NATIONAL UNIVERITY OF SCIENCE AND TECHNOLOGY NAME

NATIONAL UNIVERITY OF SCIENCE AND TECHNOLOGY

NAME: PRECIOUS BHASERA
STUDENT NUMBER: N0175710X
PROGRAMME: MSc in FINANCE AND INVESTMENT
COURSE: RISK MANAGEMENT
COURSE CODE: CFI 5208
LECTURER: MR A SIXPENCE
TOPIC:
Examine the relationship between banks’ non-performing loans and macro-economic fundamentals in Zimbabwe between the year 2010 and 2016.
Abstract

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This paper investigates the relationship between banks’ non-performing loans and macroeconomic fundamentals in Zimbabwe between the year 2010 and 2016 and covers 5 listed banks operating in Zimbabwe. Failure of credit policy is measured with the rate of nonperforming loans (NPLs) which indicates vulnerability of credit system in banking and financial industry. Several researches have been conducted in many countries where mix pattern of relationships has been found. In this research paper, five macroeconomic variables namely GDP growth rate, inflation rate, interest rate spread of banking sector, savings and rate of unemployment are tested with NPL ratio in order to ascertain significant relationship. Using panel data regression, results show that inflation rate has a positive and significant relationship on non-performing loans. The study concluded that there existed negative correlation between unemployment, real interest rates, GDP, savings and non performing loans in Zimbabwe. The asset base of the scheduled listed banks is also considered as a yardstick of comparative ranking of the banks in Zimbabwe. However, contrary to international evidence results show that large banks are not necessarily more effective in screening loan customers when compared to their smaller counterparts. In addition, the study found that global financial crisis led to higher non-performing loans in Zimbabwe.

Keywords: non-performing loan, GDP, inflation, interest rate spread, unemployment, banks.

INTRODUCTION
Banks can be defined as intermediaries between depositors and borrowers in an economy (Heffernan, 1996). Banks facilitate the flow of funds from surplus units to deficit units in an economy through its traditional role that includes accepting deposits (mainly from household sector) and extending credit to all sectors (mainly business sector). Banks are the main sources of providing blood to the economy in the form of funds. Well functioning banking sector accelerate economic growth, while poorly functioning banking sector is an impediment to economic progress and intensify poverty (Richard, 2011). Thus, economic growth in any country is not possible without a sound banking sector (Rajaraman and Visishtha, 2002). (Khan and Senhadji, 2001) argued that the performance of banking sector is the symbol of prosperity and economic growth in any country or region and poor performance of these institutions not only hamper the economic growth and structure of the particular region but also affects the whole world. Based on the traditional role of banks, we can note that loans make up the bulk of banks’ assets (Njanike, 2009). Despite the importance of lending by banks, the lending process is not as easy as can be imagined. Lending requires banks to assess the customers’ creditworthiness and their ability to repay the principal and interest on time. Nevertheless, these steps don’t lead always to a successful transaction because one cannot know what will happen in the future. Thus lending may create a big problem for banks which is called non performing loans (Chhimpa J, 2002) as cited in (Upal, 2009). A non-performing loan (NPL) is the sum of borrowed money which has ceased to “perform” or generate income in the form of scheduled interest payments and principal, for the bank. A loan is considered non-performing when the loan principal and or interest payments are due and unpaid for a period of at least 90 days or more (RBZ Report, 2013). A loan is non-performing when payments of interests and principal are past due by 90 days or more, or at least 90 days of interest payment have been capitalized, refinanced or delayed by agreement, or payments are less than 90 days overdue, but there are other good reasons to doubt that payment will be made in full (IMF, 2009). NPLs can be treated as undesirable outputs or costs to loaning banks which decreases the bank’s performance. Hennie and Sonja (2009) define NPLs as assets not generating income.

