Assessing Banks Internal and Macroeconomic Factors as Determinants of Non- Performing Loans: Evidence from Nepalese Commercial Banks

This study has attempted to ascertain the factors affecting to non-performing loans in Nepalese commercial banks using a sample of ten commercial banks for the period of 2013-2017 with 50 observations, a balanced set of panel data. The descriptive and causal comparative research designs have been adopted for the study. The dependent variable was non-performing loans, while independent variables included both bank specific factors; bank size, return on assets, total loan and advance to total deposit ratio, capital adequacy ratio and macro-economic factors; real gross domestic product growth rate and inflation. The existence of high levels of NPLs would hinder the benefits to the county through inefficient financial intermediation. Hence, there is a national level responsibility towards banks, to manage the NPL ratio at an acceptable level. Consequently, it is important to identify “what causes NPLs and significance of these factors on NPLs”. Therefore, this study would help to get an insight on the bank specific and macro-economic factors, which affect NPLs in commercial banks and in which magnitude bank specific or macroeconomic factors contribute to NPLs. The estimated ordinary least square (OLS) regression model reveals that the bank specific: ROA, LTD and CAR and macroeconomic factors GDP have significant impact on nonperforming loan in Nepalese commercial banks.


Introduction
Non-Performing Loan (NPL) has been crucial factor these days in terms of Banking sector sustainability and profitability. The economic development of a nation and stability of banking system are invariably interrelated.
International experience shows that if NPA is not managed properly, it will lead to banking failures and nationwide financial fragility. Regular monitoring of loan quality is thus essential to ensure a sound financial system and possibly provides an early alarm to regulatory authorities of banking system (Prasanna et al., 2014).
In every economy financial institutions has got a major role to play. Every developed and sound financial institution has got the ability to absorb economic jolts and keep the economic system on track (Aburime, 2009).
In that respect every country's central bank has got a major role to play in form of keeping the financial system on track, so that the consistent economic sustainability can be achieved. However, a few difficulties are faced by the central banks of different countries. The responsibility of the central bank is to regulate financial system and institutions, while financial institutions which report to central bank have the responsibility of implementing the regulations and policies set by the central bank. Commercial banks receive deposits from the customer, and then lends, it in shape of credit.
Among various indicators of financial stability bank's nonperforming loans assume critical importance since it contemplates on the asset quality, credit risk and efficiency in the allocation recourses to the productive sector. A non performing loan is any loan in which interest and principle payments are more than 90 days overdue. (IMF;2005).
In this connection, the main research question in this study as follow: Do bank specific and macroeconomic variables have an impact on the nonperforming loan of Nepalese commercial banks?
Increase non performing loans as the result of ultimate failure of credit policy. It is also observed that the financial crisis is also affected of high NPLs rate in the banking sector. The reason behind the bad debts is the low repaying capacity of the borrower. Ultimately banks have failure. and United Bikash Bank (Birgunj, Parsa) (Bajgain, Jun2, 2016).
In Nepal, NRB has also given direction for lending to Lending to Deprived Sector. At present the lending in deprived sector must be 5% of total outstanding loans As regards lending to priority sector, Banks should lend at least 25% in sectors like agriculture (10%), energy (5%), tourism (5%) and rest of the amount in others sector (export, small and medium enterprises, pharmaceuticals, cement and garment).
The total volume of non-performing loans of the commercial banks decreased by Rs. In this context, the purpose of this study is to analyze the impact of bank specific and macroeconomic variables on the nonperforming loan of commercial banks of Nepal.
Specially, it examines the non performing loan of commercial banks through the internal and environmental variables of size, profitability, capital adequacy ratio, loan to deposit ratio and annual growth of gross domestic product, and inflation. The data were collected from Economic Survey and annual reports of selected banks including their websites. The remainder of this study is organized as follows. Section two has explains about reviews of literature, Section three the methodology and section four analysis of results and section five conclusion. Sinkey and Greewalt (1991)  a positive and significant impact. The results also highlighted the importance of the institutional environment in enhancing credit quality. Specifically, better enforcement of rule of law, sound regulatory quality, better control of corruption, and free. The voice and accountability were significant in reducing non-performing loans. With regards to the business environment, quality of information published by private and public credit bureaus, and legal rights were significant in reducing non-performing loans in the MENA countries. Guy and Lowe (2011) have indicated that GDP growth, inflation and lending rate have significant negative impact on non-performing loans, while loan growth, loan to deposit ratio and ROA were shown to be insignificant variables. Sapkota (2011) has found that Nepal is also facing banking crisis and some of the bank and financial institutions have already failed during last few years and are in the process of liquidation. The Study showed that the failure of banks in Nepal was also the result of the high non-performing assets, lending without differentiating markets, products and borrowers' credit worthiness and excessive loan exposure to real estate. Roy (2014) has emphasized that level of banks" credit plays an important role in economic developments. Indian banking sector has played a seminal role in supporting economic growth in India. Recently, Indian banks are experiencing consistent increase in non-performing assets (NPA). In this perspective, this paper investigates the 18 26 commercial banks covering the period of 2002-2012 with 227 observations. The study found that macroeconomic variables such as the real effective exchange rate have significantly negative impact on non-performing loan. The impact of GDP growth rate was found to be insignificant in this study. One year lagged inflation rate has significant positive impact on non-performing loan. The banks which charge relatively higher real interest rate have higher non-performing loan, which is consistent with the findings of previous studies. The ownership dummy has positive coefficient and significant at one percent level showing that if the bank is government owned the non-performing loan would be higher than that of the private owned banks. As well, more lending in the previous years and current year reduces the non-performing loan since the coefficient of change in loan in current and previous years have negative coefficient and significant at one percent level.

