Abstract The business environment in which Small and Medium Enterprises operate plays a key role in determining their success or closure rates. In trying to make the stabilise the macroeconomic environment through such targets such as low inflation rates, stable exchange and growth rates, sustainable debt and balance of payment, sometimes these policies may result in undesirable outcomes which if undermined distorts the performance of other actors in the economy in the long run. Of particular concern is the impact of Lending rate policies on SME growth behaviour. Although from a policy perspective it is imperative to understand how Lending rates affect a firm’s ability to access finance and grow, it is astonishing to note that few studies have been done in this field. This dissertation aims to bridge this gap and contribute empirical literature on the impact of lending rates on SME growth decisions, access to credit as well as the role of electricity supply in firm growth. The study focuses on Zambia and uses the data generated by the Bank of Zambia, World Bank, Central Statistical Office and the Zambia Data Portal. Using firm productivity as a measure of SME growth, multiple linear regressions were run on the data and the study reveals a negative correlation between high Lending rates and SME growth as well as negative correlation between Electricity usage and SME productivity. This result draws importance to the financial policies undertaken by policy makers whose impacts must be assessed in totality. It also supports the revelations of the World Bank (Enterprise Surveys, 2013) of the important role of adequate electricity supply in supporting the development of the SME sector. Furthermore, the study also finds a positive correlation between Credit Granted to firms and their productivity.

1. Graduate Institute of International Development and Applied Economics
The Impact of Lending Rates On SME Growth: The Case of Zambia
Wise Banda
Dissertation prepared in partial fulfilment for the requirements for the Master of Science in
Development Finance
13Th
September, 2016

2. i | P a g e
Dedication
This dissertation is dedicated to the Zambian people whom although hardworking, are
generally let down by the very educated professionals who are supposed to safeguard and
protect their interests. Although I cannot offer much at this stage, I am confident that
this work piece will encourage boldness and rationality in drafting policies in our struggle
for progress and inspire future policy makers. In completing this work, it is my hope that
patriotism will be restored and decision makers will find the courage to act with honour
to promote the wellbeing and prosperity of Zambians above all else.

3. ii | P a g e
Acknowledgement
I would like to express my sincere gratitude to The Chevening Scholarships, the UK
government’s Global Scholarship programme funded by Foreign and Commonwealth
Office (FCO) and Partner Organisations for according me the opportunity to pursue this
MSc in Development Finance here in Reading, United Kingdom.
I would also like to thank my supervisor, Dr Srinivasan for his guidance during the
completion of this research work. Completing this academic work would not have been
possible without the unconditional support from my family and friends throughout this
whole programme, words cannot express the gratitude I feel.

4. iii | P a g e
Table of Contents
Dedication------------------------------------------------------------------------------------- i
Acknowledgement --------------------------------------------------------------------------- ii
Table of Contents--------------------------------------------------------------------------- iii
Table of Figures------------------------------------------------------------------------------vi
LIST OF TABLES ------------------------------------------------------------------------------- vii
Abbreviations and Acronyms ------------------------------------------------------------ viii
Abstract---------------------------------------------------------------------------------------ix
CHAPTER 1 - INTRODUCTION -------------------------------------------------------------- 1
1.1. Background--------------------------------------------------------------------------- 1
1.2. Research Problem-------------------------------------------------------------------- 2
1.3. Research Objectives ----------------------------------------------------------------- 3
1.4. Scope of the Study------------------------------------------------------------------- 4
1.4.1. Research Strategy--------------------------------------------------------------- 5
1.5. Structure of the Study -------------------------------------------------------------- 5
CHAPTER 2 - LITERATURE REVIEW------------------------------------------------------- 7
2.1. Introduction -------------------------------------------------------------------------- 7
2.2. Small and Medium Enterprises---------------------------------------------------- 8
2.2.1. The Definition of SMEs--------------------------------------------------------- 9
2.2.2. Sources of Finance ------------------------------------------------------------- 9
2.2.3. SMEs and Growth: Empirical Evidence ------------------------------------11
2.3. What Determines SME Growth ---------------------------------------------------13

5. iv | P a g e
2.3.1. Financial Constraints ---------------------------------------------------------14
2.4. Interest Rate Theory----------------------------------------------------------------15
2.4.1. Why Policy Makers Normally Increase Interest Rates --------------------19
2.5. The Zambian Case------------------------------------------------------------------20
2.5.1. Background---------------------------------------------------------------------20
2.5.2. Recent Developments ---------------------------------------------------------21
2.5.3. Zambian SME Constraints ---------------------------------------------------22
2.5.4. Performance of SMEs in Zambia---------------------------------------------23
2.6. Conclusion---------------------------------------------------------------------------27
CHAPTER 3 - METHODOLOGY ------------------------------------------------------------29
3.1. Introduction -------------------------------------------------------------------------29
3.2. Objectives Review -------------------------------------------------------------------29
3.3. Hypothesis Formulation -----------------------------------------------------------30
3.3.1. Hypothesis 1--------------------------------------------------------------------30
3.3.2. Hypothesis 2--------------------------------------------------------------------31
3.3.3. Hypothesis 3--------------------------------------------------------------------31
3.4. Nature and Sources of the Data --------------------------------------------------32
3.5. Estimation Model Specification ---------------------------------------------------33
3.6. Selection of Variables --------------------------------------------------------------34
3.6.1. Dependent Variable------------------------------------------------------------34
3.6.2. Explanatory Variables---------------------------------------------------------35
3.7. Estimation Method -----------------------------------------------------------------36
3.8. Limitations---------------------------------------------------------------------------37

6. v | P a g e
3.9. Conclusion---------------------------------------------------------------------------38
CHAPTER 4 - RESULTS ANALYSIS AND DISCUSSION---------------------------------40
4.1. Introduction -------------------------------------------------------------------------40
4.2. Descriptive Statistics ---------------------------------------------------------------40
4.3. Discussion and Interpretation of the Results-----------------------------------46
4.4. Inferences from these Findings ---------------------------------------------------48
4.5. Lending Rates Across Countries--------------------------------------------------48
4.6. Lending Rates and Investment Expenditure------------------------------------50
4.7. Conclusion---------------------------------------------------------------------------51
CHAPTER 5 - CONCLUSION AND POLICY IMPLICATIONS ----------------------------52
5.1. Summary-----------------------------------------------------------------------------52
5.2. Research Conclusions and Limitations of the Findings-----------------------53
5.3. Policy Implications------------------------------------------------------------------54
5.4. Areas for Further Research--------------------------------------------------------56
Bibliography -----------------------------------------------------------------------------------57

7. vi | P a g e
Table of Figures
Figure 2-1: Percentage of SMEs Financed by Banks in Sub-Saharan African------ 10
Figure 2-2: SME growth in Employment ------------------------------------------------- 12
Figure 2-3: Interest Rate Transmission Mechanism------------------------------------ 17
Figure 2-4: Lending Rates Vs Inflation Trends in Zambia ---------------------------- 20
Figure 2-5: Ranking constraints to SME growth in Zambia--------------------------- 22
Figure 2-6: Comparison of Zambian SME Loan Rejections---------------------------- 23
Figure 2-7: Performance of Zambian SMES in Terms of Percentage Growth in Sales24
Figure 2-8: Number of firms listed on the Lusaka Stock Exchange------------------ 25
Figure 4-1: Lending rates and Firm Productivity --------------------------------------- 43
Figure 4-2: Productivity and Credit Granted -------------------------------------------- 44
Figure 4-3: Lending Rates and Credit Granted------------------------------------------ 47
Figure 4-4: Lending Rates Across Countries -------------------------------------------- 49
Figure 4-5: SME Performance-------------------------------------------------------------- 50

8. vii | P a g e
LIST OF TABLES
Table 2-1: Lusaka Stock Exchange Listed Companies --------------------------------- 26
Table 4-1: Summary Statistics------------------------------------------------------------ 41
Table 4-2: Graphical Representation of the Correlation among the Variables------ 42
Table 4-3: Regression Results ------------------------------------------------------------- 44

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Abbreviations and Acronyms
AfDB
African Development Bank, 8
BOZ
Bank of Zambia, 9
CSO
Central Statistical Office, 32
EU
European Union, 13
IMF
International Monetary Fund, 8, 9, 22, 23, 24, 42, 44
Non-Bank Financial Institutions
NBFI, 21
OLS
Ordinary Least Squares, 32
Small and Medium Enterprises (SMEs)
SMEs, 8
Structural Adjustment Programs (SAPS)
SAPs, 8
Sub-Saharan African
SSA, 10
Zambia Data Portal
ZDP, 32

10. ix | P a g e
Abstract
The business environment in which Small and Medium Enterprises operate plays a key
role in determining their success or closure rates. In trying to make the stabilise the
macroeconomic environment through such targets such as low inflation rates, stable
exchange and growth rates, sustainable debt and balance of payment, sometimes these
policies may result in undesirable outcomes which if undermined distorts the
performance of other actors in the economy in the long run. Of particular concern is the
impact of Lending rate policies on SME growth behaviour. Although from a policy
perspective it is imperative to understand how Lending rates affect a firm’s ability to
access finance and grow, it is astonishing to note that few studies have been done in this
field.
This dissertation aims to bridge this gap and contribute empirical literature on the impact
of lending rates on SME growth decisions, access to credit as well as the role of electricity
supply in firm growth. The study focuses on Zambia and uses the data generated by the
Bank of Zambia, World Bank, Central Statistical Office and the Zambia Data Portal. Using
firm productivity as a measure of SME growth, multiple linear regressions were run on
the data and the study reveals a negative correlation between high Lending rates and
SME growth as well as negative correlation between Electricity usage and SME
productivity. This result draws importance to the financial policies undertaken by policy
makers whose impacts must be assessed in totality. It also supports the revelations of
the World Bank (Enterprise Surveys, 2013) of the important role of adequate electricity
supply in supporting the development of the SME sector. Furthermore, the study also
finds a positive correlation between Credit Granted to firms and their productivity.
Word Count: 13,484

