توسعه اقتصادی و دی اکسید کربن تولید گازهای گلخانه ای در چین:تجزیه و تحلیل داده های پانل استان

This paper investigates the driving forces, emission trends and reduction potential of China's carbon dioxide (CO2) emissions based on a provincial panel data set covering the years 1995 to 2009. A series of static and dynamic panel data models are estimated, and then an optimal forecasting model selected by out-of-sample criteria is used to forecast the emission trend and reduction potential up to 2020. The estimation results show that economic development, technology progress and industry structure are the most important factors affecting China's CO2 emissions, while the impacts of energy consumption structure, trade openness and urbanization level are negligible. The inverted U-shaped relationship between per capita CO2 emissions and economic development level is not strongly supported by the estimation results. The impact of capital adjustment speed is significant. Scenario simulations further show that per capita and aggregate CO2 emissions of China will increase continuously up to 2020 under any of the three scenarios developed in this study, but the reduction potential is large.

Scientific evidence overwhelmingly indicates that greenhouse gas emitted by human activity is the main cause of global warming. Stern (2007) warns that, if no action is taken to reduce emissions, the overall costs and risks of climate change will be equivalent to at least a 5% of global GDP loss each year. With progress in industrialization and urbanization, China's energy consumption and carbon dioxide (CO2) emissions have increased rapidly in the past few years. In 2009, the total energy consumption of China reached 2.9 billion tons of standard coal, with the total CO2 emissions reaching 7.7 billion tons.1 As one of the largest emitters, China has become the focus of global reduction of CO2 emissions. Thus the following questions need to be addressed. What are the main factors affecting China's CO2 emissions? What are the emission trends for the foreseeable future? How large is the reduction potential?

In this paper, we investigate the driving forces, evolution trends and reduction potential of China's CO2 emissions. A provincial panel data set of China's CO2 emissions covering the years 1995–2009 is constructed, a series of static and dynamic panel regression models are estimated, and then a best forecasting model selected by in-sample and out-of-sample criteria is used to forecast the emission trends and reduction potential up to 2020. The results are summarized as follows.