Literature Review
Ekanayake and Azeez (2015)  Return on Equity. The study utilized secondary data obtained from annual report and accounts of the selected banks for the period under study. The data were analyzed using ordinary least square method and ratio analysis.
The specific finding of the work is that return on asset and return on equity have inverse relationship with non-performing loans and loan loss provision respectively while they are positively related to loans and advances.
The conclusion therefore is that the effects of non-performing loans on Commercial Banks' performance is negative and cannot be underestimated, and poses a fundamental danger to the very existence of the Banks as corporate business entities. 19 Rajha (2016) has investigated the determinants of non-performing loans in the Jordanian banking sector during the period 2008-2012. The study used macroeconomic and bank specific factors to identify the determinants of NPLs of Jordanian banks. Using panel data regression, our results report that among bank specific factors, the lagged NPLs and the ratio of loans total assets were the most important factors that affect nonperforming loans positively. However, contrary to international evidence our results show that large banks are not necessarily more effective in screening loan customers when compared to their smaller counterparts. With respect to the macroeconomic factors, we found that economic growth and inflation rate have a negative and significant effect on non-performing loans. In addition, we found that global financial crisis lead to higher non-performing loans in Jordan.
Khan and Ahmad (2017)  and random effect panel least square regression was used to analyze data through STATA application software.
The analysis leads to the conclusion that reduced level of nonperforming loans leads to increased banks performance. It was also concluded that Return on Asset, Earning per share, Capital adequacy ratio and Breakup value per share has got a significant impact on nonperforming loans.
Wood and Skinner (2018)  return on equity, return on assets, capital adequacy ratio and loan to deposit ratio are significant determinants of

Conceptual Frame Work
The main objective of this study is to examine the determinants o NPLs of commercial banks in Nepal. Based on the objective of the study, the following conceptual model is framed. As previously discussed in the related literature review parts, nonperforming loans are affected by both bank specific and macroeconomic factors. Bank specific factors are bank size (LnTA); return on assets (ROA); liquidity (LTD); capital adequacy ratio (CAR); whereas macroeconomic factors are real gross domestic growth rate (RGDP) and inflation rate (INF). Thus, the following conceptual model is framed to summarize the main focus and scope of this study in terms of variables included. The conceptual framework is developed from the prior theoretical and empirical grounds.

Research Methodology
A sample of 10 commercial banks has been taken out of 28 commercial banks. In this study, convenience sampling technique has been used to select the banks as sample. Convenience sampling involves choosing respondents or organization as sample at the convenience of the researcher. In view of speedy collection and cost effective, this study has adopted convenience sampling technique in order to select the banks as sample.
The reason behind choosing of the latest five year from 2012 to 2017 period is to include a fresh data in the analysis. This study has adopted descriptive and causal comparative research design.

 Bank Size
The size is positive but insignificant. This evidence which is inconsistent with previous studies (Rajan and Dhal, 2003;Hu et al, 2006) can be interpreted to mean that large banks are not necessarily more effective in screening loan customers when compared to their smaller counterparts. However, literature provides conflicting theoretical opinions. A negative relationship may mean that a larger banking industry is able to adopt better risk management strategies then a smaller one. On the contrary, in larger sized industries, banks may often resort to excessive risk taking since it is difficult to impose market discipline by regulators and thus they also expect government protection in the case of failures. This is in line with the notion of "too big to fail" therefore suggesting a positive relationship between the two variables (Ghosh, 2015). The study expects a positive effect of size on NPLs.

