Test Of EKC Curve For Carbon Dioxide Emissions In China

Since the reform and opening-up, China’s economy had the growth which processes by leaps and bounds, giving China a more constructive role in international affairs. However, with the development, China also become the world’s largest emitter of greenhouse gases, facing more pressure from the other countries to cut carbon emissions. In2009, the Chinese government promised to reduce carbon intensity40-45percent by2020compared with the2005level, which is appropriate for China development stage. Will China achieve the goal and how to achieve the goal is under much discussion.One important research direction about CO2emission is to test whether CO2emission satisfied the EKC curve. Most researchers adopted EG or Johensen cointegration model to test the relationship between per capita CO2emission and per capita income, but, in general situation, per capita CO2emission is integrated of order zero, per capita income is integrated of order one, which means the traditional cointegration method is inappropriate. In this study, we use ARDL bounds test instead, which applies irrespective of the order of integration of the regressors. Besides, based on the result of factor decomposition, we also add industry structure and energy structure variables into the regression model.This study investigates the relationship between per capita CO2emission and per capita income in China over period of1952-2011. The following conclusions are derived:(1) Per capita CO2emission is mainly driven by per capita income. Energy structure factors has little influence on per capita CO2emission.The inhibitory effect of energy intensity factor is significant, but weaker than per capita income. Improvements in energy efficiency could reduce energy intensity. Structural changes in the economy has a weak positive effect on energy intensity.(2)There is a monotonically increasing curve between per capita income and per capita CO2emission for the sample period, instead of EKC curve. Income elasticity of CO2emission declines until1994, then rises with per capita income. Besides, The effect of energy structure and industry structure on per capita CO2emission is not significant.(3) The Granger causality test shows that there is bidirectional causality between per capita CO2emission and per capita income, and there is unidirectional causal relationship running from the change of energy structure and industry structure to per capita CO2emission. Which means that the policies of saving energy and reducing emission will slow down economic growth.(4) According to the long run regression model, we forecast the value of carbon intensity in2020. We find,compared with the2005level,the carbon intensity increases, which means we have to transform the mode of economic growth and implement relative policies to accomplish the target.This study adopted factor decomposition method and ARDL model to analyze the relationship of per capita CO2emission and per capita income, which provides reference and reference for the research of CO2emission. Besides, basing on the test of carbon intensity target, it also gives suggestions on the energy saving and emission reduction, which means a lot to complete the carbon intensity target.