Finance Thesis, Degree Research

1. Research Project
FIN 444
DETERMINANTS OF
COMMERCIAL BANK
PROFITABILITY IN BOTSWANA
Thuto Moyei

2. 1
Table of Contents
1.0 THEORETICAL FOUNDATION..........................................................................................................3
1.1 ABSTRACT........................................................................................................................................3
1.2 BACKGROUND ................................................................................................................................3
1.2.1 PROBLEM STATEMENT..........................................................................................................5
1.3 OBJECTIVES.....................................................................................................................................5
1.4. HYPOTHESIS OF THE STUDY......................................................................................................6
1.5 CONCEPTUAL CLARIFICATION...................................................................................................7
1.6 LITERATURE REVIEW ...................................................................................................................8
1.6.1 Bank Specific Factors ..................................................................................................................8
1.6.2 Macroeconomic Factors...............................................................................................................9
1.6.3 Macroeconomic Factors and Bank Specific Factors..................................................................10
2.0 METHODOLOGY ...............................................................................................................................11
2.1 Nature and type of Data ....................................................................................................................11
2.2 Period of the Study: ..........................................................................................................................11
2.3 Tools and Techniques of Analysis....................................................................................................12
2.4 Description of Variables ...................................................................................................................13
2.4.1 Dependent Variable....................................................................................................................13
2.4.2 Independent Variables................................................................................................................14
2.5 Sources of Data.................................................................................................................................15
2.6 Model Specification..........................................................................................................................15
3.0 ANALYSIS OF DATA, DISCUSSION & FINDINGS .......................................................................16
3.1 Findings.............................................................................................................................................16
3.1.1 Documentary analysis................................................................................................................16
3.2 Discussions of the Findings ..............................................................................................................21
3.2.1 Size.............................................................................................................................................22
3.2.2 Capital........................................................................................................................................22
3.2.3 Expenses Management...............................................................................................................22
3.2.4 Real GDP growth rate................................................................................................................23
3.2.4 Average Annual Inflation Rate ..................................................................................................23

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4.0 RECOMMEDATION AND CONCLUTION.......................................................................................24
4.1 Conclusions.......................................................................................................................................24
4.2 Recommendations.............................................................................................................................26
REFERENCES ...........................................................................................................................................26
Appendix.....................................................................................................................................................29

4. 3
1.0 THEORETICAL FOUNDATION
1.1 ABSTRACT
This study examined factors affecting profitability of private commercial banks’ in Botswana.
The study used secondary data and adopted a quantitative research approach and a multiple
regression model was used to estimate the profitability, which was measured by return on equity
as a function of bank specific and macroeconomic explanatory variables. The findings of the
study show that only GDP growth has a statistically significant and positive relationship with
banks’ profitability. On the other hand, Capital has a negative and statistically significant
relationship with banks’ profitability. However, the relationship of size expenses management
and inflation is found to be statistically insignificant. As a result, the study recommended that
private commercial banks should focus on decreasing their amount of capital as this will increase
their profitability. Finally, private commercial banks should not only be concerned about internal
structures and policies, but they must consider both the internal environment and the
macroeconomic environment together in fashioning out strategies to improve their profitability.
1.2 BACKGROUND
Bank profitability in Botswana has been squeezed since 2009 with return on equity falling into
single digits. According to the Bank of Botswana (2015), profits dropped 32 percent in the first
nine months of 2015 from a year earlier as reduced interest margins, rising bad debts and a freeze
on fees imposed by the regulator weighed on lenders in the southern African country (Bloomberg
News, 2015).
According to Mguni (2015), combined net income fell to 789.7 million pula ($73 million),
banks’ net interest income slipped about 8 percent to 2.3 billion pula, as provisions for bad and

