i AMAGWU, IBEAWUCHI FRANCIS PG/Ph.D/10/54559 EFFECTIVENESS OF MICROFINANCE SOURCES ON THE PROFITABILITY OF ENTERPRISE CLUSTERS IN SOUTH EAST, NIGERIA ENVIRONMENTAL STUDIES INSTITUTE FOR DEVELOPMENT STUDIES (IDS) Paul Okeke Digitally Signed by: Content manager’s Name DN : CN = Webmaster’s name O= University of Nigeria, Nsukka
157
Embed
EFFECTIVENESS OF MICROFINANCE SOURCES …€¦ · 1.4 Research Questions ... Using multiple regression technique and ... determinants of the choice of microfinance source used by
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
i
AMAGWU, IBEAWUCHI FRANCIS
PG/Ph.D/10/54559
EFFECTIVENESS OF MICROFINANCE SOURCES ON THE PROFITABILITY OF ENTERPRISE CLUSTERS IN
SOUTH EAST, NIGERIA
ENVIRONMENTAL STUDIES
INSTITUTE FOR DEVELOPMENT STUDIES (IDS)
Paul Okeke
Digitally Signed by: Content manager’s
Name
DN : CN = Webmaster’s name
O= University of Nigeria, Nsukka
ii
EFFECTIVENESS OF MICROFINANCE SOURCES ON THE PROFITABILITY OF ENTERPRISE CLUSTERS IN
SOUTH EAST, NIGERIA
BY
AMAGWU, IBEAWUCHI FRANCIS PG/Ph.D/10/54559
INSTITUTE FOR DEVELOPMENT STUDIES (IDS), UNIVERSITY OF NIGERIA,
ENUGU CAMPUS, ENUGU, NIGERIA
JULY 2015
iii
TITLE PAGE
EFFECTIVENESS OF MICROFINANCE SOURCES ON THE PROFIT ABILITY OF ENTERPRISE CLUSTERS IN SOUTH EAST, NIGERIA
BY
AMAGWU, IBEAWUCHI FRANCIS PG/Ph.D/10/54559
BEING A THESIS SUBMITTED IN PARTIAL FULFILMENT OF T HE REQUIREMENTS FOR THE AWARD OF PhD IN DEVELOPMENT ST UDIES
INSTITUTE FOR DEVELOPMENT STUDIES (IDS), UNIVERSITY OF NIGERIA,
ENUGU CAMPUS, ENUGU, NIGERIA
JULY 2015
iv
CERTIFICATION
Amagwu, Ibeawuchi Francis; a postgraduate student of the Institute for Development Studies
has satisfactorily completed the requirements for the award of Doctor of Philosophy (Ph.D.)
Degree in Development Studies. The work embodied in this thesis is original and has not
been submitted in part or full for any Diploma, or degree of this or any other university.
2.5 Summary of the Review of Related Literature.… … … … … 60
CHAPTER THREE: RESEARCH METHODOLOGY
3.1 Introduction … … … … … … … … 64
3.2 Design of the Study … … … … … … … … 64
3.3 Data and Sources … … … … … … … … 64
3.4 Population of the Study … … … … … … … 55
ix
3.5 Tools for Data Collection … … … … … … … 55
3.6 Determination of Sample size … … … … … … … 57
3.7 Validity of the Research Instrument … … … … … … 68
3.8 Reliability of the research … … … … … … … 68
3.9 Method of Data Analysis … … … … … … … 68
3.10 Theoretical Framework … … … … … … … 69
3.11 Models Specification, Methods of Data Analysis and Results Evaluation … 70
3.12 Assessment of Level of Support of Microfinance Providers for the Sustenance of Profitability of Enterprise Clutters in South-East, Nigeria (Objective 4) 78
CHAPTER FOUR: DATA PRESENTATIONS AND ANALYSIS
4.2 Introduction … … … … … … … … … 79 4.2 General Enterprise Characteristics and Perceptions … … … … 79 4.3 Microfinance Sources and Enterprise Profitability/Objectives 1&2 (Models 1, 2a & 2b) 83 4.4: Determinants of the choice of the microfinance Source by Enterprise clusters in South East of Nigeria (Objective 3 and Model3) 88 4.5 Assessing the level of support of Micro Finance providers for the Sustenance of profitability of Enterprise - Objective Four… … … 92 4.6 Test Of Hypotheses … … … … … … … … 84 4.7 Discussion of Findings … … … … … … … 98
CHAPTER FIVE: SUMMARY OF FINDINGS, CONCLUSION AND
RECOMMENDATIONS
5.1 Summary of Findings … … … … … … … … 105 5.2 Policy Implication of Findings … … … … … … … 106 5.3 Policy Recommendation … … … … … … … … 107 5.4 Contribution of this study to Knowledge on the Subject matter … … … 108 5.5 Suggestion for Further Research … … … … … … … 110 5.6 Conclusion … … … … … … … … … … … 110
References … … … … … … … … … … … 112
Appendix … … … … … … … … … … … 120
x
LIST OF TABLES
Table 2.1: Cross-Country approaches to defining SMEs 17
Table 2.2: Different classification of MSMEs in Nigeria 19
Table 3.1: Estimated Number of Enterprises across selected clusters in South-East 65
Table 3.2: Sample Size of Enterprises across Clusters in South-East Nigeria 67
Table 3.3: Model 1: Microfinancing source and profitability 73
Table 4.1: Summary of Enterprises Characteristics 79
Table 4.2: Perceived Challenges faced by enterprises in accessing micro finance 82
Table 4.3: Effect of microfinance sources on the profitability of enterprise clusters 83
Table 4.4: Determinants of the choice of micro financial sources for enterprises 88
Table 4.5: Assessing the level of support of Microfinance providers for the sustenance
of profitability of Enterprise (Objective 4) 94
xi
LIST OF FIGURES
Figure 2.1 Simple Illustration of the Value Chain 45
Figure 4.1: Perception of determinants of choice of microfinance choice 92
Figure 4.2: Extent of microfinance support perceived from formal and informal sources 93
Figure 4.3: Perceived extent to which funds have expanded business 95
1
LIST OF ACRONYMS Acronyms Meaning ADB African Development Bank ADP Agricultural Development Programme AU African Union CAC Corporate Affairs Commission CBN Central Bank of Nigeria
CEO Chief Executive Officer CTS Credit Tracking System DEMs Dual Economy Models DFID Department for International Development ECs Enterprise Clusters FGD Focus Group Discussion FGDs Focus Group Discussions GDP Gross Domestic Product GSM Global Systems Mobile Network ICs Industrial Clusters ICT Information and Communication Technology IGR Internally Generated Revenue
IUCN International Union for the Conservation of Nature IYMC International Year of Micro Credit LDCs Less Developed Countries LGA Local Government Area M&E Monitoring and Evaluation MAN Manufacturers Association of Nigeria MDGs Millennium Development Goals MFBs Micro Finance Banks MFIs Micro-Finance Institutions MoU Memorandum of Understanding MSEs Micro and Small Enterprises MSMEs Micro Small and Medium Enterprises MSSE Micro and Small Scale Enterprises NASME National Association of Small and Medium Enterprises NASME National Association of Small and Medium Enterprises NASSI National Association of Small Scale Industrialists NEPAD New Partnership for African Development NGOs Non-Governmental Organizations OLS Ordinary Least Square OPS Organized Private Sector PEP Poverty Eradication Programme R&D Research and Development RBRDAPs River Basin and Rural Development Authorities' Projects
2
RMB Renminbi (Chinese Currency) ROA Return on Assets ROI Return on Investment SDM Sustainable Development Model SHGC Self Help Group Contribution SMEDAN Small Medium Enterprises Development Agency of Nigeria SMEEIS Small and Medium Enterprises Equity Investment Scale SMEs Small Medium Enterprises SMIs Small and Medium Industries SSEs Small Scale Enterprises UN United Nations UNDP United Nations Development Programme UNICEF United Nations Children’s Fund UNIDO United Nations Industrial Development Organization USA United States of America VECM Vector Error Correction Model WBPs World Bank Projects WCED World Commission on Environment and Development
3
ABSTRACT
Micro and Small Enterprises (MSEs) are currently regarded as the backbone of every economy and have been globally regarded as engines of growth, vehicles for job creation, drivers of production and income generation as well as veritable tools for poverty reduction and wealth creation. The source of microfinance is equally important because at the centre of every enterprise objective is profitability and growth that can trigger its achievement of the expected roles. MSEs in Nigeria have not played these roles effectively due to the challenges of access to finance, infrastructural deficit and vocational skills deficiency. The main thrust of this thesis, therefore, is to evaluate the effectiveness of microfinance sources on the profitability of MSEs in South East, Nigeria as well as understanding the determinants of the choice of microfinance sources and the level of support that MSEs get from funds providers. The study employed multi-stage sampling technique in identifying clusters from three cities (Onitsha, Aba and Nnewi) of the South East, Nigeria and generated relevant data through instruments such as questionnaire, personal interviews and Focused Group Discussions (FGDs). A total sample of 540 enterprises out of 1994 enterprises were selected across different clusters comprising enterprises under production, trade and services in the three cities. Using multiple regression technique and logit regression, the study found that both formal and informal microfinance sources impacted significantly on the profitability of MSEs in South East, Nigeria. The study further found interest rate, repayment period, amount or volume of capital and proximity to enterprises as the major determinants of the choice of microfinance source used by MSEs in South East, Nigeria. Also, the respondents revealed that why most of them patronized informal source of microfinance is because of the quick response as well as the relationship with the provider (social capital). The study concluded that microfinance providers should be located closer to MSEs’ location for quicker response to their financing needs to the extent of taking advantage of social capital existing within the clusters as a possible cushion for the physical collaterals and documentations often requested for loan approvals. The study recommends that microfinance policy framework and interventions should encourage providers to locate closer to the enterprise clusters with the appropriate regulatory guarantee for operators.
4
CHAPTER ONE INTRODUCTION
1.1 Background of the Study
The impact of manufacturing industry in every economy cannot be overemphasized as
it goes a long way to enhance production, create jobs, reduce imports, increase
exports and hence increase National revenue and income. In Nigeria, the growth
pattern has been quite sluggish over the last decades. This fact is connected to the
high increase in the level of poverty, which is further exacerbated by the pandemic
problem of low productivity (Sulaiman, 2005). Nigeria as a nation is blessed with
both human and material resources, but Maduagwu (2000) posits that poverty in the
midst of abundance is a popular paradox characterizing the Nigerian economy.
According to the Central Bank of Nigeria (CBN) (2006), foreign exchange inflow and
outflow through the Central Bank of Nigeria amounted to United States (US) $3.25
billion and US $ 1.16 billion respectively resulting to net inflow of US $2.09 billion.
Despite this huge amount of foreign reserves, Nigerian citizens suffer from
widespread poverty.
Micro enterprises have been referred to as the arm of the industry that could be
used to reach out to relatively low scale investors and develop the home industries.
The roles of micro enterprises cannot be overemphasized in economic development,
accordingly, Chibundu (2006), states “it is encouraging to note that research findings
and empirical evidences show that significant poverty reduction is possible and has
occurred in many countries where micro enterprises are encouraged”. They stimulate
private consumption, ownership and entrepreneurial ability; generate employment,
help diversify economic activities and make significant contribution to export and
domestic trade while utilizing local raw materials.
Micro and Small Enterprises (MSEs) are globally acknowledged as a
potentially critical economic sector. They contribute about 30 per cent of global Gross
Domestic Product (GDP) and account for about 58 per cent of global working
population (Kushnir, Mirmulstein, and Ramalho, 2010). They are numerically
dominant, providing the majority of employment and are the prime sources of new
jobs. They play a critical role as safety net for the bulk of the population in
developing economies including Nigeria. In addition, they provide amenable avenue
for creating new jobs in the economy.
5
In Nigeria, the Corporate Affairs Commission (CAC) estimates that about 90% of all
Nigerian businesses in 2007 employed less than 200 persons. From the cluster
development programme in Eastern Nigeria, that is, administrative and infrastructure
costs’ survey of the manufacturing sector (Abia and Anambra States), prepared by
Skoup and Company Ltd for the International Finance Corporation and the World
Bank, February 2003, Nigeria envisions MSEs sector that can deliver maximum
benefits of employment generation, wealth creation, poverty reduction and sustainable
economic growth. Towards realizing this goal, the Nigeria’s Vision 20:2020
advocates measures to enhance the ability of MSEs to compete effectively in local,
regional and global markets, through increased productivity, greater technological
efficiency and reduced cost of doing business. In this context, growth and
competitiveness of MSEs are, therefore, the key objects of the national policy on
MSEs. In the same vein, the national policy seeks to enhance MSEs’ contribution to
GDP and employment and realize its potentials as a principal determinant of the
prospects for the growth and sustainability of Nigeria’s non-oil economy.
One of the major achievements towards MSEs development in Nigeria is the
institutionalization of a policy regime that is stable, supportive and consistent with
national economic reform agenda – the Vision 20:2020, New Partnership for Africa
Development (NEPAD) of the African Union (AU) – as well as being geared towards
realising the United Nations’ Millennium Development Goals (MDGs). For the above
to be achieved, there is the need to remember that we live in a globalizing and
increasingly interdependent world. For developing countries like Nigeria, dependence
on rich nations remains a stark fact of economic life. At the same time, the developed
world, which once prided itself on its apparent economic self-sufficiency, has come to
realize that in an age of dramatically increased capital flows, diminishing natural and
mineral resources, global environmental threats, accelerated international migration,
bourgeoning world trade in manufactured products and services, and new forms of
geopolitical tensions, it is becoming even more economically dependent on the
developing world.
The same applies to industries. They will need to relate with one another at the
national, regional and international levels in achieving the specific objectives and
broad goals of trade, economic growth and development; hence, the popular industrial
and labour maxim - “Industrial Relations for Industrial Growth and Development”.
6
Isolation and barriers have never worked to develop prosperity. According to Amobi
(2006), they have been the key obstacles preventing MSEs to boost their
competitiveness. To the United Nations Industrial Development Organisation
(UNIDO) (2006), “Firms or enterprises that have come together as a group (forming a
cluster) and which are located in close proximity have proved to be capable of rapid
economic growth, sustainable leadership in export markets, significant employment
generation and preservation of high-value added jobs”. Equally, studies from both
developed and developing countries have shown that MSEs cluster development
provides for economic development, poverty reduction and social equity (UNIDO,
2006).
The potentially networking gains of clustered firms or enterprises have led to
the view that clusters offer a specific path of regional, industrial and economic
development, as well as the possibilities of technical innovation and growth. Clusters
are also considered particularly relevant to developing countries since they motivate
significant policy initiatives within industrial development strategies. This has
fostered a growing academic literature on clusters (Markusen, 1996; Scott, 1998;
Malmberg, 1996 and 1997; Nadvi and Schmitz, 1999; Todaro and Smith, 2009).
From available literature, it is agreed that providing a microfinance framework
targeted at these clusters will create a more sustainable model to cushion the fears of
conventional banking institutions who would rather not lend to some individuals.
