Purpose: This study examines the asymmetric effects of economic growth, energy consumption, renewable energy, trade openness, and innovation on CO2 emissions in China and India. It aims to determine whether positive and negative shocks in these variables generate different environmental responses across economies undergoing energy transition. Design/methodology/approach: The analysis employs a Nonlinear Autoregressive Distributed Lag (NARDL) model using annual data from 1990 to 2023. The framework decomposes explanatory variables into positive and negative partial sums to estimate asymmetric long-run and short-run effects. Dynamic multipliers are used to trace adjustment paths, while a symmetric ARDL model serves as a robustness check. Findings: The results reveal strong and persistent asymmetries in China, particularly in energy use, renewable energy, and innovation. Positive energy shocks significantly increase emissions, while reductions produce limited environmental gains, reflecting structural rigidities. Renewable energy reduces emissions asymmetrically, and innovation exhibits direction-dependent effects. In contrast, India shows weaker and more selective asymmetries, with emissions primarily driven by short-run energy demand and limited long-run structural effects. The symmetric model fails to capture these dynamics, confirming the importance of nonlinear modeling. Conclusion: The findings demonstrate that emissions dynamics are nonlinear and country-specific. Asymmetry is more pronounced in structurally advanced economies undergoing energy transition, while developing economies remain demand-driven. These results highlight the need for differentiated and context-specific environmental policies.
Ihsen Abid (Thu,) studied this question.