5. 4
doubtful debts climbed 3.8 percent. Operating expenses have been on a five-year upward trend
for several reasons, including increased rental costs and depreciation (Bank of Botswana, 2015).
The slow growth in income, combined with increasing operating expenses, led to a higher Cost
to Income Ratio of 61.2 percent in December 2015, which fell outside the international norm for
retail banks of 55 - 60 percent range.
The banking sector also plays a very important role in the Botswana stock exchange, where it
dominates market capitalisation and has been a driving force in the growth of the BSE in recent
years. This in turn reflects the high level of importance of the sector. The banking sector
continues to dominate the financial sector more broadly, notwithstanding the rapid growth of
other segments of the financial sector, such as pension funds, over the past decade (Tacheba &
Jefferis, 2009).
Botswana has experienced consistently strong economic growth over the past two decades, with
some interruption only following the global financial crisis and the collapse in the diamond
market. The banking sector in Botswana is well developed and regulated. From only two banks
in the early 1980s the sector has now grown to 10 commercial banks, two statutory banks and
one building society. The commercial banks are dominant in deposits, holding a 98% average
market share over the past decade, according to the Bank of Botswana (2015), and have
maintained an 89% market share of the total sector loans over the same period. The four largest
banks, First National Bank of Botswana Ltd, Barclays Bank of Botswana Ltd, Standard
Chartered Bank Botswana Ltd and Stanbic Bank Botswana Ltd, hold more than 80% of the
assets in the sector (Bank of Botswana, 2015).
Credit growth slowed in 2009 but has recently started to accelerate back into double-digit
territory in real terms. Traditionally the sector has excess liquidity, with much of this being

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absorbed by the issuance of Bank of Botswana paper which has helped the sector’s profitability.
However, there is a drive to get the banks to lend more to the real economy.
Much of the lending – over 50% – is to the household sector, which has been more under
pressure than usual due to public sector wage freezes, a vulnerability highlighted in a recent
Bank of Botswana (2015) Banking Supervision Report. Even so, the banks have relatively well-
diversified loan portfolios.
1.2.1 PROBLEM STATEMENT
The global economic recovery has been sluggish and fragile since 2010, thereby constraining
economic growth prospects for Botswana (Bank of Botswana, 2015). This, in turn, had a major
negative impact on the performance of the banking sector in Botswana. Any failure in the sector
has an immense implication on the economic growth of the country.
The current consistent decrease in profitability of commercial banks motivated this study to
evaluate the financial performance of banks in Botswana. Thus, to take precautionary and
mitigating measures, there is a dire need to understand the performance of banks and its
determinants. So, to identify significant profit determinants provide an opportunity to know
which variable’s influencing banks profit, management can concentrate their attention on it at the
time decision making to adjust the factor.
1.3 OBJECTIVES
The overall objective of this study was to examine the effects of bank specific factors and
macroeconomic factors on the performance of commercial banks in Botswana, and thus inform
commercial banks management, stakeholders and other interested subjects on which are the
factors that most determine bank performance, to use in a more efficient way the bank’s
resources.

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The specific objectives of this paper are outlined below;
1.3.1. General objective of the study
The general objective of the study is to explore the effect of factors affecting bank profitability of
private Commercial Banks in Ethiopia.
1.3.2. Specific objective of the study
Specifically, this study addresses the following objectives;
 To investigate the effect of, the amount of capital and assets on the profitability of private
commercial banks in Botswana
 To examine the outcome of expenses management on the profitability of private
commercial banks in Botswana
 To explore the effect of, inflation and level of GDP growth on the profitability of private
commercial banks.
1.4. HYPOTHESIS OF THE STUDY
In line with the broad purpose statement the following hypotheses were also formulated for
investigation. Hypotheses of the study stands on the empirical studies related to a bank’s
profitability discussed on the Literature Review. The results from the literature review (to be
established in the next chapter) were used to establish expectations for factors affecting bank
profitability using statistical cost accounting model and other macroeconomic variables. Hence,
based on the objective, the present study seeks to test the following five hypotheses:
 HP1: There is a significant positive relationship between the size of a bank and bank’s
profitability.
 HP2: There is a significant negative relationship between the Expenses management of a
bank and bank’s profitability.

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 HP3: There is a significant positive relationship between the capital of the banking and
bank’s profitability.
 HP4: There is a significant negative relationship between inflation and bank’s
profitability.
 HP5: There is a significant positive relationship between real gross domestic product
growth and bank’s profitability
1.5 CONCEPTUAL CLARIFICATION
Commercial Bank: According to Business Dictionary (2017) a commercial bank is a
privately owned financial institution which (1) accepts demand and time deposits, (2) makes
loans to individuals and organizations, and (3) provides services such as documentary
collections, international banking, trade financing. Since a large proportion of a commercial
bank's deposits is payable on demand, it prefers to make short-term loans instead of the long-
term ones.
Profitability: Profitability can be defined as the ability of a company to use its resources
to generate revenues in excess of its expenses. In other words, this is a company’s capability of
generating profits from its operations (My Accounting Course, 2017).
Bank Specific Factors: are internal external factors that influence bank and are under the
control of bank management such as expenses management, Capital Adequacy, Bank Size etc
(Singh & Sharma,2016).
Macroeconomic Factors: are external factors that influence bank profitability but are
not under the control of bank management such as inflation, unemployment rate, GDP growth
etc., (Singh & Sharma,2016).

