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Impact Macroeconomic Factors On Nonperforming Finance Essay

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Risks are one of the factors that characterize the surrounding environment that every individual and institutions presides in. The level, type and magnitude of risks that are faced depend on the type of activities that elements of an environment engage in. Financial institutions and more specifically the banking industry are faced with an array of risks such as liquidity risk, market risk, operational risk credit risk among others. Credit risk is identified as one of the major oldest risk factors that banks and other financial institutions have been facing from time to time. Credit risk refers to the probability that a borrower is unable repay money lend to them by a financial lending institution. Karumba and wafula, (2012) default risk is as a result of the probability that borrowers fail or unable to repay the loans hence affecting the performance of an institution. Under IMF guidelines 2004, If a borrower is unable to repay a debt or no interest is received from a loan asset for a period more than 3months or 90 days, an institution is required to classify this loans as nonperforming loans. Nonperforming loans are known to paralyze institutions performance and also lead to financial crises for example the loan crisis in US and also the banking crisis(Inoguchi, 2012) and in kenya during 1980's and 90's. Non-performing loans are costs or expenses to banks and affect negatively the performance and operation of a bank.

Researches done have identified various factors such as macroeconomic factors, financial factors and bank specific factors to be the cause of emergence and increase or decrease of nonperforming loans in financial institutions(Louzis, Vouldis and Metaxas, 2010; Ng'etich and Wanjau 2009). Microeconomic factors deal with the entire economy both at the regional and national level and affect the entire population. Such factors include inflation, interest rates, monetary policy rates, savings, investments, unemployment, GDP, CPI, exchange rate, money supply among others and they are constantly monitored by government businesses and consumers. Studies have shown that most of these macroeconomic factors tend to have a significant varying effect on level of non-performing loans in banks.

1.2 Back ground

1.2.1 Kenyan banking system

Karumba and wafula, (2012) Kenyan banks undergo the same risks and problems emanating from such risks faced by other institutions all in different locations and use security lending as a risk measurement tool against loan advances. Nonperforming loans are as a result of loan defaults, that is, they are of no interest to an institution because no cash flow is generated from them. Ng'etich and Wanjau, (2011) stated that the aspect of non-performing loans has been receiving a lot attention because of the impact brought about by a large number of NPLs is failure or collapse of banks. Farhan, sattar, chaudhry and khalil, 2012) stated that nonperforming loans have played part in occurrence of financial crisis experienced in most parts of the world mostly in sub-Saharan Africa, America and East Asia.

Hardy (December 1998)Turbulence or occurrence of some irregular activities anywhere in an economy are likely to have an impact on the banking system. Waweru and Kalani, (2009) did a paper on the commercial bank crisis in Kenya which started in1986 and continued all through 1989, 1993, 1994 and 1998 where a total number of 37 banks went under or failed. (Ngugi, 2001) observes that there were two financial crises in Kenya one in the mid 1980's and the other in the early and late 1990's, where 6 commercial banks and 12 NBFI's faced insolvency problems between 1993 and 1996 and 5 banks were placed under statutory mandate in 1998. She observes that among the factors that led to the crisis was non-performing loans .

Failure of the banking industry in Kenya as observed by Waweru and Kalani,(2009) was caused by a lot of factors. Kenyan banks during the immediate post-colonial period constituted both foreign banks, local commercial banks and some privately owned NBFI's. The regulatory framework governing local financial institutions that period was not well defined. (Brownbridge, 1998) in his study on causes of financial distress in local banks in Africa and implications for prudential policy found that the insider lending was one of the largest contributor to bad loans, for instance, in Kenya failure of banks such as Continental bank, Trade bank, and Pan African bank was due to insider lending that was made often to politicians. Another factor identified was banks extended loans to high risk borrowers who had been declined by foreign banks hence local banks were willing to lend at higher costs. Brownbrigde observed macroeconomic instability as the propelling factor behind problem loans of banks, during 1990 in kenya the inflation rate as observed was 46% which affected banks by increasing volatility in business profits and also made loan appraisal difficult for banks. .

