Changes Of Industrial Structure, Optimization And TFP Growth Under Constraint Of Resources And Environment

The18th Party Congress report points out that,"to promote strategic adjustment of the economic structure is the main direction of speeding up the transformation mode of economic development", to solve the major structural issues is related to the whole economic and social development, the foundation of realization of short-term steady growth and the goal of promoting transformation, and the key to achieve sustainable economic and social development. China’s current economic is faced with increasing downward pressure, the pay for extensive growth mode in resources and environment have urgent requirement to match with the resources and environment, which is bound to have a lower economic growth rate, and under the premise of building a resource-saving and environment-friendly society, optimize industrial structure to release the economic potential. In fact, this paper maintains that changes and optimization of industrial structure and growth of TFP is under the constraint of resources and environment, environmental regulation provides effective forced mechanism for the optimization and upgrading of industrial structure, resource constraints plays a fundamental role in the evolution of industrial structure,internal innovation drive has key significance for industrial TFP growth and optimization and upgrading of industrial structure.Therefore,this paper argues that the changes and optimization of industrial structure will be influenced by the factor endowments,constraints of environmental regulation policy and the growth of TFP. In recent years, in order to effectively meet the smooth progress of China’s economic growth pattern,"structural adjustment" and "steady growth" is the policy orientation of the government departments at all levels of economic work, taking a new road to industrialization, the development of modern agriculture and modern service industry is the inherent technical requirements and the external policy environment under the new situation. Environmental regulation and upgrading ofindustrial structure can realize collaborative win-win? Based on factor endowments under the perspective of structure optimization, how to choose the mode of development of service industry in China? Under the restriction of resources and environment, how to decide the optimal industrial structure formation mechanism? Based on the producer’s profit maximization motives, how is the role of internal innovation driving mechanism in three industries’ TFP growth? To answer these important questions constitute the starting point of this research and the basic of the selected topic, so this paper will identify the research topics as "Changes of Industrial Structure, Optimization and TFP Growth Under Constraint of Resources and Environment".A country’s industrial structure changes reflect the allocation of resources in the transfer process. To the environmental constraint reaction, enterprises will change the configuration behaviors of factors; as an endogenous variable of industrial structure, resource endowments structure will have a significant impact on industrial structure. Therefore, environmental regulation, factor endowments and change of industrial structure are closely related. The idea of this study is arranged as follows:firstly, make a review of the theoretical literature on changes of industrial structure under constraint of resources and environment, and then establish and analyze mechanism, model and empirical on the effect of environmental regulation, factor endowments on transition of industry structure, and discuss the dynamic and spatial characteristics of China’s industrial structure under resources and environmental constraints, and conversely discuss the environmental regulation policy tool selection problem which is corresponding to achieve the optimization and upgrading of industrial structure,and the starting point of service industry’s development policies; secondly, through the dual optimization motivation analysis of producers and elements suppliers, develope an optimal nominal growth rate model which can quantitatively calculate the optimal industrial structure under the perspective of factor endowments, successfully give a quantification deviation of China’s actual industrial structure from the optimal industrial structure, and create a theoretical framework for the research on optimal industrial structure; finally, according to the element suppliers’profit maximization hypothesis, develop and establish a TFP growth determining equation, and empirical studies of technology innovation difference of China’s three industries, and provide theories and policy practice tool for technology innovation to promote the upgrading of industrial structure.In this paper the main content and the conclusion mainly have the following several points:In Chapter3, Environmental regulation affects industry upgrading mainly by demand, technological innovation and international trade mechanism, this paper analyzes the mechanism effects on industrial upgrading path direction, and then use30Provincial Dynamic Panel Data from1998to2010, we study the effects of environmental regulation intensity on industry upgrading. Dynamic panel estimation results show that, China’s overall environmental regulation intensity has positive effects on industrial upgrading path direction; and regional research results indicate that the central and western region’s environmental regulation intensity is not significant with industrial upgrading, while the eastern region’s environmental regulation intensity has accelerated industrial upgrading.China’s environmental regulation intensity selection should consider the regional differences, and reasonably slow down the speed of economic growth, to strengthen manpower capital construction and advance marketing reform, and so provide the necessary policies and supporting measures to make sure that environmental regulation and industrial upgrading will have the collaborative win-win..In Chapter4, in response to the extensively existing phenomenon of "vigorously improve the proportion of sevice industry" in the process of industrial structure adjusting, this paper construct the