This would then cultivate high confidence level by the emerging microfinance
institutions that are now expected to grant micro credits to such target markets on
enterprise clusters.
Over the years, the Nigerian government has embarked on series of policies
and institutional reforms aimed at enhancing the flow of finance from the banking
system to Small and Medium Industries (SMIs) as well as those involved in the petty-
business (micro) activities at the informal level. The much talk on the need for
government, financial institutions, corporate organizations and government agencies
to support the establishment and development of the small enterprises subsector has
its merits and demerits. Although, it is not an indication that small business operators
should fold their arms and wait for the almighty handout from these agencies, either
in the form of loans or grants, getting such support could go a long way to
7
transforming the small business landscape in a number of ways and also help to
strengthen the economy of the nation.
According to Amagwu (2006), the focus of microfinance has been on the poor
in the society and the rural populace who are believed to be the most vulnerable. He
opines that, making micro finance available to this group of people would not only
guarantee that they are in a sustainable employment but also contribute to the
economic wellbeing of the nation. In line with this argument, existing community
banks were mandated to upgrade to microfinance banks. They had to raise the
minimum share capital or shareholders’ funds of one unit bank from N5 million to
N20 million with effect from September, 2006. The minimum capital of N20 million,
according to Godwin (2007), was to be deposited with the bank’s formal application
before it can be issued a unit bank operating licence. New investors into this area were
encouraged to do so. Individuals, co-operative societies, corporate organizations,
groups, investors are free to go into this area of investment.
Every year, the government at federal, state and even local and development
centres through budgetary allocations, policies and pronouncements express strong
interest and appreciation of the crucial role of this sub-sector of the economy and
hence, made policies for energizing same. Even local and international donor agencies
have been inundated with requests from non-governmental agencies and organized
private sector associations for grants and other forms of assistance to the sector.
With the above interventions, it is necessary to ascertain whether there have
been some achievements (positive or negative) among these MSEs in the South East
Nigeria, following the various pronouncements by the governments. Among the group
of people in South-Eastern Nigeria are the artisans, petty-traders, subsistence farmers,
fishermen, traders, local textile producers, intra-city transporters, cobblers etc. These
people in the South East, Nigeria region are found within the industrial clusters at
Nnewi, Onitsha, Aba and other rural but emerging locations in the region.
Interestingly, these clusters have the advantage of proximity to several industrial raw
materials which makes it possible to produce associated semi-finished or finished
goods cheaply. Thus, this study is expected to find how effective microfinance from
both formal and informal sources affect the profitability of these micro and small
enterprises.
8
1.2 Statement of the Problem
The performance of Micro and Small Enterprises (MSEs) in Nigeria, particularly in
the South East has been affected by so many problems like poor infrastructure (that is,
inadequate power supply, bad roads, and poor transportation system), financial access,
poor corporate governance, insecurity and the hostile legal framework. At the core of
these problems is that of access to finance due to the fact that the people are mostly
informal operators. Hence, the conventional commercial banks and other formal
financial arrangements shy away from extending credit facilities to the sector.
Consequently, majority of the operators resort to informal sources like family and
friends, Isusu, cooperative societies, trust fund model and informal saving groups.
Unfortunately, these sources have limitations in ensuring effective contribution of
micro enterprises to economic growth and sustainable development.
MSEs in Nigeria have not performed optimally and, hence, have not played
the expected vital and vibrant role in the economic growth and development of
Nigeria, particularly in the South East region (CBN 2008). This situation has been of
great concern to both government and the Organized Private Sector (OPS) at various
levels considering the fact that over 70% of the Nigerian population are found in this
category.
Despite the apparent significance associated with these enterprises and the
numerous policy initiatives introduced by government in the past decade to accelerate
the growth and survival of small businesses, the performance has been disappointing.
A study conducted over thirty years on micro enterprises in the Eastern Region of
Nigeria found out that half of the MSEs in Nigeria do not survive beyond a tenth of a
century. The alarming rate of business failure gives the Nigerian economy cause for
concern and has made unemployment reach an embarrassing level. This loss of
employment opportunity has led to frustration, insecurity and uncertainty about the
future due to low performance of the existing micro enterprises in Nigeria hence, the
prevalence of chronic poverty.
According to the Manufacturers Association of Nigeria (MAN), more than
100,000 jobs have been lost between 2001 and 2007 due to continuous closure of
small businesses. Small businesses in Nigeria at present experience a lot of problems
and hardship. These bottlenecks include serious undercapitalization with difficulty in
gaining access to bank credits and other financial markets, corruption and very high
9
bureaucratic costs and government seeming lack of interest in small businesses. All
these have great damaging effect on the economy. Furthermore, inconsistencies in
government policies, natural disasters, and global economic downturn combined to
ensure the dwindling growth of micro enterprises in Nigeria. These dwindling
performances have necessitated this study which is geared towards assessing the
extent to which micro enterprises help in poverty reduction despite dismal
performance in Nigeria.
Of greater concern to all stakeholders is the fact that despite the acclaimed
strong focus on this critical segment of the economic foundation by policy makers, the
sub-sector has fallen short of expectations in terms of profitability and thus
employment generation. The situation becomes more scaring when compared with
other developing economies with similar profile in human and material resources like
Nigeria. It has been shown in the literature that there is a high correlation between the
degree of poverty, hunger, unemployment, economic well-being of the citizens of
nations and the effectiveness of the MSEs in the economic activities of the nation. If
Nigeria were to record a significant success towards attaining the Millennium
Development Goals (MDGs) for 2015, it would be important to vigorously pursue the
development of the micro and small scale enterprises sub-sector of the economy.
Attainment of the MDGs by 2015 may indeed be a mirage unless the micro and small
scale enterprises participate actively and effectively in the economic life of our nation.
Micro enterprises have been described as an engine of economic
empowerment and growth. MSEs are not just job creators but creators of wealth in the
society. While it has been argued that a small business can only make a minor
contribution to the economy as a result of its size, many micro enterprises can make
substantial contributions collectively. For example, according to data from the
European Observatory (CBN 2008), SMEs employing up to 250 people accounted for
68 million jobs in the European Union in 1995. Again, available data from some
African countries shows that in 2003, small enterprises in Kenya employed 3.2
million people, accounting for 18% of the national GDP. In Nigeria, according to
Manufacturers Association of Nigeria (MAN), small enterprises are the backbone of
the economy; they account for 95% of formal manufacturing activities and 70% of
Industrial jobs.
10
Though lack of capacity, inadequate coordination and synergy, poor
networking, isolation, lack of detailed articulation of stakeholders roles in the sector
operations and policy shortfalls have been identified as major problems of the sector,
at the center of it all is lack of access to formal credits. According to CBN (2008), less
than 5% of total credits to the private sector were allocated to micro and small scale
enterprises. It is therefore evident that MSEs do not have adequate access to formal
credit facilities and this situation had restricted the sector to informal financing
through traditional credit supports like Isusu, trade credits, cooperative societies,
market associations, Non-Governmental Organizations (NGOs), government grants
and interventions, etc.
The inadequacies in these forms of credit facilities like reliability volume,
training, standards, spread and repayments have limited the performance of such
enterprises and hence, their poor contributions to the economic growth and
development of the industrial clusters in the South East and the nation as a whole.
The introduction of micro finance banks by CBN in 2005, associated
microfinance institutions, microfinance institutions and development finance
institutions have not bridged this gap of inequality in credit accessibility in Nigeria
after close to 10 years of their operations. It becomes imperative to evaluate the
effectiveness of both the formal and informal sources of microfinance to MSEs,
especially in the South East of Nigeria. It is therefore believed that understanding
these micro credit problems and providing practical solutions for them would be the
right step towards making micro and small scale enterprises contribute effectively
towards growth and development of the industrial cluster in South East, Nigeria and
the nation as a whole, like their counterparts in other countries.
1.3 Objectives of the Study
The major objective of the study is to evaluate the effectiveness of the microfinance
sources on the profitability of Micro and Small Enterprise (MSE) clusters in South
East, Nigeria.
The sub-objectives are:
(i) To assess the impact of formal microfinance sources on the
profitability of enterprise clusters in South East of Nigeria,
(ii) To ascertain the impact of informal microfinance sources on the
profitability of enterprise clusters in South East of Nigeria,
11
(iii) To examine the determinants of the choice of the microfinance source
by enterprise clusters in south East, Nigeria,
(iv) To assess the level of support of microfinance providers for the
sustenance of profitability of enterprise clusters in South East, Nigeria.
1.4 Research Questions
The following are the research questions:
1) To what extent do the formal microfinance sources affect the
profitability of enterprise clusters in South East of Nigeria?
2) To what extent do the informal microfinance sources affect the
profitability of enterprise clusters in South East of Nigeria?
3) What are the determinants of the choice of the microfinance sources by
enterprise clusters in South East, Nigeria?
4) How much is the level of support of microfinance providers for the
sustenance profitability of enterprise clusters in South East, Nigeria?
1.5 Research Hypotheses
The following research hypotheses are presented in their null forms.
1. There is no significant impact of the formal microfinance sources on the
profitability of enterprise clusters in South East of Nigeria,
2. There is no significant impact of the informal microfinance sources on the
profitability of enterprise clusters in South East of Nigeria,
3. There exist no significant determinants (i.e. amount, interest, extent of
protocols including collateral availability, relationship with the provider) of
the choice of microfinance sources by enterprise clusters in South East,
Nigeria,
4. There is no high involvement of the microfinance providers for the sustenance
of profitability of enterprise clusters in South East Nigeria.
1.6 Significance of the Study
The significance of this study cannot be overemphasized. It is so significant in the
sense that;
• It will help to expose the various micro financing strategies employed in the
development of industrial clusters in Nigeria, with particular interest in the
South-Eastern part of the country. In addition to the above, it will help in
12
examining the strengths and/or weaknesses and relevance of these micro credit
strategies to the development of the industrial clusters in Nigeria, particularly,
in the South East.
• Since the microfinance supports for the development of industrial clusters in
Nigeria, with particular interest in the South East cannot be
effectively/efficiently carried out without active participation of stakeholders,
the study will therefore help to ascertain the contributions of various
stakeholders, and their levels of commitment in terms of relationship and
willingness in ensuring that the goals and objectives of the micro credit
supports for the development of industrial clusters in Nigeria, particularly in
the South East are actualized. Informal micro financing sources are (a) Esusu
(b) Self Help Group Contribution (SHGC) (c) TFM – Trust Fund Model, (d)
family and friends, (e) Non-Governmental Organizations (NGOs) (f) others
• The study will bring to the knowledge of the major stakeholders in the
development of industrial clusters and MSEs in Nigeria, i.e. the government,
the microfinance banks, the micro-business operators themselves, the national
and international donor/aid agencies etc., the efficacy of establishing and
developing industrial clusters in the country, the kind of impact (negative or
positive) the industrial clusters development would make on the economy,
which eventually will enable them formulate favourable and positive policies
and implement fully the developed strategies that would help the micro credit
scheme, aimed at eradicating poverty achieve its goals and objectives.
• Finally, this study will help to add to the already existing literature, especially
in the developing counties, which Nigeria is part of, and this will surely serve
as a reference material for scholars who may want to embark on further
studies on this subject matter or those related to it.
1.7 Scope of the Study
This study focuses mainly on the impact of microfinance sources on the profitability
of Micro and Small Enterprises (MSEs) in Nigeria with particular interest in the
South-East, Nigeria using enterprise clusters at Onitsha, Aba, and Nnewi. Profitability
as a key objective of every business is measured by return on investment. Micro
enterprises would be the target group based on the objectives and the information
13
required from the questionnaires. The study covers the period between 2013 and
2014.
1.8 Limitations and Structure of the Study
Like all other studies, this study witnessed its own circumstantial difficulties. The
main fact that the study employed primary survey analysis that warranted fieldwork
and questionnaires introduced all the challenges that go with it. First of all, the timing
of the fieldwork vis-à-vis the study programme was a major concern as the rainy
season could be a major hindrance to the field survey. There was, therefore, the need
to situate the field survey in a dry and friendly season in order to ease the distribution
and collection of the questionnaires.
The fieldwork itself had issues like every other field which include; reliability
of the information given, reliability of the enumerators amongst others. This was
however lessened with the degree of supervision and monitoring of the survey.
Nevertheless, this study faced peculiar issues due to the nature and occupation of the
respondents. The respondents (business men) had no time to respond to the questions
and the few that were able to respond, were still not very patient and needed a lot of
persuasion. The respondents were also very skeptical about the use of the data. Some
of them feared that the fieldworkers were actually tax officials who were sent as spies.
The respondents were equally very nonchalant about the documents as they opined
that the government had done little or nothing in the past and that that was just
another paper framework.
Also, the fieldwork was very expensive. It employed fieldworkers who went to the
three clusters at Aba, Nnewi and Onitsha and were supposed to cover the three sectors
of production that include; production, trade and services. The fieldworkers had to be
motivated to go to the clusters and spend some days. Also, the supervision required
moving to the clusters to monitor groundwork and equally implied increasing cost of
the field survey. The Focus Group Discussion (FGD) which was intended to collect
responses from questionnaires and interviews was difficult to obtain from traders as
most were busy with trading transactions and had little time to sit for discussions.
In terms of research structure, the first chapter contains the introduction,
problem statement, study objectives, research questions and hypotheses; as well as the
14
study scope, limitations, MSEs background and operational definitions as used in the
study. The second chapter reviewed not just the conceptual literature but theoretical
and empirical literature. It also summarized all reviewed literature and identified
potential gaps and how they were covered in the current study. Chapter three
presented the theoretical framework and the study design including study area, study
population, sample size, study models, estimation procedures and hypotheses testing
techniques. Chapter four presented all the analyses and study results as well as
findings, decisions on hypotheses tested and discussion of findings while the final
chapter (five) summarized the findings, identified policy implications and based on
that made recommendations. It also contains areas and issues for further research,
contributions to knowledge and conclusions.
1.9 Background Information on Development of MSEs
Microfinance institutions were created in Nigeria by the Central Bank in 2005.
However, before the emergence of formal microfinance institutions, informal
microfinance activities flourished all over the country. Informal microfinance is
provided by traditional groups that work together for the mutual benefits of their
members. These groups provide savings and credit services to their members. The
informal microfinance arrangements operate under different names: Esusu, among the
Yoruba of Western Nigeria, Utuu, for the Igbo in the South East and Adashi, in the
North for the Hausa (CBN, 2003). The key features of these informal schemes are
savings and credit components, informality of operations and higher interest rates in
relation to the formal banking sector.
The informal associations that operate traditional microfinance in various
forms are found in all the rural communities in Nigeria (Otu, Ramlal, Wilkinson, Hall,
and Hecky, 2011). They also operate in the urban centers. However, the size of
activities covered under the scheme has not been determined. The non-traditional,
formalized Microfinance Institutions (MFIs) are operating side by side with the
informal services. The financial services provided by the MFIs in Nigeria include:
savings, credit and insurance facilities. The major formal microfinance suppliers
include the Commercial Banks and Microfinance as well as the Development Finance
Institutions. However, microfinance suppliers exist so as to provide low and
accommodative rates of interest because of the existence of inequitable distribution of
wealth and income and to reach out to the poor. From the appraisal of existing
15
microfinance-oriented institutions in Nigeria, the following facts have become
evident: weak institutional capacity, weak capital base, existence of a huge un-served
market, economic empowerment of the poor, employment generation and poverty
reduction, the need for increased savings opportunity, the interest of local and
international communities in micro-financing and utilization of the small and medium
enterprises equity investment (SMEEIS) fund.