 Return on Assets (ROA)
The return on assets indicates the ability of bank management to generate profits by utilising the available assets of the bank. Theoretically, the impact of ROA on non-performing loans is ambiguous. A positive impact can be rationalized through the behaviour of bank management. In order to increase short-term earnings, bank management may portray a wrong picture to investors relating to the future profitability and positive return prospects. As a consequence investors access funds from banks and invest in less profitable projects. This results in current good performance and profitability of the banks. However, because of the incorrect forecasting, returns on investment are not in accordance with investors' expectations, resulting in inability of investors to repay their loans and, hence, increases in non-performing loans in the future (Ahmad and Bashir, 2013a).
Conversely, the negative influence of ROA on non-performing loans can rest on the view that banks with strong profitability have less incentive to generate income and are less inclined to engage in the granting of risky loans.
ROA represents efficiency in asset utilization and shows how much net income is generated out of assets. It indicates the ability of bank management to generate profits by utilizing the available assets of the bank. Thus, if the ratio of ROA is high, it indicates that it is better performance in order to generate profit. Strong bank profitability measured in terms of ROA might result from high lending rate, fees and commission that lead bank growth in size and profitability. Thus, ROA gives an idea as to how efficient management is at using its assets to generate earnings. Different researchers found different results regarding the relationship between ROA and NPLs. Ahmed and Bashir (2013) and Makri et al.(2014),) were examined positive significant relationships between ROA and NPLs. However, Boudriga et a., (2009) andSelma andJouini (2013) found negative association between NPLs and ROA by supporting the arguments that states deterioration of profitability ratio measured in terms of ROA leads to riskier activities of banks and then raise the level of NPLs. They justified that since ROA represents efficiency in asset utilization, poor utilization of assets leads higher NPLs for the banks.
Thus, this ratio is expected to have negative relationships with NPLs in this study

 Loan to Deposit (LTD) Ratio
The loan to deposit ratio is a commonly used statistic for assessing a bank's liquidity and it reflects the utilization of funds policy of the bank. An increase in this ratio is indicative of the bank deploying more funds to loans. Such a situation reflects a less liquid position for the bank. The literature suggests that the LTD ratio has a positive effect on the level of non-performing loans. The justification for such a result is that the growth of customer deposits 24 impacts positively on a bank's lending activity. Inefficiencies in the credit administration process in such circumstances can result in a higher level of non-performing loans.

 Capital Adequacy Ratio (CAR)
The capital adequacy ratio measures a bank's solvency and ability to absorb risk. It is used to protect depositors, and promote stability and efficiency in the financial system. Theoretically, the impact of CAR on non-performing loans is uncertain. On the one hand, banks with high levels of CAR may pursue opportunities more aggressively, which means increased risk taking leading to riskier credit portfolios (Demirguc-Kunt and Huizinga, 1999). The ratio of capital adequacy is also measure of bank`s financial strength since it shows the ability to withstand/tolerate with operational and abnormal losses. It also represents the ability to undertake additional business (Habtamu, 2012). As noted by Makri et al.(2014), CAR determines risk behavior of banks. It is a measure of banks solvency and ability to absorb risk. Thus, this ratio is used to protect depositors and promote stability and efficiency of financial systems. According to Makri et al.(2014), there is negative relationship with NPLs indicating a risky loan portfolio is marked by a high NPL (equivalent to high credit risk). However, Djiogap and Ngomsi (2012) found positive association between NPLs and capital adequacy ratio. It is measured by total Equity to total asset ratio.
However, it is expected to have negative association with NPLs in this study.

Gross Domestic Product Growth Rate (GDP)
Salas and Saurina (2002) have found a significant negative effect of GDP growth on NPLs. Economic growth usually increases the income which ultimately enhances the loan payment capacity of the borrower which in turn contributes to lower bad loan and vice versa (Khemraj and Pasha, 2009). Accordingly we expect a negative effect of economic growth on NPLs.

Inflation Rate (INF)
Khemraj and Pasha (2009)  25 outstanding debt; moreover increased inflation can also weaken the loan payment capacity of the borrowers by reducing the real income when salaries are sticky. So according to literature relationship between inflation and nonperforming loans can be positive or negative depending on the economy of operations (Farhan et al. 2012).
The present study has positive relation with Nonperforming loans (NPLs) of banks.

H6: Inflation rate (INF) has positive relation with Nonperforming loans (NPLs) of banks.
The selected study variables, basis of measurement and priori expected sign have been depicted in Table 1.  and Tanasković and Jandrić (2015).

Descriptive Statistics
The descriptive statistics of input data (reported in percent. The maximum inflation rate 9.90 percent is reported in 2015/16.The dispersion rate of inflation is 2.08 percent exist in the study period.