(Waweru and kalani, 2009) states that the activities of commercial bank activities expose them to credit risk, and techniques such as provision for debts and credit screening and monitoring provide a temporary cover to level of NPLs. But he further states that increase in the level of NPLs to a certain level cannot be covered by the allocated provisions. In Kenya, after the banking crisis, measures were taken to protect against such events again. (Ngugi, 2001) in response to Kenya's financial crisis the banking act was revised and approved in 1989 to improve and enhance the mandate of CKB in terms of regulation and supervision function in regard to activities of commercial banks and NBFI's.

Hardy (December 1998) shows the history of banking crisis starting with the great depression of the US, another period characterized by failure of banking system is during the 1980's and 90's where many African countries had to restructure their banking system after a crisis caused by loans to parastatals. (Nge'tich and Wanjau, 2011) state that the major contributing factor of financial and banking crises observed mostly in East Asia and Sub-Saharan Africa countries is high levels of nonperforming assets.

Non-performing loans are costs or expenses to banks and impacts negatively to the performance of a bank (Chang, 1999). The risk of non-performing loans are as a result of harsh external economic conditions such depressions (Sinkey and Greenawalt, 1991).


Karumba and Wafula, (2012) in their article on alternative for Kenyan banking industry identified that credit risk is one of the oldest and most challenging risk faced by banks, which results due to the probability that borrowers may default terms of their debt and hence putting an institutions capital into risky positions. Increase in defaults lead to piling of non-performing loans in an institutions balance sheet. Musyoki and Kadubo, (2011) in their paper on credit risk management on financial performance of banks concluded that default rate is the most important factor as it influences 54% in total credit risk influence on bank performance.

Geoffrey Irungu, (23 November 2011) on property Kenya stated that the total outstanding loan portfolio for commercial banks in Kenya was 1.2 trillion and a statistic by index mundi show the total non-performing loans was 5.4% in 2011. Nonperforming loans impacts on a bank's performance by reducing its revenue as they become expenses.

These study tends to investigate the root cause and explanatory power of factors that influence or cause variation in the level of non-performing loans in Kenyan banking industry by looking macroeconomic variables. Studies have shown there seems to be a significant relationship between macroeconomic variables and level of nonperforming loans. (Ng'etich and Wanjau, 2011) identified that interest rate spread have an impact on non-performing loans , Rottke and Gentgen, (2008) in there paper workout management of non-performing loans noted that the one of the reasons behind non-performing loans in Germany was the recessionary environment.

Statisitic show that the trend of nonperforming loans(% of gross loans) in Kenya since 2003 to 2011 has been decreasing. In 2003, 2004, 2005, 2005, 2006, 2007, 2008, 2009, 2010 and 2011 the percentage was 34.9%, 29.3%, 25.6%, 10.6%, 9%, 7.9%, 6.3% and 5.4% respectively (sourced from world bank data base).

The y axis represents percentage and X axis is years.

The study aims to investigate the relationship of macroeconomic factors and nonperforming loans during this specific period of 2002 to 2011. It is a period in Kenya that is characterized by a lot of economic changes in terms of inflation rate, banks lending rates and CBR, exchange rate fluctuations, unemployment rate, price of commodities etc. I seek to investigate explanatory power of various macroeconomic variables towards the trend of non-performing loans within the stated period.


Microeconomic factors deal with the entire economy both at the regional and national and affect the entire population. These research paper aims at investigating the impact of various macroeconomic factors on level of nonperforming loans within Kenya's banking period within the period of 2002 to 2011. These period is characterized by a decreasing trend of nonperforming loans and hence the paper seeks to establish the level of significance of various macroeconomic variables, that also experienced major variability during that period, on defaulted loans.

1.5 General objective

Impact macroeconomic factors on nonperforming loans in the Kenyan banking industry during the period of (2023- 2011)

1.5.1Specific objective

To assess the impact of gross domestic product (GDP) on nonperforming loans in Kenya

To assess the impact of monetary policy lending rate (CBR) on nonperforming loans in Kenya

To assess the impact of inflation rate on nonperforming loans in Kenya

To assess the impact of consumer price index on nonperforming loans in Kenya


What is the impact of gross domestic product (GDP) on nonperforming loans in Kenya?

