Fanyue, Li
(2018)
An empirical analysis of the determinants of credit risk in
Chinese banking sector.
[Dissertation (University of Nottingham only)]
Abstract
Abstract
For banking sector, credit risk is the main risk since the main business for banks is loans. And loans will bring about the problem of credit risk. Non-performing loans can be used as an indicator to measure this kind of credit risk. China, as a developing country, is the second economic utility all over the world. In this dissertation, we try to use some bank-specific variables and macroeconomic variables to measure non-performing loans in China during the period from 2011 to 2017.
When it comes to the methodology, most previous studies in non-performing loans employ a static model. In this dissertation, we take the first lag of non-performing loans into consideration and therefore employ a dynamic model. At the same time, we make a comparison between static model and dynamic model.
Regarding the origin of the data used in the empirical model, they were collected from Bankscope database and the World Bank database. All the data are in the form of panel data.to examine the relationships between bank‟s credit risk and its macroeconomic and microeconomic determinants.
Regarding the empirical result, it can be concluded that credit risk in the banking sector can be both significantly affected by macroeconomic factors and bank-specific factors. In our empirical research, the macroeconomic factors include interest rate, unemployment rate, inflation rate and GDP growth rate. Our results show that GDP growth rate is not significantly correlated with the credit risk but other three macroeconomic variables is significant. More specifically, the unemployment rate is positively related with the credit risk, but interest rate and inflation rate both have negative relationship with the non-performing loans.
As regard to the bank-specific determinants, the first lag of non-performing loans is positively related with the dependent variable. At the same time, the coefficient of this variable is between the coefficient in the OLS and in the fixed model. It shows that GMM is valid and accurate. The loan to asset ratio is also significant and the relationship is positive. The other four variables which are loan loss provision, loan
loss provision, equity to asset, return on average asset is not significant.
Finally, the result of this empirical research gives the Chinese banking sector some inspirations. Firstly, the effect of the first lag of non-performing loans shows that the credit risk is affected by the value of previous year. Thus, it is important for banks to make use of appropriate approach to measure credit risk of borrowers. In addition, it is also important for banks to keep a stable economic condition, since the stability of economic condition is firmly connected with the stability of financial market.
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