An empirical study on balance of trade in China based on random forest regression model

This paper studies the nonlinear relation between the balance of trade and the affection factors. The nonlinear regression model for the balance of trade is constructed by random forest (RF) method. Moreover, the ranking of importance for affection factors is given out. The empirical results in this paper reveal the balance of trade in China is affected mainly by M2, GDP, CPI, Exchange reserves, M1 and Gross Industrial output, which is helpful for the government decision-making.