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Regional Credit, Technological Innovation, and Economic Growth in China: A Spatial Panel Analysis

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  • Huan Zhou
  • Shaojian Qu
  • Xiaoguang Yang
  • Qinglu Yuan

Abstract

Based on data of 31 provinces in China for the period 2007–2017, this paper establishes spatial models by means of a transcendental logarithmic production function and analyzes the impact of regional credit and technological innovation on regional economic growth. The Jenks natural breaks method, kernel density function, and Moran index are introduced for spatial statistical analysis. Spatial weight matrices are constructed from two aspects of geographical characteristics and innovative input characteristics. The empirical results show significant spatial heterogeneity and spatial autocorrelation in economic growth, regional credit, and technological innovation. Both regional credit and technological innovation are important impacts to economic growth, whereas the interaction of regional credit and technological innovation has a negative effect on provincial economic growth. Therefore, we argue that China should rationally allocate regional credit resources, strengthen technological innovation capabilities, and boost the integrated development of regional credit and technological innovation. It is a particularly important way to facilitate regional economic integration and sustainable development.

Suggested Citation

  • Huan Zhou & Shaojian Qu & Xiaoguang Yang & Qinglu Yuan, 2020. "Regional Credit, Technological Innovation, and Economic Growth in China: A Spatial Panel Analysis," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-14, November.
    • Handle: RePEc:hin:jnddns:1738279
    DOI: 10.1155/2020/1738279
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    Cited by:

    1. Shouheng Tuo & Hong He, 2021. "A Study of Multiregional Economic Correlation Analysis Based on Big Data—Taking the Regional Economy of Cities in Shaanxi Province, China, as an Example," Sustainability, MDPI, vol. 13(9), pages 1-13, May.

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