Research on Optimization of International Trade Added Value Estimation Based on Kernel Density Estimation Under Digital Background

The kernel density estimation algorithm has the feature of starting entirely from data, which provides a new path for the optimization of trade value-added measurement. This paper first analyzes the trade value-added model and international competitiveness measurement indicators and constructs a kernel density estimation algorithm model based on the digitalization context. Secondly, we analyze the basic situation and location distribution of trade value added in China in the digital context. The trade value-added and value-added rate are measured, and the development pattern is analyzed and explored. Finally, based on the qualitative analysis, we analyze the impact response of trade value added to the degree of vertical specialization of the international division of labor and measure and optimize the international trade value added based on the kernel density estimation method. The analysis results find that the index of the degree of vertical specialization is positively correlated with the export trade addition rate. In the short run, the export trade addition rate has a greater impact on its own changes. In the long run, nearly 36.2% of the fluctuating changes in the export trade addition rate are influenced by the degree of vertical specialization. From period 3 onward, its impact on the export trade addition rate accounts for 37.2% of the level. The optimization of international trade value-added measurement based on kernel density estimation algorithm is an inevitable trend of digital development.