Correlations Analysis
The correlation matrix of variables in model is expressed in Table 3, which shows that the absolute correlation value between pair of variables is all very low (below 0.5). However, to ensure that there is no multicollinearity between variables in the model, Wooldridge (2002) had suggested testing the Variance Inflation Factor (VIF) to check the multicollinearity problem. If the VIF is higher than 10, there is the multicollinearity. Table 4 reports the VIF of all variables in the model, which all well below 10, and there is no multicollinearity between independent variables in the model.
The Table 3 shows that there is negatively associated between bank size and nonperforming loan ratio which indicates that higher the bank size lowers the nonperforming loan. The ROA and CAR are also negatively associated with the nonperforming loan. It indicates that when ROA and CAR increases the nonperforming decreases.  The result shows that there is positive relationship of loan to deposit ratio and revealed that higher the LTD ratio, higher the nonperforming loan ratio. The GDP is positively associated with NPLs, it indicates that there positive relation exit between GDP and NPLs. The results shows that there is positive relationship of INF with NPLs which implies that INF is moving in the lines of nonperforming loan ratio. Table 4 shows the R-squared which indicates the proportion of variability in the dependent variable which is explained by the regression model. The result indicates that the estimated model explains 51.0% of the variation in the non-performing loans ratio. Moreover, when R-squared is adjusted for positive bias 44.2% of the variation in the non-performing loans ratio is due to the explanatory variables.

Regression Analysis
Size (LnTA) has negative and statistically significant with NPLs. The result indicated that the inverse relation between size and NPLs. The priori hypothesis is rejected. The results consistent with study of  had acknowledged the adverse relationship between the size of a bank and its NPL ratio. Rajan and Dhal (2003), Louzis et al. (2012) had reached the same conclusion with banks in India and Greece.
The ROA has negative and significant with nonperforming loan. The Priori hypothesis is accepted. It shows that the profitability increases NPL decrease and vice versa. The significant negative impact of the ROA on non-performing loans substantiates the view that risk taking is reduced in banks exhibiting high levels of performance. The result is also supportive of the bad management hypothesis and accords with the findings of Boudriga et al. (2010) and Beaton et al. (2016). However, the result is contrary to the significant positive effect of ROA on non-performing loans found by Swamy (2012) and Ahmad and Bashir (2013a).
Total loan and advance to total deposit have positive and significant with nonperforming loan. The result implies 28 that when LTD is increases NPLs also increases. The Priori hypothesis is accepted. The empirical results indicate that the LTD has a significant positive effect on non performing loans. This finding suggests that with the growth in deposits banks engage in extensive lending, which leads to an increase in bank lending relative to deposits.
Such aggressive lending behaviour results is in banks allocating funds to low quality borrowers, thereby increasing the riskiness of the loan portfolio and the level of non-performing loans. The result is supports the previous findings of Swamy (2012) and Ahmad and Bashir (2013a).
Capital adequacy ratio has negatively correlated with NPL ratio (-0.209) and statically significant (  The study focused on commercial banks in Nepal. The banks almost lend all the sectors of the economy and government as well but rising defaults on these loans are a matter of concern of this sector. The study presents an opportunity for commercial banks working in Nepal to change their lending policy, according to changes in bank specific and macroeconomic determinants which has an impact on rising default rates. The main purpose of the study is to determine the bank specific and macroeconomics determinants of nonperforming loans (NPLs) of commercial banks in Nepal. The study is based on secondary source of data of ten commercial banks.
Convincing sampling method has been used in this study. The study has explained only six independent variables to analyze the effect of bank's specific and macroeconomic determinants on non performing loans with reference to Nepal from 2012/13 to 2016/17 leading to the total observations of fifty. Thus, the study concluded that bank specific: ROA, LTD and CAR and macroeconomic factors GDP have significant impact on nonperforming loan.
For future studies, researcher may also consider long time horizon and more variables like level of loan disbursed, collaterals value, and terms of credit, credit culture of society and bank ownership structure. Similarly, the methodological approach combining quantitative and qualitative approaches could be utilized in future 30 studies on non-performing loans. The studies could be undertaken at a disaggregated level by decomposing loans by specific purpose (commercial, residential, and real estate mortgages), and by examining the interactions and relationships between non-performing loans and different types of borrowers, namely: individuals/households, small and medium-sized enterprises, and corporate borrowers. The research is based on a single country. Future empirical work on the determinants of non-performing loans can be conducted on other developing or developed countries.
The study suggests that the bank managers can control the NPL by boosting the profitability (ROA), diversifying the investment portfolios instead of lending, setting a reasonable credit growth, and restructuring the LTD. In addition, bank must stress on the risk management and strictly conform to credit rules and procedures. The government needs to have reasonable policies to maintain the stable economy growth, attract more investments by favorable mechanism, promote the growth of businesses, and improve the laws and financial system in accordance with international standards.