Applying Panel Quantile Regression to Analyze the Determinants of Carbon Emissions in China’s Cement Industry

Climate change resulting from CO2 emissions from industrial activities has got people’s attention. Over the past 30 years, China has undergone rapid process of urbanization, leading to a substantial increase in CO2 emissions from the cement industry. This study employs the STIRPAT model to examine the effects of economic growth, real estate investment, infrastructure investment, and energy efficiency on carbon emissions in the cement industry. We utilize both the panel fixed-effect regression model and the panel quantile regression model, using panel data from 30 provinces from 2004 to 2017. The panel quantile regression analysis reveals a dynamic relationship between the factors and CO2 emissions. Economic growth demonstrates a positive impact on CO2 emissions across all quantile levels, with a stronger effect observed as CO2 levels increase. Real estate and infrastructure investment exhibit positive influence on CO2 emissions, although the impact patterns vary. Energy efficiency exhibits a negative impact on CO2 emissions across most quantile levels, excluding the upper 80th quantile where the correlation is relatively weaker. In contrast, the fixed-effect regression model shows that economic growth and real estate investment has negative relationship with CO2 mission. Different result might be influenced by extreme values. The main findings will be useful to policy makers for enabling and accelerating progress achieving sustainable development in China’s cement industry.