Complexity theory for the modern Chinese economy from an information entropy perspective: Modeling of economic efficiency and growth potential

PLoS One. 2020 Jan 28;15(1):e0227206. doi: 10.1371/journal.pone.0227206. eCollection 2020.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • China
  • Economic Development*
  • Efficiency
  • Entropy
  • Humans
  • Industry*
  • Models, Economic*

Grants and funding

This research was performed according to the National Natural Science Foundation of China (Grant No. 71874202, 71874201) and within the Russian state assignment of Russian Academy of Science, Central Economic and Mathematical Institute (No. of state registration АААА-А18-118021390173-4). National Natural Science Foundation of China grant received School of Economics and Management, China University of Petroleum-Beijing by Professor Lianyong Feng. Jun Yan is his PhD student and belong to the same affiliation. Russia grant received Central Economic and mathematical Institute, Russian Academy of Science, laboratory of the microeconomic analysis by the head of member of RAS George Kleiner. Alina Steblyanskaya is the researcher at the Library for the fulfillment of the grant. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.