Which provinces should pay more attention to CO2 emissions? Using the quantile regression to investigate China's manufacturing industry

Abstract

At present, China's carbon dioxide (CO2) emissions ranked first in the world. Moreover, the manufacturing industry is the biggest contributor to CO2 emissions. Most of the existing studies use the average estimation method to investigate the main drivers of CO2 emissions in this industry. However, the data distribution of economic variables is often not normal distribution, and the tail of the data hidden important information. In order to provide a realistic basis for emission reduction in this industry, this paper applies the quantile regression approach to investigate the driving forces of CO2 emissions under high, medium and low emission levels. The empirical results indicate that the effect of economic growth on CO2 emissions in the upper 90th and 75th–90th quantile provinces are higher than those in the other quantile provinces. The influence of energy intensity in the 25th–50th quantile provinces is lower than those in the other percentile provinces. The impact of urbanization in the upper 90th quantile provinces is the strongest in all the quantile provinces. However, the influence intensity of energy structure in the lower 10th quantile provinces is the highest in all the quantile provinces. Therefore, policymakers should focus on the heterogeneous effects of driving forces on CO2 emissions in different quantiles during the process of CO2 emission reduction.