The choice of China’s economic growth path from the perspective of the population

LU Jin1 WANG Enze1 GUO Zhiyi2

(1.School of Economics, Qingdao University)
(2.School of Economics, Lanzhou University)

【Abstract】Based on the fact that the traditional homogenous production function cannot fully and accurately describe the significant differences in the economic growth paths among the provincial regions in China, this paper applies the finite mixture model with concomitant variables to the balanced panel data of 30 provincial regions from 2000 to 2017. From the perspective of demographic structure, the heterogeneity of China’s economic growth path is analyzed and the total factor productivity and factor contribution are accounted for. The three-category finite mixture model shows that there are three heterogeneous growth paths in China during the sample period. Under different paths, the decline of the natural population growth rate and the increase of urbanization rate and the labor ratio have helped to stimulate the effect of labor force on economic growth. The increase in the level of aging and the decline of human capital have enhanced the dependence of economic growth on capital. Meanwhile, under the three growth paths, although the contribution of capital is the highest, the improvement of human capital will be conductive to increase the contribution of total factor productivity to economic growth. In addition, compared with the finite mixture model with concomitant variables, the traditional growth model underestimates the contribution of total factor productivity and labor, and overestimates the contribution of capital to economic growth.

【Keywords】 population; economic growth; path option;


【Funds】 The National Social Science Fund of China (18BJL117)

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(Translated by HE wenshan)


    [1]. ① For more model details, readers can refer to the research by Owen et al. (2009). [^Back]

    [2]. ① Considering the serious lack of data of Tibet, they are excluded from the samples. [^Back]

    [3]. ① Due to the limited space, the results of the finite mixture model without concomitant variables are not listed. [^Back]

    [4]. ① Due to the limited space, the comparison of contribution of different factors between the traditional growth regression model and the finite mixture model are not listed. [^Back]


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This Article


CN: 11-1043/C

Vol , No. 05, Pages 85-95+128

October 2019


Article Outline


  • 1 Introduction
  • 2 Empirical model setting and description of variables and data
  • 3 Empirical analysis
  • 4 Conclusion
  • Footnote