Green versus non-green technology innovation and environmental quality: Cointegration and counterfactual analysis

Despite growing interest in green innovation and green investment as solutions to climate change, existing literature largely examines these elements in isolation, overlooking their combined effects and the contrasting role of non-green technologies. Addressing this gap, the present study investigates the impact of both green and non-green technological innovations on carbon emissions in Canada, while incorporating the roles of green investment, institutional quality, and geopolitical risks. Using annual time series data from 1990 to 2023, the study employs a novel dynamic autoregressive distributed lag (DARDL) approach to explore the cointegrating and counterfactual relationships among these variables. The findings indicate that green innovation and green investment significantly enhance environmental quality by reducing carbon emissions. In contrast, non-green innovation, along with institutional quality and geopolitical risks, is associated with increased emissions and environmental degradation in the long run. Furthermore, the interactions among green and non-green innovations, as well as between green innovation and green investment, and non-green innovation and green investment, show negative links with carbon emissions. Additionally, a counterfactual analysis is conducted to assess the impact of ±1% and ±5% shocks from the independent variables on the dependent variable. To further validate the robustness of these findings, the study utilizes the Kernel-based Regularized Least Squares (KRLS) machine learning algorithm. Finally, the study discusses key policy implications based on the results.