What is the impact of monetary policy lending rate (CBR) on nonperforming loans in Kenya?

What is the impact of inflation rate on nonperforming loans in Kenya ?

What the impact of consumer price index on nonperforming loans in Kenya?




The study focuses on the impact of macroeconomic variables on nonperforming loans within the banking industry in Kenya. The time scope under consideration on the trend of nonperforming loans of banks will be the period between 2002 and 2011, while the geographical scope will cover the whole banking industry in Kenya.





These study tends to look at literature done on impact of macroeconomic factors on nonperforming loans by several researchers from different sources; books, articles, websites, journals and others. The review mostly will look at the works and researches done in different countries and observe the level of significance of macroeconomic variables in influencing the level of nonperforming loans.

2.3 Literature review

divided into four parts, definitions, causes, npl in other countries, finally macroeconomic factors.

2.3.1 Review of past studies

According to IMF guide on financial soundness and indicators (2004) paragraph 4.45 defines a loan as a financial asset created when a borrower is extended credit by a financial institution on an agreement that repayment will be done based on the specifics of the agreement and that a security may be provided(secured) or not(unsecured). Loans can be classified under secured and unsecured loans, where secured loans are loan advances extended on basis of a collateral while unsecured loans no collateral is provided. (Karumba and Wafula, 2009) stated that banks Kenyan banks depend on collateral lending as risk measure against issued loans.

(Guarav Akrani, 7/9/2011) define nonperforming loans as loans whose principal payment and interest are not met by the borrower/customer, and observes the period for determining whether a loan has become non-performing under international guides to be 45 to 90 days but this may differ in different countries like in India it is 180days. According to the Malaysian Law Journal, "non-performing loan (NPL)", is defined as any loan to a person by a licensed institution, which has been in arrears for a period of times as may be determined by the licensed institution. According to IMF guides 2004 this definitions may vary in different financial setting in other states but the basic underlying meaning is more or less the same and (Hippolyte and Fofack, 2005) stated that how nonperforming loans are identified vary among different states mostly in Africa due to factors such as regulatory frameworks, policies governing institutions and different structural frameworks.

(Guarav Akrani, 7/9/2011) stated the different types of nonperforming assets to be; standard assets, sub-standard assets, doubtful assets and loss assets. Standard asset loans or assets that are responsive to the terms of agreement in terms of repayment of the interest and principal they are said to be performing. Sub-standard loans are loans whose period for determining whether they are nonperforming is 12months but another definition of sub-standard loan by (Hippolyte and Fofack, 2005) is a loan whose terms of agreement have not been met for a period of at least 6months hence as applied in sub-Saharan Arica. Doubtful assets are assets whose repayment has not been made for a period of more than a year or 12months and loss assets are assets that cannot be recovered.

Nonperforming loans are as a result of both external and internal factors of a financial institution environment. (Guarav Akrani 7/9/2011) broadly identifies this factors as speculation, default, fraudulent practices, diversion of funds, internal and external factors. These study is more inclined towards the external factors and more importantly the macroeconomic factors. Although studies tend to show varying factors as causation for nonperforming loans most studies have identified macroeconomic factors and bank specific variables as major reasons. (Louzis Vouldis and Metaxas, 2010) observed that presence of significant influence of macroeconomic factors and bank specific variables on nonperforming loans in Greece, (Vogiazas and Nikolaidou, 2011) investigated the determinants of nonperforming loans in the Romanian banking system and found that there was an influence macroeconomic factors on the NPL's.

A number of countries have experienced or are facing issues regarding nonperforming loans, Inoguchi, (2012) a study done in Malaysia on non-performing loans stated that in southeast Asia where companies rely mostly on bank loans, a sound banking system is necessary. He also stated that non-performing loans pose a great danger to a banking system as evidenced in most countries an example of US subprime mortgage crisis. Louzis, Vouldis and Metaxas, (2010) in their study in Greece stated that coming up with factors that determine default risk is an important issue to the regulatory authorities concerned with the financial stability of banking industry and despite the effort by banks to come up with techniques and measures to curb the level of default risks of loans the by proper screening and monitoring of borrowers, macroeconomic factors seem to have a major effect on the level of non-performing loans among other factors such as bank specific characteristics.

