Yali Ye and Sakgasit Ramingwong

Published in Data Science and Engineering (DSE) Record 2022 Vol. 3 No. 1 pp. 12-24



This research uses a combination of principal component analysis and mul-tiple linear regression analysis for the analysis of the influencing factors and the degree of influence on the foreign trade of Sichuan Province, China. Firstly, a visual analysis of the current situation of foreign trade in Sichuan province is conducted, which includes the structure of foreign trade mode, foreign trade commodity structure, and foreign trade partner structure of Sichuan prov-ince. Second-ly, the indicators that may affect the foreign trade of Sichuan prov-ince are selected and the empirical model is constructed using these indica-tors. Principal component analysis was used to extract principal components, and then regression analysis was conducted on the extracted principal com-ponents. Finally, the empirical results show that the gross regional product, consum-er price index, foreign direct investment, average disposable income of resi-dents, and investment in research and experimentation have a positive im-pact on Sichuan's foreign trade, and the RMB harms foreign trade.