9. 8
1.6 LITERATURE REVIEW
The study of bank performance started in the late 1980’s (Olweny and Shipho, 2011) with the
application of Market Power (MP) and Efficiency Structure (ES) theories (Athanasoglou et al.,
2005.) The MP theory states that increased external market forces results into profit. Moreover,
the hypothesis suggest that only firms with large market share and well differentiated portfolio
(product) can win their competitors and earn monopolistic profit. On the other hand, the ES
theory suggests that enhanced managerial and scale efficiency leads to higher concentration and
then to higher profitability. According to Olweny and Shipho (2011) balanced portfolio theory
also added additional dimension into the study of bank performance. It states that the portfolio
composition of the bank, its profit and the return to the shareholders is the result of the decisions
made by the management and the overall policy decisions.
From the above theories, it is possible to conclude that bank performance is influenced by both
bank specific factors and macroeconomic factors. According to Singh and Sharma (2016) the
internal factors include bank size, capital, management efficiency and risk management capacity.
The same scholars contend that the major external factors that influence bank performance are
macroeconomic variables such as interest rate, inflation, economic growth and other factors like
ownership.
1.6.1 Bank Specific Factors
The study of Frederic (2014) examined the factors responsible for determining the performance
of domestic commercial banks in Uganda. The study used linear multiple regression analysis
over the period 2000-2011 to analyze the data of all licensed domestic and foreign commercial
banks. The study found that, management efficiency; asset quality; interest income; capital
adequacy and inflation influence on the bank’s performance in Uganda.

10. 9
Gul and Khalid (2011) used panel data from 2006-2009 for Pakistani banks & found gearing
ratio, NPL & asset management to be significantly affecting the profitability of Pakistani
conventional banks. Macit (2011) conducted a research on Tarkish commercial banks and
observed that NPL ratio is negatively related to both ROA & ROE.
Wen (1985) concludes that a bank’s asset and liability management, its funding management and
the non-interest cost controls all have a significant effect on the profitability record. There are an
abundant number of studies concluding that one of the primary factors influencing the bank
profitability is the control on the expenses. A study undertaken by Tregenna (2009) to evaluate
the determinants of bank profitability in the US concluded that bank efficiency does not strongly
affect profitability. The author found that high profits among American banks were a result of
concentration rather than efficient performance. He then highlighted the importance of attaining
efficiency, arguing that high profits derived from market share, rather than efficient operations,
cannot prevent banks from bankruptcy in the event of a crisis.
In contrast, Demirguc-Kunt and Huizinga (2000) argue that lower profitability should be a
reflection of increased efficiency due to greater competition among banks. In other words, the
author suggests that high profits in the sector indicate inefficiency. Thus, there are mixed
findings from previous studies with some confirming either positive, negative, or no impact on
bank profitability. To the best knowledge of the researcher, this study will be a first attempt in
Botswana to investigate the impact of bank internal factors and external factors on profitability
1.6.2 Macroeconomic Factors
The use of GDP growth as a variable does not feature extensively in the literature. However,
Wood (2004) concludes that the behavior of real GDP fails to explain the greater variability of
banking sector profits in the UK than in Germany. But they do not say that GDP variability did
not affect profits, only that they could not use it to explain different UK/German banks

