We use non-performing loan ratio and insolvency risk to measure bank risk and construct panel data regression models to examine the effects of the interbank market rate, central-bank rate and bank-level lending rate on bank risk in China. Empirical results show that interbank market rate and the central-bank interest rate are positively correlated with bank risk, while the bank-level lending rate is negatively correlated with bank risk. We also analyse and explain the difference between the effects of the US interest rates and China's interest rates on its own bank risk. Finally, we put forward some policy implications.

This paper applies the Panel Smooth Transition Regression (PSTR) model to simulate the effects of the interest rate and reserve requirement ratio on bank risk in China. The results reveal the nonlinearity embedded in the interest rate, reserve requirement ratio, and bank risk nexus. Both the interest rate and reserve requirement ratio exert a positive impact on bank risk for the low regime and a negative impact for the high regime. The interest rate performs a significant effect while the reserve requirement ratio shows an insignificant effect on bank risk on a statistical basis for both the high and low regimes.

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The authors use a panel data regression model to examine the effects of main monetary policy instruments on commercial bank risks in China from 1998 to 2011. The interest rate has a positive effect on bank risk while the interest rate margin, the reserve requirement ratio and open market operation have a negative effect. Among the three monetary policy instruments, the reserve requirement ratio has the greatest effect on bank risk, the interest rate (the interest rate margin) the second largest and the open market operation the weakest. Their findings provide guidance to the monetary authority and regulatory authorities in monetary policy and banking regulation in China.

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