Greening the finance for climate mitigation: An ARDL–ECM approach.

Green finance is an effective policy instrument in mitigating climate change, but to date little is known about its impact on carbon dioxide (CO 2) emissions. This study extends the literature on the relationship between green finance and CO 2 emissions while taking trade openness and economic development into consideration to comprehensively explore the conservation/feedback hypothesis using the Autoregressive-Distributed Lag–Error Correction Model (ARDL–ECM) on data collected from 2000 to 2019. By constructing a green finance index comprising green credit, green securities, green insurance, and green investment, results include the following. (1) Support was found for the conservation hypothesis running from green finance, trade openness, and economic development to emissions per capita; the conservation hypothesis also was supported for the unidirectional relationship running from trade openness and economic development to green finance. (2) Green finance is found to be significantly and negatively related to emissions per capita in both the short and long term. (3) Trade openness shows a positive effect on emissions per capita. Robustness tests are provided. This study deepens policy implications of green finance in the post-pandemic era and highlights the moderating role of renewable energy in the green finance impact on carbon mitigation. • This study constructs a green finance index for China. • The autoregressive distributed lag–error correction model is employed. • Green finance contributes to carbon mitigation in both the short and long run. • CO 2 emissions are Granger result of green finance, trade openness and economic growth. • Trade openness and economic growth are Granger causes of each other. [ABSTRACT FROM AUTHOR]