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Page 14 of 21 Özbek et al. Carbon Footprints 2025, 4, 30 https://dx.doi.org/10.20517/cf.2025.43

Table 5. A-ARDL cointegration test results
Model-1 k Test statistics I(1) critical values
1% 5% 10%
A-ARDL(1,1,1,1,1) 4 F 7.172 5.304 4.512
OV
4.98 *
t -4.96 -4.36 -4.04
DV
-4.33 *
F 6.69 4.61 3.74
IV
3.79 *
Diagnostic tests Test statistics Probability values
Breusch-Godfrey 1.96 0.18
White 31.59 0.44
Ramsey RESET 2.57 0.13
Jarque-Bera 0.44 0.80
CUSUM Stable
CUSUMQ Stable
Model-2 k Test statistics I(1) critical values
1% 5% 10%
A-ARDL(1,2,1,1,1) 4 F 7.17 5.30 4.51
OV
4.82869 *
t -4.96 -4.36 -4.04
DV
-4.65815 **
F 6.69 4.61 3.74
IV
3.86720 *
Diagnostic tests Test statistics Probability values
Breusch-Godfrey 2.00 0.16
White 33.19 0.36
Ramsey RESET 1.24 0.28
Jarque-Bera 0.14 0.93
CUSUM Stable
CUSUMQ Stable

The relevant significance levels at critical values refer to the upper limit values of I(1). 10%, 5%, and 1% significance levels are highlighted with *,
and **, respectively.

The CCR estimator in Table 6 is used as a robustness test. According to the CCR results, a 1% increase in
GDP, GDP2, NREN, and TO causes a 2.17% increase, a 0.14% decrease, a 1.09% increase, and a 0.05%
decrease in EF, respectively. The effects in question are also statistically insignificant for the TO variable.
The other variables are significant at the 1% significance level. On the other hand, similar to the FMOLS
results, the C and Trend variables are also significant. Similar to the FMOLS results, the CCR estimator has
also strengthened the results and proven the existence of the EKC hypothesis. The turning point is obtained
as = 7.75. Since this value obtained is the elasticity coefficient, its equivalent in dollars is
approximately $2,321. This result represents the point at which income growth in the Indian economy
affects environmental degradation at the maximum level (peak point).

Table 7 shows the results of Model-2 established to test the RKC hypothesis.