The overall development of China's domestic sports goods manufacturing industry has shown a positive trend. As of October 28, 2014, the industry in East China maintained the highest share of sales revenue and experienced sustained growth. From 2003 to 2014, the region's sales revenue increased from 1,873 million yuan to a significant proportion of the national total, with an impressive growth rate of 261.79%. In other regions, such as North, Northeast, Central, Northwest, and Southwest China, the sales figures were relatively similar, but their development paths varied over the past seven years. Notably, Central and Southwest China saw a remarkable increase in sales revenue—4595.75% and 1379.95%, respectively—despite starting from a lower base. North and Northeast China also demonstrated steady growth, while the Northwest region faced a decline of 91.11%. From a national perspective, the industry recorded a 203.83% increase in sales volume between 2003 and 2014, reflecting a healthy and growing domestic sports goods manufacturing sector. To analyze the long-term relationship between cultural education levels, national income, and the development of the sports goods industry, a panel cointegration model was applied. Before conducting regression analysis, it was essential to check the stationarity of the data to avoid spurious results caused by non-stationary time series. This involved unit root tests on panel data. Four different testing methods were used to ensure robustness. The variables were transformed into logarithmic form because the difference in logarithms approximates the growth rate of economic variables, which are typically stationary and suitable for classical regression models. This approach also helped to capture the long-run elasticity between cultural education, national income, and sports goods production. The unit root test results showed that the first-order differences of the variables were stationary. The test specifications included only an intercept term without a trend, and the lag order was determined using the Schwarz Information Criterion (SIC). The statistical significance levels are presented in parentheses. Overall, the findings suggest a stable and meaningful relationship among the key economic indicators and the growth of the sports goods manufacturing industry.

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