Stochastic Environmental Research and Risk Assessment, cilt.38, sa.5, ss.1855-1871, 2024 (SCI-Expanded)
This study is intended to expose the connectedness of green financing and other green policies like renewable energy and technological progress towards identifying the best practice to achieve climate goal cum sustainable environmental development for China within the period 1985–2021. Amid the increased utilization of fossil fuels in China’s economic activities and its position as the highest carbon emitting country in the world, China is considered a financial stable economy with access to renewable energy source such as hydroelectric power. For effective research into the objective of this study, the study builds on mechanism of the green finance—renewable—technology and emission nexus with the help of linear dynamics of ARDL bound and VECM granger causality methods. Empirical results from both approaches have given insight to the selected objectives of this study. According to ARDL dynamics: (i) the coefficients of linear (1.802) and non-linear(− 1.860) (i.e. square term) of financial development are positively and negatively connected to the carbon emissions. This confirms the presence of inverted U-shape relationship between the financial development and carbon emissions. (ii) the relationship between hydroelectric power representing renewable energy and CO2 is negative—(− 0.19) and significant at 1% level. This results depicts the reduction power of hydroelectric power on CO2, (iii) also, a negative (− 0.000982) linkage between number of patent application representing technological innovation and environmental development through carbon emissions responses is established. Also, findings from VECM granger causality approach back the findings from ARDL through a nexus between the variables of interest (finance, hydroelectric power, and technology and carbon emissions). Findings point to the ability of green financing to reduce carbon emissions if green financing policies are utilized effectively in regulating carbon emissions.