I ran xtabond2 command to study the dynamic relationship between institutions and per capita carbon emissions and carbon intensity. The main difference between the two regressions below is the dependent variable. The dependent variable in the first regression is per capita carbon emissions, while in the second is the carbon intensity of energy use.
Code:
qui xtabond2 lpccarb L.lpccarb lrgdp c.lrgdp#c.lrgdp lenguse lpopden indus period3-period31, gmm(L.(lpccarb) L.(lrgdp lrgdp2 lpopden lenguse indus), collapse lag(1 4) ortho) iv(i.year lenguse lpopden, equation(level)) robust twostep small ortho margins , dydx(lrgdp) at((p10) lrgdp) at((p25) lrgdp) at((p50) lrgdp) at((p75) lrgdp) at((p90) lrgdp) Warning: cannot perform check for estimable functions. Average marginal effects Number of obs = 2,953 Model VCE : Corrected Expression : Fitted Values, predict() dy/dx w.r.t. : lrgdp 1._at : lrgdp = 7.722011 (p10) 2._at : lrgdp = 8.404015 (p25) 3._at : lrgdp = 9.261054 (p50) 4._at : lrgdp = 10.13737 (p75) 5._at : lrgdp = 10.63512 (p90) ------------------------------------------------------------------------------ | Delta-method | dy/dx Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- lrgdp | _at | 1 | .3619309 .1424492 2.54 0.011 .0827356 .6411262 2 | .2485135 .1102424 2.25 0.024 .0324425 .4645846 3 | .1059876 .0753118 1.41 0.159 -.0416209 .2535961 4 | -.0397445 .0579482 -0.69 0.493 -.1533208 .0738318 5 | -.1225195 .0631338 -1.94 0.052 -.2462595 .0012204 ------------------------------------------------------------------------------
Code:
qui xtabond2 co2int L.co2int lrgdp lrgdp2 frleg frleg2 c.frleg#c.lrgdp lpopden indus period3-period31, gmm(L.( co2int lrgdp lrgdp2 frleg c.frleg#c.frleg lpopden indus), collapse lag(1 4) ortho ) iv( period3-period31 frleg frleg2 c.frleg#c.lrgdp lpopden , equation(level)) robust twostep small ortho margins , dydx(lrgdp) at((p10) lrgdp) at((p25) lrgdp) at((p50) lrgdp) at((p75) lrgdp) at((p90) lrgdp) Warning: cannot perform check for estimable functions. Average marginal effects Number of obs = 2,944 Model VCE : Corrected Expression : Fitted Values, predict() dy/dx w.r.t. : lrgdp 1._at : lrgdp = 7.723423 (p10) 2._at : lrgdp = 8.404617 (p25) 3._at : lrgdp = 9.26136 (p50) 4._at : lrgdp = 10.13833 (p75) 5._at : lrgdp = 10.63704 (p90) ------------------------------------------------------------------------------ | Delta-method | dy/dx Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- lrgdp | _at | 1 | 1.207137 .459612 2.63 0.009 .3063144 2.10796 2 | 1.207137 .459612 2.63 0.009 .3063144 2.10796 3 | 1.207137 .459612 2.63 0.009 .3063144 2.10796 4 | 1.207137 .459612 2.63 0.009 .3063144 2.10796 5 | 1.207137 .459612 2.63 0.009 .3063144 2.10796 ------------------------------------------------------------------------------
When I ran margins command, I don't know why do I get same dy/dx for carbon intensity at different percentiles? However, that's not the case with per capita carbon emissions (see margins results from the first equation).
#1. Am I running the wrong postestimation command?
#2. Why is the marginal effect of institutions on EKC relationship same at different percentiles for carbon intensity?
#3. Can someone also help me with the interpretation of margins command? I read that it's not a unit change but in fact a small change in x affecting y. Please correct me if I am wrong.
Thank you.
Ritika
0 Response to Margins postestimation command after xtabond2
Post a Comment