Abstract
This paper uses an econometric model of hierarchical data space to do empirical research on the knowledge spillover effect of industrial industries in Guangdong Province. Specifically, three-dimensional panel data (regions, industries, and time) of 21 prefecture-level cities and 31 industrial industries in Guangdong Province from 2005 to 2016 were used and spatial correlation, time factors, and hierarchical nesting effects were taken into consideration to establish hierarchical data. The spatial econometric model uses an industrial structure to empirically analyze the impact of the knowledge spillover effect of the industrial industry in Guangdong on its economic development.
Highlights
It has been a topic of debate both at home and abroad for the knowledge of what kind of industrial structure knowledge spillover has had a significant impact on the development of industrial industries
The spatial econometric model uses an industrial structure to empirically analyze the impact of the knowledge spillover effect of the industrial industry in Guangdong on its economic development
The innovation of an industry can bring about the innovation of other industries and form a reciprocal effect on spatial aggregation, thereby promoting the growth of the overall industrial economy
Summary
It has been a topic of debate both at home and abroad for the knowledge of what kind of industrial structure knowledge spillover has had a significant impact on the development of industrial industries. Empirical studies on knowledge spillovers at home and abroad explore the impact of knowledge spillovers in different countries and regions on employment, economic growth, patents, etc. Liu Manfeng and Wu Zhuoxian (2013) [14] collected high-tech industrial cluster data from 2008 to 2010 to establish a double-logarithmic spatial econometric model, studied the knowledge spillover effect of high-tech industries, and found that the MAR effect and Jacobs effect are prominent in China. Three aspects of such research need to be further improved: First, no spatial correlation is considered, second, the correlation in the time dimension is not considered, and third, the hierarchical nesting effect is not considered In view of these three types of issues, this paper adopts a hierarchical data space econometric model to empirically study the impact of knowledge spillovers in high value-added industrial industries in Guangdong on economic growth. The model (7) is estimated using a hierarchical data space econometric model
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