
2) In the two-step estimate case, is Windmeijer (2005) finite sample corrected standard errors automatically considered?
Thanks in advance
I'm using xtabond2 program to run a System-GMM regression but due to my lack of experience in estimating such a kind of model I'm not sure if I'm doing this correctly.
To summarize, my dependent variable is I (co2 emissions) and my regressors are Lagged I, P (population), Arpc (per capita GDP), T (technology), Jovens (% of the young population), Urb (% of the urbanized population). I'm also controlling for time fixed effects and to do that I have manually created time dummies for each period of 11 years (year1-year11). Moreover, I'm considering P, Arpc and T as endogenous on the other hand Jovens and Urb as exogenous.
Then I've wrtitten:
Code:
xtabond2 L(0/1).I P Arpc T Jovens Urb year3-year11, gmm( (L.I P Arpc T ), laglimits(1 2) collapse equation(diff)) gmm( (L.I P Arpc T), laglimits (1 2) collapse eq(level)) ivstyle(year3-year11 Jovens Urb, eq(level)) robust
Code:
Warning: Two-step estimated covariance matrix of moments is singular. Using a generalized inverse to calculate robust weighting matrix for Hansen test. Difference-in-Sargan/Hansen statistics may be negative. Dynamic panel-data estimation, one-step system GMM Group variable: Ufs Number of obs = 243 Time variable : Year Number of groups = 27 Number of instruments = 27 Obs per group: min = 9 Wald chi2(15) = 12631.21 avg = 9.00 Prob > chi2 = 0.000 max = 9 Robust I Coef. Std. Err. z P>z [95% Conf. Interval] I L1. .6907989 .1206875 5.72 0.000 .4542556 .9273421 P .3544818 .1373551 2.58 0.010 .0852707 .6236929 Arpc .0193619 .1761628 0.11 0.912 -.3259108 .3646347 T .2768321 .1494431 1.85 0.064 -.016071 .5697353 Jovens .5500081 .6569872 0.84 0.402 -.7376632 1.837679 Urb .1433756 .3570893 0.40 0.688 -.5565066 .8432577 year3 .1007848 .0325687 3.09 0.002 .0369514 .1646182 year4 .0568161 .0276051 2.06 0.040 .002711 .1109211 year5 .0044997 .0342335 0.13 0.895 -.0625967 .0715962 year6 0 (omitted) year7 -.0018433 .0437424 -0.04 0.966 -.0875769 .0838903 year8 .0895687 .047629 1.88 0.060 -.0037824 .1829197 year9 .0757619 .0492587 1.54 0.124 -.0207834 .1723072 year10 .0882288 .0575049 1.53 0.125 -.0244787 .2009363 year11 -.0233054 .0688169 -0.34 0.735 -.158184 .1115732 _cons -2.485526 3.38637 -0.73 0.463 -9.122689 4.151637 Instruments for first differences equation GMM-type (missing=0, separate instruments for each period unless collapsed) L(1/2).(L.I P Arpc T) collapsed Instruments for levels equation Standard year3 year4 year5 year6 year7 year8 year9 year10 year11 Jovens Urb _cons GMM-type (missing=0, separate instruments for each period unless collapsed) DL(1/2).(L.I P Arpc T) collapsed Arellano-Bond test for AR(1) in first differences: z = -2.02 Pr > z = 0.043 Arellano-Bond test for AR(2) in first differences: z = -0.05 Pr > z = 0.958 Sargan test of overid. restrictions: chi2(11) = 21.87 Prob > chi2 = 0.025 (Not robust, but not weakened by many instruments.) Hansen test of overid. restrictions: chi2(11) = 9.95 Prob > chi2 = 0.535 (Robust, but weakened by many instruments.) Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for levels Hansen test excluding group: chi2(3) = 4.92 Prob > chi2 = 0.177 Difference (null H = exogenous): chi2(8) = 5.03 Prob > chi2 = 0.754 gmm(L.I P Arpc T, collapse eq(diff) lag(1 2)) Hansen test excluding group: chi2(3) = 6.95 Prob > chi2 = 0.074 Difference (null H = exogenous): chi2(8) = 3.00 Prob > chi2 = 0.934 gmm(L.I P Arpc T, collapse eq(level) lag(1 2)) Hansen test excluding group: chi2(3) = 4.92 Prob > chi2 = 0.177 Difference (null H = exogenous): chi2(8) = 5.03 Prob > chi2 = 0.754 iv(year3 year4 year5 year6 year7 year8 year9 year10 year11 Jovens Urb, eq(level)) Hansen test excluding group: chi2(1) = 0.50 Prob > chi2 = 0.482 Difference (null H = exogenous): chi2(10) = 9.46 Prob > chi2 = 0.489
Question:
1) Is my equation correctly specified in terms of what I want to estimate?
2) In the two-step estimate case, is Windmeijer (2005) finite sample corrected standard errors automatically considered?
Thanks in advance
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