Nonperforming loans have played major roles in bringing down economies of not only the developing states but also the developed states in the world. (Hippolyte and Fofack, 2005) stated that if increase in nonperforming loans in a banks statements without constant monitoring and taking measures to protect against them, the resultant effect would be emergence of a financial crisis if NPL's increase beyond a bank's total capital. (Farhan, sattar, chaudhry and khalil, 2012) in their study on nonperforming loans in Pakistan concluded that non-performing loans have proved to be a major contributing factor in economic crises and financial crises all over the world for instance the Euro zone crisis, the subprime mortgage crisis in the US, East Asian crisis and also sub-Saharan Africia. . (Hippolyte and Fofack, 2005) stated that most of the financial crises experienced in most parts of the world are as a result of increased level of nonperforming assets.

European nonperforming loan report 2011 by Earnest and Young observed that the rate of growth of economies after the financial crisis has been very slow in developed countries(2.5%) as opposed to developing countries at a rate of 6%. The report stated that southern Europe experienced worse economic times with increased interest rates, a fall in prices in the mortgage industry, a fall in the construction industry and high unemployment rates led to an increase of NPL's in banks balance sheets. For instance, in Germany the report states after the crisis the level of NPL's rose from 200billion Euros to 250b Euros, while in Spain the economic downturn led to an increase in NPL's from 93.3billion Euros in 2009 to 107.2billion in 2010 a 14% increase.

(Hippolyte and Fofack, 2005) in his study on nonperforming loans in sub-Saharan Africa stated that a high level of banking and financial crisis during 1980's and 1990's was experienced by a large number of developing countries as a result of poor performance of banking and financial institutions. There was a high level of credit risk due to an increased number defaults by loan/debt holders which was 30% of total loans during 1990's and reached a high of 32% in 1993 the highest experienced in developing countries. Impaired loans lead to increased financial costs and a great deal of other implications mostly for developing countries mostly African states that are usually characterized by debts from international organizations and foreign countries. They concluded significant influence on nonperforming loans to be caused by macroeconomic factors and various bank specific variables in most of the sub-Saharan African states.

(Rottke and Gentgen, 2006) in there paper workout management of nonperforming loans pointed out that In the united states of America the crises(1989-1994) from savings and loans that led to high level of nonperforming loans in the property industry was driven mostly by volatile exchange rates, pressure of oil prices, and a competitive environment that was caused by changes in the regulatory frameworks that led to cross-state banking. There was observed increased risk taking activities and lending rose from 18% to 27% in real estate loans between 1980 and 1990. The crisis came as a result of default in the loans due to harsh economic conditions.

In some countries the cause of nonperforming loans is related to political instability or system of ruling. China, due to its socialist system, is a civil law country that operates more on standard practice than on law. China does not have a robust legal infrastructure or sophisticated legal banking frameworks, though China has passed special banking legislation to accommodate and facilitate the growth of a modern banking industry. The reason behind non performing loans in china therefore is due to political matters, (Rottke and Gentgen, 2006) "During the centrally planned economy from 1949 onwards loans were granted by state owned banks to state owned companies without proper credit due diligence at predetermined standardized conditions by the government. Especially, in the overheated economy of the 1990s domestic credits extended enormously and grew by 30% per year between 1992 and 1995."

Theoretical review

Basel accords

credit risk arises whenever a lender is exposed to loss from a borrower, counterparty, or an obligor who fails to honor their debt obligation as they have agreed or contracted hence leading to nonperforming assets in banks balance sheets. The 1998 Basel 1 accord placed restrictions on the level of risk a bank could get into in regards to the level of capital it had, that is, the level of lending beyond a total capital was restricted. This was to provide security for depositors funds from loss and to shield the whole financial system from crises in case there was emergence of an economic contraction/downturn and lead to collapse. Under Basel 2 new treatment of credit risk is given specifying approaches available to banks to calculate level of credit risk, that is, standard approach, foundation internal rating based approach and advanced IRB approach.

