Research Of The Low Carbon Economy Efficiency In China’s Provincial Regions Based On RAM Model

Under the background of global warming, environmental pollution and energycrisis and other problems that threaten human development and survival, the wholeworld reached a broad consensus in response to global warming. Development oflow-carbon economy needs China to focus on coordinated development among theresources, the environment and economics. We need to consider the carbon emissioninto the economic development inspection system in order to achieve the less energyconsumption and the less emission. Through the technological innovation, systeminnovation, industrial transformation, new energy development and other means toachieve social development as well as environmental protection. Then we come closerto the low-carbon economic development model. Therefore, at the transition periodChina is facing with the tradeoff of energy saving and the economic growth. It is aresearch hotspot that the judgment of the current level of coordination of them.This paper uses the foreword outcome of the DEA method, namely RAM model,as well as nonparametric rank sum test and convergence inspection methods toresearch the issues of low-carbon economy development in China. This paperresearches the static level of the low-carbon economy efficiency and the dynamicevolution of the low-carbon economy efficiency from a comprehensive view.Therefore, we can reach a comprehensive understand of the equilibrium state ofChina’s provincial energy, carbon emissions and economic growth. Based on theenvironmental technology theory, we calculated the economic efficiency and carbonemission efficiency through the RAM models. And based on the additive structure ofthe RAM model, we constructed a new model, namely the RAM model for thelow-carbon economy efficiency. Using it we evaluated the state of the balanceddevelopment of the economic growth, energy, and carbon emissions. And through thedecomposition of slack variables we analyzed and discussed the endogenous sourcesof less balanced growth for energy reduce, carbon emissions reduce and economicgrowth. We introduced assumption of the sequence production possibilities set intothe RAM model and ML index, in order to build a low-carbon total factor productivityindex and decomposition analysis was done to reseach changes in the deep-seatedcauses.The conclusions are as follows. First, China’s rising trend of low-carboneconomic efficiency mainly comes from the improvement of carbon environmentalefficiency. China’s economic efficiency, environmental efficiency and low-carboneconomy efficiency have differences between the regions. It is from the east, centralto west. Overinvestment and excessive energy consumption are the reasons for theinefficiency of China’s economic efficiency, carbon emission efficiency andlow-carbon economic efficiency. The low-carbon economic efficiencies of the wholecountry, east area and west area all show significant σ convergence. There is aconvergence in them. But we can not determine whether there is σ convergence incentral. Second, extensive development mode damages the growth of China’s lowcarbon total factor productivity. Currently, the high cost of the environment restricts the growth of the quality of China’s development. China urgently transforms to thewell development of energy, carbon emissions and economic development, namelythe transformation of low-carbon economy growth model. Before2006, the growth oflow-carbon total factor productivity is mainly pursued by the regional effects ofpromoting efficiency. After2006, China has shown a technological progress.The values of research are as follows. First, we build a RAM model baseddual-output in order to research the low-carbon economic efficiency. We realise thereasonable judgment of the coordinated development degree among the energy,carbon emissions and economic growth. We reach the formation of low-carboneconomic efficiency calculations system, and through decomposition analysis of theslack variables we research the deep reason of the non-efficiency. All of them offer anew perspective to explore the problems of energy, economic growth and carbonemissions. Second, the paper constructs a low carbon total factor productivity index.It improvers the current production maybe set and thus avoids the macroeconomicimpact of fluctuations on the index calculation and the technical setback misjudgment.