Has a significant negative impact on the development of sporting goods manufacturing industry

The development of the sporting goods manufacturing industry has been significantly affected by cultural education levels and national income, as revealed through panel cointegration analysis conducted between 2014 and 2010. The β-coefficient estimates across different regions show considerable variation, suggesting that the influence of cultural education, national income, and sports product manufacturing development differs across areas. While some regions exhibit strong long-term positive correlations, others display contrasting patterns. Comparing the coefficients from two panel cointegration equations, it becomes evident that per capita income has a more substantial impact on the growth of the sporting goods industry than cultural education levels. This implies that economic factors play a more critical role in driving this sector compared to educational indicators. The analysis of seven major regions in China using Dynamic Ordinary Least Squares (DOLS) provides a comprehensive view of how cultural education and income levels affect the development of sporting goods manufacturing. In North China, Northeast China, East China, South China, Central China, and Southwest China, both cultural education and per capita income have a significant positive impact on the industry, with income showing a stronger influence. However, there are notable differences in the magnitude of these effects across regions. In contrast, in the northwest region, both cultural education levels and per capita income have a negative effect on the development of the sporting goods manufacturing industry. This discrepancy raises important questions. Despite an increase in college graduates and per capita GDP in the northwest region, sales revenue in the sporting goods sector has declined. This suggests a complex relationship where higher education and income do not necessarily translate into improved performance in the industry. Further research is needed to understand the underlying factors behind this negative correlation and to explore potential strategies for improving the sector’s growth in this region.

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