11. 1 | P a g e
CHAPTER 1 - INTRODUCTION
1.1. Background
Ever since the peak of structural adjustment programs in the 1980s and 1990s, Small
and Medium Enterprises (SMEs) in Africa have always been side-lined by economists and
policy makers as drivers of economic growth in preference to large scale multinational
companies. The rationale was that of trickle-down effect, where the large corporations
would inject the much needed capital into the economy, bring in modern technologies
and expertise as well as provide employment for the locals. As such, many hastily
embraced the IMF and World Bank induced Structural Adjustment Programmes (SAPs)
(Mkandawire & Soludo, 2002). Faced with high national debt levels, high inflation and
weak economies, developing countries implemented Structural Adjustment Programs
(SAPS) where they sold large scale state enterprises to pave way for this foreign inflow of
capital, technologies and the employment that would ensue under economic liberalisation
and market oriented policies. Although some multinational companies did indeed set up
subsidiaries in developing countries, owing to the incentives under SAPs, the trickle down
benefits have not been to the anticipated levels (Mkandawire & Soludo, 2002). In order to
ensure macroeconomic stability, policy makers embarked on liberal policies that were
aimed at curbing inflation, stabilizing exchange rates, debt sustainability and raising
interest rate to attract foreign investment to the capital starved enterprises. However,
although most developing countries saw little improvement in economic performance and
stability since the SAPS, a concern emerged on the unfavourable performance of the
SMEs.
In recent studies, many scholars and policy analysists have realised the importance of
SMEs in economic growth and private sector development (Beck, et al., 2005; Beck,
2007). To this end, many international development institutions have identified SMEs as

12. 2 | P a g e
engines of growth and are investing significant efforts in promoting their growth. As noted
by Beck, et al., (2006), the World Bank, AFDB, IMF have changed their approach to
development and now provide financing to SMEs and also support government policies
and programmes that aim at improving the business environments in which firms
operate. Despite the extensive literature on the challenges in the macroeconomic
environment that hampers SME growth, including that of access to finance, there is little
research that explores the link between interest rates in influencing this environment
more especially Lending rates and their impact on SMEs. Among the noted constraints
as argued by Beck et al., (2005), include access to finance, Taxation, corruption,
institutions and regulatory environment, poor infrastructure and of course the policy
environment. Hence this research focuses on lending rates and how they influence SME’s
growth and investment decisions as well as access to finance in Zambia.
1.2. Research Problem
Ever since the liberalisation of the economy, Zambia has seen significant capital inflows
to various sectors of the economy and has enjoyed impressive economic growth averaging
7% between 2010 and 2014 (World Bank, 2016; IMF, 2015). In order to sustain this
capital inflow as well as attract major business investments, policy makers have been
implementing policies that try to stabilize the macroeconomic environment. Among these
include curbing inflation to single digit currently at 7.1% BOZ (2016), stabilising the
exchange rate volatility, and maintaining stable balance of payments position. However,
the country has recently been experiencing declining economic performance. The IMF
mission in their recent consultation visit to the country in 2014 noted that the country
has been facing a deteriorating current account as a result of falling copper prices,
Zambia’s major export; fiscal imbalances and policy uncertainties causing downward
pressure on the exchange rate and significantly lowering the growth rate from 6.7% in
2013 to 3.7% in 2014, and an estimated further economic decline to 3% for 2015 (IMF,

13. 3 | P a g e
2016). In light of this harsh economic reality, the Bank of Zambia’s implemented tight
monetary policy by hiking the reserve requirements and raising the interest rates.
Although inflation and exchange rate volatility stabilized, this action did not have a
favourable bearing on other players of the economy most notably the Small and medium
enterprises. It is this attempt to address larger problems that in usually result in
economic distortions for other players. Hence the need for this research which
investigates the impact of Lending rates on the growth of Small and Medium Enterprises.
The Bank of Zambia tightens monetary policy through either raising the reserve
requirement or increasing the policy rate, which is the benchmark lending rate used by
financial institutions (Mbao, et al., 2014). In so doing, the monetary base and
consequently liquidity in circulation is reduced in an attempt to lower aggregate demand
and fight inflation. Large scale enterprises can cope with this development as their
markets and sources of capital are usually across borders, mostly in Europe and Asia.
However, for most SMEs which rely almost entirely on the local market for both financing
and sales, such developments become hostile for them and threaten their very survival.
Little research in this field justifies the need for this dissertation which explores the
impact of Lending rates on SME growth and their ability to access finance.
1.3. Research Objectives
The aim of this research is to contribute to existing empirical knowledge on the broader
impact of financial policies on other sectors of the economy than the originally intended
targets. In particular, the research examines the impact of high lending rates on growth
of SMEs and their ability to access financing. In view of this purpose of the study, the
research will try to answer the following questions:
a) What is the impact of Lending rates on SME growth as Measured by
productivity?

14. 4 | P a g e
b) Do Lending rates also affect the credit granted to firms?
c) How do Zambia’s lending rates fare among similar countries in Sub-Saharan
Africa and the world, do countries with lower lending rates have more
productive SMEs?
d) Does lowering the lending rates improve SME expansion through increased
investments in capital and machinery?
The contributions of this research work are primarily empirical although the findings to
be presented may provide the basis for better modelling of Financial and Economic
Policies for SME growth in the future.
1.4. Scope of the Study
The area of focus of the research is on SMEs in Zambia although for comparative
purposes, other Sub-Saharan African (SSA) countries will be reviewed. This is in order to
get a clear understanding whether the research results are applicable to countries with
similar contexts. The dissertation is centred on SMEs that borrow from formal financial
institutions because flows of credit to firms that do not borrow from financial institutions
is not well documented and such data is not readily available. However, it is possible that
bank interest rates may influence the availability of credit from other sources such as
Non-Bank Financial Institutions (NBFI), family and friends as well as the terms on which
they are offered.
Additionally, despite many factors that constrain SME growth, the scope of this study is
limited to three namely; Lending rates, Credit Granted by banks and the role Electricity
in SME growth with major focus on lending rates.

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1.4.1. Research Strategy
The research employs a case study analysis of Zambia by giving trends, descriptive
indicators and current economic outlook of the country. Based on these developments,
empirical analysis of the impact of interest rates on SME growth in Zambia will be done
using regression analysis. A comparison of the findings with five other Sub-Saharan
African countries will help emphasize the case. This strategy is useful in understanding
how policy differentials among countries is affecting their business environment, with
regards to interest rates and consequently the growth of the SMEs. Zambia is of particular
interest as it normally falls prey to economic shocks due to its over reliance on large scale
enterprises especially in the mining sector and there have been calls to diversify the
economy, thus the SME sector if promoted provides a lucrative alternative. Hence, this
research provides a wealth of knowledge especially with regards to economic
diversification focusing on Small and Medium Enterprises. The link between interest
rates and investments will be explored by controlling for other determinants using the
investment function; 𝑖 = 𝑓(𝑥, 𝑦) .
1.5. Structure of the Study
From this introductory chapter, the remainder of the dissertation is structured as follows:
chapter two will present the Literature review which will highlight the underlying
theoretical and conceptual framework of this research. In this vain, an extensive review
of interest rate theories as well as empirical research on SME growth, characteristics and
other relevant aspects will be presented in order to give direction and build the research
case. The chapter closes by summarising the empirical evidence regarding effects of
interest rates on investment as well as key determinants of SME growth. The third
chapter details the methodology and tools used to analyse the data. From the description
of the data collection and sampling methods, to selection of the dependent and

16. 6 | P a g e
independent variables, the chapter continues to highlight the econometric model and
software used.
Consequently, Chapter four will follow and present empirical results and summary
statistics of the analysis. Based on this, a detailed interpretation and discussion of the
findings shall close the chapter. And in concluding the dissertation, Chapter 5 will
summarise the research findings and highlight the policy implications for economists and
policy makers.

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CHAPTER 2 - LITERATURE REVIEW
2.1. Introduction
For some time now, the role of SMEs in development have been undermined especially in
developing countries in preference for large scale enterprises. The various arguments
advanced for this are that large scale enterprises especially foreign ones bring with them
the vital capital injections, expertise and technological transfers while at the same time
create employment and present tax benefits for the domestic economy. As such, many
developing countries’ policy makers have been more concerned about creating a
macroeconomic atmosphere which favour such large scale multinational companies and
foreign investments at the expense of the local industries. Although most of the policies
aimed at creating this environment would benefit all stakeholders at large, some of them
have had the effects of undermining the growth of Small and Medium Enterprises (SMEs).
Despite evidence from Beck et al., (2006) finding no causal relationship between SME
growth and economic development, it does however establish a positive correlation
between the two. This means that, countries that achieve higher levels of economic
growth also exhibit a vibrant SME sector. Besides, evidence is vast from around the world
that today’s large scale enterprises were once SMEs themselves. Of central focus to this
paper are lending rates and how they impact SMEs’ ability to access financing and
transform into large scale enterprises.
This chapter sets the conceptual and theoretical framework for the research by reviewing
empirical studies on the topic. The chapter explores the underlying theories and empirical
studies on interest rates as well as how they impact various aspects of economic growth.
The study proceeds to define the main concepts and discusses the major debates on
lending rates, investments, access to finance and characteristics and determinants of
SME growth. Thereafter, a detailed study of the relationship between Lending rates and

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a firm’s investment decisions shall follow. Furthermore, the chapter meticulously
highlights the relationship between Lending rates and how they affect a firm’s ability to
access finance both from the supply side and demand side. Empirical evidence from
existing literature is presented to support the research. The rationale here is to draw
attention to the link between lending rates and how they influence a firms’ productivity
as well as its ability to access to credit and consequently make investment decisions. A
case study of Zambia shall be presented outlining the economic and financial reform
background as well as an examination of the interest rate policy and its determinants.
By comparing the performance of SMEs in Zambia with those of other Sub-Saharan
countries, the chapter concludes by building the hypothesis to ascertain the relationship
between the two which is then tested in Chapter 4.
2.2. Small and Medium Enterprises
Small and Medium Enterprises are a vital part of a well-functioning economy. Developed
countries have witnessed exceptional rise of start-ups transform into giant multinational
corporations. From Tech companies such as Microsoft, Apple, Tesla, social media
companies like Facebook, Google, LinkedIn and trading companies like Amazon, eBay,
Alibaba as well as transport and media companies like Virgin, SpaceX, Tesla and General
Motors all were once tiny companies some of which originated in university dormitories
and homes to later became the major growth companies of the past three decades. Just
like advanced countries, developing countries also need to promote their small and
medium enterprises if they are to accelerate their economic growth. Empirical evidence
reveals that SMEs create more than 50% of the total formal employment and they also
generate the highest rates of job creation even surpassing large corporation, (Ayyagari, et
al., 2007; Ayyagari, et al., 2011).

