Research on the Impact of Sci-Tech Finance on Industrial TFP

Abstract

The improvement of industrial Total Factor Productivity (TFP) is the basis for the high-quality development of China’s economy. Sci-tech finance affects industrial TFP through screening and allocation mechanism, governance mechanism, and integration mechanism. Based on provincial panel data from 2009 to 2016, this paper constructs a comprehensive index of regional Sci-tech finance and explores the impact of Sci-tech finance on industrial TFP from two perspectives: differences in financial development levels and transmission paths. The results show that Sci-tech finance has a significant role in promoting the industrial TFP, but this promotion needs to meet certain financial development conditions. In high-level financial development areas, the promotion effect is significant. It is not linear. The effect is a threshold effect with the diminishing marginal efficiency. Sci-tech finance mainly promotes industrial TFP through boosting the industry’s scientific and technological innovation capacity. Policies and channels of Sci-tech finance to support science and technology innovation are put forward.

Keywords:

• Sci-tech finance
• threshold
• industry
• TFP

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 High-level financial development areas: Beijing, Tianjin, Shanghai, Jiangsu, Chongqing; Medium-level financial development areas: Hebei, Shanxi, Liaoning, Jilin, Heilongjiang, Zhejiang, Fujian, Jiangxi, Shandong, Henan, Hubei, Hunan, Guangdong, Guangxi Zhuang Autonomous Region, Sichuan, Shaanxi; Low-level financial development areas: Inner Mongolia Autonomous Region, Anhui, Hainan, Guizhou, Yunnan, Gansu, Qinghai, Ningxia Hui Autonomous Region, Xinjiang Uygur Autonomous Region. Hainan Province, Guizhou Province, Yunnan Province, Gansu Province, Qinghai Province, Ningxia Hui Autonomous Region, and Xinjiang Uygur Autonomous Region.

2 In the existing literature, Sobel and Bootstrap tests are commonly used to further test mediating effects. However, the Sobel test requires that the product of parameter ${\alpha }_{21}{\alpha }_{32}$ must obey normal distribution, and the data obtained in practice often cannot meet this requirement, which leads to certain limitations of the Sobel test method. Therefore, the bootstrap test proposed by Preacher and Hayes (2008) was adopted in this paper to overcome the defects of Sobel test.

Additional information

Funding

It was supported by the Humanities and Social Science Planning Project of Ministry of Education of China (No. 20YJA790040), Department of Science and Technology of Shaanxi Province (No. 2023-CX-RKX-065), and Fundamental Research Funds for the Central Universities (No. 2022ZYYB17).