Nonperforming Loans

  One of the main problems of SMEs is how to finance their investments. The role of banks in this regard is crucial, since they can be a type of sources of financing through lending credits directly to SMEs. The key role of the paper thus relies on analyzing the effect of SMEs financing by the Iranian banking system.   The objective of this paper is to determine the influence of loans demanded by the SMEs on finance performance of the various Iranian banks. In addition, it studies the role of other important characters related to lending, bank efficiency, and economic performance in finance to SMEs through the banking system.   It is motivated by the hypothesis that macroeconomic-cyclical indicators and bank-specific variables influence the nonperforming loans in the banking system. This is carried out by an application to a logit model. Our findings indicate that several variables have significant effects on nonperforming loans in the Iranian banking system . Return of asset, equity return, SME loan to total loan ratio, inflation, current asset to current liabilities ratio, total SMEs€™ loans to total liabilities ratio and total SMEs€™ loans to total assets ratio have the pronounced significant impacts on nonperforming loans of the Iranian banking . The coefficient of loans to SMEs is significantly positive, which implies that a loan to SMEs increases nonperforming loans method while raising risks to the banking system. JEL Classification: C35, D22, E51

The evidence of the recent years in the banking network of Iran indicates the increasing trend of nonperforming loans each year; thus, the main objective of the current study is to examine the impact of bank specific factors, esp. capital adequacy ratio on the NPLs. Six years dynamic panel data (2007-2012) of 19 banks are applied to scrutinize the relationship between capital adequacy ratio as well as other determinants and the NPLs. Applying correlation and regression analysis shows that the research model which has been utilized is of decent statistical qualification. Results emphasize that banks should control and amend their credit advancement policy with respect to factors influencing the NPLs to have lower non-performing loan ratio and should take into account their risk weighted assets and riskiness of their loan portfolio before they commence lending. In advance of lending to high risky projects and to low quality borrowers, banks should pay attention to the interests of both stakeholders and banks as well as they should consider the riskiness level of their loan portfolio to provide the accurate information relating to their performance because of the probability of high risk project failure which might evidently lead to the growth in NPLs. JEL Classification: C21, G23, G32

Financial statements of nineteen mature banks have been patronized to examine the impact of macroeconomic indicators and bank-specific determinants on the NPLs ratio through Quantile and Panel Data regression approaches. The impact of macroeconomic indicators on credit risk is statistically estimated for banking network via two directions. First, different quantiles are econometrically calculated, assessed and compared during 2007-12. Second, the Panel Data estimation is utilized in the same way to verify the outcomes of quanitle regression and to check the robustness. Results indicate that the impact of real money supply on the banks’ NPLs in 25%, 50%, and 75% of data is positive and significant in line with empirical evidence. The coefficients of the other variables (including the ratio of individual banks’ performing loans to total deposits, individual banks’ performing loans to total loans ratio, as well as GDP would be positively significant as well. The real interest rate has negatively-significantly driven NPLs. The banks’ NPLs are generally exacerbated by the impact of higher real money supply over the long run, real interest rate in the money market and upper return in the assets market mainly because of the negative-inflationary transmission effect. JEL Classifications: C16, C23, E51, G21