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2.2.1. The Definition of SMEs
The definition of Small and Medium Enterprises varies depending on the target region
and institutions involved. Additionally, different aspects of SMEs are considered when
defining them. Some scholars define SMEs in terms of number of employees, while others
define them in terms of performance measures such as annual turnover and Balance
sheet capital injection. The European Union defines a small and medium enterprise as a
company that employs 250 or fewer employees, or has an annual turnover of up to
€50million and a balance sheet of up to €43 million (European Union, 2012). Gibson and
Vaart (2008) on the other hand defines an SME as “a formal enterprise with annual
turnover, in U.S. dollar terms, of between 10 and 1000 times the mean per capita gross
national income, at purchasing power parity, of the country in which it operates.” Although
the later definition is ideal as it uses annual turnover to categorise the SMEs, the most
former is commonly due to the ready availability of such data on employment as
compared to turnover as most SMEs rarely keep updated financial information1.
According to Caner (2014), SMEs are characterised by high failure rates, produce
intermediate low value added goods, and are mostly informal and semi-formal enterprises
that usually lack corporate business acumen. Perhaps it is because of this trait that
makes it hard for them to raise financing as 50% of them do not have access to formal
credit (World Bank, 2016). Caner (2014) adds that due to their informal nature, they
normally hire unreported labour and are prone to tax evasion issues.
2.2.2. Sources of Finance
Empirical evidence reveals that due to their informal nature and small size SMEs find it
difficult to raise finances from financial institutions (Beck, et al., 2006). In their infancy,
they rely extensively on personal resources as well as that from family members and
1
Most SMEs especially in developing countries operate on a thin line between the formal and informal sectors

20. 10 | P a g e
informal sources. For capital intensive projects, such large investment funding can only
be accessed from commercial banks especially in developing countries where capital
markets are under developed. According to Mankiw (2016) financing constraints such as
the cost of borrowing, can prevent firms from taking up profitable investments. Non-
Bank Financial Institutions are also influenced as some of them source their capital
directly from banks hence contributing to their higher interest rates.
Figure 2-1 below presents the percentage of total firms financed by the banks.
Figure 2-1: Percentage of SMEs Financed by Banks in Sub-Saharan African
Source: Enterprise Surveys of the World Bank (2013)
Figure 2-1 shows that a small percentage of SMEs in Sub-Saharan Africa are financed
by Banks, with Mauritius attaining the highest percentage at 30.8% while the rest of the
countries under review recorded financing below 26%. Zambia recorded an alarming
lower percentage attaining only a meagre 6.6% of SMEs financed by banks.
According to the research by Vaselin (2014), fully financially constrained firms have no
loans because their loan applications were rejected or the firm did not apply for credit
due to harsh credit terms even though they needed it. Other scholars, (Ayyagari, et al.,
2006; Beck, 2007; Beck & Demirguc-Kunt, 2006) suggest that firms may not apply for

21. 11 | P a g e
credit due to; (1) having enough funds generated from business operations; (2) harsh
conditions from lenders which may include high interest rates, technical requirements
and collateral requirement for credit grants; (3) Or simply that the firm’s applications
were rejected based on strict credit criteria ultimately forcing them to seek other sources
(Vaselin, 2014). Alternatively, many firms seek external sources of funding such as
informal sources like money lenders, family and friends which are viewed as being more
efficient with more flexibility in their lending approach compared to the big banks ( Cull
, et al., 2008)
2.2.3. SMEs and Growth: Empirical Evidence
The debates as to whether growth in Small and medium enterprises leads to overall
economic growth has been well documented. Evidence from Beck (2007) in his cross-
country studies suggests a positive correlation between the two, where countries that had
a larger SME base showed higher or faster growth compared to those that had a smaller
SME base. Although this was the case, the findings do not establish a causal relationship
between SMEs and economic growth. Additionally, SMEs accounted for a greater share
of employment in the private sector of most economies thereby consolidating their
contribution to economic growth (Enterprise Survey, 2013). As developing countries begin
to attain stronger growth, SMEs begin to play a more cardinal role in industrial
development and restructuring, providing intermediate goods and services, allowing for
increased specialisation and complementing larger enterprises with inputs and services
(Fjose, et al., 2010).

22. 12 | P a g e
Figure 2-2: SME growth in Employment
Source: Enterprise Surveys of the World Bank (2013)
Figure 2-2 shows the percentage increase in employment created by SMEs. It can be noted
that SMEs have contributed to employment growth with percentages between 10% to
12.2% for the majority of the countries. SMEs in Angola and Gabon appear to be growing
faster than the rest by this measure at 18.7%. Only Zambian SMEs seem to contribute
very minimal to employment creation at only 1.5%.
Despite acknowledging the role of SMEs in providing intermediate goods, Caner (2014)
draws attention to the low value added goods and services they produced as well as the
SMEs’ short life span due to high bankruptcy rates among them. Perhaps this is the
reason why scholars and policy makers had for a long time neglected the SME sector in
preference for large enterprises and multinational corporations as drivers of growth
(McPherson, 1992). According to their arguments, large companies bring in the much
needed foreign capital, technologies and expertise and would eventually drive economic
growth while sharing the benefits with the local people through job creation and trickled
down effect. A disadvantage of relying too much on large scale foreign companies however
is that, the goods they produce are not necessarily intended for the local market. This is
because they mostly aim to penetrate international markets and their pricing strategies

23. 13 | P a g e
may ultimately make them overlook the local markets in preference for lucrative
international markets.
Additionally, they create an industrial gap as they do not mostly produce intermediate or
low value goods which may be needed by the local markets in which they are based.
Hence, SMEs emerge to fill up this gap. After realising the volatile nature of large
enterprises especially in this era of increased globalisation and capital mobility, there
have been renewed interest in SME research and development from both scholars and
policy makers in the recent past. SMEs are believed to be the engines of economic growth
but poor institutions, policies, market failures and macroeconomic instabilities impede
their expansion (World Bank, 2016).
2.3. What Determines SME Growth
Recent studies have reinvigorated the importance of SMEs in economic development.
Ayyagari et al. (2007) in their research found that SMEs create more employment than
the large corporations which were initially promoted. Development institutions such as
the World Bank, African Development Bank among others have now dedicated significant
funding and resources to try to promote the SME industry. The idea is to stimulate the
sector as the engine of economic growth given their outreach potential and magnitude of
their impact. The vision is that they would graduate into large scale multinational
enterprises and contribute even further to economic growth. As noted by McPherson
(1992), much of the support to the SME sector is through policy reform as well as
business skills training to the entrepreneurs in an effort to make them compete with large
scale enterprises.
Macroeconomic instability creates a hostile business environment that undermines
SMEs’ performance. Specific challenges include weak regulatory and contract
enforcement institutions, corruption, costs of doing business as well as financial and

24. 14 | P a g e
economic policies (Enterprise Surveys, 2013). These challenges have given rise to the high
failure rates of SMEs especially in developing countries where most of them stagnate or
fail completely before their 3rd birthday. Liedholm and Mead (1993) assert that the
economic situation prevailing in a country plays a key role in the emergence of SMEs.
According to their argument, new SME start-ups in developing countries are more likely
to reflect primarily a case of people seeking a way of sustaining themselves due to
economic hardships. On the contrary, in developed countries, new enterprises arise as a
result of a growing demand for goods and services in expanding sectors. As such, the
number of New start-ups varies inversely with the aggregate level of economic activity in
developing countries while the opposite is true for developed countries.
Many scholars, such as Levine (2005) and Beck et al. (2005) among others emphasised
the context of the macroeconomic environment in which firms operate as a constraint,
one of them being the financial policies. Sound financial policies are a necessary condition
for attaining economic growth as they are usually the key determinants of the business
environment in the economy. From them, exchange rates, inflation, taxation and interest
rates among others are derived. Mwenda and Mutoti (2011) assert that repressive
financial policies affect the business environment and cause credit rationing thereby
influencing savings and investment decisions, returns on assets and the ability to access
finance.
2.3.1. Financial Constraints
Of all the constraints facing SMEs, access to finance ranks the highest. According to the
World Bank (2016), 50% of SMEs do not have access to finance with the number rising
to 70% when micro-enterprises are considered. This translates to about $2.6trillion credit
gap for both formal and informal SMEs. Research by Beck, et al. (2008) and Beck et al.
(2006) reveals that size plays a key role in determining access to finance, with smaller
firms having more difficulties in accessing finance compared to larger ones. Evidence

25. 15 | P a g e
from Ayyagari, et al. (2006) finds that financial constraints limit a firm’s size and growth.
Furthermore, due to lending institutions’ preference for large enterprises, SMEs use less
finance from formal sources such as Banks and rely more on internal sources, supplier
credit and informal sources such as money lenders and family and friends (Ayyagari, et
al., 2006; Enterprise Surveys, 2013).
Economic policies, especially financial policies have a significant influence in shaping the
business environment in which firms operate. Financial policies determine profitability
and turnover of both the SMEs and the commercial banks which provide their financing,
through directly affecting the operational costs and margins respectively. Hence monetary
policies of raising interest rates appear to be at the root of these access to finance
challenges.
2.4. Interest Rate Theory
Interest rates have for a long time been considered the key determinants for capital flows.
Neoclassical economic literature emphasizes the negative relationship between interest
rates and capital flows (Mankiw, 2009). Although this may be true in most cases, there
are different aspects of interest rates that are worth noting. These include the interest
rates earned on investments, also called the rates of return; and the interest rates paid
out for renting assets, otherwise known as Lending rates. In some literature, they are
used interchangeably, although they could be mutually exclusive, the lender may not
necessarily be the borrower.
From the earning perspective (supply side), interest rates represent the returns on
investment made and are considered income. Hence the higher the interest rates, the
higher the returns on investments and consequently more capital inflows. Examples for
such assets which are motivated by high interest rates include equity, capital, bonds and

26. 16 | P a g e
many others. The higher their yields, the more attractive they become. This rationale is
well explained in the international capital mobility theories (Begg, 2014; Mankiw, 2016).
On the paying side (demand side), interest represents the price of borrowing and is thus
considered as a cost. In this regard, the high lending rates entail high costs of borrowing
and results in lower investment expenditure by the firms. This is the basis of the
investment function which stipulates a negative relationship between interest rates and
investments (Mankiw, 2016).
This background is the basis of credit lending decisions by banks which fall on the supply
side. Firms on other hand fall on the demand side. Bernanke and Gertler (1995) review
lending decisions by banks using balance sheet channel. Bougheas, et al. (2006) further
elaborate on this view by explaining that banks base their lending decisions on financial
performance factors such as profitability, credit history, debt levels and so on. In most
developing countries, Banks are the major providers of financing due to the undeveloped
capital markets. In Sub-Saharan Africa, this is even more evident as the numbers of firms
raising funds through the stock markets are very minimal compared to developed
countries and emerging markets. This argument is also supported by Kashyap and Stein
(1994).
Hence, the tight monetary policies through high interest rates present an adverse
situation compounding the problem of SME growth through access to finance more
especially on SMEs that rely to a large extent on bank lending for larger capital needs.
Figure 2-3 shows this transmission effect.

27. 17 | P a g e
Figure 2-3: Interest Rate Transmission Mechanism
Source: Bank of Georgia2
Figure 2-3 it can be noted that in an effort to curb inflation and reduce price levels, an
increase in interest rates reduces the availability of credit on the market. Furthermore,
because the cost of borrowing also increases, firms scale down on expansionary
expenditures and investments and the overall result is a reduction in aggregate demand
and growth. Consequently, SMEs will fail if they are subverted by bad policies which
affect both their operational costs and their ability to take up expansion opportunities. It
is imperative however, to note that repressive financial policies may not be implemented
to sabotage the economy, but may rather be in response to solve an urgent economic
condition such as inflation, foreign exchange volatility or curb capital flight.
On the supply side, monetary policy results in credit rationing by banks through
aggressive pricing of loans to reflect opportunity costs, the risks in balance sheet
2
There are many theories which express the transmission mechanism of high interest rates, however, the one from
the (Bank of Georgia, 2010) expresses it in a more simplified version.

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information, as well as the costs of borrowing (Bougheas, et al., 2006). Where the central
bank adopts a policy rate, the situation is usually worse as banks adjust their lending
rates by charging a margin on this indicative rate. Brownbridge (1998) in his analysis of
the financial reforms of Zambia reaffirms this and adds that such pricing leads to adverse
selection as most credit worthy firms avoid the high interest loans leaving only the risky
ones thereby impairing the banks’ credit portfolio.
In situations where interest rates are guided by a central bank policy rate system, Banks
normally use this as the indicative rate for the cost of capital and would charge a margin
above or below the policy rate to maximise their earnings. Hence the overall consequence
is the general rise in the lending rates in the economy. The impact is severe for those
SMEs that rely on Bank financing and usually leads to high default rates due to inability
to pay the high interest rates. Non-Bank Financial Institutions are also influenced by
these lending rates as most of them use bank lending rates as their benchmarks. Hence
rates charged by NBFIs are even higher.
In addition to this, the credit available from other sources; family, friends and money
lenders, is usually of small amounts for capital expansion (Cull et al., (2011). All these
scenarios leave little room for raising finances from financial institutions. Hence, the tight
monetary policies through increasing the interest rates present an adverse situation more
especially to SMEs that rely to a larger extent on Bank lending for larger capital project
and investments.
Firms require financing to undertake investments. Mankiw (2016) defines investment in
three categories namely business fixed, residential fixed and inventory investment.
According to this definition, business fixed investment is where firms grow and expand
by purchasing new structures, equipment and intellectual property products. Residential
investment on the other hand involves purchases of housing while inventory investment
comes about as a result of a firm’s increases in its stock (Ibid). This research refers to

29. 19 | P a g e
business fixed investment spending. From neoclassical economic theory, increases in real
interest rates leads to a reduction in investment hence the negative relationship between
the two. In order for firms to produce goods and services, they require capital to purchase
land, machinery and equipment as well as the technologies.
2.4.1. Why Policy Makers Normally Increase Interest Rates
Policy makers around the world have always implemented ambitious policies in their bid
to meet macroeconomic targets. The primary focus has thus been on attaining positive
economic growth rates, stable exchange rates, low unemployment and of course low
inflation rates. It is in trying to stabilize inflation that the link with interest rates becomes
more pronounced. Mankiw (2016) views interest rates as the prices that link the future
with the present. According to this view, central banks raise interest rates using the
Fischer equation and quantity theory of Money. The quantity theory of money shows that
money supply, or the rate of money growth determines the inflation rate in the economy.
Hence, it is usually in response to inflationary pressures that policy makers base their
monetary growth decisions. In doing so, they actually affect the interest rates as well.
Thus if interest rates rise in response to rising inflation, then the real interest rates, which
is the difference between the two, will also rise.
𝒓 = 𝒊 − 𝝅 (Equation 2-1)
𝑊ℎ𝑒𝑟𝑒 𝑟 = 𝑟𝑒𝑎𝑙 𝑖𝑛𝑡𝑒𝑟𝑒𝑠𝑡 𝑟𝑎𝑡𝑒𝑠, 𝑖 = 𝑛𝑜𝑚𝑖𝑛𝑎𝑙 𝑖𝑛𝑡𝑒𝑟𝑒𝑠𝑡 𝑟𝑎𝑡𝑒 𝑎𝑛𝑑; 𝜋 = 𝑖𝑛𝑓𝑙𝑎𝑡𝑖𝑜𝑛
Hence through this interaction, the effects of inflation on real and nominal interest rates
can be determined. Understanding this theory is cardinal in analysing how interest rates
and inflation should move. Empirical evidence from the IMF shows a positive correlation
between the two. In the Zambian context, lending rates and inflation rates have generally
been declining steadily since mid-1990s although there were some up swings between

30. 20 | P a g e
2008 and 2010, they are still relatively high. Inflation has generally been contained below
10% since 2007. Figure 2-4 highlights this trend.
Figure 2-4: Lending Rates Vs Inflation Trends in Zambia
Source: Author’s computations using BOZ data
Besides raising the cost of borrowing, lowering domestic investment expenditure due to
the high earnings on savings and adverse selection issues, high interest rates have more
ramifications. As argued by Mankiw (2016), in a worst case scenario, higher interest
rates can reduce economic growth and even trigger a recession as a result of slowing
investments and economic activity (see Figure 2-3).
2.5. The Zambian Case
2.5.1. Background
From independence, Zambia did not have a clear SME policy until 1981 as the majority
of the businesses in the economy where state run. This was largely due to the import
substitution industrialisation policies undertaken by the government. Due to the
commodity and oil crisis of 1975 which saw copper prices tumble and economic
0.0
20.0
40.0
60.0
80.0
100.0
120.0
140.0
160.0
180.0
200.0
1990 1995 2000 2005 2010 2015 2020
Lending Rates vs Inflation
Interest Annual Inflation

31. 21 | P a g e
downturn, the government embarked on a new policy to promote SMEs although this
impact was insignificant (Mumbi & Kafula, 2011). It was not until the 1990s when the
new government embarked on massive privatisation campaigns and economic
liberalisation programs which saw the selling of state enterprises, and massive job
downsizing that a significant number of Zambians began indulging in SME activities due
to the resulting unemployment.
Reforms and readjustments continued for another dozen years until the late 2000s when
the country started enjoying a period of sustained economic growth averaging 7%
annually. The financial sector reforms, debt cancellation and good copper prices
contributed to an improved balance of payment position and saw the country attain
budget surpluses and accumulate foreign reserves.
2.5.2. Recent Developments
SMEs in Zambia have been performing much lower than their counterparts in Sub-
Saharan Africa and other developing countries. This has been largely attributed to the
unstable macroeconomic environment. Recent macroeconomic developments showed a
number of economic challenges facing the country. According to the IMF (2016) mission
report, a volatile exchange rate resulting from the fall in the copper prices sent the
country’s currency in free fall. This situation has been exacerbated by increased
borrowing from the international markets which made debt repayments high and left the
country in deficit. Furthermore, the rise in inflation forced central bank activity on the
market through open market operations and raising of interest rates as they struggled to
curb inflation and maintain positive growth which had taken a dive from a peak of 7%
enjoyed in 2008 to 3.4% in 2016 (IMF, 2016). These increased rates entail a rise in the
cost of borrowing. The situation is further worsened by electricity shortages, budget
deficit and increasing debt stock all putting the country under intense pressure. Likewise,
high inflation, and rising interest rates have made financing conditions very tight. It is

32. 22 | P a g e
forecasted that growth will slump further to about 3 percent in 2016 less than half of
what the country enjoyed between 2008 to 2013 (IMF, 2015; World Bank, 2016).
2.5.3. Zambian SME Constraints
This adverse macroeconomic environment has led to poor overall performance of Zambian
firms. Like SMEs in most developing countries, Zambian SMEs also face harsh conditions
for them to survive and mature into large scale enterprises. Among the top constraints
include access to finance, practices of informal sector and electricity shortages.
Figure 2-5: Ranking Constraints to SME growth in Zambia
Source: Enterprise Surveys of the World Bank (2013)
Because of the high Lending rates, recently hiked to a record 15.5% (BPR)3 in 2016,
difficult credit terms, only a small proportion of firms in Zambia are financed by banks
(BOZ, 2016). In addition to this, the World Bank Enterprise Survey, reveals a sharp
decline in the percentage of firms seeking financing from banks from 15% in 2007 to
3
Bank of Zambia Policy Rate

33. 23 | P a g e
9.9% in 2013 (Enterprise Surveys, 2013). Perhaps this is explained by the large number
of firms whose loan applications got rejected (see Figure 2-6).
Figure 2-6: Comparison of Zambian SME Loan Rejections
Source: Enterprise Survey of the World Bank (2013)
From Figure 2-6, Zambia tops the group in having the highest number of rejected loans for
SMEs at 34.1%. This figure is closely tailed by Sudan at 33.8%. The rest of the Sub-
Saharan African countries ranged between 10.2% and 28% of rejected loans.
2.5.4. Performance of SMEs in Zambia
Similarly, growth of firms in Zambia slowed as annual sales growth slumped to 11%
between 2010 and 2012, to 20% between the period 2005-2007. The performance of
Zambian firms has been below par compared to other SSA countries. In terms of
percentage of annual sales growth, Zambian firms grew at the least pace at 11.4% while
for the rest of Sub-Saharan countries, Sales growth ranged from 17.9% for Guinea-
Bissau, to 66.3% for Angola.

