Investigating the connections between China's economic growth, use of renewable energy, and research and development concerning CO2 emissions: An ARDL Bound Test Approach

This study investigates how economic growth, use of renewable energy, research and development can impact carbon dioxide emissions in China during the time frame 1990-2019. To detect stationarity in data, unit root tests, including Augmented Dickey-Fuller, Phillips-Perron, KPSS, and KSUR approaches, were employed within the observation. Also, the Autoregressive Distributed Lag or ARDL bound approach for short-run and long-run tests was performed to detect the elasticity of independent variables. Later, the research employed several diagnostic inspections, such as the ARCH LM, BG-LM, and White inspection for homoscedasticity, Ramsey RESET and the Durbin-Watson approach. CUSUM and CUSUM squares methods were used for detecting stability. Findings show China will face environmental adversity for higher economic growth. Furthermore, carbon emission is negatively related to renewable energy usage in China. Increasing renewable energy usage will reduce carbon emissions. Additionally, this study observed a significant relationship between carbon emissions through research and development. Further, DOLS for robustness detection has been used in this study. The study recommends policies to achieve economic growth with a minimal amount of carbon emissions through increasing renewable energy usage along with well-planned research strategies to achieve an emission-free sustainable environment.