Panel ARDL Analysis of Trade, Energy Innovation and Carbon Emissions in N-11 Economies

Abstract

The present study investigates the dynamic interrelationships between trade openness, energy innovation, renewable energy consumption, economic growth, and carbon dioxide (CO2) emissions in the Next-11 (N-11) economies for the period 2000–2024. This study employs annual panel data and panel autoregressive distributed lag (ARDL) technique with pooled mean group (PMG) estimator to examine the short-run dynamics and long-run equilibrium relationships among the variables. The empirical results indicate that the error correction coefficient is significant and negative (-0.322661) confirming the presence of a stable long-run cointegrating association and implying that about 32 percent of the disequilibrium is corrected in one year. In the long run, renewable energy consumption has a highly significant and negative effect on CO₂ emissions with a coefficient of -0.101619 while trade openness has a significant mitigating effect with a coefficient of -0.015851. In contrast, the coefficient for economic growth is 0.010406, which shows a positive marginal effect of economic growth on emissions, and the coefficient for energy innovation is 1.67, which implies that general innovation would increase emissions initially until green technologies are effective. Short run: Only renewable energy consumption has marginal significance while the remaining variables do not have statistically significant immediate effects. The bounds testing approach is used to verify cointegration and the Hausman test is used to check the suitability of the PMG estimator. These findings highlight the importance of the N-11 economies to accelerate renewable energy adoption, encourage environment-specific innovations, and utilize trade openness for green technology transfer for sustainable development and emission reduction goals.