11. 10
performance. If this variable is not statistically significant in explaining profitability, then the
conclusions of the authors are reinforced. Otherwise, the expected sign should be positive since
higher growth implies both lower probabilities of individual and corporate default and an easiest
access to credit. Obamuyi (2013) used secondary data for studying 20 Nigerian commercial
banks during the period 2006-2012, finding same key determinants of bank profitability. Ongore
& Kusa (2013) study examined the effects of bank specific factors and macroeconomic factors
on the performance of commercial banks in Kenya during the period from 2001 to 2010. They
analyzed ten years’ panel data for 37 commercial banks, using linear multiple regression model.
In their paper, they researched 154 banks over the 1980- 2006 periods. It should be noted that
major of this work is the analysis of external factors. According to their results they show that
the inflation, real interest rates, the exchange rate and monetary policy are significant
macroeconomic indexes of bank performance in Nigeria. But they also reported that stock
market development, banking sector development and financial structure are not statistically
significant; and the relationship between bank profitability and tax policy in Nigeria is
inconclusive.
1.6.3 Macroeconomic Factors and Bank Specific Factors
Staikouras and Wood (2003) examined the determinants of European bank profitability from
1994 – 1998. The authors found that the profitability of European banks is influenced not only
by factors related to their management decisions but also to changes in the external
macroeconomic environment.
Khrawish (2011) conducted a study on Jordanian commercial banks over 2000-10 and found that
ROA and size, leverage, capital adequacy ratio, net interest margin and expense management
efficiency is positively related while ROA & GDP, inflation are negatively related.

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Samad (2015) examines the impact of both bank specific and macroeconomic variables that
affect profitability of Bangladesh banking industry. The study was conducted on a panel data set
consisting 42 Bangladeshi commercial banks. The study used bank specific variables such as
bank financial risk, bank operational efficiency, and bank sizes as well as macroeconomic
variables such as economic growth are examined to estimate their impact of bank profits. The
paper indicates that factors such as loan-deposit ratio, loan-loss provision to total assets, equity
capital to total assets, and operating expenses to total assets are significant factors. Bank sizes
and macroeconomic variable show no impact on profits.
2.0 METHODOLOGY
2.1 Nature and type of Data
The study is based on the secondary data, and the nature of research is Exploratory, Descriptive
& Analytical both that generates a hypothesis by analyzing a data-set and looking for correlation
between Banks’ profitability and independent variables, using annual time series data for the
period from 2005 to 2015. The profitability and internal factor variables data has been collected
from the annual Bank of Botswana Supervision reports of 10 licensed commercial banks
published by the Central Bank of Botswana (BOB) and available on its website. The External
factor variables data has been collected selected indicators report published by Statistics
Botswana (BOB) and available on its website.
2.2 Period of the Study:
The study period is of eleven years, starting from the year 2005 to 2015. This time period
witnessed many crisis like subprime mortgage crisis, global financial crisis, European sovereign
debt crisis that shook the global economy. That is why the study covers a period of eleven years

13. 12
from 2005 to 2015, as it covers the major financial crisis and gives a more clear view of the
volatility of bank profitability.
2.3 Tools and Techniques of Analysis
The analysis of the data forms the core part of the study.
In order to analyze the data and draw conclusions on this study, Excel has been used as the major
tool of analysis and the various statistical techniques like linear correlation analysis and
descriptive statistics have been used through EXCEL.
Five independent variables have been identified for the purpose of the study:
The study aims to find the correlation between bank profitability (ROE) and each independent
variable respectively.
The following tools and techniques of analysis have been used in the study:
 Microsoft Excel – To do data analysis from 2005 to 2015
 Correlation Analysis – To find out the Correlation between the ROE & the variables.
 Descriptive statistics – To measure the bank sector stability in Botswana: Descriptive
statistics are statistics that describe the distribution of the data used. Eg mean, median,
kurtosis, skewness etc.
The panel secondary data for the study was obtained from the Annual Banking Supervision
Reports of 10 Licensed commercial banks. The cross-sectional element is reflected by the
different commercial banks in Botswana and the time series element is reflected in the period of
study (2010 – 2015). As Saona (2011) observes, the main advantage of using panel data is that it
allows overcoming of the unobservable, constant, and heterogeneous characteristics of each bank
included in the study. The names of the 3 banks in alphabetical order are Barclays Bank of

14. 13
Botswana, Standard Chartered Bank Botswana & First National Bank Botswana. Data on GDP
growth were compiled from the Central Bank of Botswana Annual Report.
2.4 Description of Variables
2.4.1 Dependent Variable
The Return on Assets (ROA) is a financial ratio used to measure the relationship of to total
assets. ROA is regarded as the best and widely used indicator of earnings and profitability.
For this study, bank profitability is defined by return on assets (ROA), defined as the banks’ after
tax profit over total assets. ROA is considered as the key proxy for bank profitability, instead of
the alternative return on equity (ROE), because an analysis of ROE disregards financial leverage
and the risks associated with it.
External
Factors
Inflation rate
Real GDP
growth
Internal Factors
Capital
Size
Expenses
Bank Profitability
(Dependent Variable)
Independent
Variables

