Industrial Structural, Energy Saving And Emission Reduction Of China:an Econometric Analysis

Since2006,"energy conservation and emission reduction" has become an essential part of China’s sustainable development strategy. From historical data, the heavier industrial structure is a significant source of energy consumption, and industrial adjustment and upgrading is an important entry point and main measure for governments to implement "energy conservation and emission reduction". From the previous documents about the relationship between industrial structure and energy/carbon intensity of China, the main methods are linear regression model and index decomposition methods. However, because of economic cycle and macro-control, China’s industrial structure has a typical non-linear characteristics, which led to the existing research conclusions are often inconsistent with the reality, and its policy recommendations have limitations. Based on the data characteristics and the theory of energy economy, this thesis applied latest and proper econometrical models to analysis the relationship between industrial structure and "energy conservation and emission reduction" of China. This research is expected to produce some conclusions in line with the actual situation of China, and give some inspiring policy recommendations. The main research contents and conclusions and its innovative profile are as following:(1) Based on the results of different theories and methods, the effects of industrial structure (measured by the ratio of industry added value to GDP) on energy intensity (measured by energy consumption per unit of GDP) are variously in different periods of China. According to data features between industrial structure and energy intensity during1980-2009, this paper applied a threshold cointegration model to analysis the nonlinear relationship between them. The results exposes that industrial structure has nonlinear effects on energy intensity when industrial structure is around40.435%:during the periods of1983-1994,1998-2002and2009, the industry/GDP was declined, and industrial structure produced negative effects on energy intensity weakly and discontinuously; during the periods of1980-1982,1995-1997and2003-2008, the adjustment of industry/GDP was not conducive to the reduction of energy intensity. This conclusion suggests that readjusting the industrial structure and transforming the pattern of economic growth are long-term strategies for sustainably pushing the decline of energy intensity. In short-term, it suggests readjust the industry/GDP to below than40%. Compared with the existing research literatures, the conclusions of this study clearly shows the direction and magnitude of structural adjustment in China.(2) Based on the Kaya identity and the data characteristics of China’s economic growth and structural adjustment, a nonlinear model was tested and estimated in order to reflect whether the effects of structural adjustment on carbon intensity were subject to economic growth or not. The results show mat if the rate of economic growth is higher than9.053%, industrial structure and energy mix were not conducive to decline in carbon intensity. Furthermore, the scenario analysis which depends on the Monte Carlo simulation show that the expected values of the average annual decrease rate of China’s carbon intensity are4.34%(2011-2015) and3.51%(2016-2020). It means the carbon intensity in2020is expected to decline by41.19%compare to2005. It also suggests that the rate of economic growth in the interval of7%to8.4%can contribute to carbon emission reduction. Obviously, the positive analysis of the nonlinear model is fully reflects China’s economic background and carbon emission’s characteristics, and simulation-based scenario analysis eliminate subjective factors in similar studies, so the conclusion is robust and rationality. Therefore, the conclusion of the study has an important application value and practical significance for China’s carbon emission reduction in the future.(3) There is a significant difference of resource allocation in different provinces of China, but past papers about energy efficiency often ignore it. Take account of the heterogeneity of resource allocation in provinces, this paper takes rationalization of industrial structure as a threshold variable, and uses a threshold effects stochastic frontier model to analysis the total factor energy efficiency. The test and estimate results show that the economic growth of the different provinces has three technological clubs, and the more reasonable of industrial structure, the higher total factor energy efficiency. Furthermore, the decomposition results show that the less rational industrial structure, the higher contribution of factor inputs, especially the capital investment, on economic output, and the lower contribution of technological progress on economic output. The above conclusions mean that change the economic growth pattern, and enhance the level of rationalization of the industrial structure by technological progress are effective ways to improve energy efficiency.(4) Because carbon emission generates by energy consumption, this paper uses environmental directional distance functions, which is estimated by super-DEA model to improve the efficiency frontier provinces’ estimators, to calculate the total-factor energy efficiency (TFCE). Then, it uses some panel data models to examine the relationship between economic growth pattern, which is characteristic by investment driven, the industrial structure adjustment and the total-factor energy efficiency. The results indicate China’s economic growth pattern is not benefit to improving TFCE; labor flow between industries produces "structure bonus" on TFCE, and capital flow between industries produces "structure burden" on TFCE; the change and upgrade of manufacturing industry structure doesn’t benefit to improve energy efficiency, but it is help to enhance TFCE. These conclusions indicate that it is long-term ways to improve energy/carbon efficiency by transforming economic growth pattern, and getting rid of the barriers between industries, and enhancing the optimization of manufacturing structure by digestion and absorption of new international technology and self-innovation. Compared with the existing literatures, this article provides a new perspective and a new evidence for implement "energy conservation and emission reduction" through industrial structure from the rationalization of industrial structure and the optimization of manufacturing structure.