Abstract

The study is pioneer to investigate the role of renewable energy, tax revenue and women governance in reducing CO2 emissions in 29 Asian developing countries over the period 1996–2020. To this end, dynamic and static panel data models such as GMM and quantile regression are employed for unbalanced and heterogeneous data. The results suggest that quantile regression model is more robust than GMM for the estimation. The findings show that the renewable energy has significant and negative effect on CO2 emissions in all quantiles whereas the impacts of tax revenue and women governance on CO2 emissions are varying across the quantiles. On this occasion, the findings confirm that renewable energy can be used as a policy variable while tax revenue and women governance are not reliable for policy implications. Furthermore, the findings revisit the previous studies. Since the renewable energy has significant and negative association with CO2 emissions in Asian developing economies, policy implications must consider renewable energy transition in order to reduce carbon dioxide emissions.

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