15. 14
2.4.2 Independent Variables
Capital: refers to the amount of own funds available to support a bank’s business and,
therefore, bank capital acts as a safety net in the case of adverse development. Capital is
calculated as the ratio of equity to total assets.
Based on past literature, the relationship between capital and profitable is said to be
unpredictable (Sharma & Singh, 2016). It is because while positive relationship had been found
by some studies (Berger 1995); other studies found a negative relationship between capital and
profitability (Saona, 2011).
Bank Size: Bank size accounts for the existence of economies or diseconomies of scale.
The variable is measured as the natural log of total assets (Saona, 2011). The theory of the
banking firm asserts that a firm enjoys economies of scale up to a certain level, beyond which
diseconomies of scale set in. its implies that profitability increases with increase in size, and
decreases as soon as there are diseconomies of scale. Thus, literature has shown that the
relationship between the bank size and profitability can be positive or negative.
Expenses Management: Expenses management relates to the idea of efficient
management of banks’ resources. For this study, the variable measures the ratio of operating
expenses to total assets. As Athanasoglou et al. (2005) observe, a negative relationship is
expected between expenses management and profitability, since improved management of the
expenses will increase efficiently and hence raise profits.
Inflation Rate: The inflation rate is expected to have a negative impact on bank
profitability. It is because inflation rate directly impacts bank interest income and expenses, and
the net result that further affects profitability.
GDP growth: A higher (lower) GDP indicates favourable (unfavourable) business
opportunities under which a bank can achieve higher (lower) profitability. It is because an

16. 15
increase in economic activities of the country signals that customers demand for loans will
increase.
2.5 Sources of Data
The secondary data used in this study were obtained from the annual financial statements of the
commercial banks. The data collected using data collection excel sheet were coded. Then the
data was analyzed using Microsoft Excel software.
2.6 Model Specification
A multiple linear regression model and t-statistic were used to determine the relative importance
(sensitivity) of each explanatory variable in affecting the performance of banks.
The paper made use of both descriptive and multiple regression analyses. The descriptive
approach was used to analyze the means and further shows the normality of the distribution. A
preliminary estimation of the correlation coefficients of the variables was carried out in order to
determine the explanatory variables that would finally appear in the regression model.
The specification of the regression model for the study is based on the empirical works of Saona
(2011). Five explanatory variables are included in the regression analysis. The empirical model
takes the following form:
ROE= ὰit+ β1CAP+ β2CAP+ β3CAP+ β4CAP
Code Description Measure
CAP Capital Equity/Total Assets
SIZ Size Log(total Assets)
EXP Expenses Management Operating Expenses/Total Assets
INF Inflation rate Average yearly inflation

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GDP Annual Gross Domestic Product growth Annual Gross Domestic Product growth
3.0 ANALYSIS OF DATA, DISCUSSION & FINDINGS
3.1 Findings
The purpose of this section is to present the results of data obtained from document analysis.
Therefore, the results of the documentary analysis (structured reviews of financial records)
presented in the following subsections.
3.1.1 Documentary analysis
The major purpose of this study is to assess factors affecting profitability of private commercial
banks in Botswana. The main data sources to this study end are obtained from annual reports of
Statistics Botswana and Banking supervision annual reports of Bank of Botswana.
3.1.1.1 Descriptive statistics
Table 1 presents the outcomes of the descriptive statistics for main variables involved in the
regression model. Key figures, including mean, median, standard deviation, minimum and
maximum value were reported. This was generated to give overall description about data used in
the model and served as data screening tool to identify some abnormal inconsistencies.
According to table 2, all variables comprised 11 observations and the profitability measure used
in this study namely; ROA indicates that the Botswana private commercial banks attained, on
average, a positive before tax profit over the last eleven years. For the total sample, the mean of
ROA was 2.8% with a minimum of 1.4% and a maximum of 4.0%. That means, the most
profitable bank among the sampled banks earned 4.0 Thebe of profit before tax for a single Pula

