Assessing CO2 emissions in China's iron and steel industry: Evidence from quantile regression approach

China is currently the largest carbon dioxide (CO2) emitter in the world, and the iron and steel industry is the main contributor to the growth in CO2 emissions. Most of the existing studies use the average estimation method to investigate the main drivers of CO2 emissions in the iron and steel 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 study uses the quantile regression model to explore the driving forces of CO2 emissions under high, medium and low emission levels. The results show that the effect of economic growth on CO2 emissions in the upper 90th quantile provinces is stronger than those in other quantile provinces due to the differences in fixed-asset investment and automobile production. However, the impact of energy efficiency in the upper 90th quantile provinces is lower than those in other quantile provinces. The influence of industrialization in the lower 10th quantile provinces is stronger than those in other quantile provinces. The influence intensity of energy structure has a similar story owing to the differences in coal consumption. Therefore, policymakers should focus on the heterogeneous effects of driving forces on CO2 emissions in different quantiles during the process of carbon reductions. (C) 2017 Elsevier Ltd. All rights reserved.