Affiliation:
1. Nanjing Xiaozhuang University, Nanjing, Jiangsu 211171, China
2. Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 210016, China
Abstract
The paper constructs an economic growth model that contains human, physical capital, innovation, and energy factors and estimates the output elasticity of seven provinces and cities in East China in the period of 2004–2018. Having calculated the contribution rate of these different factors to economic growth, the paper finds that factors of production have a different elasticity that impacts the growth of different regions and industries and notes that energy and physical capital are the most significant factors for the growth of primary and secondary industries. This highlights that industrial growth has not freed from the path dependence of extensive input, and the authors cite Shanghai and Jiangsu as typical regions in this regard. The former’s growth largely depends on physical capital and energy, and the latter’s growth depends on the input of diverse elements including innovation. The latter is better suited to the needs of the “new normal” economic growth. The authors construct a simulation model of economic growth based on system dynamics, and system simulation results show that energy and material capital investment not only have the most significant effect on economic growth in East China but also provide clear evidence of extensive economic growth. The paper then demonstrates that increasing the optimal allocation of input factors and the rational flow between regions is conducive to improving output efficiency and provides the results of the Malmquist index calculation: on the whole, there is no obvious technological progress in East China. Shanghai, Jiangsu, and Zhejiang are, however, provincial-level regions of this part of the country which demonstrate significant technological progress in East China. In conclusion, the paper suggests that this region of China will be unable to maintain its current level of economic growth because of the combined influence of factor input constraints and insufficient technological progress.
Funder
National Social Science Foundation of China
Cited by
2 articles.
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