Abstract
This paper discusses the determinants of credit spreads in China and the United states. Based on the sampled data of corporate bonds in the two countries from 2011 to 2017, we fit the yield curve of the treasury bonds with the Nelson-Siegel Model and calculate the credit spreads of each corporate bond. Then we use multiple linear regression and vector auto regression model (VAR) to analyze the determinants. The results indicate that the model can explain a large part of the credit spreads and the goodness of fit reaches over 60%. The specific results are as follows: (1) GDP and stock market volatility are negatively correlated with the credit spreads of Chinese corporate bonds but positively correlated with that of American corporate bonds with high significant level; (2) M2, stock market indexes and risk-free yield rate are negatively correlated with the credit spreads of both countries despite the fact that of all these three determinants M2 is not significant in the U.S. market and the risk-free rate of return is not significant in the Chinese market; (3) the slope of treasury bond yield curve is positively correlated with the credit spreads of corporate bonds in both countries; and (4) the impulse response shows that the impact of the determinants on credit spreads is obviously weaker than the impact of credit spreads on the determinants, which indicates that credit spreads might have a certain degree of predictive function.