For banks to decide or specify whether a loan is performing or nonperforming standard approach is the method to use under Basel 2 accord because it measures the probability of default which looks at the likelihood that a borrower will default over a given period, it also measures the proportion of exposure that will be lost in case of default (loss given default), and finally it measures the amount of the facility likely to be drawn if default occurs. According to IMF guide on financial soundness and indicators (2004) paragraph 4.45 defines a loan as a financial asset created when a borrower is extended credit by a financial institution on an agreement that repayment will be done based on the specifics of the agreement and that a security may be provided(secured) or not(unsecured).

The causation factors of nonperforming assets that face borrowers according to (Ranjan and Dhal, 2003) may be either internal or external. The internal factors include factors that are a hazard to the improvement of business activities either by misappropriation of finances needed for the purposes either by diversification or taking up new projects, business failure inefficient management product obsolescence, inappropriate technology etc. while external factors include factors that affect the business from outside this may include economic recessions, non-payment in other countries, price escalations, natural calamities etc. other theories trying to link real economy to NPL's include the theory that long lasting recessions within an economy tend to lead to an increased level of NPL,s overt time and Irvin Fishers theory of debt-deflation (1993) that states that deflation where one of the effect is usually a fall in prices causes NPL,s.

Credit portfolio management theories and models

For a bank to diversify the risk associated with lending of funds to borrowers, it has to have a portfolio of loans that includes different types of loans with different levels of risk. There are four credit portfolio models that have been introduced to measure credit portfolio risk; KMV portfolio manager introduced in 1993, J.P Morgan credit metric 1997, Credit Suisse First Boston introduced credit Risk+ 1997, and McKinsey portfolio-view in 1997.

McKinsey portfolio-view in 1997

It is the first macro-factor model introduced by McKinsey that involves a view about the situation of the economy. It is a conditional approach that includes risk of the economy which has a large predictable impact on credit migration and on default probabilities. The historical default rate for industry/country combinations are described as function of macroeconomic variables specified by the user. the model captures the fundamental aspect that economy-wide defaults rise and fall with macroeconomic conditions( Eric Kuo, 2008, credit portfolio management).

(probability of Default) = f(GDP growth, Unemployment rate, inflation, interest rates,….)

Macroeconomic factors deal with the entire economy both at the regional and national and affect the entire population. Such factors include inflation, interest rates, monetary policy rates, savings, investments, unemployment rate, GDP, CPI among others and they are constantly monitored by government businesses and consumers. Studies have shown that most of these macroeconomic factors tend to have a significant varying effect on level of non-performing loans in banks. Mckinsey poertfolio view model has been proved to work by empirically for instance, (Ng'etich and Wanjau, 2011) in their study concluded that interest rate spread, as one of the macroeconomic factors, has a significant effect on non performing loans in banks because it tends to increase the cost of lending to borrowers despite the type of interest rate charged, be it fixed or floating rate, the impact on banks non performing loans is more or less the same.

(Louzis Vouldis and Metaxas,(2010) noted that studies relating macroeconomic environment and loan qualities to bank stability have been investigated and formulates an hypothesis stating that increased economic activities lead to a decline in the level of non-performing loans because consumers and firms have enough funds to repay loans, but as the economic activities continue increasing creditors with poor ratings are also given loans such that if a crisis hits the number of NPL's are high. They concluded that the studied macroeconomic variables, that is, gross domestic product (GDP), the level of unemployment rate, and the lending rate had the highest significant effect on NPL's hence proving Mckinsey's model of portfolio view.


Independent variables dependent variables

Consumer price index

Central bank rate (CBR)

Nonperforming loans

Money supply


Economic growth (GDP)

The conceptual framework represents nonperforming loans as a function of consumer price index, CBR , money supply and gross domestic product. The researcher will assume a linear relationship between the independent variables and the dependent variable.


The dependent variable in an equation is the variable that depends on changes of independent variables. Nonperforming loan as the dependent variable has proved to have a major effect on the performance of financial institutions and emergence of nonperforming loans are linked to other factors.


