ANALYSIS OF DETERMINANTS THAT INFLUENCE NON PERFORMING LOAN S AT BOC, CCB, ICBC AND ABC (FOUR CHINA STATE OWN COMMERCIAL BANKS) DURING PERIOD 200 7 TO 2013

Abstract

The objectives of this research are to investigate the effect of Gross Domestic Product Growth Rate ((∆ GDP ), Lending Interest Rate LIR ), Index of Business Condition IBC) and Inflation Rate IR ) to Non Performing Loan s (NPL s ) which is as important issues of Financial Performance at BOC, CCB, ICBC and ABC (four China state own commercial banks) during period 200 7 to September 2013 . This research is using time series data from People s Bank of China , China Banking Regulation Committee and World Bank financial report quarterly from Q1 of 20 0 7 to Q3 of 2013. Analysis technique which is used is multiple linear regression analysis and this research is using several tests which are hypothesis testing and classical assumption testing. Hypothesis testing is using t test to test partial influence and F test to test simultaneous influence in level of significance 5%. Other test in this research is classical assumption test including normality test, multicolinierity test, heteroscedastisity test and autocorrelation test. During the research period, it shows that the research data was normally distributed. According to multicolinierity test, heteroscedasticity test and autocorrelation test, there is no deviation of classical assumption in the research data, thus it indicat es that the data have fulfilled the condition to use multiple linier regression model. The result of F test in this research shows the significant jointly influence of ∆ GDP, LIR, IBC and IR toward NPL s of at BOC, CCB, ICBC and ABC (four C hina state own commercial banks) banks). While the research of t test shows LIR IBC and IR partially has positive and significant influence toward NPLs . On the other hand ∆ GDP has negative and significant influence toward NPLs . This research recommends that at BOC, CCB, ICBC and ABC (four C hina state own commercial banks) should be concern to factors that influence NPLs to prevent the problem of NPLs