JOURNAL OF CONTEMPORARY FINANCE AND ECONOMICS ›› 2021, Vol. 0 ›› Issue (2): 42-56.

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R&D Spillovers and the Complexity of China's Industrial Products under the Dual-Circulation Pattern

LI You   

  1. Jiangxi University of Finance and Economics, Nanchang 330013, China
  • Online:2021-02-15 Published:2023-12-29

Abstract: The increase in product complexity can promote the sustained economic growth. The more types and quantities of complex products a country can produce, the more invincible the country is in the international economic competition. This paper discusses in detail the mechanism of R&D spillovers influencing product complexity under the dual-cycle pattern and uses the data of 32 Chinese industries from 2000 to 2017 to empirically test the effects of R&D spillovers on the product complexity in China's industries. The results of the theoretical mechanism analysis show that under the new development pattern with the domestic big cycle as the main body and the domestic and international double cycles promoting each other, R&D spillovers can promote product complexity through competition effects, feedback effects, market demand-induced effects, demonstration and imitation effects, and human capital effects. The results of the empirical test show that intra-industry R&D can significantly promote the increase of product complexity. Although inter-industrial R&D is positively correlated with product complexity, it is not significant. Foreign R&D has significantly promoted the complexity of Chinese industrial products through import channels and other channels; foreign direct investment has also played a significant role in promoting the increase in the complexity of China's industrial products. The industrial human capital is an important factor in the increase of the complexity of China's industrial products. Product complexity has a significant cumulative feature, and the product complexity of the previous batch plays a significant role in promoting the complexity of the current products.

Key words: dual-circulation pattern, product complexity, R&D spillover, panel data model