Abstract
Development is the eternal theme of the times. However, the transformation of the development mode is imminent, and we should abandon the extensive economic development mode and turn to the efficient development of an intensive mode. The high-tech industry will be the decisive force in future industrial development. The agglomeration of the industry will help form economies of scale, thereby improving the effective allocation of resources and promoting productivity. The increase in green economy efficiency is a key factor in achieving green development and an important indicator of achieving the coordinated development of economic development and environmental protection. Therefore, in this study, we try to improve the efficiency of the green economy through industrial agglomeration to achieve green development. In order to solve this problem, we took the Yangtze River Economic Belt as the research object, used Super Slacks-based Measure (SBM) data envelopment analysis (DEA) and general algebraic modeling system (GAMS) to study the green economy efficiency, and then used the system generalized moment method (SGMM) to study the impact of high-tech industry agglomeration on green economy efficiency. According to the empirical test, we found that (1) the green economy efficiency of the Yangtze River Economic Belt shows a volatile upward trend, (2) the green economy efficiency of the Yangtze River Economic Belt differs with time and by region, (3) the agglomeration of the high-tech industry has a lagging effect on the improvement of green economy efficiency, and (4) the regression coefficients of economic development and foreign direct investment are positive and those of environmental regulation and urbanization are negative. Finally, in this paper, we provide corresponding policy recommendations to promote the agglomeration of high-tech industries, thereby improving the efficiency of the green economy.
Highlights
The development of the global social economy progressed with the deepening of the industrial revolution
Common methods used for measuring economic efficiency include stochastic frontier analysis (SFA), the Solow residual method, and data envelopment analysis (DEA)
We used the Super-Slacks-based Measure (SBM) DEA model created by Tone [40] to introduce the slack variable into the objective function, which solves the problem of effective sorting
Summary
The development of the global social economy progressed with the deepening of the industrial revolution. The Outline for the Development of the Yangtze River Economic Belt was officially issued in September 2016, proposing the innovation drive to promote industrial issued in September. 2016, proposing theand innovation driveoftogreen promote industrial transformation, transformation, as well as the upgrading construction ecological corridors, as the two as well as the upgrading and construction of green ecological corridors, as the two keyindustries tasks for key tasks for the development of the Yangtze River Economic Belt in China [2]. It mainly is closely related to ecological economics, but has a more politically applied includes the environmental protection, new energy, and clean production industries. Green that natural resources continue to provide the resources and environmental services on which growth must drive investment and innovation to support sustainable development and create new humans depend. The high-tech industry in the Yangtze River Economic Belt developed rapidly.
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