Abstract
This study revisits the influence of renewable energy intake, globalization, trade, and GDP on carbon pollution in the United States of America (USA). Although previous studies have mostly used parametric techniques, we investigate the cointegrating association between carbon dioxide emission (CO2e) and its known drivers using the non-parametric quantile autoregressive distributed lag (QARDL) methodology considering data from 1970 to 2019. This technique allows us to check whether the impacts are homogeneous or heterogeneous across different emission quantiles and helps in proposing dynamic policies accordingly. The findings reveal that across all the quantiles the long-run parameter of renewable energy consumption shows an inverse relationship with the CO2e. On the other side, the nexus between globalization and CO2e is positive across all quantiles. It is interesting to note that trade does not affect CO2e in any quantile while GDP has a favorable influence only in the lower quantiles. Additionally, we used a quantile Granger causality technique and discovered a pertinent bidirectional link that corroborates the QARDL model's findings. This study also promoted a dynamic policy paradigm that is centred on the Sustainable Development Goals (SDGs) to achieve SDG-13 by mitigating climate change effects and attain SDG-7 by promoting clean energy consumption in the USA.
•The nexus between clean energy use, globalization, trade and CO2 is explored.•A quantile autoregressive distributed lag method has been leveraged.•Renewable energy use negatively influence carbon emissions across all quantiles.•The nexus between globalization and CO2 is positive across all quantiles.•Trade does not affect emissions in any quantile.