LITERATURE REVIEW
A lot of research has been done and no conclusive relationship was obtained. Farhan et al. (2012) in their study of the impact of selected independent variables (Interest Rate, Energy Crisis, Unemployment, Inflation, GDP Growth, and Exchange Rate) on the non-performing loans of Pakistani banking sector found that Interest Rate, Energy Crisis, Unemployment, Inflation, and Exchange Rate has a significant positive relationship with the nonperforming loans of Pakistani banking sector while GDP growth has significant negative relationship with the nonperforming loans. Glen and Mondragón-Vélez (2011) look at 22 advanced economies during the period 1996-2008 and found that the developments of loan loss provisions were driven mainly by real GDP growth, private sector leverage and a lack of capitalization within the banking system. On the other hand, Vogiazas & Nikolaidou (2011) investigated determinants of non-performing loans in the Romanian banking sector during the Greek crisis (Dec. 2001 to Nov. 2010), and found that unemployment and inflation rate and Romania’s GDP influence the credit risk of the country’s banking system. While Bofondi and Ropele (2011) found that non-performing loans are positively associated with unemployment rates and negatively associated with the growth domestic product rate, Louzis, Vouldis and Metaxas (2011) used dynamic panel data to highlight the factors causing non-performing loans in the Greek banking sector from 2003 to 2009 and according to them economic growth (GDP), unemployment and lending rates are the determinants of non-performing loans in the banking sector of Greece. Espinoza and Prasad (2010) estimate a dynamic panel over 1995-2008 on around 80 banks in the Gulf Cooperation Council. They found that lower economic growth and higher interest rates trigger an increase in NPLs. They also found a positive relationship between lagged credit growth and NPLs. On the other hand, Berge and Boye (2007) found that non-performing loans are highly correlated with the lending rates and unemployment for the Nordic banking system covering the time span from 1993 to 2005. In addition to that, Rinaldi and Sanchis-Arellano (2006) investigated household non-performing loans for a panel of European countries and found that disposable income, unemployment and monetary conditions are determinants of nonperforming loans. Salas and Saurina (2006) conducted a research in Spain to identify the factors which explains the variation in non-performing loans from 1984-2003 According to the authors, high interest rates and GDP growth determines non-performing loans. Hoggarth, Sorensen, and Zicchino (2005) conducted a research in UK during the time period 1988-2004 and found that inflation and interest rates have positive relationship with non-performing loans.
METHODOLOGY
Data was analysed using Stata 12 to find the relationship between the dependent variable (NPLs) and the independent variables (macro economic variables).
Hypothesis Testing
H0 There is a significant relationship between none performing loans and macro-economic fundamentals
H1 There is no significant relationship none performing loans and macro-economic fundamentals. Using panel data regression, results are shown below:

Regression equation: y=a + bx =; NPL = a +bin-bgdp-bint –bune -bsav + e
The results show that GDP is negatively correlated with NPLs. This can explain that when standards of living are decreasing more borrowing in form of loans increases because people will have less disposable income. The negative relationship with interest rates can be explained by the fact that when interest rates are increasing stakeholders will not be willing to take up loans since they will be expensive. A negative relationship between NPLs and unemployment can mean that when employment rate increases disposable income increases and the need for loans will decrease and also the requirement of employment before opening an account hence if unemployment increase also decreases NPLs. This can also be explained by the increase in ability to pay back loans and ability to meet monthly loan obligations. When savings are increasing borrowing may be low and ability to pay back loans will be enhanced hence a negative relationship. Inflation has a positive relationship with NPLs meaning that high inflation impacts on the disposable income and reduces the ability to pay back loans hence high NPLs.
Conclusion
Using panel data regression, results report that macro economic variables affect non performing loans among other factors. However, contrary to international evidence results show that large banks are not necessarily more effective in screening loan customers when compared to their smaller counterparts. With respect to the impact of macroeconomic factors on nonperforming loans, results show that economic growth, interest rates, employment and savings rates have a negative and significant effect on non-performing loans. Global financial crisis also had an impact on non performing loans thus the crisis may lead to higher non-performing loans in Zimbabwe. Based on findings, Zimbabwean banks should pay more attention to several factors when providing loans in order to curtail the level of impaired loans. They need to take effective measures to strengthen their loan portfolio and reduce their credit risk to ensure stability of the financial system and the economy at large. These banks should also take the performance of the real economy into account when extending loans given the reality that loan delinquencies are likely to be higher during periods of economic downturn. Finally, banks should not expand their loan portfolio by extending credit to higher risk customers. The Reserve Bank of Zimbabwe should also expand its monitoring framework to include macroeconomic prudential indicators such as GDP and inflation rate when assessing the stability and soundness of the banking system. Further investigations are needed to better understand the interactions and relationships between non-performing loans and the different types of borrowers, namely; individuals, small and medium enterprises, and corporate borrowers. In addition, it is important for other studies to investigate the procedures that banks undertake to handle non performing loans.

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