The role of green financing, agriculture development, geopolitical risk, and natural resource on environmental pollution in China

Due to climatic uncertainties, the biosphere experienced tremendous growth of anthropogenic activities, which eradicates the sustainable environment for living beings. Thus, the continuous rise in environmental pollution detains the attention of the environmentalist to discover strategic approaches to maintain the green ecological era. Therefore, the present study aims to identify the role of green financing, agriculture development, geopolitical risk, and natural resources on China's environmental pollution (CO2 emission). We use time series data ranging from 1995 to 2020 using the Quantile Autoregressive Distributed Lags (QARDL) method proposed by (Cho et al., 2015). Further, we use Causality-in-Quantile to check the asymmetric association. However, the empirical results of causality signify an asymmetric relationship and bi-directional causality among all the variables. In addition, the results of QARDL indicate the negative and significant p-values of error correction parameters throughout the qualities, which confirmed the reversions to the long-term association between the determinants and CO2 emission. Whereas across all the quantiles, the negative and significant association of green financing (GFIN) with CO2 emission in QARDL is found, and other factors such as geopolitical risk (GRP), agriculture development (AGR), and Natural resources (NNR) show a positive and significant association with CO2 emission mainly in the upper quantiles. While the results of short-run QARDL analysis indicate that GFIN, GPR, and NNR are positively associated with CO2 emission, the significance level varies, GPR and GFIN are highly significant with environmental pollution at upper quantiles (0.05-0.40), and NNR is highly significant at all quantiles (0.05-0.95). Based on these estimations, some concrete implications are proposed for the practitioners to minimize the repercussion of CO2 emissions in China.