Factors that affect changes in dependent variables. Consumer price index (CPI)

In Kenya, the Consumer Price Index or CPI measures changes in the prices paid by consumers for a basket of goods and services. Central bank rate (CBR)

This is a monetary policy tool used by central banks, it is the lending rate to commercial banks and its used to control interest rates charged by commercial banks in the market. These study tends to investigate the relationship between changes in CBR on nonperforming loans. Money supply M3

Money Supply M3 in Kenya increased to 1670.86 KES Billion in September of 2012 from 1638.46 KES Billion in August of 2012. Money Supply M3 in Kenya is reported by the Central Bank of Kenya. Historically, from 2000 until 2012, Kenya Money Supply M3 averaged 798.18 KES Billion reaching an all time high of 1670.86 KES Billion in September of 2012 and a record low of 345.90 KES Billion in May of 2000. Kenya Money Supply M3 includes M2 plus long-term time deposits in banks. Economic growth (GDP)

Gross domestic product is the measure of value of all goods and services produced within the borders of a given country, it is used as a measure of economic heath or status of a given state.

the study seeks to investigate the explanatory power of changes in GDP on the trend of nonperforming loans. Data from indexmundi.com gives the trend of GDP real growth rate on an annual basis and adjusted for inflation;





























Source; indexmundi.com


3.1 Research design

The study aims to conduct longitudinal research, because panel data methods will be used, in the quest to answer the question on the effect of macro-economic factors on nonperforming loans in the Kenya's banking industry that has been of a concern for a period of 10years (2002-2011). Explanatory research was chosen for robust study and deep search into the macro-economic factors to achieve the goal of the study by determining the relationship and explanatory power of macroeconomic variables on nonperforming loans.

3.2 Target Population

The target population will consist of all the Kenyan banks within Kenya's banking industry from where data on nonperforming loans will be derived from. The researcher views this as an appropriate population because it will give a general clear picture of the effect of economic changes on bank's loan performance. Currently in Kenya, statistics by the CBK show that the population of financial institutions comprises of 43 licensed commercial banks and 1 mortgage finance company. 27 of the commercial banks are locally owned and 13 are foreign owned.

3.3 Sampling Design

The study uses aggregated percentage of nonperforming loans for all commercial banks for a period of 10 years from 2002 to 2011 with an aim of achieving comprehensive.

3.4 Data collection

The study will use secondary data sources to acquire data for the purposes of conducting the research. The data will be sourced from various sources that is the central bank of Kenya's annual reports, surveys and publications on commercial banks performance , another source will be the Kenya National Bureau of Statistics (KNBS) statistical data on macroeconomic variables will be obtained and the final source will be data bank from world bank surveys. These institutions are the major source of information concerning most aspects of Kenya economically and socially. Data on nonperforming loans is available at the world bank data source and the central bank of Kenya reports, while data on the selected macroeconomic variables will be obtained from KNBS.

3.5 Data Analysis

Econometrics models will be used in the study to analyze the collected data so as to get accurate results. Data will be analyzed using multiple linear regression method, univariate analysis and descriptive statistics, charts and graphs. (Eviews 3) will be used to aid in the analysis of the study.

3.5.1 univariate and descriptive analysis

To analyze each variable and the general trends of data from 2002 to 2011 for the commercial banks in Kenya the researcher will use univariate analysis to check for normality in variables and bivariate analysis to give a graphical representation.

3.5.2 Regression analysis Model

A multiple linear regression model will be used to determine the importance of each independent variable in affecting NPLs. A model to show the regression analysis of nonperforming loans as the dependent variable and GDP, Money supply, consumer price index, and CBR as the independent variables is given below;

(probability of Default) = f(GDP growth, Money supply, consumer price index, CBR)

NPLt =f (α0+α1M3t+α2CPIt+α3CBRt+α4GDPt+εt)


NPLt = Nonperforming loans of banks at time t

M3t = Money supply t

CPIt = Consumer price index t

CBRt = Central bank rate t

GDPt = Gross Domestic Product at time t

εt = Error term

α0,α1,…,α5 = parameters

α0 = Constant

The error εt term accounts for omitted variables and errors in measurement

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