Exploring asymmetric influence of R&D expenditures on CO₂ emissions in China: evidence from nonlinear ARDL model

R&D spending upsurges technological advancement and innovation which results in lowering energy consumption and environmental degradation. The current study investigates the asymmetrical impact of R&D spending on CO₂ emissions in China via employing annual data from 1980 to 2021 and the NARDL model for empirical analysis. The estimated results of the NARDL model confirmed that there are asymmetries in positive and negative coefficients of R&D spending in China. The results depict that the positive shock in R&D spending exerts a negative and statistically significant impact on CO₂ emissions in both runs implying that an increase in R&D spending lowers CO₂ emissions. However, the negative coefficient of R&D spending yields a positive and statistically significant impact on CO₂ emissions revealing the fact that a negative shock in R&D spending results in the upsurge of CO₂ emissions in China. According to these findings, the impact of positive and negative shocks in R&D spending on CO₂ emissions is asymmetric. The findings also show that the impact of a negative shock in R&D spending is greater than the impact of a positive shock on CO₂ emissions. In addition to the negative shock in R&D spending, increases in energy consumption, economic growth, and FDI inflows also contribute to an upsurge in CO₂ emissions in China. The robustness of the estimated results is assessed using standard fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models. The FMOLS and DOLS results have been confirmed to be sound and consistent with the results of the NARDL model. The study suggests that the economic strategies should aim at investing in R&D spending to foster environment-friendly technological innovations and to lower environmental degradation in China.