Abstract

The purpose of this research is to identify the influence of GDP growth rate, bank interest rate, inflation rate, capital adequacy ratio, and return on asset towards non-performing loans in Chinese commercial banks partially and simultaneously. This study has applied descriptive statistical analysis, classical hypothesis testing, multiple linear regression, and hypothesis testing. When selecting the observation data, this research adopts the intentional sampling method and panel data, 70 units of observational data in total, one part of the data was taken from the financial reports of seven selected sample companies on the Shanghai Stock Exchange in China, and another part of the data was taken from the kyle website. The method used in a quantitative approach with the instrument is EViews 10. The result indicates that BIR and IFR have a partially negative significant influence on NPL. However, GDP growth rate, CAR, and ROA have a negative insignificant effect on NPL. Simultaneously, all of the independent variables have a significant effect on NPL which is described by the value of 63.9% and the left 36.1% is explained by another factor that is excluded in this study. Furthermore, IFR was chosen as the most significant factor which influences NPL.

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