optimal industrial structure model embracing factor endowments and technology choices, put forward and argues the important proposition that " the proportion of service industry should be improved in synchronization with the service efficiency", and then we establish two kinds of spatial weight matrix to express economic dependency, using dynamic spatial panel model to test the relationship of factor endowment, the adoption of technology and industrial structure from1998to2010of every area in our country, the results are:(1)confirm that the interprovincial factor endowment, technology adoption and the change of industrial structure have a significant positive correlation between the space, industry structure trend of service is not at random distribution, and rely on a similar geographic features of regions of factor endowment and technology adoption strategy;(2) the higher the factor endowments, the more prominent the service industry’s Three-Dimensional Expansion, technology adoption strategies promote the Horizontal Pushing;(3)Service industry’s Three-Dimensional Expansion mode of China is lagged behind. From the viewpoint of structure optimization, the service industry’s Three-Dimensional Expansion significantly outperforms Horizontal Pushing mode.In Chapter5, Through combining the optimization motivation of producers and that of element providers, we induce an equation of optimal output-growth of each industry, the whole of which is perceived as a micro-economic agent. The explanatory variables involved in the equation are each industry’s output growth rate, capital growth rate, the Lerner index of each industry (which equals the inverse of the absolute value of the demand elasticity) and the stochastic discount factor (with which the whole society measure capital prices). Moreover, the equation still includes three parameters:output elasticity of labor, subjective utility discount factor and relative risk aversion. Based on1992-2009provincial panel data (income as a control variable), we estimate the demand elasticity of price of each industry’s product. Then employing the Stochastic Frontier Approach (with dependent variable being per-capita output and independent variable being per-capital and technological inefficiency factors being education, institution and geographical environment), and based on1996-2002provincial panel data, we estimate each industry’s output elasticity of labor. And then we estimate the subjective utility discount factor, relative risk aversion through GMM method and calculate the stochastic discount factors based on above estimated coefficients. Finally, according to the equation of optimal growth of industry-level output, we calculate China’s three industries’optimal growth rates and optimal industrial structure from1992through2009. The result indicates that there almost exists a coincidental trend shared by each industry’s real growth rate and its optimal growth rate, however the gap still varies with time. A similar scenario exists in the relationship between China’s actual industrial structure and its optimal industrial structure.In Chapter6, based on venture’s motivation toward maximum profit under the basis of Chapter5, we develop a model which determines the technological innovation with factors such as the actual growth of elements’price, the growth of capital, the change of price-controlling power or scale (represented with the change of Lerner Index), the growth of innovation cost (represented with the growth of discount rate of capital market).Then we estimate the growth of China’s industry-level TFPs based on the related data during1992-2010, and further investigate the impacts of influential factors of industry-level innovation with a SVAR model. The empirical results indicate that the actual growth of elements price results in the accelerating of each industry’s innovation, and the capital growth and the growth of discount rate of capital market may have different influence on each industry’s innovation, and the empirical results give evidence for "Schumpeterian" hypothesis. In the end we put forward some strategies for the development of China’s strategic emerging industries.With respect to the avaiable literature, the main contributions or points of innovation of this paper lies in the following four aspects:(1) From the perspective of theoretical and empirical, study the three kinds of conduction mechanisms of environmental regulatory constraints on changes of industrial structure, and use dynamic panel data model to study the effects of environmental regulatory of different regions on industrial structure, the results pointed out that the importance of choice of environmental regulatory tools according to regional characteristics to promote the optimization and upgrading of industrial structure.(2) Build a theoretical model of optimal industrial structure covering endowment, technology adoption, and demonstrate that optimal proportion of the service industry decreases monotonically following the comparative advantage assumption.The spatial econometric analysis of effects of factor endowments and technology adoption on industrial structure shows that, the improvement of the service industry proportion may not be in the direction of industrial upgrading, and should focus on starting from the point of increasing industrial efficiency, optimizing the allocation of resources to achieve the optimization of industrial structure.(3) Based on producers and suppliers’double optimization motivation, develop an optimal nominal growth rate model to take the lead in realizing the quantitatively calculation of the optimal industrial structure, and give reference standards and the corresponding operational industrial policy tool for the goal settings of optimization of industrial structure upgrading.(4) The TFP growth rate equation embracing the actual factors prices growth, technological innovation subjects’ price control capability or scale increasing (representatives with Lerner index increment), the capital market discount rate increment and technological innovation subjects’capital growth rate, and use the Bootstrap likelihood ratio test methods to study the long-term dynamic relationship of three industries’ TFP growth rate and its influencing factors.