I used dynamic panel estimation model - GMM to examine the relationship between institutions and carbon emissions. I have used a quadratic term and interaction term in the same equation. I want to know how to find the turning point when there is a linear, quadratic term and interaction term in an equation.
I ran the following command:
Variables of interest:
frleg: Institutions
i.inclevel: categorical variable with 4 different income levels. High-income level countries is the base category.
Code:
xtabond2 co2int L.co2int i.inclevel frleg frleg2 c.frleg#i.inclevel lpopden indus period3-period31, gmm(L.(co2int frleg frleg2 c.frleg#i.inclevel lpopden indus), collapse lag(1 4) ortho) iv(period3-period31 c.frleg#i.inclevel frleg2 frleg, equation(level)) robust twostep small ortho
Code:
. Dynamic panel-data estimation, two-step system GMM ------------------------------------------------------------------------------ Group variable: cty Number of obs = 2937 Time variable : year Number of groups = 121 Number of instruments = 75 Obs per group: min = 3 F(42, 120) = 32.71 avg = 24.27 Prob > F = 0.000 max = 30 -------------------------------------------------------------------------------------- | Corrected co2int | Coef. Std. Err. t P>|t| [95% Conf. Interval] ---------------------+---------------------------------------------------------------- co2int | L1. | .6831759 .0431564 15.83 0.000 .5977293 .7686226 | inclevel | high-income, OECD | 0 (empty) low-income | 2.143515 .9536475 2.25 0.026 .2553593 4.031671 lower-middle-income | 1.462294 .7817783 1.87 0.064 -.0855731 3.01016 upper-middle-income | 1.53233 .6849764 2.24 0.027 .1761243 2.888536 | frleg | 7.7978 3.146071 2.48 0.015 1.568798 14.0268 frleg2 | -4.561939 1.862 -2.45 0.016 -8.248569 -.8753081 | inclevel#c.frleg | high-income, OECD | 0 (empty) low-income | -3.563873 1.382582 -2.58 0.011 -6.301289 -.8264566 lower-middle-income | -1.873472 1.08048 -1.73 0.085 -4.012747 .2658019 upper-middle-income | -1.923528 .9477975 -2.03 0.045 -3.800101 -.0469549 | lpopden | .0289588 .0539836 0.54 0.593 -.077925 .1358426 indus | .0023753 .0034381 0.69 0.491 -.0044318 .0091824 _cons | -2.699571 1.347477 -2.00 0.047 -5.367482 -.0316595 -------------------------------------------------------------------------------------- Instruments for orthogonal deviations equation GMM-type (missing=0, separate instruments for each period unless collapsed) BOD.L(1/4).(L.co2int L.frleg L.frleg2 1bL.inclevel#coL.frleg 3L.inclevel#cL.frleg 4L.inclevel#cL.frleg 5L.inclevel#cL.frleg L.lpopden L.indus) collapsed Instruments for levels equation Standard period3 period4 period5 period6 period7 period8 period9 period10 period11 period12 period13 period14 period15 period16 period17 period18 period19 period20 period21 period22 period23 period24 period25 period26 period27 period28 period29 period30 period31 1b.inclevel#co.frleg 3.inclevel#c.frleg 4.inclevel#c.frleg 5.inclevel#c.frleg frleg2 frleg _cons GMM-type (missing=0, separate instruments for each period unless collapsed) D.(L.co2int L.frleg L.frleg2 1bL.inclevel#coL.frleg 3L.inclevel#cL.frleg 4L.inclevel#cL.frleg 5L.inclevel#cL.frleg L.lpopden L.indus) collapsed ------------------------------------------------------------------------------ Arellano-Bond test for AR(1) in first differences: z = -4.76 Pr > z = 0.000 Arellano-Bond test for AR(2) in first differences: z = -0.32 Pr > z = 0.750 ------------------------------------------------------------------------------ Sargan test of overid. restrictions: chi2(32) = 79.01 Prob > chi2 = 0.000 (Not robust, but not weakened by many instruments.) Hansen test of overid. restrictions: chi2(32) = 40.32 Prob > chi2 = 0.148 (Robust, but weakened by many instruments.) Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for levels Hansen test excluding group: chi2(24) = 36.88 Prob > chi2 = 0.045 Difference (null H = exogenous): chi2(8) = 3.44 Prob > chi2 = 0.904
1# How to estimate the turning point for institutions (frleg) with respect to each income-level of countries? i.e. turning point for low, middle or upper-middle income countries.
I know if there were no interaction term in this regression, then using the formula b/|2a| would have worked. But, how do I estimate with respect to each income group category?
Can someone please help me with me?
Thank you.
Ritika
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