SMEEIS, however, is said to have failed due to the fact that, it required a
partnership of ownership between the micro enterprises and the microfinance
operators as a means of involving the banks fully into developing these enterprises.
This effort failed partly because the entrepreneurs had a jealous and, of course,
protective ownership attitude of their enterprises and so did not accept to get in terms
with the banks. On the other hand, several bureaucratic engagements that are involved
in becoming co-owners such as the Memorandum of Understanding (MoU) scared the
banks from actively getting involved. This led to the creation of the Microfinance
Development Fund in 2013 by CBN. This project was launched with a seed capital of
₦220 billion, having 80% devoted to micro enterprises and 20% to small and medium
size enterprises. The Microfinance Development Fund that is now operational has the
advantage of asserting specific amounts for interest rates, sectorial loan quotas, and
sex ratios. Unlike the SMEEIS that compelled both banks and entrepreneurs to be co-
owners, the Microfinance Development Fund allows banks to operate from a distance
yet ensures that the modalities are moderate.
1.10 Operational Definition of Terms
Micro Enterprise: It is a firm whose total cost including working capital and
excluding cost of land is not more than ten million naira (N10,000,000) and/or with a
labour size of not more than ten (10) full-time workers and/or an annual turnover of
less than two million naira (N2,000.000) only.
Small Enterprises: It is an enterprise whose total cost including working capital but
excluding cost of land is between ten million naira (N10,000,000) and one hundred
million naira (N100,000,000) and/or a workforce between eleven (11) and forty nine
(49) full-time staff and/or with annual turnover of not more than ten million naira
(N10,000,000) in a year.
Medium Enterprises: It describes a company with total cost including working
capital but excluding cost of land of more than one hundred million naira
16
(N100,000,000) but less than three hundred million naira (N300,000,000) and/or a
staff strength of between fifty-one (51) and two hundred (200) full-time workers
and/or with an annual turnover of not more than twenty million naira (N20,000.000).
Industrial Clusters: It refers to geographical proximate group of interrelated
enterprises and associated institutions in a particular business environment linked by
commonalities and complementarities. Clusters are considered to increase the
productivity with which companies can compete, nationally and globally.
Micro Credit: This means making financial services available to the poor, low income
earners and Small Scale Enterprises (SSEs). The United Nations (UN) declared 2005
International Year of Micro Credit (IYMC).
Microfinance Institution: This is an institution that extends small loans or
microfinance to applicants who typically belong to the lowest strata of society. Loans
are extended to borrowers to allow them to initiate a business, repair their homes and
improve the general living conditions of their families and the community.
Cluster Strategy: It is an economic development strategy that provides a coordinated
and efficient way to promote economic growth. By making a cluster approach a key
part of a state economic development strategy, state agencies are more likely to
coordinate their efforts, avoid duplication of services, and develop a more
comprehensive approach to economic development.
Poverty Alleviation: Poverty alleviation (or reduction) describes strategies to
ameliorate poverty. It is any process which seeks to reduce the level of poverty in a
community, or amongst a group of people or countries. Poverty alleviation
programmes may be aimed at economic or non-economic poverty.
Economic Development: It refers to the sustained increase in the economic standard
of living of a country's population, improving the quality of human life through
increasing per capita income, reducing poverty and enhancing individual economic
opportunities by developing technology, making more productive and efficient use of
physical capital, and increasing human capital.
Social Development: This refers to the improvement in qualities of life and human
well-being by organizing human governance and affairs to accomplish such tasks as
the alleviation of poverty, the reduction of income disparities, the elimination of
violence, the guaranteed right to clean water and health services, the increased respect
17
for nonhuman creatures and their ecosystems, and the structuring of a just legal
system and system of representation.
Profitability: This term is used to describe the gain or compensation to an
entrepreneur or a firm for engaging in economic activities. It is usually defined by
returns on investment or assets. Profitability is derived from gross earnings either
after tax or before it.
Private Sector-led Growth: This is the private sector engagement as the main driver
of economic and social progress, with businesses, not governments, providing the
bulk of the investment, innovation, employment and income, which can bring about
the growth and productivity increases.
18
CHAPTER TWO REVIEW OF RELATED LITERATURE
2.1 Introduction
This chapter reviews conceptual, theoretical and empirical literature on issues around
microfinance and micro financing, cluster and clustering and an analysis of
microfinance in the Nigeria context. Details of the issues are organized under the
conceptual framework, theoretical and empirical literature and Nigerian situational
analysis.
2.2 Conceptual Literature
Micro financing is the provision of financial services to poor and low income
households without access to formal financial institutions (Conroy, 2003).
Microfinance is also described as banking for the poor. Microfinance programmes
provide loans, savings and other financial services to low income earners and poor
people for use in small businesses. Originally based on traditional forms of
community financing (a cross between finance and development assistance),
microfinance is found all over the world, especially Africa, Latin America and Asia.
The microfinance movement began in earnest in the early 1980s (Anyanwu, 2004).
According to Khan (2007), Micro Finance Institutions (MFIs) cover a variety of
activities like qard-hasan, financing housing, meeting basic needs, and promoting and
financing small entrepreneurs. All these aspects can be covered in a comprehensive
integrated programme tagged ‘micro-financing’ as practiced in Bangladesh and
Bolivia over the last 20 years.
Microfinance institutions are essentially needed to serve the poor city
dwellers, residents in slums or squatter settlements in appalling conditions. They lack
access to basic services such as education and health care, consequently, they lack
basic skills for employment. Many of them are women who are poorly trained, and
play dual roles of provider and caregiver. These poor people are more exposed to the
threats of contaminations, bad sanitation, and disease than the rest of the population
(Ornorodion, 2007).
Micro enterprises constitute the most dynamic and heterogeneous sector in
Nigeria (CBN 2006). Between 1990 and 1995, an average of 84 out of 100 new jobs
was generated by micro enterprises. The GDP contribution to the economic sector is
19
harder to estimate due to its scale and widespread informality. Measurements of micro
enterprises’ participation in GDP range from less than 10% to 50%, depending on the
economy and method of estimation. There are two views of the micro enterprise
sector with different policy implications. The first one considers workers in the micro
enterprises sector as either underemployed or surplus labour (Chari, 2000). These
workers are not employed in the formal sector due to their low skills (unemployment
view).
The second view focuses on the fact that some workers choose this sector for
its flexibility and earning opportunities (micro-entrepreneur view). While the
existence of high levels of poverty in the sector is strongly suggested by the first view,
poverty is not necessarily a permanent micro enterprise condition according to the
second view. Since late 1970s, the African Development Bank (ADB) has adopted the
micro entrepreneur view, which posits that micro enterprises development can be an
effective mechanism for poverty reduction through market-driven and productive
activities. Policies oriented towards supporting and promoting micro enterprises have
three major fronts: micro finance, change in the regulatory framework, and business
development services. There are also other policy interventions that have a positive
impact on micro enterprise development such as, the provision of productive
infrastructure and child care programmes for female workers.
2.2.1 Defining Micro, Small and Medium Enterprises (MSMEs) in Nigeria
Micro, Small and Medium Enterprises (MSMEs) is a core necessity in developing
well-targeted policies, legislation, programmes and services. It is vital to define
MSMEs in order to build a consistent and reliable database and identify object for
evaluating impact of policies and developing appropriate responses. The challenge
lies in the fact that MSME is not an absolute concept, but relative to large business
and industrial sectors, both of which are also relative to the size and nature of the
domestic economy. Criteria for defining the scale of a business vary from country to
country, depending on country’s circumstances. Some countries define MSMEs by
total assets, others by employment rate, turnover, or paid-up capital; while some
countries by sectors and several others use more than one indicator. In developing a
national policy, it is proper to state if there should be one exclusive definition, how
complex that definition should be and whether the definition should vary to some
degree according to specific policy, legislative and programme objectives.
20
Experiences of other countries are mixed. Some countries, such as the United
States legislate on SME definitions. But, in many countries, the central statistical
authorities or lead policy agency may use one or more criteria, while separate
programme departments pre-determine different criteria in order to achieve
organization-specific programme objectives. International approaches in defining
SMEs can be deciphered from the examples as follows (Table 2.1).
Table 2.1: Cross-Country approaches to defining SMEs Country Classification approaches and criteria
Australia Australian Bureau of Statistics defines small businesses as those employing fewer
than 20 persons. The Australian Tax Office uses a definition of average annual
turnover of less than $1million and net assets of less than $3million. By contrast,
the Export Insurance scheme targets small businesses with annual turnover not
exceeding $10million
China China is introducing new criteria for enterprise classification based mainly on
sales revenue and total assets. Small enterprises have sales revenue and total assets
not more than RMB 50million, medium enterprises have between RMB 50-500
million
India Small scale industry has different meanings for different agencies. The Planning
Commission, National Sample Survey Organisation, Central Excise Department
have varying definitions relating to annual turnover, fixed assets and/or investment
ceilings.
South
Africa
The National Business Act of 1996 identifies four different categories – micro,
very small, small and medium – differentiated by sector, and then by number of
full-time employees, the value of annual turnover and total gross asset value
(excluding fixed property). While turnover and gross asset criteria vary
significantly across sector, there is a great deal of commonality with respect to the
employment criteria. Employment criteria for the manufacturing, construction and
utility sectors are: micro – 5, very small – 20, small – 50, medium -200. But, in the
service industries, these employment criteria are: micro – 5, very small – 10, small
– 50, medium – 100.
United
Kingdom
There is no single definition for small businesses. But, the Small Business Service
defines businesses according to number of employees: micro, 0-9; small
21
Country Classification approaches and criteria
businesses, 0-49; medium sized businesses, 50-249; and large businesses, 250+
employees. It is, however, noted that size is relevant to sector, a firm of a given
size could be small in relation to one sector where the market is large and there are
many competitors; whereas a firm of similar proportions could be considered large
in another sector with fewer players and generally smaller firms within it. It is also
recognized that it may be more appropriate to define size by the number of
employees in some sectors but more appropriate to use turnover in others. Across
government, it is most usual to measure size according to numbers of full-time
employees.
United
States
The Small Business Act requires that the definition of a small business be varied
by industrial sector to reflect essential differences between the sectors. The
fundamental definition used by the Small Business Agency is the numerical “size
standard” which is almost always stated in terms of either number of employees or
average annual receipts. In developing the standards, the SBA considers economic
characteristics of particular industry, average firm size, start-up costs and entry
barriers and distribution of firms by size.
Canada For statistical purposes, small businesses are defined as those with less than 100
employees in manufacturing and less than 50 employees in the service sectors.
Source: International Experiences in Governmental Policies and Processes for SMEs: A Comparative Analysis. Prepared for the International Development Research Centre by Growth Connections, December 17, 200: p 37
In Nigeria, the current classification is based on number of employees and
assets (excluding land and buildings). But, defining MSMEs based on multiple
criteria could be problematic, since it could lead to non-mutually exclusive categories.
This is because of potential enterprise asymmetry across criteria, that is, incidence of
outliers due to sectoral biases. For instance, some enterprises, depending on the levels
of capital-intensity vis-à-vis labour-intensity may not match the dual employment-
cum-assets-based criterion. Some enterprises may have very low size of labour
employment but high capital outlay, e.g. Information and Communication Technology
(ICT) enterprises. A contradistinction is enterprises that have very high labour
employment but very low capital outlay, e.g. low technology manufacturing. Besides,
22
inflationary trend may erode the assets-based definition and make it necessary to
revise the definition periodically.
Some of the current classifications in Nigeria are shown in Table 2.2, as follows. Table 2.2: Different classification of MSMEs in Nigeria
Agency Employment based classification
Assets based (excluding real estates)
Micro Small Medium Micro Small Medium IFC <10 10-50 50-100 -------- <N2.5million --------- CBN SMIEIS study <10 10-50 51-300 -------- ---------- --------- WB RPED <20 20-49 50-99 -------- --------- --------- UNIDO NMES ≤5 5≤20 21≤75 FMI <10 11-35 36-100 ≤1million 1<N40million N40-150million NBS <10 10-19 Sourced from several reports Based on the cross-country experiences, the Nigerian National Policy of MSMEs
adopted definition based on the number of employees in the business. This is because
of many factors:
• In practice, the number of employees is the most common standard used in
national SME policies worldwide.
• Experience shows that the number of employees is the most unifying criterion
for classifying enterprises, others such as turnover or assets base tend to be
more asymmetric across sectors.
• Governments worldwide adopt the size of employees. Most governments
usually measure size according to numbers of full-time employees.
• The criterion – number of employees – is the most amenable to
synchronization across the various government agencies – National Bureau of
Statistics, Federal Ministry of Industry, etc, and across sectors of the economy
• Number of employees is already the most popular criterion adopted by various
government agencies and development stakeholders in the country
However, the use of number of employees does not preclude specialized agencies
such as export promotion, loan guarantee and tax authorities from targeting
enterprises for their respective organizational programmes based on turnover or other
criteria. Also, the definition can be varied by sectors of the economy. For example,
the benchmark number of employees for small enterprises may be lower for service
23
sectors due to higher capital intensity. Similar situation of varying benchmark for
enterprise size exists in United States, Canada, South Africa and United Kingdom.
2.2.2 Sector Classification of MSMEs
Another dimension of MSMEs characterization is the classification by sector and/or
sub-sector. MSMEs are classified according to several schemes.
2.2.3 Generic Categorization
MSMEs can be classified based on traditional sectors, for example, primary
(agriculture, mining), secondary (manufacturing) and tertiary (commerce, finance and
personal services). Furthermore, manufacturing MSMEs are often classified into
categories which include: Chemicals and Paints; Food and Beverages; Metal; Non-
metal; Paper, Printing and Publishing; Pharmaceuticals; Plastic, Textile and Leather
and Wood (The World Bank, 2003).
Another classification of the MSMEs manufacturing sector includes Food
Processing; Textiles and Garments; Wood (including furniture and paper processing);
and Metal, Machinery and Chemicals (The UNIDO 2001 & 2004).
2.2.4 Technological Intensity Criterion
MSMEs are often classified according to levels of technological intensity of the
products. Based on this criterion, five classes can be distinguished: primary products;
manufactures and high-technology manufactures. Primary products include minerals,
agricultural and forest products exported in unprocessed state. Resource-based
manufactures include processed foods, simple wood products, dyes, leather and
organic chemicals. Low-technology manufactures are characterised by well-diffused
technologies largely embodied in capita products, low Research and Development
(R&D) and skill requirements, and low economies of scale. They include textiles,
garments, footwear, other leather products, toys, furniture and glassware. Medium-
technology manufactures are heavy industries like automobiles, industrial chemicals
and standard electric and electronic products. They have relatively high capital
requirements, complex technologies, with moderate levels of R&D but advanced
engineering and design skills and large scale production. High-technology
manufactures are complex electrical and electronic products, aerospace products,
24
precision instruments, fine chemicals and pharmaceuticals. They call for advanced
manufacturing capabilities, large R&D investments, advanced technology
infrastructure and close interaction between firms, universities and research
institutions (Ministry of Finance, 2004).
