Modeling the impact of structural changes in international trade on economic growth based on principal component analysis

China's domestic demand is weak, the growth of domestic demand is constrained, some industries are overproducing, and many enterprises are facing great challenges in production and operation. This paper focuses on analyzing the influencing factors of export trade structure, constructing a regression model according to the related theory of influencing factors, and analyzing the covariance of variables and determining the variable indicators affecting economic growth through principal component regression analysis. Based on the BEC criterion and the research experience of the previous researchers, the international trade structure indicator model applicable to China was established, and the least squares method in multiple linear regression was used, and the test was carried out according to the analytical steps of the Granger test. The adjusted R square is 0.4686, the regression variance F value is 7.198, the significance is 0.0245, less than 0.05 indicates that the regression equation is valid and the proposed variables can be used for role analysis. The results of regression analysis show that every 1% increase in the coefficient of comparative advantage raises economic growth by about 0.0635%. The change of international trade structure has a positive impact on economic growth, but the current change of international trade structure has a certain path dependence, so there is a lag in the performance of the response of the change of international trade structure to economic growth.