18. 17
invested in the assets of the firm. On the other hand, the least profitable bank of the sampled
banks earned 0.5 thebe of profit before tax for each Pula invested in the assets of the firm. The
standard deviation statistics for ROA was 0.007 which indicates that the profitability variation
between the selected banks was very small. The result implies that these banks need to optimize
the use of their assets to increase the return on their assets. The macroeconomic variables
incorporated in this study have the mean value of 4.7% and 7.6% with the standard deviation of
5.0% and 2.8% for real growth rate in GDP and the general rate of inflation, respectively. The
comparison between minimum and maximum values with the mean value of real growth rate in
GDP shows there is higher variability in the variable. Nevertheless, there is greater variability in
real growth rate in GDP which has large standard deviation in relation to the general rate of
inflation variable.
Table 1
Distribution of Data

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The values Skewness and kurtosis between -2 and +2 are considered acceptable in order to prove
normal univariate distribution. All variables satisfy both the skewness kurtosis range expect GDP
(Kurtosis-3.11) and therefore the test predicts that variables are generally normally distributed
and the panel data can be considered for empirical analysis
3.1.1.2 Correlation analysis
Table 2
As could be seen in table 2, the expenses management real GDP growth rate and average annual
inflation are positively correlated variables with ROA. This correlation clearly shows that, the
expenses management real GDP growth rate and average annual inflation profitability also
moves to the same direction. On the other hand, the size and capital seems to be negatively
correlated with the profitability measure, indicating that, the size and capital, profitability moves
to the opposite direction. Surprisingly, the inflation rate and expenses management was
positively correlated with ROA, indicated by the correlation of 0.60 and 0.10 respectively. In
similar to the inflation rate and expenses management, amazingly, the size and capital was
negatively correlated with profitability with a correlation of -0.73 and -0.40 respectively between
the inflation rate and expenses management and ROA.
Moreover, as shown in table 2, there were fairly low data correlations among the independent
variables. These low correlation coefficients indicate that, there is no problem of
multicollinearity in this study. Moreover, Kennedy (2008) stated that multicollinearity problem

20. 19
exists when the correlation coefficient among the variables are greater than 0.70, but in this study
there is no correlation coefficient that exceeds 0.70. Accordingly, in this study there is no
problem of multicollinearity which enhanced the reliability for regression analysis.
3.1.1.4 Regression analysis
This section presents the empirical findings from the econometric results on factors affecting
profitability of private commercial bank in Botswana. The section covers the empirical
regression model used in this study and the results of the regression analysis.
Empirical model: As presented in the second chapter the empirical model used in order to
identify factors affecting profitability of private commercial banks using statistical cost
accounting model was provided as follows:
Table 3

21. 20
ROE=-0.02(SIZ)-0.004(CAP) +0.76(EXP)+0.01(GDP)+0.15(INF)
The estimation result of the operational panel regression model used in this study is presented in
table 3. From table 3 the R-squared statistics and the Multiple-R squared statistics of the model
was 88% and 94% respectively. The result indicates that the changes in the independent
variables explain 94% of the changes in the dependent variable. That is size, capital, expenses
management, gross domestic product, and inflation rate collectively explain 94% of the changes
in ROA. The remaining 6% of changes was explained by other factors which are not included in
the model. Thus these variables collectively, are good explanatory variables of the profitability
of private commercial banks in Botswana. The null hypothesis of F-statistic (the overall test of
significance) that the R-square is equal to zero was rejected at 1% as the p-value was sufficiently
low. F value of 0.024 indicates strong statistical significance, which enhanced the reliability and
validity of the model.
Based on the results shown in table 3, all external independent variables used in this study, real
GAP growth rate and average annual inflation are statistically significant impact on profitability.
On the other hand, among the three bank-specific independent variables, only Capital is
significant. Among the significant variables, Size, expenses management and inflation rate were
significant at 5% significance level since the p-value for both variables were less than or equals
0.05 since the p-value was 0.03, 0.02 and 0.06 respectively. Whereas variables like Capital and
GDP growth were insignificant at 10% significance level since the p-value was 0.92 and 0.76
respectively.
Besides, table 3 also shows that the coefficient of Capital and Size against ROA was negative as
far as the coefficient this variables were negative -0.024 and -0.004 respectively. This indicates