2.2.5 National Bureau of Statistics Classification
Recently, the National Bureau of Statistics divides business firms into 14 categories,
namely, agriculture, hunting and forestry; fishing; mining and quarrying;
manufacturing; electricity, gas and water; building and construction; wholesale and
retail trade; hotels and restaurants; transport, storage and communication; financial
intermediation; real estate, renting and business activities; public administration and
defence; health and social work and other community, social and personnel. This
existing classification is further extended to the national policy.
2.3 Theoretical Literature
Developing and less developed economies currently strive to boost micro enterprises
and small enterprises especially those that exist within a cluster. This struggle to boost
these micro enterprises and small enterprises are in line with the current global
concern and paradigm shift for sustainable development. Three appropriate theories or
models that underpin this move are the growth pole, the dual economy and the
sustainable development models. It is noteworthy that this current study is not entirely
focused on microfinance effect on enterprises growth and profitability per se but on
the microfinance sources for these Micro and Small Enterprises (MSEs), and their
effects on profitability, in other words, it is a study on capital structure. It deals with
the importance of financing choice to MSE’s profitability. Financing choice raises
particularly important research and policy questions for enterprises. Micro and Small
enterprises (MSEs) promotes micro and small scale investments that may end up
generating sufficient revenues from otherwise unrealized market activities while
yielding a return on the investment.
Financing choice involves a tradeoff between risk and return to
maximize shareholder wealth (Berger and Bonaccorsi di Patti, 2006). The objective of
an optimal financing choice for any enterprise is therefore, to have a mix of debt,
preferred stock, and common equity that will maximize shareholders wealth. For
example, changes in financial leverage affect enterprise value. A lower debt ratio can
25
enhance the rate of return on equity capital during good economic times. On the
contrary, a higher debt ratio increases the riskiness of the enterprise’s earnings stream.
One of the important financial decisions confronting an enterprise is the choice
between debt and equity. The seminal paper dealing with irrelevance of debt in capital
structure for determining enterprise value by Modigliani and Miller (1958) included a
number of assumptions — one of which was absence of corporate tax. Subsequently,
when Modigliani and Miller (1963) factored corporate tax in the model, it was found
that theoretically, the value of an enterprise should increase with debt because of
higher interest tax shield. But monotonic increase of debt for higher tax shield
increases bankruptcy cost especially when profitability of the enterprise is low and
fluctuating. This leads to ‘trade off’ theory of capital structure that postulates an
optimum debt level or target level, where the marginal increase of present value of tax
saving is just offset by the same amount of bankruptcy cost.
This section in addition to the growth pole, the dual economy and the
sustainable development models therefore, reviews trade off, agency cost hypothesis
and pecking order theories of capital structure and relates them to MSEs. Details of
these theories are reviewed below.
2.3.1 The Growth Pole Theory
The main tenet of Perroux's (1950) growth pole hypothesis is that a growth pole is 'a
place of passage of forces, which attracts men and objects to it and also repels
them'. It is a centre 'from where centrifugal and centripetal forces operate'.
Boudville (1966) had polarized a region which is characterised by the dominance
of a regional centre (growth space) to which all flows, such as, goods, services,
capital, ideas or political allegiance are predominantly directed. The regional
centre or growth centre links a heterogenous continuous area into inter-dependent
and inter-regional units. According to Lasuen (1969), the spatial investment-
strategy of growth centers purport to advance developmental efficiency and
equality goals, and have thus become the predominant investment policy strategy in
many countries, especially, the developing ones.
Basically, it is held that "growth does not appear everywhere at the same
time; it manifests itself in points or 'poles' of growth; with variable terminal effects
for the economy as a whole" (Perroux, 1950). In a specifically geographic sense, a
growth centre has been defined as '... an urban centre of economic activity, which can
26
achieve self-sustaining growth of the nation' (Mergos, Papadaskalopoulos,
Christofakis, Arseniado and Kalliri, 2004). Thus, initially, growth is held to be
concentrated at a matrix of favourable points, and subsequently the growth impulses
so generated are transmitted to the surrounding area - 'the growth space'. Hence,
according to Mergos et al (2004), '...the spatial incidence of economic growth is a
function of distance from a central city... The growth potential of an area situated
along an axis between two cities is a function of the density of interaction
between them…’ The growth potential of a region is thus held to be closely related
to the 'intensity of interaction’ between the growth centre and its surrounding regions.
Indeed, it has been argued that 'the spatial structure of a region and the size and
spacing of its towns may be the crucial factors in explaining regional potential'
(Lasuen, 1969), hence, the popularity of the concept in developing nations, including
Nigeria.
A crucial aspect of the growth centre concept is the idea that growth generated
in the growth centres will spread to their hinterland. The spread mechanism may take
the form of stimulation of food production for urban industrial markets; increased
production of industrial raw materials for processing industries; employment
opportunities for any surplus rural labour following agricultural mechanism within the
growth-space; financial remittances to the rural areas by migrant workers; diffusion of
innovations into growth space; and subsidiary investments made by rich firms located
at the growth centre in surrounding regions (Lasuen, 1969).
It is also argued, however, that there is an opposing set of backwash effects including
‘the migration of the educated, the skilled, the professionals, and the technical
workers from the hinterland to the growth centre and consequent adverse changes on
the former’s skill mix; the diversion of savings that might have been used
productively in the hinterland; the displacement of any embryonic industries that
might exist in the hinterland, and the stronger relative pull of the growth centre on
new locators...’ (Otero, 1999). Thus, powerful backwash effects may, in fact, 'erode'
the economy of the surrounding regions rather than stimulate growth. There is a
constant interplay of spread and backwash effects with the net result that the
hinterland is either impoverished or enriched depending on the strength of spread
effects (Otero, 1999: 20).
27
The logical implications of this for policy making is that any growth-centre
strategy must devise mechanisms for stimulating strong spread effects, while at the
same time cushioning the effects backwash forces. In view of the role played by urban
growth centre in the spread of innovations, a growth-centre strategy may substantially
raise a region's capacity for the spread and adoption of innovations. However, it is
important to stress that preliminary research ought to be conducted so as to identify
the major constraints on the spread and adoption of innovations in the region
concerned, as mere creation of a set of growth centres in a region may not necessarily
remove all the obstacles to the acceptance of new ideas and technology. Isolated
growth centres, however powerful in generating growth, may not bring about
transformation, but will rather parasitize on the hinterland (Otero, 1999:20).
The main attraction of the growth centre concept and its variants as a planning
strategy is the recognition that market forces alone often create spatial inequalities in
economic development and there is often the need for a deliberate policy of
intervention to correct this trend. The strategy advocates the identification and
creation of growth centres of different orders in any space economy which will help
speed up and even out development across space. As a development planning
strategy, it has been used in many countries, especially the developing ones (Otero,
1999:21). According to Kudiabor (1974), the Ghanaian government used it and
designed a four-tier hierarchy of growth centres in the economy as a strategy of rural
development. This comprises: (a) rural development service centres, (b) growth
centres at the district level, (c) growth centres at the regional level and (d) growth
poles at national level.
Industrial/enterprise clusters are a typology of a growth pole. In Nigeria, the
Federal Government's Integrated Rural Development Approach comprises
Agricultural Development Projects or the World Bank Projects; the Farm Settlement
Schemes; the River Basin and Rural Development Approach; and the Local
Government Reform of 1976, were all deliberate interventionist planning policies
aimed at developing the rural areas based on the diffusion and growth centre models.
As a result of the 1976 Local Government Reform, for instance, 301 local government
headquarters emerged as new lower order growth centres that would facilitate a more
even and faster grassroots-oriented development. Similarly, the Agricultural
Development Programme (ADP) or the World Bank Projects (WBP) and lately, the
28
River Basin and Rural Development Authorities' Projects (RBRDAPs) were designed
to serve as growth centres from where ideas, techniques and innovations in agriculture
would diffuse to the wider hinterland.
In all, there has been much variation in the performance of these projects, but
many of them have enjoyed limited success (Kudiabor, 1974). This is because the
projects lacked an essential ingredient in rural development planning. The main
impact of the schemes has been 'implosive' rather than the ultimately desired
'explosive' growth (Otero, 1999). The growth centres have proved to be 'parasitic'
rather than being 'generative' because they were not tuned properly to the needs,
interests, aspirations and capabilities of the local people. Rather, the process has
further heightened inter-regional inequalities instead of levelling them up.
In the same vein, Kudiabor (1974) had seriously criticised the growth centre
strategy or the development 'from above' paradigm, which had its roots in neo-
classical economic theory. The logic of the growth centre strategy is that productive
investments should be concentrated in urban-industrial centres so as to take advantage
of the external economies, labour specialization and cumulative causation processes.
It is argued that from these dynamic growth centres, development would ‘trickle
down' or diffuse to the rest of the spatial economic system.
Questioning the idea, Kudiabor (1974), further pointed out that these spread
mechanisms are very slow in effecting substantial changes in the rural sector because
of the fundamental weaknesses of interaction in the communication field between the
rural and urban centres. Moreover, a matrix of 'backwash effects' usually reduces the
beneficial influence of any spread effects. The distinct failure in Nigeria of the spatial
policy of concentrating investments and power in a few places so as to gradually
transform the surrounding regions has led to a search for more effective strategies.
In line with objectives 1 and 2 of the study, it is imperative to energise
industrial clusters as “growth poles” or centres of industrial experiments for
interventions. Understanding the existing credit processes to the operators and their
limitations would inform and determine new and more effective strategies to be
adopted in making the industrial clusters “growth poles” in name and indeed. Since
micro-credits to such clusters positively affect the poor, women and Small Scale
Enterprises (SSEs), such a framework will make the SSEs contribute effectively
29
towards economic growth which will enhance the attainment of MDGs and ultimately
lead to sustainable development.
Michael Porter “Clusters” Theory of Competitive Advantage
An economic definition of a city is an area with relatively high population density that
contains a set of closely related activities. Firms often also prefer to be located where
they can learn from other firms doing similar work. Learning takes place in both
formal relationships such as joint ventures, and informal ones, such as from tips learnt
in evening social clubs or over lunch. These spillovers are also agglomeration
economies, part of the benefits of what Alfred Marshall called “industrial districts”
and they play a big role in Michael Porters “Clusters” theory of competitive
advantage (Todaro and Smith, 2009:608). Firms located in such industrial districts
also benefit from the opportunity to contract out work easily where an unusually large
order materializes. Thus, a firm of modest size does not have to turn down a big job
due to lack of capacity, an arrangement that provides “flexible specialization”.
Furthermore, firms may wish to operate in well-known districts for the marketing
advantages of locating where consumers know to get the best selection (Todaro and
Smith, 2009:328).
Another interesting sample of the new, post-neoclassical genre of international
trade modes is contained in Micheal E. Porters’ fundamental departure from the
standard, neoclassical factor endowment theory that posits a qualitative difference
between basic factors and advanced factors of production.
The study argues that standard trade theory applies only to basic factors like
undeveloped physical resources and unskilled labour. For the advanced factors which
are more specialized and include highly trained workers with specific skills and
knowledge, resources such as government and private research institutes, major
universities, leading industry associations and industrial clusters, standard theory does
not apply. Porter (1990: 675-676) concludes that:
The central task facing developing countries is to escape from the straitjacket of factor – driven national advantage...where natural resources cheap labour, locational factors and other basic factor advantage provide a fragile and often fleeting ability to export...and are vulnerable to exchange rate and factor cost swings. Many of these industries are also not growing; as the resource intensity of advanced economies falls and demand becomes more specialized...Creation of advanced factors is perhaps the first priority.
30
It is a well-known fact that some economies, like the four Asian Tigers (Taiwan,
South Korea, Singapore and Hung Kong), have succeeded in transforming their
economies through purposeful effort from unskilled labour to skilled labour and to
capital – intensive production. Other Asian countries, notably China and the MIT
countries of Malaysia, Indonesia and Thailand, are also following in their footsteps.
This is also true of the current four rapidly developing and large “BRIC” countries:
Brazil, Russia, India and China (World Economic Forum et al, 2007:7-8). However,
for the vast majority of poor nations including Nigeria, the possibility of trade itself
stimulating similar structural economic changes is more remote without the
application of judicious development policies, which include pragmatic economic
policies on industrial clusters.
Understanding the dynamics of industrial clusters in the South East of Nigeria
will provide the framework of interventions needed to upgrade the operations of firms
within the clusters, especially skill upgrade, firm expansion (vertical and horizontal),
network and establishment of industrial estates, parks and training institutes. The
essence is to increase the social capital and the external economies coming from such
centres. It also provides stakeholders with defined roles and responsibilities and
evaluation of such and how they impact on the activities of the operation in such
locations. This theory supports and amplifies our research objectives 3 – 4 which set
out to assess the parameters used in providing micro-credit support, the commitment
of stakeholders, willingness and commitment of these stakeholders to the sustenance
of MSEs in the south East.
The Classical and Neo-Classical Model
The proponents of the model (Boeke, 1953; Lewis, 1954; Ranis and Fei, 1961; and
Keynes, 1936) argue that the growth of an economy whether rural or urban, is a
function of capitalist investment and employment of labour. Because of the fact that
capital tends to flow into sectors characterised by high rates of return and high
marginal productivity of capital while labour similarly moves into a sector
characterized by high wage rates, the classical and neo-classical proposition stipulates
that the promotion of economic development in the rural areas should involve
measures which will raise the rate of return to capital investment and the earnings of
labour.
31
To a certain extent, the classical and neo-classical model has some relevance
to industrial cluster development and urbanization in a developing country, such as
Nigeria, where emigration of labour and capital from agriculture is usually attributed
to much lower return to these factors of production in rural areas than in urban
investments. Nevertheless, the model has a number of obvious limitations.
First, it ignores the importance of improved quality of labour as a factor in
economic development, especially, since it is well known that in both the advanced
and developing countries, agricultural and economic development are positively
related to the quality of the labour force. Second, the model ignores the role of
community service and infrastructures, which by generating external economies,
account for high rate of return to capital investment. Third, the model places
exaggerated emphasis on factor and input prices as determinant of investment and
growth, thereby ignoring the role of institutional and organizational arrangements.
Finally, the model fails to take into consideration the crucial role of technology,
which by shifting the production function upwards to reduce costs and increase the
rate of return to capital investment (Otero, 1999).
2.3.2 The Dual Economy Models
The dual economy models (classical, neo-classical and post-Lewisian), stipulate that
the typical less-developed country is characterised by the existence of two distinct
sectors, namely, the modern sector and the traditional (rural) subsistence sector. While
the modern sector is market oriented and uses considerable capital equipment and
technology, the subsistence sector produces for family consumption and it relies on
non-purchased inputs, such as, family labour and land for production. Unlike the
modern sector, the subsistence sector is also characterised by absence of savings and
capital formation.
