Abstract
Complexity modelling of economic efficiency and growth potential is increasingly essential for countries and provinces. Evaluating the monetary flows, kinetic energy (efficiency) and potential capacity (resilience) provides crucial information for economic development. In the paper, the authors analyze growth opportunities for the Chinese economy from a system science point of view, using the perspective of information entropy, based on the input-output tables. Over the past four decades of reform and opening-up, China has made remarkable progress in its economic development. In 2007, China’s GDP was at its fastest pace in history at 14.2% growth. However, after the financial crisis in 2008, the global economy experienced a downward trend and China's economic development also settled on a medium-low level of development. The traditional perspective is to rank regional development only based on GDP growth, whereas here, the authors advocate another evaluation method based on efficiency and potential growth. Unbalanced regional economic development has become problematic and has become a barrier for sustainability of China’s economy. The results of the research indicate firstly that China’s regional development in 2007 and 2012 has been unequal between the provinces. Secondly, the authors found that Shandong province had significantly higher indicators for efficiency and potential growth than others in the same circumstances. Authors observe that provinces tend to carry out industrial policies and adjust the structure of industry on a local level. This analysis demonstrates that the spatial imbalance of efficiency and potential of economic development under the perspective of provincial-level regions. From the perspective of industry, it indicates that the supply chain is too short, mainly focusing on the mining and processing of resources and minerals in the original upstream industry chain, while the downstream is not fully utilized. These represent some unique insights yielded through this type of analysis that authors advocate applying more broadly.
Highlights
In the paper, the authors pursue the goal of comparing China’s provinces and industries in order to identify which one is the most efficiency and has the highest potential growth
What are the characteristics of economic development? Can the parameters of efficiency and resilience reflect the underlying economic characteristics? The authors try to analyze Chinese economy by using a system science approach, complex science methodology
According to Bogdanov “the aim of Tectology is the systematization of organized experience”, through the identification of universal organizational principles: “all things are organizational, all complexes could only be understood through their organizational characteristics
Summary
The authors pursue the goal of comparing China’s provinces and industries in order to identify which one is the most efficiency and has the highest potential growth. In 1997, professor Wang Hengjun of Xiaan university of Posts and Telecommunications in China advocated applying the concepts of energy and entropy in physics into economics and put forward the concepts of economic energy, Entropy perspective for economic development efficiency and resilience economic entropy, absolute economic entropy, and relative economy He believed that entropy caused economic crises, which was an inevitable social and economic phenomenon [9]. Some of which involve to take into account of multiple components–internal and external subsystems and monitoring the entropy of complex systems, as reflected in the works of Vladimir Bulygin, Gennadiy Averin, Vladimir Opritov and Alexander Banaru[12,13] It is research gap in case of input-output data analyzing by use of information entropy. Analyse the efficiency and resilience (potential capacity) of the Chinese economy from the point of view of a complex economy and analyze the entropy of the internal provinces and industries subsystems. Third part is the obtaining results presentation concerning Province economy modeling and industrial economy modeling
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