Research on the Factors Influencing the Global Unemployment Rate: Taking China as an Example

Abstract

This article is aiming at finding out the independent variables that can affect the unemployment rate. Twelve independent variables and 572 observations from 1978 to 2021 are chosen. Based on an assumption, these twelve variables do correlate with the unemployment rate. To find out the more accurate relationship between the variables and the unemployment rate, the Multiple Linear Regression Model is built, and in order to avoid the collinearity problem during building the model, the stepwise regression model need to be employed. To get the results, the regression coefficients are compared, especially the VIF value. After identified by the model, only leave four variables. In the end, it shows that the impact of labor force, total imports and exports of goods, number of high schools on the unemployment rate is significant positive, additionally, the impact of the number of libraries on the unemployment rate is significant negative. Beyond that, other factors have no apparent effect on the unemployment rate.