Briefly, in the original Lewisian model (Lewis, 1954; Ranis and Few, 1961),
industry via capital accumulation provides the 'engine of growth'. The agricultural
sector is important but plays a supportive and passive role in the growth sense by
merely providing a pool of unlimited cheap unskilled labour for use by industry
(Todaro and Smith, 2009). Agriculture also supplies cheap food to the urban industrial
dwellers. From the foregoing, the development process in the classical Lewisian
scheme consists of the progressive enlargement of the capitalist industrial sector.
Thus, in a labour surplus economy, aggregate employment increases as capital
32
formation increases in the industrial sector. In such a scheme, the agricultural sector
continues to play a passive role provided it is a source of cheap unlimited labour. But
when cheap unlimited labour is exhausted, agriculture now imposes a limit to the
expansion of the capitalist industrial sector. The increase in wages causes profits to
decline and consequently, capital accumulation and employment will fall (Todaro and
Smith, 2009).
In neo-classical dualism (Jorgcnson, 1961; Dixit, 1969; and Zarembka, 1970),
the agricultural sector is no longer the passive supplier of food and unlimited cheap
labour. Rather, it plays a more active role since steady-state equilibrium in a dualistic
economy depends on the rate of agricultural output per man. Thus, enlargement of the
industrial sector is not at the expense of the agricultural sector, as in the basic
Lewisian theory, but depends on investment in, and hence, expansion of agriculture.
The post-Lewisian dual economy is characterized by the availability of an unlimited
cheap labour and unlimited cheap land. In such an economy, capital accumulation
plays the classic role of being the 'engine of growth', but for steady growth,
agriculture must be commercialised - a process which requires considerable
investment by government in the agricultural sector as in Nigeria (Otero, 1999).
Given the above characteristics of the two sectors, the formulators of the dual
economy models had no difficulty in prescribing it as the most appropriate
development strategy for developing economies. This approach consists of
concentrating resources in the dynamic, commercial modern sector and withdrawing
resources from the subsistence sector for this purpose. It was believed that this
strategy would ensure cumulative growth of incomes, employment and rapid
structural transformation of the underdeveloped economies. Indeed, Ranis and Feith;
(1961) were at pains to emphasize that as development advanced in the modern
sector, a time would come, when surplus labour would cease to exist in the
subsistence sector. At this point, government would undertake measures to raise
labour productivity on the subsistence sector in an effort to prevent inflationary prices
of farm products from putting a damper on the process of industrialization of the
urban areas.
Although the two-sector models are simple, roughly in conformity with the
historical experience of economic growth in the West, and highlight some basic
relationships in dualistic development, they have three assumptions, which are at
33
variance with the realities of migration and underdevelopment in most contemporary
Third World Countries (Todaro, and Smith, 2009).
First, the models implicitly assume that the rate of labour transfer and
employment creation in the urban (capitalist) sector is proportional to the rate of
capital accumulation; the higher the growth rates of the modern sector, the faster the
rate of new job creation. But what if surplus capitalist profits are reinvested in more
sophisticated labour-saving capital equipment rather than duplicating the existing
capital as it is implicitly assumed in the two-sector models?
The second assumption of the models, at variance with reality, is that 'surplus'
labour exists in rural areas while there is full employment in the urban areas. Most
contemporary research indicates that almost exactly the reverse is true in most Third
World countries (including Nigeria). There is substantial open unemployment in the
urban areas but little general surplus labour in rural locations (Todaro, 1977), because
of disguised unemployment in peasant farming. The third unreal assumption of the
models is the notion of the continued existence of constant real urban wages until the
point where the supply of rural surplus labour is exhausted. One of the most striking
features of urban labour markets and wage determination in developing countries has
been the tendency for these wages to rise substantially over time, both in absolute and
relative to the average rural incomes, even in the presence of rising levels of open
unemployment.
According to Otero (1999), as a guide to rural development, the models have
very serious shortcomings. First, the models do not give an accurate representation of
the structure and performance of a typical underdeveloped country. There are no
countries where the agricultural (subsistence) sector is characterized by absence of
saving, capital formation and growth. It is true that compared to the small and fast
growing industrial sector, the savings and capital formation are quite small but this is
not to say that there are no savings at all in the sector as the models portray (Gaile
(1978).
The dualistic models have a partial view of the relationship between the two
sectors. For example, by concentrating on capital accumulation in the industrial
sector, the models portray an incomplete interaction between agriculture and industry.
But a complete interaction between the two sectors has three components, namely; the
problem of capital accumulation, the problem of agricultural output, and the 'market
34
surplus' problem. Only the problem of capital accumulation was tackled by the
models, particularly, the Lewisian version (Otero, 1999). The models concentrated
emphasis on the industrial sector and this means, in essence, that the basic issue of
optimal resource allocation between agriculture and industry for maximum overall
growth remained unanalyzed.
Second, Mergos et al (2004) queried the suitability of the models when
applied to Africa in general, and Nigeria in particular. His basic objection is that the
dual-sector models' assumptions do no simply fit the facts; and for planning purposes,
any policies based on the theory derived from such assumptions, will produce
erroneous results. An example of such assumption is the key Lewisian notion of
unlimited cheap labour. Nicholas (1969) argued further that the growing urban
unemployment in Africa only superficially resembles unlimited labour supply; but in
essence, only voluntary unemployment is allowed in the Lewisian model. By contrast,
Nicholas (1969) view of the urban unemployment situation in Nigeria, presumably,
strengthened by the Callaway School Leaver unemployment hypothesis is more of the
Keynesian involuntary type (Boudville, 1966). The Callaway School Leaver problem
seemingly weakened the link between the industrial labour force and the agricultural
sector because the surplus labour is not endogenous to the industrial sector.
Third, the authors of these models have a narrow conception of development
as a process of concentrating resources on already developed urban areas. As the
experience of most developing countries shows, such a strategy does not lead to
development because the resulting neglect of the rural areas where the majority of the
population dwells creates a situation where food and raw material shortages, low
income and inflation of food prices, adversely affect both demand and cost structure.
This, therefore, impede the process of industrial development. In addition, the
concentration of efforts in the dynamic urban sector, in line with the prescriptions of
the dualistic models, causes a gap in the earnings of urban and rural resources and
contributes to the outflow (migration) of capital and labour resource industries from
the rural to urban areas. The effect of this is massive unemployment in urban areas,
tremendous demand for urban social services, and the provision of scarce funds from
productive investments to the provision of costly urban social services (Gaile (1978).
Fourth, the application of the surplus labour theory in Helleiner’s Land-
surplus model used to explain the secular expansion of export crop production in
35
Nigerian during the first half of the century (Helleiner, 1960). One of Helleiner’s
objections to the surplus labour theory is that, for a class of tropical countries typified
by Nigeria, agriculture is historically the ‘prime mover of economic growth’ through
expansion of agricultural exports. This is an apparent contrast to the Lewisian theory
in which the growth process is pivoted on the expansion of the capitalist industrial
sector through capital accumulation.
Fifth, the dual economy models assign a very restricted role to agriculture. In
the opinion of their formulators, the role of agriculture is to serve the ends of
industrialization via the provision of cheap food, cheap raw materials and the release
of labour and other resources. It is not realized that a strategy of cheap food, cheap
raw materials and cheap labour has adverse effects on rural purchasing power and can
seriously determine the capacity of agriculture to play the very limited role prescribed
for it.
Sixth, the models generally mislead policy makers in the underdeveloped countries by
exaggerating the capacity of urban industries for cumulative growth (Gaile, 1978).
This emphasis rests on assumptions regarding entrepreneurial ability of urban
industrialists, the capacity of urban industrialists for savings and investments of
profits, and the availability of worthwhile and profitable investment projects in the
urban areas of the underdeveloped countries. However, the development experience
of most less-developed countries bears testimony to (i) the scarcity of real
entrepreneurial talents in these countries, (ii) the inability of most urban industries to
make substantial profits despite their monopoly of the domestic markets, (iii) the very
small value added in a number of manufacturing industries, (iv) the tendency for most
of the profits to be sent away as dividends to foreign shareholders, and (v) the failure
of industries to train a sizeable number of local skilled people and generate
employment (Gaile, 1978).
Finally, when one takes into account the labour-saving bias of most urban
technological transfer, the widespread non-existence of rural 'surplus' labour, and the
tendency for urban wages to rise rapidly even where substantial urban open
unemployment exists, the dual economy models can be seen to offer limited analytical
and policy guidance for the Third World unemployment and migration problems
(Todaro, 1977). Kofi (1974) observed that the rural sector was neglected because
everyone was pre-occupied with wage employment in keeping with the Lewisian
36
model. According to Kofi (1974), 'Lewis Dual Theories' have failed in helping to
absorb the unemployed. Nevertheless, the models do have some redeeming analytical
value in that they do, at least, emphasize two major elements of the employment
problem - 'the structural and economic' differences between the urban and rural
sectors, and the central importance of the process of labour transfer which links them
together (Olatunbosun, 1975).
Even though Nigerian's rural development policies and programmes right from
the colonial period to date lacked clearly stated theoretical orientation, the strategies
have largely been in line with the Lewisian prescriptions. The recognition of the
existence of differences between the urban and rural areas and the perception of the
need to bridge the gap between the two sectors, all indicate a tacit acceptance of the
basic tenets of the dual sector models. The concentration of development projects in
the urban centres, which has been the case in the country in accordance with dual
economy models, has resulted in the rapid expansion of the modern industrial (urban)
sector. But this expansion has not been enough to absorb the unemployed rural
migrants. Rather, the situation encouraged rural-urban migration causing spiralling
demand for limited urban employment and created a situation of urban unemployment
or underemployment. Even though the greater proportion of those who migrated from
the rural areas into the urban areas remain jobless and do not usually share in the
transfer of resources from the rural sector, they often prefer to remain in the cities
because urban misery is better than rural woes (Olatunbosun, 1975).
These arguments as interesting and useful as they appear to be, do not offer
any deliberate contradiction that the basic element of dual economy model (classical,
neo-classical and post-Lewisian) is in tandem with the realisation of objectives 3 and
4 of the study, which take root in the sustenance of MSEs. Since we have identified
effective provision of microfinance to Enterprise Clusters (ECs) as a framework for
industrial growth, this model is supporting sustainable development of the dualistic
rural and urban areas which involves economic empowerment, income and
The marginal benefit of further increases in debt declines as debt increases while the
marginal cost increases, so that an enterprise that is optimizing its overall value will
focus on this trade-off when choosing how much debt and equity to use for financing.
Modigliani and Miller in 1963 introduced the tax benefit of debt. Later work led to an
optimal capital structure which is given by the Trade-off theory. According to
40
Modigliani and Miller (1963), the attractiveness of debt decreases with the personal
tax on the interest income. An enterprise experiences financial distress when the
enterprise is unable to cope with the debt holders' obligations. If the enterprise
continues to fail in making payments to the debt holders, the enterprise can even be
insolvent. The first element of Trade-off theory of capital structure considered as the
cost of debt is usually the financial distress costs or bankruptcy costs of debt. It is
important to note that this includes the direct and indirect bankruptcy costs.
Trade-off theory of capital structure can also include the agency costs from
Agency theory as a cost of debt to explain why companies do not have 100% debt as
expected from Modigliani and Miller (1963). 95% of empirical papers in this area of
study look at the conflict between managers and shareholders. Others look at conflicts
between debt holders and shareholders. Both are equally important to explain how the
Agency theory is related to the Trade-off theory of capital structure.
The direct cost of financial distress refers to the cost of insolvency of a
company. Once the proceedings of insolvency starts, the assets of the enterprises may
be needed to be sold at distress price, which is generally much lower than the current
values of the assets. A huge amount of administrative and legal costs are also
associated with the insolvency. Even if the company is not insolvent, the financial
distress of the company may include a number of indirect costs like cost of
employees, cost of customers, cost of suppliers, cost of investors, cost of managers
and cost of shareholders.
The enterprises may often experience a dispute of interests among the
management of the enterprise, debt holders and shareholders. These disputes
generally give birth to agency problems that in turn give rise to the agency costs. The
agency costs may affect the capital structure of an enterprise. There may be two types
of conflicts - shareholders-managers conflict and shareholders-debt-holders conflict.
The introduction of a dynamic Trade-off theory of capital structure makes the
predictions of this theory a lot more accurate and reflective of that in practice.
41
2.3.5 Pecking Order Theory (Pecking Order Model)
The theory is an approach to defining the capital structure of a company as well as
how the business goes about the process of making financial decisions. Pecking Order
Theory was first suggested by Donaldson in 1961 and it was modified and developed
by Nicola Majluf and Stewart C. Myers in 1984. The theory seeks to explain how
companies prioritize their financing sources. The general idea is that companies will
tend to take the course of least resistance, obtaining finance from sources that are
readily available, and then steadily moving on to sources that may be more difficult to
utilize.
While the specifics of the Pecking Order Theory are somewhat involved, the
general idea can be explained by using the example of a local business entity. When it
comes to financing the operation, the business is likely to make use of its internal
resources first, such as using funds in a savings or other interest bearing accounts to
manage operational costs or to order more stocks or raw materials for use in the
operation. When this first line of financing is exhausted or not available for some
reasons, the business will then turn to lenders or investors as a means of generating
the funds needed to keep the company going. When no other options are available, the
business may choose to make use of the equity found in any assets held by the
business.
It postulates that the cost of financing increases with asymmetric information.
Financing comes from three sources, internal funds, debt and new equity. Companies
prioritize their sources of financing; first preferring internal financing, and then debt,
lastly raising equity as a “last resort”. Hence, internal financing is used first; when
that is depleted, then debt is issued; and when it is no longer sensible to issue any
more debt, equity is issued. This theory maintains that businesses adhere to a
hierarchy of financing sources and prefer internal financing when available, and debt
is preferred over equity if external financing is required (equity would mean issuing
shares which meant 'bringing external ownership' into the company). Thus, the form
of debt an enterprise chooses can act as a signal of its need for external finance.
The Pecking Order Theory is popularized by Myers and Majluf (1984) when
they argue that equity is a less preferred means to raise capital because when
managers (who are assumed to know better about true condition of the enterprise than
investors) issue new equity, investors believe that managers think that the enterprise is
42
overvalued and managers are taking advantage of this over-valuation. As a result,
investors will place a lower value to the new equity issuance.
Pecking order theory starts with asymmetric information as managers know more
about their enterprises prospects, risks and value than outside investors. Asymmetric
information affects the choice between internal and external financing and between
the issue of debt and equity. Therefore, there exists a pecking order for the financing
of new projects.
Asymmetric information favours the issue of debt over equity as the issue of
debt signals the board’s confidence that an investment is profitable and that the
current stock price is undervalued (where stock price is over-valued, the issue of
equity would be favoured). The issue of equity would signal a lack of confidence in
the board and that the board feels the share price is over-valued. An issue of equity
would therefore lead to a drop in share price. This does not, however, apply to high-
tech industries where the issue of equity is preferable due to the high cost of debt
issue as assets are intangible.