34. 24 | P a g e
Figure 2-7: Performance of Zambian SMES in Terms of Percentage Growth in Sales
Source: Enterprise Survey of the World Bank (2013)
In view of the above situation, the study reviewed the stock market to ascertain whether
firms were sourcing their funds from the capital markets or perhaps expanding and
listing there. Just like in many developing countries, the number of firms raising funds
through capital markets is very small compared to developed and emerging markets
(Kashyap and Stein, 1994). Mostly companies that manage to raise such finances are
usually large scale enterprises. However, many firms in Zambia have failed to expand
into large scale ones, and two thirds of the companies listed on the stock market were
originally state run enterprises with only few exceptions having graduated from SME
category into large scale enterprises.

35. 25 | P a g e
Figure 2-8: Trends for Number of Firms Listed on the Lusaka Stock Exchange
Source: World Bank (2016)4
From this graph, the number of listed companies in Zambia quickly shot up between
2000 and 2002 when they peaked at 30. However, the following years saw a sharp decline
to 10 companies in 2003. At 2014, the numbers improved to 20 listed companies
although this is still below the 2002 levels. Ironically, about two thirds of the listed firms
are former state owned parastatals with very few independent local firms making the list.
The rest are multinational firms.
4
The break in trends between 2016 and 2014 is as a result of unavailability of data.

36. 26 | P a g e
Table 2-1: Lusaka Stock Exchange Listed Companies
COMPANY LISTING DATES INDUSTRY5
1.Lafarge Zambia plc 22/05/1995 Manufacturing (g)
2.British American Tobacco (Z) Ltd 15/12/1995 Retail Trading (m)
3. Real Estate Investments Zambia Plc 28/08/1996 Property (m)
4. Zambia Sugar Plc 27/09/1996 Agriculture processing (g)
5. Zambian Breweries Plc 09/06/1997 Manufacturing (g)
6. National Breweries Plc 16/03/1998 Manufacturing (g)
7. Standard Chartered Bank Plc 30/11/1998 Banking (m)
8. ZCCM-Investment Holdings Plc 12/01/2000 Investments (g)
9. Taj Pamodzi Hotels Plc 24/12/2001 Hospitality (m)
10. Puma Energy (Z) Plc 18/06/2002 Oil Marketing (m)
11. Shoprite Holdings Plc 19/02/2003 Retail (m)
12. ZAMEFA Plc 08/09/2004 Manufacturing (g)
13. Zambeef Products Plc 05/04/2005 Agriculture Processing (l)
14. Cavmont Capital Holdings Plc 13/09/2006 Investments (l)
15. AEL Mining Services (Z) Plc 23/10/2006 Mining (m)
16. Investrust Bank Plc 18/06/2007 Banking (l)
17.Copperbelt Energy Corporation Plc 21/01/2008 Energy (l)
18. Airtel Networks Plc 11/06/2008 Mobile Telecommunication (m)
19. ZANACO plc 27/11/2008 Banking (g)
20. Zambia Bata Shoe Plc 31/03/2009 Manufacturing (m)
21. Prima Reinsurance Plc 30/08/2013 Insurance (l)
22. Madison Financial Services Plc 01/09/2014 Finance (l)
Source: Lusaka Stock Exchange (LUSE, 2016).
From this Table, it can be noted that the growth of the listed companies has been slow.
The table asserts the argument that very few SMEs grow to the extent of listing with only
about 27% of locally owned firms reaching this level. Former parastatals which were
privatised form a significant portion at 32% while the multinationals dominate at 41%.
5
The Firm ownership history is presented together with the industry where; (m) = Multinational, (g) = Formerly
State owned, (l) = Local

37. 27 | P a g e
Similarly, the percentage of firms in Zambia that export directly or indirectly, has
slumped slightly lower than six years ago. The Enterprise Survey (2013) reveals that,
exporting SMEs dropped from 15% in 2007 to 12% in 2012. And export sales decreased,
from 4% in 2007 to 2% in 2012. All these results seemingly reveal the characteristics
and the macroeconomic environment in which SMEs operate in Zambia.
2.6. Conclusion
A vast amount of literature including that of Levin (2006) emphasised the importance of
the macroeconomic environment in determining SMEs’ success. Sound financial policies
are a necessary part of this environment for accelerating economic growth and SME
development. Repressive financial policies such as credit rationing, high inflation, high
interest and high tax rates affect savings, asset returns and the allocation of credit.
Consequently, SMEs fail if they are subverted by poor policies which affect both their
operational costs and their ability to take up expansion opportunities (Mwenda & Mutoti,
2011).
The deteriorating performance of SMEs in Zambia raises concern over the kind of
macroeconomic environment in which they operate especially the financial policies. The
destitution of SMEs in accessing financial services is having a toll on their performance.
Unsurprisingly, access to credit is the most commonly reported obstacle by firms in
Zambia. As highlighted in this chapter, only a small number of firms raise their funds
from commercial banks. However, in order for them to mature or commercialise, they
require external finance hence the existing lending rate policies become imperative to
their growth and survival.
This chapter has presented the theoretical and conceptual background for the
dissertation. The chapter explored characteristics and nature of Small and Medium
Enterprises as well as determinants and constraints to their growth. Moreover, the

38. 28 | P a g e
relationship between interest rates, inflation and access to finance has been highlighted.
Using the transmission mechanism, the study highlighted how high interest rates impede
access to credit and consequently SME growth. An overview of SME macroeconomic
developments and performance in Zambia was reviewed. The next chapter presents the
tools and methodologies to be used in determining the extent to which lending rates affect
the performance of Small and Medium Enterprises (SMEs).

39. 29 | P a g e
CHAPTER 3 - METHODOLOGY
3.1. Introduction
This chapter explains the tools and methods used to collect, analyse and present the
data. As argued by Biggam (2011), the methodology is an important component of
research as it validates the research and provides a means for replicating or building on
the study by other researchers using the similar methods thereby authenticating the
research. The primary focus of this study is on the impact of Lending rates on SME growth
although the study also explores the role of Credit Granted and Electricity supply in
influencing that growth. Despite extensive literature emphasising the importance of
SMEs in economic growth, many developing countries still side-line SMEs in preference
for large scale enterprises. Hence, the chapter formulates and tests the hypotheses in
order to answer the research objectives.
It begins by a review of the objectives of this study and formulating the research
hypotheses. Thereafter the Chapter will outline the nature and sources of the data,
specify variables and the estimation method for this research. Finally, this chapter will
present the research limitations and a summary of the main points.
3.2. Objectives Review
In view of the purpose of the study, the following objectives were outlined: -
a) To ascertain the significance of Small and Medium Enterprises in stimulating
sustainable economic growth and development especially for developing countries like
Zambia.
b) To assess the impact of austerity measures namely contractionary fiscal and
monetary policies on the growth and expansion of SMEs.

40. 30 | P a g e
c) To identify ways of overcoming the challenges faced by SMEs and policy
implications for inclusive sustainable development for policy makers.
The contributions of this research work are primarily empirical although the findings to
be presented may provide the basis for better modelling of Financial Policies for SME
growth in the future.
3.3. Hypothesis Formulation
Based on neoclassical economic theories as well as empirical evidence for various
literature and given the above objectives, the study formulates the hypothesis to be tested
as below;
3.3.1. Hypothesis 1
Boivin, et al (2010) illustrates that monetary policy targeted at price stability has a muting
effect on economic activity. His findings reveal a correlation between policy interest rates
and economic activity. According to this view, an increase in money supply leads to a fall
in interest, capital outflow, depreciation and an increase in output. This is an ideal
situation for local SMEs to expand and increase their capacity and increasing exports as
the price of local goods become cheaper due to the low exchange rates. Given the lower
interest rates, SMEs are expected to have better access to finance needed for their growth.
On the other hand, contractionary monetary policy reduces money in circulation, raises
interest rates and reduces output. As such, SMEs are expected to have difficulties to
access finance, lower sales on international markets as their products becomes expensive
due to the appreciation of the exchange rates. Hence, hypothesis 1 is that high lending
rates will reduce Productivity (SME Growth). This is the primary objective that the study
tests.

41. 31 | P a g e
3.3.2. Hypothesis 2
As argued by Beck and Demirguc-Kunt (2006), access to credit plays an important role
in SME growth. Although Access to finance on its own depends on other factors, this
study views it in as a consequence of high lending rates. In this regard, it is observed
from the credit supply perspective. As discussed in Chapter 2.4.1, Contractionary
monetary policies reduce money in circulation, increase interest rates and reduce
aggregate demand. Due to the high policy rates on which commercial banks base their
lending decisions, the cost of lending increases. Large firms normally go unaffected by
these changes due to their bargaining power and the size of their transactions. Smaller
firms on the other hand bear the brunt. As the cost of bowing increases due to the high
lending rates, few SMEs are expected to access cred from banks. Hence, Credit Granted
by banks to SMEs presents an ideal way of measuring the indirect impact of high lending
rates on SME growth. Firms need credit for them to grow and expand. Hence by assessing
the productivity of firms when granted credit, the hypothesis will be tested. Hence, the
hypothesis is that SME productivity increases with credit granted.
3.3.3. Hypothesis 3
As highlighted in the empirical evidence in Chapter 1.2 & Chapter 2.3, the business
atmosphere in which firms operate plays a key role in determining their opportunities for
expansion. The combined financial policy environment and institutional infrastructure
ultimately determines the SMEs ability to enter the industry, grow or stagnate. In their
studies, Liedholm and Mead (1993) found that SME growth varies inversely with
aggregate levels of economic activity which itself is enhanced through proper
infrastructure such as the availability of efficient transport, communication and
electricity services among others. Thus, this study reiterates importance of electricity as
an explanatory variable to SME growth. Hence, the hypothesis is that Electricity Supply