22. 21
that there is an inverse relationship between the aforementioned independent variables and ROA.
Thus the increase of capital will lead to a decrease in ROA.
On the other hand, Expenses management annual inflation rate and gross domestic product had a
positive relationship with profitability as far as their respective coefficients were 0.759, 0.008
and 0.149. This revealed that there was a direct relationship between the above five independent
variables and ROA. In general as per the regression results provided in table 3 among the 5
independent variables used in this study 3 of them were significant.
In general, so far, the results of the documentary analysis which includes tests for the classical
linear regression model, descriptive statistics, correlation matrix & regression analysis have been
presented. The results of the tests for the classical linear regression model showed as the data fit
the basic assumptions of CLRM.
3.2 Discussions of the Findings
The preceding sections presented the result of the documentary analysis. The purpose of this
section is to discuss the results obtained from data sources. The analysis is based on the results of
the documentary analysis using the results of the regression analysis between the dependent
variable and the independent variables presented in table 4.6 presented in the preceding section.
According to Table 3, shows the results of regressions that use ROA as a dependent variable for
private commercial banks’. Accordingly, the intercept has positive and statistically insignificant
impact on profitability. It can be explained as during the study period private commercial banks
earn a positive income flows unrelated to the balance sheet items.

23. 22
3.2.1 Size
The coefficient of Size which is measured by the natural log of total assets was negative and
statistically significant at 5% significance level (p-value=0.029) and rejects the hypotheses that
there is a significant positive relationship between the size of a bank and bank’s profitability. The
coefficient of Size was relatively lower as compared to other variables; it shows that an increase
in Size will result in slight decrease profitability, which implies that Botswana banks are
operating above their optimal level.
3.2.2 Capital
The coefficient of Capital which is measured by the ratio of equity to total assets was negative
but statistically insignificant (p-value=0.923) and approves the hypothesis that there is a
significant positive relationship between the capital of the banking and bank’s profitability. It can
be interpreted as; one pula increase in the amount of capital would generate 0.004 thebe decrease
on profitability private commercial banks, which implies that Botswana bank management is
inefficient (Staikouras & Wood, 2004). The finding was also consistent with previous studies of
Saona (2011).
3.2.3 Expenses Management
Unlike, the coefficient of Capital and Size the coefficient of investment was positive and
statistically significant (p-value=0.019) and the data don’t support the hypotheses that there is a
significant negative relationship between the Expenses management of a bank. Thus, it is not
normal to expect positive relationship with profitability. But, the regression result fails to support
this conjecture indicating that for each Pula reduced on the expenses would generate 0.76 thebe
decrease on profitability of commercial banks.

24. 23
3.2.4 Real GDP growth rate
The coefficient estimate of real GDP growth revealed a positive and statistically insignificant
association with the profitability of private commercial banks at 5% significance level (p value
of =0.756). The magnitude of the coefficient estimate (0.008) indicates the existence of weak
positive relationship between real GDP growth and profitability of private commercial banks.
The findings was in accordance with prior expectation and theory that suggested whenever there
was a positive GDP growth, the economic activities in general were increasing and the volume of
cash held for either businesses or households was increasing. These conditions contributed to
decrease the likelihood that borrowers delay their financial obligations. In addition, strong
positive growth in real GDP creates a new and potential demand for financial services that can
easily translates into more income.
Hence, it can be concluded that, the existing unstable economic growth in Botswana over the
sampled period creates an erratic demand for financial services and ultimately slightly increases
the profitability of private commercial banks. The findings suggested that, real GDP growth was
not one of critical determinants of profitability private commercial banks which disapproves the
hypothesis that there is a significant positive relationship between real gross domestic product
growth and bank’s profitability.
3.2.4 Average Annual Inflation Rate
Inflation affects banks profitability through different channels and its impact on profitability can
be positive or negative. If the inflation is not anticipated, the banks may be slow in adjusting
their interest rates and this adversely or negatively affects bank profitability. On the other hand,
if the inflation is anticipated, banks may get an opportunity to adjust their interest rates
accordingly and resulted with revenues that increased faster than costs. Despite this fact, the

25. 24
coefficient estimate of inflation in this particular study revealed a positive association with the
profitability of private commercial banks’ in Botswana. This implies the existence of converging
relationship among inflation and profitability of private commercial banks. However, this
positive association was statistically significant at a confidence level of 5%; thus, the findings
suggested that inflation was not a major factor that determine the profitability of private
commercial banks of Botswana as far as the parameter for this variable is significant as
illustrated by a p-values of 0.046. This is because of the existence of a higher real interest rate
which is obviously higher than the real inflationary rate, resulting in costs increased slower than
revenues.
In Botswana the maximum lending rate is now determined by Central Bank of Botswana and
currently at 7.5%, since the implementation of the monetary policy decision of February 18,
2015. However, during most of the period of study, banks were able to adjust their lending rate
in accordance with inflation rate. For instance, the average annual inflation rate in Botswana over
the period of consideration was 7.66% with a maximum of 12.6%. Despite this fact, the average
lending rate exceeds 7.66% over the sample period. This clearly indicates the lending rate in
Botswana was far above from the market interest rate. In conclusion the result clearly reveals as
private commercial banks profitability is not influenced by inflation during the period of the
study.
4.0 RECOMMEDATION AND CONCLUTION
4.1 Conclusions
The overall objective of this study was to examine the effects of bank specific factors and
macroeconomic factors on the performance of commercial banks in Botswana using multiple

26. 25
linear regression method. By considering the nature and objective of the research, a quantitative
research approach was adopted. To collect the necessary data the study used survey of
documents (structured review of financial records). The collected data from a sample size of ten
private commercial banks over the period of 2005 to 2015 were analyzed using descriptive
statistics, correlation matrix and multiple linear regression analysis. The analyses were made in
accordance to the stated hypotheses formulated in the study.
In order to conduct the empirical analysis, one dependent variable (profitability measured by
ROE), and five independent variables were selected; capital, size, expenses management,
inflation and GDP growth. The variables were selected by refereeing different theories and
empirical studies that have been conducted on banks profitability. Consequently, the empirical
findings of this particular study suggested the following conclusions:
First, the coefficient of the constant term is positive and statistically insignificant. The positive
coefficient of constant term which represents economies of scale suggests that private
commercial banks in Botswana during the study period earn net positive income from off-
balance sheet activities. That means that these banks enjoy increasing returns to scale in their
operation.
Second, the empirical findings of this study provide evidence that the profitability of private
commercial banks in Botswana is negatively affected by internal factors except expenses
management. Specifically, the size and amount of capital have significant effect on the
profitability of private commercial banks. All other asset variables have no significant effect on
private commercial banks profitability.

27. 26
Third, all external factors are positively related to profitability. The GDP growth and inflation
have statistically significant and positive relationship with profitability.
4.2 Recommendations
From the results obtained from the regression analysis the result suggested that, among three
bank specific factors capital was the major factor that can positively and negatively contribute to
the profitability of private commercial banks in Botswana. Therefore, private commercial banks
should focus on decreasing the capital as this will enhance their performance rewarding
shareholders.
Additionally, private commercial banks should not only be concerned about internal structures
and policies, but they must consider both the internal environment and the macroeconomic
environment together in fashioning out strategies to improve their profitability.
Finally, the study sought to investigate factors affecting profitability of private commercial banks
in Botswana. For comprehensive investigation future researcher could increase the number of
observations by increasing the sample size and extending the period of time with unbalanced
data. In addition, future research could cover cross countries to capture countries differences and
to uncover difference from financial system and regulation factors.
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Appendix
P'Million

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Item 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Profit
749 939 935 1,313 1,236 1,047 1,652 1,772 1,775 1,478
Operaring E
786 848 1,124 1,553 1,594 1,681 2,096 2,364 2,709 2,782
Total Assets
18,543 30,413 37,265 45,251 44,023 49,590 51,600 57,954 56,962 67,994
Total Equity
1,412 1,655 1,883 2,420 3,035 4,069 4,696 5,548 647 7,724
Variable 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
ROA 4.0% 3.1% 2.5% 2.9% 2.8% 2.1% 3.2% 3.1% 3.1% 2.2%
Size=log(TA) 4.268 4.483 4.571 4.656 4.644 4.695 4.713 4.763 4.756 4.832
C=E/TA 7.6% 5.4% 5.1% 5.3% 6.9% 8.2% 9.1% 9.6% 1.1% 11.4%
EM=OE/TA 4.24% 2.79% 3.02% 3.43% 3.62% 3.39% 4.06% 4.08% 4.76% 4.09%
GDP Growth 4.60% 8.40% 8.30% 6.20% -7.70% 8.60% 6.00% 4.50% 9.90% 3.20%
Inflation rate 8.60% 11.60% 7.10% 12.60% 8.20% 6.90% 8.50% 7.50% 5.90% 4.40%
Banks Supervision & Statistics Botswana Annual Reports