Tests of the Pecking Order Theory have not been able to show that it is of
first-order importance in determining an enterprise's capital structure. However,
several authors have found that there are instances where it is a good approximation
of reality. On the one hand, Fama and French (2002) and Myers and Shyam-Sunder
(1999) found that some features of the data are better explained by the Pecking Order
than by the Trade-off theory. Goyal and Frank showed, among other things, why
Pecking Order theory fails where it should hold, namely, for small enterprises where
information asymmetry is presumably an important problem.
The Pecking Order Theory explains the inverse relationship between
profitability and debt ratios as shown below.
Enterprises prefer internal financing.
1. They adapt their target dividend payout ratios to their investment
opportunities, while trying to avoid sudden changes in dividends.
2. Sticky dividend policies plus unpredictable fluctuations in profits and
investment opportunities mean that internally generated cash flow is
sometimes more than capital expenditures, and at other times less. If it is
more, the enterprise pays off the debt or invests in marketable securities. If it
43
is less, the enterprise first draws down its cash balance or sells its marketable
securities rather than reduce dividends.
3. If external financing is required, enterprises issue the safest security first. That
is, they start with debt, then possibly hybrid securities such as convertible
bonds, then perhaps equity as a last resort. In addition, issue costs are least for
internal funds, low for debt and highest for equity. There is also the negative
signaling to the stock market associated with issuing equity and positive
signaling associated with debt.
In comparing the two theories, the main difference between them is the potential
benefit from debt in a capital structure. This benefit comes from tax of the interest
payments. Since the Modigliani and Milner’s capital-structure irrelevance theory
assumes no taxation, this benefit is not recognized, unlike the trade-off theory of
leverage where taxation system and its benefit are recognized.
2.3.6 Agency Theory
Agency theory explains the processes in determining capital structure to consider the
costs associated with the difference in interest between the owner and the
management company. Jensen and Meckling (1976) suggested the presence of two
potential conflicts in agency theory (also known as the agency problem), namely the
conflict between shareholders and creditors and a conflict between shareholders and
the management. The reduction in the cost of conflict in the agency problem is called
the agency cost. According to the Eng and Mak (2003), potential agency problem will
be even greater if managers are not involved in the company's share ownership so that
managers use policy on their own outside of the policy for the purposes of private
shareholders. If managers participate in the ownership of the shares of the company,
managers are much more concerned about the interests of shareholders because
managers also want the dividend distribution as shareholders.
Agency Costs
According to Jensen and Meckling (1976), agency conflicts lead to agency costs
which manifest in three types:
44
a. Monitoring Cost: cost that is spent by the principal to monitor the activity and
behavior of management, such as paying auditor to audit the financial report,
and insurance to protect company’s assets.
b. Bonding Cost: cost that is spent by the company to give an insurance to the
shareholders to make sure that managers would not do anything that will harm
the company
c. Residual Loss: cost that is spent by the principal to influence manager’s
decision to increase the shareholder value
Agency cost happen when agent’s interest and principal’s interest are not aligned,
because managers assumed to be self-interested and this will reduce the shareholder
value (Jensen and Meckling, 1976).
2.3.7 Micro Enterprises in Developing Economy
Microenterprises are defined as unorganized, privately owned manufacturing/service
enterprise whose work force ranges between two and ten employers (Adebayo et
al:2001).Therefore, micro enterprises provide income and employment for significant
proportion of workers in rural and urban areas by producing basic goods and services
for rapid growing population. Adelaja (2005) declared they account for more than
60% of all regional enterprises and up to 50% of paid employment. Micro enterprises
development is seen as a broad-based growth expected to improve the well-being of
poor men and women by providing significant income and employment generating
opportunities, and by encouraging indigenous investment. Consequently, there is an
increasing policy focus on the need to strengthen entrepreneurship and the
contribution of micro enterprises to attain economic growth with equity, as well as in
addressing gender and poverty reduction issues (Billsborrow: 1994: Kpakol: 2005;
Akinboyo: 2007). Internationally, according to Eyiuche (2005), micro enterprises
development can be found to contribute to any or all of following objectives:
• Promoting national and regional economic development goals.
• Promoting empowerment, particularly in creating new jobs.
• Alleviating poverty and assisting those who are disadvantaged.
• Facilitating the transition to a market economy.
• Promoting equity and addressing uneven development.
• Promoting democracy and the development of civil society.
45
Okonjo-Iweala (2005) holds the view that the critical development issues in
Nigeria today revolves around the need to design and implement policies and
strategies for an efficient, competitive and diversified industrial system which creates
employment, generates wealth and thus, eradicates poverty. To achieve these goals, a
strong entrepreneurial base is an essential driver of growth and prosperity in a modern
economy. It is therefore, the vision of government to entrench a culture that values
and supports entrepreneurship such that everybody with talents, potentials, drives and
courage to succeed in business should be given the opportunity irrespective of their
gender. This is because micro enterprise empowers the populace and provides greater
possibilities for the use of available local raw material for vertical and horizontal
linkages (Okonkwo: 1996). The development of micro enterprise would greatly
improve the economy and the welfare of Nigerians by minimizing the incidence of
marginalization and improvement of greater part of the society. New business brings
new or improved products and services to consumers, thereby increasing competition,
and challenges to existing business hence, improving their performance. It, therefore,
becomes imperative that micro enterprises are the answer to the poverty-bedeviled
economies.
2.3.8 Micro and Small Enterprises/Industrial Clusters
Literature abounds on the progress made on academic and policy research on
industrial clusters, in particular the ways in which clustering enhances
competitiveness and promotes growth. There is an implicit assumption that such
growth translates into rising levels of employment and incomes, with improving
conditions and standards for labour engaged in clustered SMEs. Yet, for the most part,
such issues are rarely explored. In particular, relationships between clustered firms
and workers are insufficiently analyzed.
Industrial clusters can make a potential important contribution to this agenda.
Not only do they enhance the ability of small firms to compete in global markets but
also promote sustainable employment and incomes and thus, better the situation for
the working poor. This assumption is grounded in the notion that SMEs account for a
significant proportion of manufacturing employment in developing countries, and that
they are predominant in labour intensive sectors with a propensity of employment of
the working poor. Clusters, as a distinct form of industrial organization, allow SMEs
to overcome constraints on their size, and offer possibilities of collective action in the
46
face of common problems. Such benefits are brought into sharper perspective by the
process of globalization which, while offering new opportunities for developing
country enterprises and workers, inter alia, raises the vulnerability of small firms, and
those who work in them, to external shocks. Clusters are also relevant in that they
offer potentially important benefits of developing social capital and social protection
through local trust-based relations. Such forms of social assets can be of significant
advantage to firms and to labour. At the same time, it is important to recognize the
heterogeneity between clustered firms, and amongst labour within clusters, and to
recognize that the gains from clustering can be unevenly distributed.
Determinants of the Cluster Growth Path
The growth path of enterprise clusters is determined by five major factors:
• Size of the market and nature products.
• The stock of economies of scale and scope.
• The rate of upgrading.
• The nature of the supporting institutions.
• The form of collective efficiency. Size of the Market and Nature of Products
The size of market is reflected on the number of participants and its
geographical spread. Market size is an important factor for cluster development
because the scale of product demand determines the growth rate of the producer. At
this end, the impacts of clustering in Africa are limited because of low demand for
their products caused by low income. Relative growth in African clusters is due to
positive changes in money income, because small enterprises can gain from such
changes without increasing their own efficiency (Pederson, 1997: 26). Such growth is
related to what Humphery and Schmitz (2000) and also Kaplinsky and Readman
(2001) described as "immiserising growth" because increase in money income does
not mean increase in real income. Policy measures are required to induce the
increase on real income in Africa. McCormick (1998) further argued that interregional
restrictions on movement of goods and people, and underdeveloped distribution systems
undermine market development in Africa.
The quality of the products offered to final consumer plays an important role to
the growth of any SME cluster. The traditional quality standard of any product is
47
measured by the value of the products' characteristics. This implies that the
durability, the reliability, and the conformity to specification and safety standards of the
products are considered as important criteria. In recent times the issue has also shifted
not only to ensure the quality of end-product, but also of being able to verify the quality
control process that has been used, and the quality values that have been installed at each
and every stage of production (Nadvi, 1999; Kaplinsky and Readman, 2001).
Product quality is a function of process and functional upgrading. Improved
efficiency implies that the product quality has been raised through better application of
factors and management on one side, and that the firms can provide documented,
verifiable and acceptable quality assurance for their buyers on the other. Some
entrepreneurs visited in Enugu still do not engage in intensive learning processes in
production engineering and investments. Furthermore, organisational deficiencies
observed in the firms are due to what Schmitz (1982) and Hansohm (1992) described as
limitation in advanced planning in African production system. This leads to unsystematic
production processes and poor product quality standards. The costs and benefit
analyses are ignored, therefore, resulting in a high cost of production and waste of
scarce resources.
The Stock of Economies of Scale and Scope
The ability to penetrate larger market is important for SME cluster dynamics. Reaching
larger market will not only induce proportionate increase in productivity but also lead to
increasing returns. Increasing returns are the by-product of economies of scale. Such
returns arise when an increase in all production inputs results to a more than
proportionate increase in output (Schmitz, 1997). Stocks of economies of scale that
induce increasing returns are measured by the ability of the firms to reach more markets
and to acquire more capital goods, effective managerial skills and opportunity to enjoy
division of labour in the production. African small enterprises are found to be
unorganised in production activities. Low investment on capital goods and lack of
division of labour in production make the enterprises to remain weak (Hansohm, 1992;
McCormick, 1998).
Economies of scope on the other hand arise due to the efficiency of the firm to
engage in more than one activity successively. There are three kinds of economies of
scope namely, concurrent scale economies; coordinative scale economies; and technical
know-how and working skills sharing economy (McCormick, 1998). Concurrent scale
48
economies are the economies gained by enterprises in diversifying their products with
the least possible output costs (e.g. fabricating bakery ovens/palm kernel nut crackers).
This aspect of an economy is commonly found in Nigerian machine makers (Oyeyinka,
2001) but generally still very weak in Africa. Coordinative scale economy implies that
the enterprise have the organisational ability to integrate factors of production in an
effective production system. Sharing of technical know-how and skilled workers are
benefits gained by small firms clustering in developing countries because individual
firms cannot alone afford the costs of high technical skilled workers or invest in capital
goods (Brautigam, 1997).
The Rate of Upgrading
Control over the market only cannot sustain the profitability of SME clusters in the long
run. Profitability of the firms in the cluster can be sustained firstly, through the nature of
internal process that encourage learning. Secondly, by acquiring specific comparative
advantage or competence, this is important in maintaining the firms' competitiveness.
The third factor is the path chosen by the firms, because changes in any firm are path-
dependent (Kaplinsky and Readman, 2001). Thus, through upgrading, these three factors
are rapidly identified in order to meet the needs of markets quicker than the rivals.
Upgrading is important for firms. The processes are systemic in nature and are achieved
effectively when firms are linked together. It is important to understand the concept of
value chain in order to get true picture of upgrading. The relationship between value
chain and upgrading are based on identifying not only the key problems in entire
production organisation but also the methods through which upgrading can occur. An Up-
grading can occur at each stage of the chain as shown below in Figure 2.1:
Figure 2.1 Simple Illustration of the Value Chain Source: Kaplinsky, R. and Readman, J. (2001), Integrating SMEs in Global Value Chains, Towards Partnership for Development, Vienna: UNIDO.
Value chain is the process which is required to bring a product or service from the
conception, through the intermediary phases of production, then delivery to the final
consumers and finally disposed off after use (Kaplinsky, 2000). Upgrading can be
Design
Production
Marketing
Consumption
Recycling
49
done in different chains namely, process upgrading, product upgrading, functional
upgrading and chain upgrading. Process upgrading occurs when SMEs can improve
effectively by organising the internal working process of entire production system
better than their local rivals. Product upgrading entails ability to introduce new
products or improve old products faster than the local rivals. Functional upgrading
takes place in firms where the productivity is increased by improving the quality of the
management skills and the organisation of the labour factor. Chain upgrading in turn
means moving to the new value chains. An example is moving from household
products to industrial input products (cf. Kaplinsky, 2000; Humphery and Schmitz;
2000 Kaplinsky and Readman, 2001). Kaplinsky and Readman (2001) further warned
that rate of upgrading should not be more than the competitors; otherwise, it will lead to
immiserising growth. This is an important case particularly for African clusters,
because the market in the region is underdeveloped and competition is very low.
The policy that aimed at improving quality standard for example, should first
consider how to stimulate market competition in the region. SMEs development in the
region can be effective only when the market is developed and growth can be
sustained in the long run when the capability to upgrade is developed.
[
The Nature of Institutions Supporting the Cluster
It is now generally accepted in economic discussions that institutions are important
not only in industrialisation process but also to development in general. Clustering
can foster economic exchange quickly. Therefore, it is important that a third party
is available in order to support the transactions. Furthermore, the quality of the
service rendered by the third party should be dynamic and in line with the growth-path of
the cluster. To understand the importance of institution in cluster development, it is
important to make brief overview on the role of social capital in economic development.
Social capital is defined as a capital jointly owned by parties in relationship and
is not divisible. None of the parties has exclusive right of ownership of the capital. It is
the final arbiter of competitive relations, because it generates positive interactions
within a firm, among groups of firm, within an industrial district in order to reduce
transaction costs and propagate growth. It is a critical variable and has influence on the
mobilisation of other factors of production such as financial capital and labour, crucial in
producing public goods (Burt, 1992; Putnam, 1993). The voluntary and spontaneous
50
cooperation existing within a given community depends on stock of inherited social
capital. It can be referred to as "moral resources", which are resources that increase in
value when they are frequently used in transactions, but depreciate when they are not
applied. This is called social capital of trust (Hirschman, 1985). Trust manifests as a
result of the existing cooperation among a set of actors in order to maximise their
current desires (Sabel, 1992). The more it is displayed in a relationship, the greater a
mutual confidence is developed. Social capital is then classified in two forms –
collective and specific social capital.
Collective social capital exists when the cooperative norm is embedded in
the production of common goods of various kinds by group of firms or a community. The
costs and benefits of deflecting or cooperating are determined by internal and external
sanctions existing in the community (Putnam, 1993). Furthermore, it is defined as the
mutual cooperation that sustains the survival of economic relations, repeated market
transactions and inter-firm transactions in a community or in an industrial cluster
(Gambetta, 1988; Barr, 2001). Such capital is open for all members in the community. It is
a by-product of common values that allow participants to obtain gains from
transactions. The capital possesses considerable value such as trust, which has impact
on reducing the need for various forms of monitoring. Monitoring the actors’
behaviours and transactions usually implies not only considerable direct costs, but has
also the negative effects in generating distrust in business community (Dasgupta, 1988;
Dei Ottati, 1994). Social capital can play an important role in integrating the economic
policy makers in finding solutions to economic problems in any region and can also
induce effective socio-economic problem solving (Putnam, 1993; Brown and Ashman,
1996; Gsanger, 2001). Conflicts between heads of institutions and heads of corporate
organisations have led to negative economic growth in Enugu state region. For example,
the vegetable oil factory, Nachi in Enugu, was closed because of management problems
on the one side and conflict among the shareholders on the other. Thus, it renders
(US$ 40 million) project to be useless as well as making roughly 500 employees to be
jobless.
Specific social capital is based on personal reputation necessary to sustain repeated
transactions. The effect of reputation is recorded in the economic exchange of self-
enforcement agreements that are not backed by explicit contracts. The desire to continue
successful business exchanges induces the partners to avoid conducts which might
51
interfere with attending such objective. This implies that the reactions of the other
parties are integrated in general business reputation (Raub and Weesie, 1990). Personal
reputation is very effective when the economic activities are linked because information
about past performances of an actor can be easily accessed. Both collective and specific
social capital can then be substituted by institutional trust when the society become
more heterogeneous and the volume of business transactions increase and become more
complex. Zucker (1986) and North (1990) acknowledged the importance of institution as
the third party that can maintain the rules of the game in transactions by enforcing
contract agreements and prevent opportunistic behaviours. In Nigeria, such institutions
exist, but are very weak, and are, thus, undermining private sector development.
Fafchamps (1996) observed that enforcement of commercial contracts is problematic in
Ghana due to institutional problem and unstable economic conditions under which the
firms operate.
The Nature of Collective Efficiency Existing in the Cluster
Recent literatures in developed countries have explained how the concept of collective
efficiency is being used to the success of exporting cluster concept in developing
countries (Schmitz, 1995; Nadvi, 1996; Rabellotti, 1997; Humphrey and Schmitz, 1998
McCormick, 1998; etc). Such efficiencies are likely when enterprises operate in a close
proximity. Collective efficiency is defined as the competitive advantages derived by
small firms from local external economies and the joint action. There are two sets of
benefits believed to arise from clustering of producers. First are the efficiency gains, in
other words, external economies that firms can reap simply by being located near each
other (Marshall, 1890; Mishan, 1971; Nadvi, 1996; McCormick, 1998). The second is
the gains for firms acting together to achieve some desired ends (Nadvi, 1996; Schmitz,
1997; McCormick, 1998).
External economies are not new in economic discussions. Marshall made a lead
way without definition by pointing out the importance of localisation of industries and the
significance of concentration of specialised industries in a particular locality. According
to Marshall, concentration of small firms of similar character can help to improve
efficiency and competitiveness (Schmitz, 1995: 535). The question is what are the
gains associated with externality? Krugman (1991) analysed the gains associated with
agglomeration of industries in geographical location. Such gains include pooling of
52
labour, quick access to intermediate inputs and technological spillovers. In this context,
clustering facilitates easy supply of inputs, pooling of specialised skills workers and
rapid diffusion of know-how and ideas (Schmitz, 1995). Further investigations show
that externalities alone cannot sustain a cluster growth-path because such gains were
incidental by-product of some other firms' legitimate activities. Nadvi (1996) made a
distinction between external economies and joint action. He used the term active
collective efficiency to emphases on the importance of deliberate actions needed to
improve performance.
Joint actions are some deliberate and strategic actions that do not oppose
market competition but needed to sustain the growth of the cluster. The actions are
deliberately and jointly pursued in order to strengthen the growth, to overcome impeding
constraints or to induce a positive turning point of the cluster. Some empirical results
have shown that joint action plays an important role in SME upgrading (Kaplinsky, 2000;
Kaplinsky and Readman, 2001); in product quality standard to meet export condition
(Nadvi, 1996); in transaction costs reduction (Brautigam, 1997). The question is how
effective is collective efficiency in African clusters? As Pedersen (1997) stressed, the
gains from collective efficiency can be achieved through growing market. Expansion
requires overall collective efficiency in absolute terms through specialisation and
vertical integration. In this context, the growth of the African clusters tends to be
limited because of the partial monopoly they enjoy in the local market without increasing
their efficiency. Furthermore, collective efficiency in African clusters cannot be effective
due to the quality of human capital.
Clustering sets into motion, a range of potential benefits that can directly
affect the poor, as waged workers, home workers, own-account workers as well as
small entrepreneurs. This can be through externality gains, joint action, and local
social capital.
1. External Economies: Agglomeration benefits may not only raise efficiency but
they may also make it possible for smaller firms to access markets through a division
of labour. Economies of scale and scope can allow individual small firms to survive
by specializing in specific tasks within the production process and by accessing
specialist skills and services and inputs from within the cluster. Similarly, external
economies that arise from agglomeration can result in a significant lowering of costs
in accessing inputs, labour and information. Again, this can help small firms to
53
survive and grow in ways that would be infeasible if they operate in isolation.
Knowledge spill-overs found in clusters may also make it feasible for small firms to
acquire new know-how, new products and new production techniques that could not
be obtained through markets. Clustering can thus enhance the individual capacities of
small firms to access markets, and acquire skills, knowledge, credit and information.
2. Joint Action: Clustering can also promote collective capacity. In addition to
the direct economic benefits that passively accrue to small firms by virtue of their
location within the cluster, there are significant gains from active local collaboration
that clustering can set into motion. Local cooperation, both between individual firms
and through cluster institutions can strengthen the ability of clustered actors to
compete in markets, by sharing costs and by engaging in joint tasks such as shared
marketing and distribution. Moreover, such forms of joint actions can help clustered
firms confront external threats and challenges. These external challenges are
pronounced as local clusters engage in global markets. Globalization, namely, the
increasingly rapid flows of capital, goods, peoples, and ideas across borders, can help
bring local actors into global markets and enhance their income earning opportunities.
Globalization can also potentially increase the vulnerability of local actors to sudden
changes in global demand, in trading rules and in financial stability. Thus, with
globalization, there is also greater instability and vulnerability. Clusters can help
SMEs reduce their exposure to exogenous shocks and risks. Local institutions such as
business associations and collective service centres can help clustered firms acquire
the skills and the technical abilities to reduce their vulnerability to the exigencies of
globalization, thereby enhancing the well-being of workers and producers.
3. Social Capital: Local initiatives and local collaboration are themselves often
strengthened by local social capital. Clusters tend to have a strong presence of social
capital, which can take the form of shared norms and/or common identities. This can,
potentially, help reduce vulnerability, help flows of knowledge within the cluster,
provide the basis to strengthen local institutions, and help firms upgrade. There is the
need to consider how social capital works to do this, and in particular how it may
mitigate against poverty. Social capital can also serve to raise local competition as
much as it helps local cooperation. Divisions within communities can reduce local
cooperation and serve to worsen poverty impacts. Also, there is the need to note the
54
different ways in which social capital works for different types of firms (large versus
small) and workers (men versus women, or high versus low castes). Finally, it is
important to recall that social capital is not static. Its forms and operations can change
over time. In particular, it is affected by economic change (and growth) within the
cluster. Clusters can set into motion processes that improve the ability of small firms
to improve market access through externality gains and joint action. This can raise
incomes for those who work in clusters, raise their assets and capabilities and have a
significant impact on lowering levels of poverty and social deprivation. Joint action,
often cemented through social capital, can improve local networks and support
mechanisms that help reduce future risks and vulnerability to shocks.
Clusters are dynamic. They evolve as a consequence of local and external
linkages. A key process of change within clusters comes about through local
upgrading. This results in enhancing human capital, improving technological
capacities for firms and enhancing capabilities for workers and small producers. There
has been substantial recent discussion on upgrading in clusters (UNIDO, 2002;
Humphrey and Schmitz, 2003) - which raises the competitiveness of firms, improves
their ability to appropriate a larger share of value added, and advances their position
within global value chains through distinct forms of upgrading -product, process and
function. The significance of cluster upgrading for poverty cannot be overemphasized.
Raising human capital improves productivity and leads to rising incomes and wages
as well as sustaining employment growth. Moreover, it is only through a systematic
pattern of upgrading, often aided through national innovation and learning systems
that clusters are able to compete in global markets on the basis of the high road to
growth.
This requires a stronger explanation of why the high road to growth (as
opposed to increasing competition on wage costs) might have a more positive impact
on poverty reduction in the medium to long-term. But upgrading not only relies on
local and external linkages, it also has consequences for such linkages. That is to say,
the process of upgrading is often determined by the nature of governance of ties
within the cluster as well as ties between cluster actors and external players within the
value chains in which clusters are inserted. Global lead firms can exercise significant
power in determining the actions of local firms, and thus the autonomy of clustered
firms to engage in tasks that enhance their technical and resource capacities.
55
Moreover, external ties can over time erode local linkages and weaken cluster
governance. This implies that clusters have to be seen in the context of dynamic
trajectories – where certain types of producers and workers gain and others lose. For
example, as firms upgrade does the demand for new skills affect all workers
uniformly, or do some categories of workers (say women) become marginalized by
not being provided the requisite training and skills?
A strong nexus exists amongst cities, urbanization, industrial clusters and
development. To a large extent, cities ‘over-formed’ because they provide cost
advantage to producers and consumers through what are called agglomeration
economies (Todaro and Smith, 2009).
Agglomeration economies come in two forms namely, urbanization and
localization economies. Urbanization economies are effects associated with the
general growth of a concentrated geographic region. Localization economies are
effects captured by particular sectors of the economy such as finance or automobiles,
as they grow within an area. Localization economies often take the form of backward
and forward linkages. When transportation costs are significant, users of the inputs of
an industry may benefit from a nearby location to save on these costs. This benefit is a
type of forward linkage. In addition, firms of the same or related industries may
benefit from being located in the same city, so they can all draw from a large pool of
workers with the specific skills used in that sector or specialized infrastructure. This is
a type of backward linkage. Workers with specialized skills appropriate to the
industry prefer to be located there as well as that they can readily find a new job or be
in a position to take advantage of better opportunity (Todaro and Smith, 2009).
It may not matter so much where such industrial clusters are located as they
somehow got an early start in a place, perhaps because of a historical accident. For
example, in the United States, many innovative computer firms located in Silicon
Valley, Califonia, simply because other firms are located there. Analogously,
suppliers of shoe firms are located in the Sinos Valley in Southern Brazil and in
Guadalajara in Mexico, because so many shoe firms located in those regions. Some of
the benefits are gained by the fact of location in what is called “passive collective
efficiency”. But other benefits must be achieved through collective action, such as
developing training facilities or lobbying government for needed infrastructure as an
56
industry rather than as individual firms. This is “active collective efficiency” (Todaro
and Smith, 2009).
Again, not all of the efficiency advantages of an industrial district are realized
through passive location. Others are actively created by joint investments and
promotional activities of a firm in the district. One such factor determining the
dynamism of a district is the ability of its firms to find a mechanism for such
collective action. While the government can provide financial and other important
services to facilitate cluster development, social capital is also critical, especially
group trust and a shared history of successful collection action, which requires time to
develop (Todaro and Smith, 2009).
2.4 Empirical Literature
Over the years, academics and evaluators have conducted many studies on the impact
of microfinance, especially microcredit. Yet, the average effect is still unknown
because nearly all studies to date share similar shortcoming. For instance, when
studying complex social systems such as families and communities, it is extremely
hard to use a correlation to prove causation. If affluence and microcredit go hand-in-
hand, does that mean that the better-off borrow more or that borrowing makes people
better-off?
Mano, Iddrisu, Yoshino and Sonobe (2011) examined how micro and small
enterprises in Sub-Saharan Africa become more productive and the impacts of
experimental basic managerial training. The performance of MSE clusters is
especially low in Sub-Saharan Africa. While existing studies often attribute the poor
performance to factors outside firms, problems within firms are seldom scrutinized. In
fact, entrepreneurs in these clusters are unfamiliar with standard business practices.
Based on a randomized experiment in Ghana, the study demonstrated that basic-level
management training improves business practices and performance.
Loca and Kola (2013) analyzed how and to what extent microfinance services
in Albania have affected the entrepreneurial activity, and how these entrepreneurial
companies can benefit by using it. In order to do so, the study focused on different
aspects of microfinance impact to firms credited by MFIs in Albania. The
methodology combined the application of both quantitative and qualitative tools
including questionnaire on different indicators addressed to beneficiaries. Qualitative
information was collected through Focus Group interviews and Semi-structured
57
interviews to understand the situations that people faced how they used and perceived
microfinance, especially enterprises served by microfinance sector in Albania. The
results indicated a strong relationship between being MFIs clients and the change in
enterprise profits over the last 12 months. The study concluded that lending practices
have a positive effect on entrepreneurial activities in increasing employee salaries, in
job creation or generating employment, in increasing profit margin of enterprises
served as shown by the cases and models analyzed. This is consistent with objectives
1 and 2 of this study.
Furthermore, Kessey (2014) examined micro credit and the promotion of
small and medium enterprises in informal sector of Ghana. The study showed that
among SME entrepreneurs who repay credit on monthly basis there is a default rate of
2. 8 per cent while those who repay annually have default rate of 6.5 per cent. The
study recommended that it would be necessary for Micro Finance Institutions to
extend to other products such as business advisory products and social products to
SMEs, to raise their productivity and improve upon their performance. This was based
on an observation that only Micro Credit would not take SMEs out of poverty in
developing countries. This is in line with objective 4 of this study.
Wanambisi and Bwisa (2013) investigated the effects of Micro Finance
Institutions lending on micro and small enterprises performance within Kitale
Municipality. This study adopted a descriptive survey research with the use of
frequency tables, pie charts and figures. The association between microfinance
lending and MSE performance variables was established through Chi square and
correlation tests at 95% significance level. A multivariate logistic regression was used
for significant bivariate variables at 95% significance level. The study discovered that
the amount of loans was significantly and positively related with performance of
MSEs in Kitale Municipality. The study therefore recommended that Micro Finance
Institutions should reduce the period required for MSEs to participate in training and
group formation to facilitate speedy access to MFI loans. It also recommended that
the amount of loan given by MFIs to MSEs should be increased to enable the MSEs
grow to medium scale enterprises. This is consistent with objectives 1 to 4 of this
study.
58
Ali, Peerlings and Zhang (2012) examined clustering as an Organizational
Response to Capital Market inefficiency for Micro-enterprises in Ethiopia. The study
showed that industrial clusters, through specialization and division of labor can ease
the financial constraints of micro enterprises, even in the absence of a well-
functioning capital market. By using data from microenterprises of the handloom
sector in four regions of Ethiopia, the study found that clustering lowers capital entry
barrier by reducing the initial investment required to start a business. This effect is
found to be significantly larger for microenterprises investing in districts of high
capital market inefficiency, indicating the importance of clustering as an
organizational response to a credit constrained environment. The findings highlighted
the importance of cluster-based industrial activities as an alternative method of
propagating industrialization when local conditions do not allow easy access to credit.
Ocholah (2013) determined the effect of micro financing on the performance
of women owned enterprises in Kisumu City, Kenya. Specifically, the study
determined the effect of microfinance on productivity, profitability and growth and
expansion of women owned enterprises. The study population comprised 3000
registered women businesses, out of which a sample of 341 was drawn. Clustering,
simple random and purposive sampling approaches were applied. Questionnaire and
interview were used to obtain primary data. Quantitative data was analysed by use of
both the descriptive and inferential statistics. The results indicated that micro
financing in sufficient quantities would have greater effect on profitability,
productivity and growth and expansion of women owned enterprises. The study is
significant in reformulating women business credit policies, for improving credit
services to entrepreneurs.
Mersland & Strøm’s (2007) study focused on the performance and corporate
governance works. The study employed panel data analysis and regression analysis to
find the impact of board characteristics, ownership type, competition and regulation
on financial measures like ROA, yield, and outreach, to name a few. It found that the
presence of female Chief Executive Officer (CEO) has huge impact on the size of
loans provided.
Thapa (2007) worked on comparison between cross-continental MFIs in terms
of financial sustenance. The paper also supported that MFIs increasing their
59
accessibility to poor cannot be self-sufficient as far as the factor of sustainability is
concerned.
Similarly, Hartungi (2007) studied the various factors involved in the success
of MFIs in Indonesia. The major activities identified were dynamic adaption of MFI
with the local conditions, and the usage of the technology (information technology as
specific) in the outreach to the people. The study underlined that the active
involvement of the MFI employees and increase in transparency helped in better
functioning of MFIs in Indonesia. It concluded that prior intimation of the incentives
to the client and employees provided better efficiencies for the MFIs. This is
consistent with objective four of this study. Also, the role of MFIs as evident in the
above empirical result is similar to the objective three of this particular study. Thus, a
basis upon which this study can examine the extent to which control and evaluative
measures employed by the micro finance providers in ensuring the sustenance of
MSEs is established.
Kim & Kim (2008) in their research paper used descriptive analysis as the first
step to understand the characteristics of the ranges, variance etc. The second stage
consisted of factor analysis to attain the important factors which could estimate the
maximum variance. The final stage consisted of regression analysis to understand the
relationship between the dependent and independent variables in South Korea. This
format helped the authors in understanding the characteristics of the process involved
in a better manner.
Moreover, Petridou & Glaveli (2008) in their study found that the
implementation of the microfinance results in the improvements of the lives of the
society who utilizes the scheme. The study found that the earning capabilities of the
women folk in the rural sector also increased through the implementation of
microfinance. It further found that literacy, or the knowledge of scheme was affected
as microfinance increases, and that the women could understand the economics of the
present dynamic world. The study further concluded that the increase in income and
consumption from the lower section of society resulted in the improvement of the
society in general.
In a paper by Rodman (2009), it is discovered that there was no changes in
household income, spending, or diet between 1–2 years after microfinance has been
obtained. It found that borrowers did appear to cut back on some types of spending,
60
including paid helpers, health insurance, and home improvements, perhaps because of
belt-tightening at the beginning of new, loan-enabled investments. In the same vein,
in India, there was no impact on total income, spending, health, or school enrollment
rates after some 15–18 months after credit was offered. However, it was found that
microcredit boosted profits for families that already had a business, more land or more
working-age or literate women. In Kenya the study used diaries rather than a one-off
follow-up survey to track subjects’ financial transactions. Despite the small sample of
122 people that were randomly offered an account, and only 67 took it, the study
found significant impacts on the recipients (Remeyi and Quinoess 2000). Rodman
(2009) adopted similar research methodology of random sampling with descriptive
and inferential statistical analysis to arrive at the same findings.
In their own study, Crombrugghe et al. (2008) used the regression analysis to
understand the relation between the financial self-sustenance and operational self-
sustenance in India. The independent variables considered in the paper were yield,
cost per customer, age etc. The paper found that there is no need for increasing the
size or monitoring costs of loans in order to meet the financing costs. Their findings
informed objectives 4 of this study, which seeks to ascertain the level, nature and
extent of relationship and willingness of stakeholders in micro-financing provision
and the sustenance as well as performance of MSEs clusters.
In the Nigerian context, not so many works have examined the effect of micro
finance of enterprise clusters as a strategy for enterprise performance. However, some
related works including Osotimehin et al., (2012) examined the challenges and
prospects of micro and small scale enterprises development in Nigeria. Most business
enterprises in Nigeria by classification are grouped under micro and small scale
enterprises. This study was conducted in Lagos State, South Western Nigeria with the
use of questionnaire and interview to gather relevant data that was statistically
analyzed. The study opined that, the phenomenal growth of small and medium
enterprise in Nigeria is mainly due to the people’s quest to be self-employed and not
because it is easy to establish or manage. Financial constraints and lack of managerial
skill hamper the efficient performance of micro and small scale enterprises in Nigeria.
It recommended that government and other non-governmental organization should
regularly organize seminars for potential and actual small and medium enterprise
operators on how to plan, organize, direct and control their businesses. It also
61
recommended that micro, small and medium enterprises operators’ should device
effective marketing strategies and good management customers relations at all times.
Babajide (2011) investigated the effects of micro-financing on micro and
small enterprises (MSEs) in South West Nigeria. The study used survey data of 443
micro enterprises and validated the reliability of the instruments with Cronbach alpha.
The results suggested that, micro financing enhances the survival of micro and small
enterprises but the enhancement was not sufficient for growth and expansion of such
micro and small enterprises. Also the study showed that micro-financing is not
financially effective and practiced in Nigeria as many Micro Finance Banks (MFBs)
grant more individual loans than group-based loans, thereby increasing their running
cost and putting their portfolio at a risk.
Also, Irobi (2008) compared the performance of loans granted to small and
medium enterprises by banks with that of micro-credit institutions in Nigeria, using
Ondo State as a case study. The study employed descriptive statistics method to
analyse the data collected through primary source. The paper revealed that the
average repayment rate of 92.93% for banks was higher than the 34.06% for the
micro-credit schemes. That is, the banks performed at much higher levels than
microcredit schemes. Based on the findings, it was recommended that there should be
stern efforts by the credit institutions in screening of loan applications, monitoring of
approved loans and enforcing loan contract. Thus, government should provide the
basic infrastructural facilities, which unnecessarily increase the cost of doing business
in the country.
Furthermore, Suberu et al. (2011) assessed the impact of microfinance
institutions on small scale enterprises in Nigeria. The Simple random technique was
employed in selecting the small scale enterprises used in the research. The findings
revealed that, a significant number of the small scale enterprises benefited from the
microfinance institution loan even though only few of them were suitable to secure
the required amount needed. Interestingly, it was also found that the microfinance
institutions have grown phenomenally in the last ten years. Majority of the small scale
enterprises acknowledged positive contributions of microfinance institutions loan
towards promoting their market excellence and overall economic company
competitive advantage. Rather than tax incentives and financial supports, the study
recommended that the government should provide adequate infrastructural facilities
62
such as electricity, good road network, and training institutions to support small scale
enterprises in Nigeria.
Akinbola et al., (2013) examined the extent to which micro financing has
contributed to entrepreneurial development and found out the extent to which
marketing techniques have been employed for effective and efficient delivery of their
services. The study employed questionnaire to collect data from bank customers. The
study was limited to the customers of ten micro finance banks located in Ojo Local
Government Area (LGA) of Lagos State, Nigeria. The result suggested that micro
finance banks have been able to contribute significantly to the entrepreneurial
development in Nigeria. The descriptive statistics showed that some marketing
techniques have not been fully employed by micro finance banks. This is consistent
with the major objective of this study.
Olowe et al. (2013) investigated the impact of microfinance on SMEs growth
in Nigeria. The study was restricted to Ibadan metropolis and used a total of 82 SME
operators that constituted the sample size. Pearson correlation coefficient and multiple
regression analysis were used to analyze the data. The results from this study showed
that financial services obtained from MFBs have positive significant impact on MSEs
growth in Nigeria. The results also revealed that duration of loan has positive impact
on SMEs growth but not statistically significant. It also showed that high interest rate,
collateral security and frequency of loan repayment could cripple the expansion of
SMEs in Nigeria. The paper recommended that MFBs should lighten the condition for
borrowing and increase the duration of their customers’ loan and also spread the
repayment over a long period of time.
On the other hand, some authors have challenged the positive effects of
microfinance on poverty reduction and alleviation. For instance, Adam (2007)
observed that microfinance institutions in Nigeria have grown phenomenally, driven
largely by expanding informal sector activities and the reluctance of commercial
banks to fund emerging microenterprises. But, the number of beneficiaries of
microfinance institutions is an insignificant proportion of the people in need of
microfinance services. It has been estimated that formal microfinance institutions only
service less than one million clients in a country where over 70% of the country’s
population live below the poverty line (Dahiru and Zubair, 2008). The results also
63
suggested that micro-financing is unsuccessful at reaching the group most prone to
destitution, the vulnerable poor.
Essien et al (2013) came closest to this study by examining both formal and
informal credit sources and the role of social capital. The study examined credit and
receipt and enterprise performance by small scale agro-based enterprise in the Niger
Delta region of Nigeria. It used a multi-stage sampling technique in selecting 264
agro-based enterprises and 96 agro-based that accessed informal and formal credit
received by the enterprise. The results revealed that gender, age, and social capital are
significant determinants of informal credit while gender, education, age, size and
collateral are significant determinants of formal credit.
The findings from the above empirical literature are in line with the focus of
this study and major objectives, thereby providing enough empirical evidence with
which to compare the findings of this current study.
2.5 Summary of the Review of Related Literature
A review of theoretical literature have shown that the growth pole theory holds the
views that growth does not appear everywhere at the same time; it manifests itself
in points or 'poles' of growth; with variable terminal effects for the economy as a
whole. This supports the importance of starting from somewhere like a cluster of
enterprises since the theory is also of the opinion that growth generated in the growth
centres will spread to their hinterland. The spread mechanism may take the form of
stimulation of food production for urban industrial markets; increased production of
industrial raw materials for processing industries; employment opportunities for any
surplus rural labour following agricultural mechanism within the growth-space;
financial remittances to the rural areas by migrant workers; diffusion of innovations
into growth space'; and subsidiary investments made by rich firms located at the
growth centre in surrounding region.
The Dual Economy Models (DEMs) stipulate that the typical less-developed
country is characterised by the existence of two distinct sectors, namely, the modern
sector and the traditional (rural) subsistence sector. These models have been criticised
by the fact that they have a partial view of the relationship between the two sectors
and their suitability when applied to Africa in general, and Nigeria in particular is still
doubtful.
64
Sustainable Development Model (SDM) believes that in order for
development to continue indefinitely, it should balance the interests of different
groups of people, within the same generation and among generations, and do so
simultaneously in three major interrelated areas namely, economic, social and
environmental. The models have been applauded by most scholars for the fact that
sustainable development integrates economic, social and environmental issues in
development for both intra-generational and inter-generational interests, needs and
equity. These theories therefore, apply to this study as it related to the objectives of
the study in terms of the poles of growth, production function, characterization of
sectors, and affinity to develop as the study examines micro finance performance and
enterprise performance of clusters.
Trade-off theory raised an important issues relating to experience in terms of
dispute of interests among the management of an enterprise, debt holders and
shareholders. These disputes (shareholders-managers conflict and shareholders-debt-
holders conflict) generally give birth to agency problems that in turn give rise to the
agency costs. The agency costs may therefore affect the capital structure of any MSE.
The introduction of a dynamic Trade-off theory of capital structure makes the
predictions of the Trade-off theory a lot more accurate and reflective of that in
practice.
Perking Order model postulates that the cost of financing increases with
asymmetric information which may come from three sources (internal funds, debt and
new equity). The theory suggests that enterprises prioritize their sources of financing,
first preferring internal financing, and then debt, lastly raising equity as a “last resort”.
This has implications based on the ambition of such enterprise by first using internal
financing; when it is depleted, then debt is issued; and when it is no longer sensible to
issue any more debt, equity is issued.
Agency theory, on other hand, explains that in determining capital structure,
there is the need to consider the costs associated with the difference in interest
between the owner and the enterprise management which raises the issue of agency
costs. In summary, the theory argued that agency cost happens when agent’s interest
and principal’s interest are not aligned, because managers assumed to be self-
interested and this will reduce the shareholder value.
65
In the empirical angle, earlier studies about micro-financing have evaluated
whether micro-credit programmes in Nigeria reach the relatively poor and vulnerable
in their operations. Recent studies for Nigeria and other developing countries have
shown evidence of positive impact as it relates to first six out of seven Millennium
Development Goals (MDGs). Studies by Adam, (2007); Irobi, (2008); Wrigth, (2000);
Zaman, (2000); as well as McCulloch and Baulch, (2000) do subscribe to the fact that
microfinance is becoming an effective and powerful tool for income improvement of
the economically active.
At the international scene, there exist related empirical works at country level
and across regions. At the regional level, there exist studies like those of Remenyi and
Quinones (2000) in Asia and Pacific regions, as well as Mano et al., (2011) in Sub-
Saharan region. Country specific studies include; Barnes and Erica (1999), Ellul
(2005), Wang (2010), Wellalage (2012), Cull et al. (2007), Mersland & Strøm’s
(2007), Thapa (2007), Hartungi (2007), Crombrugghe et al. (2008), Kim & Kim
(2008), Petridou & Glaveli (2008), Rodman (2009), Loca and Kola (2013), Zheng
(2013), Sanvicente and Bortoluzzo (2013), Kessey (2014), Wanambisi and Bwisa
(2013), Ali et al. (2012), and Ocholah (2013) who carried out such studies in
Zimbabwe, Indonesia, India, South Korea, Philippines, Kenya, Albania, Ghana, and
Ethiopia.
In Nigeria, related empirical studies include Osotimehin et al., (2012) who
examined the challenges and prospects of micro and small scale enterprises
development in Nigeria, Babajide (2011) investigated the effects of micro-financing
on micro and small enterprises (MSEs) in South West Nigeria. Irobi (2008) compared
the performance of loans granted to small and medium enterprises by banks with that
of micro-credit institutions in Ondo State. And Suberu et al. (2011) assessed the
impact of microfinance institutions on small scale enterprises in Nigeria. Also,
Akinbola et al., (2013) examined the extent to which micro financing has contributed
to entrepreneurial development in Ojo LGA of Lagos State. And, Olowe et al. (2013)
investigated the impact of microfinance on SMEs growth in Ibadan. These studies
were all necessary to the Nigerian society as they looked at micro financing and
enterprise performance from several aspects, and in different regions.
However, this study departs from existing studies as it is targeted at
performance using profits based on the microfinance source. It is not a study that look
66
at how microfinance has affected enterprises in clusters but rather examines how
different microfinance sources (formal, informal and both) have affected the
performance of micro and small enterprises operating in a cluster. Also the study
explores the relationship in the different sectors of economic activities (clusters),
which include production, trade and services. A look at micro enterprise operating in
a cluster will reveal the reality of the spread mechanism. These mechanisms which
may take the form of stimulation of food production for urban industrial markets,
increased production of industrial raw materials for processing industries,
employment opportunities for any surplus rural labour following agricultural
mechanism within the growth-space and diffusion of innovations into growth space.
In addition, the study concentrates on three cities in two states of the South East,
namely Aba, