经济复杂度:测算与应用

Economic Complexity:Measurement and Application

经济复杂度是运用网络科学和生物学方法,测度经济体的经济发展质量和产业升级转型概率,刻画经济体的技术含量和发展能力的重要概念。由于经济复杂度方法能有效解释经济增长的国别差异、在产业升级方向和风险识别方面具有可操作性、产业政策指导上具有较强的针对性,学界和政界对经济复杂度的相关研究日益重视。然而,关于经济复杂度的理论基础和测算方法,学者们并未形成共识。因此,本文拟提炼经济复杂度的理论基础,比较各种经济复杂度的算法,梳理学者们对经济复杂度的相关应用研究,并通过计算中国1998年至2013年分省份的经济复杂度指数,对中国经济复杂度进行了截面和时间序列的比较研究,得出中国部分省份存在过早去工业化现象、经济复杂度不高的结论。同时,对经济复杂度的研究方法进行了述评,为进一步深化对经济复杂度的研究奠定基础。

Economic complexity is an important concept to measure the quality of economic development and the probability of industrial upgrading and transformation of an economy using network science and biological methods,and to characterize the technological content and development capability of an economy.Since the economic complexity approach can effectively explain the country differences in economic growth,is operable in terms of industrial upgrading direction and risk identification,and has strong relevance in industrial policy guidance,the academic and political circles have paid increasing attention to the research related to economic complexity.However,scholars have not reached a consensus on the theoretical basis and measurement methods of economic complexity.Therefore,this paper intends to refine the theoretical basis of economic complexity,compare various algorithms of economic complexity,sort out scholars’relevant applied research on economic complexity,and conduct a cross-sectional and time-series comparative study on China’s economic complexity by calculating China’s economic complexity index by provinces from 1998 to 2013,and concludes that there is premature de-industrialization and low economic complexity in some Chinese provinces.At the same time,a review of economic complexity research methods is conducted to lay the foundation for further deepening the research on economic complexity.