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
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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.
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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.
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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 ------------------------------------------------------------ 10
2.2.3. SMEs and Growth: Empirical Evidence ------------------------------------ 11
2.3. What Determines SME Growth --------------------------------------------------- 13
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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 ------------------------------------------------------------------ 21
2.5.1. Background --------------------------------------------------------------------- 21
2.5.2. Recent Developments --------------------------------------------------------- 21
2.5.3. Zambian SME Constraints --------------------------------------------------- 22
2.5.4. Performance of SMEs in Zambia -------------------------------------------- 24
2.6. Conclusion --------------------------------------------------------------------------- 28
CHAPTER 3 - METHODOLOGY ------------------------------------------------------------ 30
3.1. Introduction ------------------------------------------------------------------------- 30
3.2. Objectives Review ------------------------------------------------------------------- 30
3.3. Hypothesis Formulation ----------------------------------------------------------- 31
3.3.1. Hypothesis 1 -------------------------------------------------------------------- 31
3.3.2. Hypothesis 2 -------------------------------------------------------------------- 32
3.3.3. Hypothesis 3 -------------------------------------------------------------------- 32
3.4. Nature and Sources of the Data -------------------------------------------------- 33
3.5. Estimation Model Specification --------------------------------------------------- 34
3.6. Selection of Variables -------------------------------------------------------------- 35
3.6.1. Dependent Variable ----------------------------------------------------------- 35
3.6.2. Explanatory Variables -------------------------------------------------------- 36
3.7. Estimation Method ----------------------------------------------------------------- 37
3.8. Limitations --------------------------------------------------------------------------- 39
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3.9. Conclusion --------------------------------------------------------------------------- 40
CHAPTER 4 - RESULTS ANALYSIS AND DISCUSSION --------------------------------- 41
4.1. Introduction ------------------------------------------------------------------------- 41
4.2. Descriptive Statistics --------------------------------------------------------------- 41
4.3. Discussion and Interpretation of the Results ---------------------------------- 47
4.4. Inferences from these Findings --------------------------------------------------- 49
4.5. Lending Rates Across Countries -------------------------------------------------- 49
4.6. Lending Rates and Investment Expenditure ------------------------------------ 51
4.7. Conclusion --------------------------------------------------------------------------- 52
CHAPTER 5 - CONCLUSION AND POLICY IMPLICATIONS ---------------------------- 53
5.1. Summary ---------------------------------------------------------------------------- 53
5.2. Research Conclusions and Limitations of the Findings ----------------------- 55
5.3. Policy Implications------------------------------------------------------------------ 55
5.4. Areas for Further Research ------------------------------------------------------- 57
Bibliography ----------------------------------------------------------------------------------- 59
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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 --------------------------- 23
Figure 2-6: Comparison of Zambian SME Loan Rejections --------------------------- 24
Figure 2-7: Performance of Zambian SMES in Terms of Percentage Growth in Sales
-------------------------------------------------------------------------------------------- 25
Figure 2-8: Number of firms listed on the Lusaka Stock Exchange ------------------ 26
Figure 4-1: Lending rates and Firm Productivity --------------------------------------- 44
Figure 4-2: Productivity and Credit Granted -------------------------------------------- 45
Figure 4-3: Lending Rates and Credit Granted ----------------------------------------- 48
Figure 4-4: Lending Rates Across Countries -------------------------------------------- 50
Figure 4-5: SME Performance ------------------------------------------------------------- 51
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LIST OF TABLES
Table 2-1: Lusaka Stock Exchange Listed Companies --------------------------------- 27
Table 4-1: Summary Statistics------------------------------------------------------------ 42
Table 4-2: Graphical Representation of the Correlation among the Variables ------ 43
Table 4-3: Regression Results ------------------------------------------------------------- 45
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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
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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
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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,
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2007). To this end, many international development institutions have identified SMEs
as 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
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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, 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
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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?
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.
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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.
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
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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 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
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and determinants of SME growth. Thereafter, a detailed study of the relationship
between Lending rates and 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.
1 Most SMEs especially in developing countries operate on a thin line between the formal and informal sectors
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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 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)
From
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Figure 2-1, it can be seen 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 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
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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).
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
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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 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
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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
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.
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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 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
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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 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
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especially on SMEs that rely to a large extent on bank lending for larger capital needs.
Figure 2-3 shows this transmission effect.
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
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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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
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.
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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 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
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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 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).
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
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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
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
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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 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.
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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 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).
3 Bank of Zambia Policy Rate
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Figure 2-6: Comparison of Zambian SME Loan Rejections
Source: Enterprise Survey of the World Bank (2013)
From
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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.
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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.
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Figure 2-8: Trends for Number of Firms Listed on the Lusaka Stock Exchange
Source: World Bank (2016)4
As can be observed from
Figure 2-8, the number of listed companies 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.
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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)
5 The Firm ownership history is presented together with the industry where; (m) = Multinational, (g) = Formerly State owned, (l) = Local
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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 2-1, 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%. 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
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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
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).
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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.
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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.
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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
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electricity as an explanatory variable to SME growth. Hence, the hypothesis is that
Electricity Supply 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
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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 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.
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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.
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
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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.
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.
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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
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.
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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 = 𝜶𝟎 + 𝜷𝟏𝒙𝑖 + ⋯ + 𝜷𝒌𝒙𝒏 + 𝜺𝒊 (Equation 3-1)
Where;
𝒚𝒊 = Measures SME growth in terms of Sales
𝜶𝟎 = The intercept point at which the regression line crosses the 𝑦 𝑎𝑥𝑖𝑠
𝜷𝟏 … 𝜷𝒌= These are coefficient results from the regression using the software STATA
𝒙𝒊….. 𝒙𝒏 = 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 − 𝛽1𝐿𝑒𝑛𝑑𝑖𝑛𝑔 𝑅𝑎𝑡𝑒𝑠𝑖 + 𝛽2𝐶𝑟𝑒𝑑𝑖𝑡 𝐺𝑟𝑎𝑛𝑡𝑒𝑑𝑖 + 𝛽3𝐸𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦𝑖 + 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
40 | P a g e
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:
𝑯𝟎 = No relationship between the explanatory variables and Productivity.
𝑯𝟏 = 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 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.
41 | P a g e
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 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.
42 | P a g e
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
43 | P a g e
levels of P < 0.01 and P < 0.05. According to Andren (2007), a P -Value reflects the
likelihood that a 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 𝜷𝟏 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
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
44 | P a g e
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.
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
80
.00
10
0.0
012
0.0
014
0.0
0
Pro
ductivity
80.00 100.00 120.00 140.00Electricity
80
.00
10
0.0
012
0.0
014
0.0
0
Pro
ductivity
10.00 20.00 30.00 40.00 50.00Credit Granted
10
.00
20
.00
30
.00
40
.00
50
.00
Cre
dit G
rante
d
20.00 30.00 40.00 50.00 60.00 70.00Lending Rates
80
.00
10
0.0
012
0.0
014
0.0
0
Pro
ductivity
20.00 30.00 40.00 50.00 60.00 70.00Lending Rates
45 | P a g e
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
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
46 | 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
0.00
20.00
40.00
60.00
80.00
100.00
120.00
140.00
160.00
0 2 4 6 8 1 0 1 2 1 4 1 6
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
47 | P a g e
Source: Output from Author’s Calculations using STATA
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.
48 | P a g e
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:
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.
49 | P a g e
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 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
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
50 | P a g e
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 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.
51 | P a g e
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
52 | 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
-40
-20
0
20
40
60
80
100
Ch
ile
Ind
ia
Ch
ina
Ph
ilip
ines
Mex
ico
Vie
tnam
Bo
tsw
ana
Sou
th A
fric
a
Tan
zan
ia
Ken
ya
Uga
nd
a
An
gola
Nig
eria
Zam
bia
2010 2014 2012 2015 2010 2015 2010 2007 2013 2013 2013 2013 2014 2013
SME Performance across countries
Sales growth Investment Growth Employment Growth
53 | P a g e
and Nigeria had lower 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.
54 | P a g e
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
55 | P a g e
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 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.
56 | P a g e
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 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
57 | P a g e
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.
Important implications can be drawn from these findings. In undertaking
stabilisation measures such as curbing inflation, exchange rate volatility as well as
regulating the growth of money supply in the economy, policy makers should examine
the impact of such policies in totality especially with regards to the impacts on the
smaller but significant players in the economy such as SMEs. As has been revealed,
policies that affect these players eventually affect the entire economy (Mbao, et al.,
2014). A logical inference for policy making purposes is that financial policies and
conditions need to be adjusted and transformed to suit the industrial base and its
needs in Zambia.
The low growth of the SME sector has been attributed to a number of factors but
access to credit which is hampered by high lending rates as well as erratic electricity
supply has had profound impacts. Although policy makers have been preaching
economic diversification, this cannot be achieved without the full participation of
Small and Medium Enterprises, hence reiterating the need for financial and economic
policies that directly aim to boost their growth. Business incubation programmes, as
are common in East Africa, Financial management training and international trading
literacy program supported by policy makers could go a long way in creating capacity
and exploring cross border opportunities (Mbao, et al., 2014). Likewise, state backed
credit guarantee schemes could help SMEs acquire machinery and equipment for
their production needs.
58 | P a g e
Furthermore, in order attract large enterprises, the country needs to have a vibrant
SME sector that produces products that feed into these corporations otherwise it
would not be a viable investment destination. Deliberate policies such as lower
borrowing costs, tax holidays and other incentives, Multi-facility Economic Zones
could be extended to the SME sector as well to make it more competitive and enable
them to acquire the necessary capital and equipment to boost their output. Providing
a conducive infrastructural environment especially in terms of improving electricity
supply and transport systems would further provide multiplier effects of productivity.
One of the strategies the Asian tigers implemented to surpass emerging African
Countries in the 1970s was that while African nations including Zambia were
abandoning the import substitution policies through privatisation, Asian Tigers
continued with them and sourced foreign capital which boosted their manufacturing
base. Because of this large manufacturing base, they are the favourites to attract
large scale production companies. African countries thus have to invest in their local
manufacturing base and industries if they are to attain meaningful development.
5.4. Areas for Further Research
Although this dissertation has addressed the lending rates impact on SME growth, a
number of areas in the study of SMEs still require further exploring. The study
explored lending rates on SME growth in the context of formal borrowing. However,
most SMEs source their financing from the informal sources such as family, friends
and money lenders and Non-Bank Financial institutions most of whom have different
ways of determining their lending rates. Hence, further research in this direction to
understand how they determine their rates, and to examine whether adverse
conditions of the formal financial institutions cause more SMEs to approach the
informal sources of finance would be an interesting undertaking.
59 | P a g e
Furthermore, it would be stimulating to undertake an investigation into actual use
of the financing that SMEs acquire from formal financial institutions to ascertain
whether a policy could be instigated to ease their operations.
60 | P a g e
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