42. 32 | P a g e
is positively correlated to Productivity, in testing this, the study expects to find lower SME
growth associated to low electricity availability and high SME growth associated with
periods of high electricity availability.
3.4. Nature and Sources of the Data
This dissertation uses secondary data from the Bank of Zambia (BOZ, 2015), Central
Statistical Office (CSO, 2015), Zambia Data Portal (ZDP, 2015). The approach is both
qualitative and quantitative and uses a desk review method of analysis. Secondary
research is ideal in this case due to the wealth of data gathered by Official institutions
which increases the reliability of the data. The Bank of Zambia (BOZ) publishes daily and
fortnight data on key financial indicators such as Lending rates, Credit Granted,
Exchange rates and many more and is thus the ideal source for collecting trends in the
study’s key variables. The Central Statistical Office (CSO) publishes quarterly data on
employment and economic statistics in Zambia while the Zambia Data Portal is a
comprehensive database for industrial productivity in Zambia as well as key economic
indicators. Hence, the later and former provided data on Electricity and manufacturing
productivity in Zambia. Thus, when considered in totality, all these sources provide a
wealth of information that is adequate to answer the objectives of this research.
To assess the relationship between Lending rates and SME growth, the study employs a
multiple linear regression model using ordinary least Squares (OLS). This method is
widely used in research to test for correlation between variables. Cross country
comparisons were done through trend analysis where trends among countries were
assessed to determine if there were variations. For this study, SME performance in
Zambia was compared with countries selected from Sub-Saharan Africa. This was in
order to control for the political and economic context of the countries, which is similar.
The time series data therefore measures changes in SME Productivity due to variations
in Lending Rates, Credit Granted and Electricity Supplied between the period 1996 to

43. 33 | P a g e
2015. To run regressions, the data was analysed using the statistical software STATA,
although any other software could be used and should yield similar results.
3.5. Estimation Model Specification
The research was conducted on SMEs in the manufacturing sector in Zambia and a
comparative analysis of other Sub-Saharan countries. The study employed multiple
regression analysis methods using Ordinary Least Squares (OLS) with time series data
from the Bank of Zambia, Central Statistics Office and Zambia Data Portal.
The aim of this dissertation is to examine the impact of lending rates on the growth of
small and medium enterprises and ascertain whether a causal relation possibly exists
between these variables. In this essence, the hypothesis to be tested is whether a negative
correlation exists between high lending rates and SME growth as measured by firm
productivity. Nonetheless, it is worth noting that there are many other factors that may
affect SME growth other than lending rates. Hence, additional variables must be included
in order to capture the multi-dimensional nature of SMEs growth and gauge the extent
of their influence on it. Although SME growth has been measured by other variables such
as employment, turnover, profitability and many others, this study adopts a single
dimensional measure using productivity as the indicator that epitomises SME Growth.
This measure has been chosen not only because of availability of data, but most
importantly to control for the effects of other variables that may affect SME growth that
are not captured.
From the previous chapters, the derived hypothesis assumes a direct connection between
lending rates and SME growth hence the need to control for size, age and ownership.

44. 34 | P a g e
3.6. Selection of Variables
The variables chosen the purposes of this research are presented in the following
sections.
3.6.1. Dependent Variable
The dependent variable is the variable which is impacted upon by the explanatory
variable. In other words, it is one which varies due to the influence of an independent
variable. For purposes of this study, SME Productivity has been selected to measure the
variation in SME Output caused by the independent variables.
3.6.1.1. Productivity
The dependent variable for this research is Firm Productivity also known as Output per
year. Productivity has been chosen amongst employment, turnover and profitability, to
depict SME growth due to the readily availability of the data as well as its high
responsiveness to changes in economic factors hence making it a great variable for this
study. Data for this variable has been collected from the Central Statistical Office (CSO)
and Zambia Data Portal (ZDP) on the manufacturing SMEs in Zambia per year. The
manufacturing sector has been chosen because it is the sector that receives the least
incentives and subsidies in Zambia hence controls for bias that may arise due to
government intervention policies.
The analysis focuses on how SME Productivity responds to changes in lending rates there
by providing the basis to determine the correlation. Although Productivity is measured in
tonnes, this has been adjusted to index form (1000) in order to make the data more
comparable to measures of other variables in this study. Therefore, SME Growth is
measured by the dependent variable growth in Productivity, and is explained by changes
Lending rates, Credit Granted to SMEs and Electricity supplied to firms.

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3.6.2. Explanatory Variables
The selected explanatory variables for the research model are Lending rates, Credit
Granted and Electricity availability. These have been chosen because they are the top
constraints that were reported in the Enterprise Surveys (2013) by Zambian
manufacturing firms. Therefore, it was cardinal to understanding exactly how they
influence SME growth.
3.6.2.1. Lending Rates
This is the primary explanatory variable whose impact the study seeks to invest. Lending
rates the interest rates that financial institutions charge to their SME clients as a cost of
borrowing and so presents a valuable measure in checking how it affects SME growth.
The Lending rates in this study are calculated as the average lending rates composed of
the BOZ Policy Rate plus the lending margin charged by the financial institutions per
year. This is because weighted lending rates omit the lending margin which, although
varies across financial institutions, is a key determinant to SMEs access to Credit as
illustrated in Interest Rate Theory 2.4. Although NBFIs, money lenders and other sources of
finance may have their own lending rate rates, this study focuses on commercial bank
lending rates which rely on the policy rates.
3.6.2.2. Credit Granted
Credit Granted refers to the amount of loans and other credit facilities granted to the
private sector per year. The rationale is to observe how monetary policies such as
increases in the policy rates and consequently the lending rates impact the amount of
Credit that commercial banks grant to firms. Demonstrating this relationship will
exemplify the robustness of the research model. This will moreover, examine the
assertions that SMEs seek other sources of funding as the cost of borrowing increases

46. 36 | P a g e
although this is from the supply side (see Chapter 2.3). Access to finance entails how
easy it is to access funding for expansion and growth among SMEs as they take advantage
of new opportunities.
3.6.2.3. Electricity Supplied
As outlined in Chapter 2, Zambia has been facing erratic electricity supply for the past
few years. Despite the demand for electricity surging both domestically and regionally,
the country has made little strides in increasing its electricity generation capacity. Hence,
this variable is intended to measure the economic impact of erratic electricity supply on
the productivity especially of SMEs which rarely afford to use other alternatives such as
mobile power generators and power banks. This ultimately affects the cost of production
hence productivity.
3.7. Estimation Method
This study primarily aims to examine the impact of Lending rates on the growth and
expansion of Small and Medium Enterprises in Zambia. The objective is to determine the
correlation between these variables. As noted by Varian (2010), a model’s power comes
from the elimination of irrelevant details thereby allowing the economist to concentrate
on the critical aspects of the economic reality they seek to understand. Thus the chosen
model demonstrates the relationship between the policy variables and SME growth in a
simplified way. Previous chapters have highlighted the variables to be used in the
regression model namely Productivity, Lending rates, Credit Granted and Electricity
availability. Hence, the econometric model to be used is as follows:
𝒚𝒊 = 𝜶 𝟎 + 𝜷 𝟏 𝒙𝑖 + ⋯ + 𝜷 𝒌 𝒙 𝒏 + 𝜺𝒊 (Equation 3-1)
Where;
𝒚𝒊 = Measures SME growth in terms of Sales

47. 37 | P a g e
𝜶 𝟎 = The intercept point at which the regression line crosses the 𝑦 𝑎𝑥𝑖𝑠
𝜷 𝟏 … 𝜷 𝒌= These are coefficient results from the regression using the software STATA
𝒙𝒊….. 𝒙 𝒏 = These are the variables to be estimated
𝜺𝒊 = This represents factors that may affect SME growth but are not included I the model.
The linearity of the variables is determined by the slope and intercept of the variables.
Regression analysis is commonly used to ascertain correlation between two or more
variables. Thus correlation exists if the variables exhibit linearity while the opposite
entails nor known relationship between the variables. Regression analysis therefore, tries
to establish this relationship in order to form grounds to accept or reject the null
hypothesis which assumes no relationship between variables. Fitting in the selected
variables into Equation 3-1, the regression model then becomes:
𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦𝑖 = 𝛼0 − 𝛽1 𝐿𝑒𝑛𝑑𝑖𝑛𝑔 𝑅𝑎𝑡𝑒𝑠𝑖 + 𝛽2 𝐶𝑟𝑒𝑑𝑖𝑡 𝐺𝑟𝑎𝑛𝑡𝑒𝑑𝑖 + 𝛽3 𝐸𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦𝑖 + 𝜀𝑖 (Eq. 3-2)
This Equation 3-2, states that SME productivity depends on the lending rates, Credit
granted and Electricity as well as other factors that have been captured by the error term
𝜀𝑖. The signage of the coefficients is important as they reveal the nature of the relationship.
In Equation 3-2, lending rates are negatively related to productivity while credit granted
and electricity are positively related to it. The null hypothesis would thus be:
𝑯 𝟎 = No relationship between the explanatory variables and Productivity.
𝑯 𝟏 = A correlation between at least one of the explanatory variables and
Productivity exists.
3.8. Limitations
Despite the data have been collected from reputable official sources, limitations exist to
its use. One limitation is that the definition of SMEs differs across countries regions and

48. 38 | P a g e
aspects. SMEs can be defined in terms of size, turnover, profitability and employment.
Hence the chosen aspect of defining an SME also determines the number of SMEs that
fall under that categorisation. Some firms in Zambian context could be large enterprises,
but when defined in international terms, they would fall into SMEs. Hence, for purposes
of this study, large Enterprise are those that have managed to penetrate international
markets. Thus, those that haven’t are still in their infancy and are thus considered as
SMEs. This is important in order to draw logical conclusion from the collected data as it
is not categorised into large or small enterprises.
Another is that the productivity data collected is the aggregate data collected for
manufacturing sector in Zambia and does not separately categorise small from larger
enterprises. This may lead to inaccuracies and generalisations in the results. However,
this limitation is eased by the study’s chosen definition of SMES, which ultimately places
majority of Zambian firms in the SME sector due to their capacity.
Similarly, credit granted by the commercial banks is the aggregate amount granted to the
private sector. The private sector definition does not separate small firms from large firms
thereby posing a similar challenge as the previous case. Furthermore, some of the data
collected was scanty or missing in some cases. In order to solve this problem, the mean
value and modes were used to fill the missing values.
3.9. Conclusion
This chapter highlighted the tools and methods used to collect and analyse the data. The
chapter elaborated on the sources and nature of the data to be used, the selected
variables and regression models as well as the hypotheses that have been deduced for
testing in the proceeding chapters. As observed by Levine (2006), many theoretical models
predict that a higher level of macroeconomic stability through appropriate financial
policies will induce a faster rate of economic growth, not just an increase in the level of

49. 39 | P a g e
economic development. It is hypothesized in this study that lower lending rates would
produce similar results. The challenge however is striking a balance between these two
objectives of attaining macroeconomic stability while at the same time promoting the local
private sector. The next chapter presents the results and discussion of the findings.

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CHAPTER 4 - RESULTS ANALYSIS AND DISCUSSION
4.1. Introduction
This chapter presents the results of the regressions outlined in the preceding chapter
with respect to impact of Lending rates on Small and Medium Enterprise growth. The
chapter also elaborates how these findings meet the research objectives as outlined in
Chapter 1. It begins by highlighting descriptive statistics on the nature of the data and
outlining key observations. Thereafter the empirical results of the impact of lending rates
and credit granted on SMEs growth as measured by the firm productivity variable will be
presented and discussed.
The research uses productivity macro level data spanning a 15 years’ period from 2000
to 2015 from the Bank of Zambia, Central Statistical Office and Enterprise Survey. As
stipulated earlier in Chapter 3, the econometric model includes three variables: Lending
Rates, Electricity and Credit Granted. The data covers a range of variables on
manufacturing firms in Zambia. To ensure a focused analysis, the study excludes small
scale and artisan mining, as well as primary agricultural companies.
The Chapter concludes by discussing the implications of these results and how they
answer the research objectives.
4.2. Descriptive Statistics
In attempting to answer the main research questions, the study ran a regression to test
the importance of Lending Rates in improving Small and Medium Enterprise growth by
controlling for the effects that may be caused by other variables highlighted earlier. In
order to accept or reject the null hypothesis, this study used significance levels of P <
0.01 and P < 0.05. According to Andren (2007), a P -Value reflects the likelihood that a

51. 41 | P a g e
given outcome occurred randomly. In this vain the lower the P-Value given the threshold
criteria, the more statistically significant the coefficient is in explaining variation.
As highlighted in the literature review, Lending rates are expected to have a negative effect
on the growth of SMEs because high Lending rates increase the cost of borrowing and
firms find it challenging to access credit and undertake expansionary investments to
increase productivity. Hence, if it is found in this analysis that higher Lending rates do
indeed reduce SME growth, as measured by their output and productivity, the
𝜷 𝟏 coefficient should be statistically significant and negative.
Table 2 below presents the summary statistics of the variables under investigation.
Table 4-1: Summary Statistics
Source: Author’s calculations6
The major variables in this model are Productivity and Lending rates. In this summary
in Table 4-1, the average productivity is 108.61 with an interval of 83.2 minimum
productivity and 140.6457 maximum productivity. The Mean lending rate7 was 41% for
the period under review with the minimum recorded Lending Rate of 25% and maximum
of 64.8%. Similarly, the average Electricity supplied or consumed per year ranged
between 76.2 and 144.08 with a mean of 107.76; while Credit Granted ranged
between17.06 and 46.61 with a mean value of 30.76 each year.
6
Note that Productivity is in index format (1000) and calculations relate to the manufacturing sector only
7
Lending Rates are the Average Lending Rates i.e. (Weighted Lending Base Rate + Lending Margin)
CreditGran~d 15 30.76104 9.453956 17.05696 46.60998
Electricity 15 107.7583 20.20856 76.2 144.0796
LendingRates 15 41.65333 12.98531 25 64.8
Productivity 15 108.6123 18.21915 83.2 140.6457
Variable Obs Mean Std. Dev. Min Max
. summarize Productivity LendingRates Electricity CreditGranted

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Based on the regression model established in Chapter 2, Productivity is a function of
Lending Rates (LR), Credit Granted (CG), and Electricity. This is a linear regression model
and is commonly used in research to establish whether a causal relationship exists
among the underlying variables. Furthermore, this model also reveals a correlation
between the variables. Figure 3 shows the linear correlations between productivity and
each of the explanatory variables: Lending rates, Credit Granted and Electricity.
Table 4-2: Graphical Representation of the Correlation among the Variables
Source: Authors’ computations, output from regression
Table 4-2 shows the negative correlation between lending rates and productivity. Figure 4-1
goes on to detail this relationship and it can be noted that the relationship between
lending rates and firm productivity is almost perfectly symmetrical. As lending rates
reduce, firm productivity increases proportionately. A fascinating point to note is how
80.00
100.00120.00140.00
Productivity
80.00 100.00 120.00 140.00
Electricity
80.00
100.00120.00140.00
Productivity
10.00 20.00 30.00 40.00 50.00
Credit Granted
10.0020.0030.0040.0050.00
CreditGranted
20.00 30.00 40.00 50.00 60.00 70.00
Lending Rates
80.00
100.00120.00140.00
Productivity
20.00 30.00 40.00 50.00 60.00 70.00
Lending Rates

53. 43 | P a g e
well the lending rates effectively influence productivity with periods of low lending rates
corresponding to high productivity such as 2005 and 2006, 2012, 2014, 2015 and 2016.
Figure 4-1: Lending rates and Firm Productivity
Source: Authors’ computations based on Zambia Data Portal and BOZ
Figure 4-2 on the other hand shows a positive relationship between productivity and
electricity as well as credit granted. This result affirms the access to finance literature
that emphasise the role of credit in promoting SME growth and expansion. From the
graph, firm productivity increased proportionately to the increase in credit granted to
firms by banks. Furthermore, electricity also played a significant role in increasing
productivity will periods of increase electricity consumption correlating with periods of
high productivity.
0.00
50.00
100.00
150.00
200.00
0 2 4 6 8 10 12 14 16 18
Relationship between Lending Rates and SME
Productivity
Productivity Lending Rates

54. 44 | P a g e
Figure 4-2: Productivity and Credit Granted
Source: Authors’ computations based on data from Zambia Data Portal and BOZ
After running a multiple regression of the impact of lending rates and other explanatory
variables on SME productivity, Table 3 presents the results.
Table 4-3: Regression Results
Source: Output from Author’s Calculations using STATA
0.00
20.00
40.00
60.00
80.00
100.00
120.00
140.00
160.00
0 2 4 6 8 10 12 14 16
Total Manufacturing Credit Granted
_cons 64.67494 14.01411 4.61 0.001 33.8301 95.51978
CreditGranted .8683522 .2422789 3.58 0.004 .3350998 1.401605
Electricity .3047864 .1177559 2.59 0.025 .0456074 .5639653
LendingRates -.3749356 .1385824 -2.71 0.020 -.6799534 -.0699178
Productivity Coef. Std. Err. t P>|t| [95% Conf. Interval]
Total 4647.1263 14 331.937593 Root MSE = 4.3735
Adj R-squared = 0.9424
Residual 210.402208 11 19.1274735 R-squared = 0.9547
Model 4436.72409 3 1478.90803 Prob > F = 0.0000
F( 3, 11) = 77.32
Source SS df MS Number of obs = 15
. regress Productivity LendingRates Electricity CreditGranted

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The resulting estimates suggest that the independent variables lending rates, credit
granted, and electricity have a profound impact of productivity of SMEs. The results
further assert the negative effect of lending rates and corruption on SMEs productivity.
From this analysis, Lending rates have a significant negative correlation with productivity
at 5% significance level, therefore the null hypothesis is rejected at the same significance
level. The lending rate coefficient of -0.3749 entails that a 1% increase in lending rates
causes productivity to reduce by approximately 37% and vice versa.
Additionally, Electricity as was anticipated, also showed a strong positive correlation with
productivity at 5% significance level, therefore the null hypothesis is rejected at the same
significance level. Its positive coefficient of 0.304 entails that a 1% fall in electricity supply
to firms culminates into approximately a 30% fall in firm productivity and vice versa. This
supports the assertions of erratic electricity supply as affecting growth in Zambia as
observed by the IMF (2015) mission.
Similarly, Credit Granted to firms by banks has a significant positive correlation with
productivity at 1% significance level and the null hypothesis is thus rejected at the same
level. The positive coefficient of 0.868 implies that a 1% increase in credit granted
increases firm productivity by approximately 86%. Moreover, the R-Squared produced a
good result. Otherwise known as the coefficient of determination, the R-Squared indicates
the proportion of the dependent variable, in this case productivity, that is explained by
the independent variables. In this regard, the R-Squared demonstrates how well the
regression model used in the research fits the data points. The chosen model gave an R-
Squared of 0.9547 and adjusted R-Squared of 0.9424. This entails that about 95.47% of
the variations in SME productivity is explained by the independent variables of this
chosen regression model. This demonstrates the strength of the chosen model.
Accordingly, the regression model thus becomes:

56. 46 | P a g e
𝒚𝑖 = 𝟔𝟒. 𝟔𝟕𝟒𝟗𝟒 − 𝟎. 𝟑𝟕𝟒𝟗𝟑𝟓𝟔𝑳𝑹𝑖 + 𝟎. 𝟑𝟎𝟒𝟕𝟖𝟔𝟒𝑬𝑳𝑖 + 𝟎. 𝟖𝟔𝟖𝟑𝟓𝟐𝟐𝑪𝑮𝑖 + 𝜺𝒊 (Equation 4-1)
Where y is productivity, 𝑳𝑹𝑖 is Lending Rates, 𝑬𝑳𝑖 is Electricity supplied and 𝑪𝑮𝑖 is Credit
Granted and εi is the error term. These empirical studies support research findings by
other scholars have emphasised the importance of access to finance and the
macroeconomic environment in which SMEs operate in supporting their growth
(Ayyagari, et al., 2011; Beck, 2007; Beck & Demirguc-Kunt, 2006). Furthermore, as
highlighted in the (Enterprise Surveys, 2013), among the major growth constraints faced
by SMEs, access to finance and electricity, ranked on top of the others. These results
empirically prove the causal link between lending rates, credit granted and firm
productivity. They also suggest a strong correlation between electricity usage with firm
productivity and growth. In summary, the regression results have presented strong
grounds to reject the null hypothesis and emphatically suggest a high probability of a
causal relationship between lending rates, credit granted, electricity supply and SME
growth in Zambia.
4.3. Discussion and Interpretation of the Results
As affirmed by the extensive literature in Chapter 2, Small and Medium Enterprises are
mostly influenced by factors in the macroeconomic environment in which they operate.
From infrastructure to deliberate policies, all these have a bearing on the performance of
firms, their success or failure. This study has revealed the excruciating impact that
lending rates have on firm growth and consequently that of the overall economy.
Studies by Beck et al (2007) and Ayaggari et al (2006) emphasised the importance of
access to finance on SME growth. Mankiw (2016) presented interest rates theories that
showed the transmission effect of interest rates on overall economic activity especially
with regard to investment expenditures. Thus the negative effect of lending rates on SME

57. 47 | P a g e
productivity as evidenced by this study agrees with existing empirical research on SME
growth especially with regards to the role of credit. This is because credit granted is also
negatively related to lending rates. Figure 4-3 highlights this relationship.
Figure 4-3: Lending Rates and Credit Granted
Source: Author’s computations8 based on data from BOZ.
The African Development Bank, World Bank and many other development institutions
have realised the importance of the macroeconomic environment especially policies and
access to finance in supporting SME growth. Hence, they are now more concerned with
policy support interventions and strengthening institutions that promote SME growth.
Moreover, the IMF (2015) in their mission report on Zambia noted that erratic electricity
supply was adversely affecting overall growth. In fact, erratic electricity supply is one of
the major factors that was sighted as a probable cause of Zambia’s poor economic
performance between 2011 to 2015 and will likely continue to be so for the 2016 – 2017
8
Note that the Credit granted is in millions (‘000,000) of Zambian Kwacha
0
10
20
30
40
50
60
70
0 2 4 6 8 10 12 14 16
Credit grants vs Lending Rates
Lending Rates Credit Granted

58. 48 | P a g e
economic outlook. The findings of this study are in line with these observations as they
showed the positive effect of electricity supply or usage with overall firm productivity.
4.4. Inferences from these Findings
Of all the above scenarios, the main objective that lending rates affect the growth of Small
and Medium Enterprises holds. Lending rates have also been proved to have a negative
effect on the credit granted by financial institutions. As lending rates decreased, the
amount of credit granted by financial institutions increased (see Figure 8). This is
probably because as lending rates increase, fewer people approach Banks for credit due
to the increased cost of borrowing. However, this argument would hold more strongly if
firms’ borrowings from non-bank financial institution and other sources of funding
increased during the same period, which is beyond the scope of this study. Access to
finance literature by Beck el al. (2008) reveals that very few SMEs actually borrow from
commercial banks and formal financial institutions. The results in this study reveal more
credit being granted to SMEs when lending rates are lower than when they are higher
presents a sensible case.
4.5. Lending Rates Across Countries
In ascertaining how lending rates in Zambia fare compared to other countries, Figure 9
presents the answer to this objective.

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Figure 4-4: Lending Rates Across Countries
Source: Author’s Calculations using data from Enterprise Survey 2013
From Figure 4-4, a comparison of the trends in average lending rates across developed,
emerging and developing countries between 1996 to 2015 is presented. From this graph,
an appalling revelation emerges. Rich countries have the lowest lending rates compared
to the rest of the world with the United Kingdom leading at 0.5% for the countries under
review. Similarly, emerging countries of India, China, Mexico also exhibited lower lending
rates compared to poorer ones in Sub-Saharan Africa. Middle income countries which
include Botswana, Namibia and South Africa also showed low interest rates compared to
low income countries. In the last segment, developing countries in Sub-Saharan Africa
showed the highest lending rates of over 90% to18% for Angola, 28% to 17% in Kenya,
19% to 22% for Uganda and 42% to 15% in Zambia for the period under review. Thus, of
all the countries under review, Zambia, Uganda and Angola revealed the highest lending
rates.
0.00
20.00
40.00
60.00
80.00
100.00
120.00
Comparison of average Lending Rates across selected countries
1996 - 2001 2002 - 2007 2008 - 2012 2013 - 2015

60. 50 | P a g e
4.6. Lending Rates and Investment Expenditure
The third objective that this dissertation sort to investigate is whether lowering the
lending rates improves SME expansion through increased investments in capital and
machinery. The study compared performance of SMEs across emerging and developing
countries on Sales Growth, Investment Growth and employment growth for the 2010 –
2015 period with the lending rates data from figure 10. The Firms’ performance is
highlighted in Figure 7 below.
Figure 4-5: SME Performance
Source:
SME
Finance Forum Database
By comparing the rates for both figure 6 and 7, both emerging and developing countries
showed increased investment growth during the period 2007 to 2013. Chile and
Botswana showed higher investment expenditure at around 76.2% for Chile and 67.7%
for Botswana and both had low interest rates during this period of between 4% to 9% for
both. Similarly, Zambia (34.6%) had more investment growth than Philippines (28.7%)
and India (24.9%), and just about the same growth with Mexico (35%) although these
countries had much lower lending rates than Zambia during the same period. Same
applies to Kenya (43.8%) and Tanzania (40%) while Uganda and Nigeria had lower
-40
-20
0
20
40
60
80
100
Chile
India
China
Philipines
Mexico
Vietnam
Botswana
SouthAfrica
Tanzania
Kenya
Uganda
Angola
Nigeria
Zambia
2010 2014 2012 2015 2010 2015 2010 2007 2013 2013 2013 2013 2014 2013
SME Performance across countries
Sales growth Investment Growth Employment Growth

61. 51 | P a g e
investment growth. These results are peculiar and show lack of correlation and provide
an interesting area for future research. Therefore, these results are inconclusive.
4.7. Conclusion
This chapter has presented the analysis and findings of the study using both the
regression and trend analysis. Using data from the Zambia Data Portal on manufacturing
firms in Zambia, the regression results revealed a significant impact of lending rates on
access to credit and SME productivity. Furthermore, electricity was also found to
positively impact firm productivity. The main findings are consistent with the existing
literature on the topic as highlighted in Chapter 2. Most assumptions of the research
have been substantiated thereby indicating the suitability of the chosen model for the
analysis. In so doing, this Chapter has adequately addressed the three main objectives
the research set out in Chapter 1.
Notwithstanding thereof, the results also revealed some baffling, counter-intuitive
findings which do not seem to fit with the existing literature. Perhaps the foreseen data
limitations and scope of the study could have warranted such results and affected the
definiteness of the model. However, these noted nonconformities do indeed present an
interesting case for future investigations.

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CHAPTER 5 - CONCLUSION AND POLICY IMPLICATIONS
This chapter concludes the study by summarizing the objectives, main conclusions as
well as policy implications of the results. The chapter also addresses the limitations of
the research and areas of future research. In linking theory and research, this study
submits a compelling case that developing countries’ policy makers should consider when
aiming for overall macroeconomic targets. In so doing, the fate of the Small and Medium
Enterprises which are the building blocks of the economy can be safeguarded.
5.1. Summary
This dissertation set out to investigate the impact of lending rates on the growth of small
and medium enterprises. The research contributes to existing empirical knowledge on
SME growth and the broader impact of financial policies on other sectors of the economy
than the originally intended targets. Small and medium enterprises have been identified
as engines of growth and building blocks of the bigger economy. However, the
macroeconomic policies implemented by policy makers especially those of increasing
lending rates to tackle inflation and possibly attract foreign capital have had detrimental
effects on the growth of the small and medium enterprise industry in Zambia. This has
negatively affected their ability to access credit as it raised the cost of borrowing. The
situation has been exacerbated by the erratic supply of electricity which has been the
norm in Zambia due to the main hydro power generation corporations operating below
capacity thereby failing to consistently supply energy to the productive sector, of which
the Small and Medium Enterprises require a good deal of it.
An extensive wealth of literature and empirical research has emerged on SMEs especially
with regards to constraints to their growth as well as their contributions to the economy.
In many developing countries development agenda, Small and Medium enterprise had
initially been side-lined in the development with more preference given to Large Scale

63. 53 | P a g e
multinational companies and state back agricultural industries. As a result, this created
a gap in the processing and other small scale manufacturing industries to link the two
industries. Although small and medium enterprises have continued to exist for some
time, the lack of deliberate policy support to see them grow and expand into large scale
multinational industries had been a case of great concern.
In this disposition the study sought to examine three objectives. Firstly, it examined the
impact of Lending rates on SME Productivity and how this influences their Access to
finance and consequently their growth. The second objective was to determine how
lending rates in Zambia fare among similar other countries around the world. This sought
to establish the performance of firms in countries with low rates compared to those with
high interest rates. Thirdly, the study examined cases to ascertain whether countries
with lower lending rates saw increased expenditure on investment expenditure on capital
and machinery.
This study used the Ministry of Commerce’s definition of SMEs in order to categorise
enterprises in terms expansion and commercialisation. Using data from the Bank of
Zambia, Central Statistical Office and Zambia Data portal as well as World Bank on the
manufacturing industry, trends in lending rates and productivity have been established
and presented. Additionally, a selection of a range of variables based on extensive
literature review of SME growth and its underlying factors. As observed by the Enterprise
Survey (2015), the significant ones were Electricity, Access to finance, activities of the
informal sector, Tax rates and Tax administration.
5.2. Research Conclusions and Limitations of the Findings
The findings from the empirical analysis endorse the hypothesis that high lending rates
have a negative effect on SME growth. Likewise, Electricity supply has also been proved
to have a profound effect of firm productivity in Zambia with high output and productivity

64. 54 | P a g e
being associated with high electricity usage or availability. The assumption that lending
rates influence the ability access credit have also been confirmed.
Hence from this dissertation several conclusions can be drawn. The impact of lending
rates on SME growth was estimated using the regression model as the expected variation
in firm Productivity given a change in lending rates. Despite significant and conclusive
results from the regression model, the scanty nature of the data as well as indices used
may have limited the accuracy of the conclusions, although the assumed errors are not
expected to significantly alter the findings.
From the results, it has been revealed that the determinants of SME growth also
interrelate with each other, as was the case with lending rates influencing the mount of
credit granted. It may therefore be assumed or deduced that lending rates also be
interrelated with many of the other factors that affect SME growth. This study has
nonetheless proved the overall assumptions on lending rates and their impact on the
growth of SMEs and thus contributes to existing literature on the subject.
5.3. Policy Implications
Ever since the Structural Adjustment era of the early 1990s, the economic disposition of
Zambia has always favoured large scale foreign businesses over Small and Medium
Enterprises (see Chapter 1 and 2). Even today, the current industrial policies are tailored
towards attracting foreign investment and large companies with little policy direction
deliberately targeted at SMEs. As such, the domestic industrial base propelled by these
SMEs has tremendously suffered. The country now has a missing manufacturing and
processing base to support the primary industries, whose output is supposed to feed into
the large scale industries as inputs. From having a strong industrial base under the
deliberate import substitution policies of the 1960s to the 1990s, Zambia today depends
on imports even for basic everyday commodities.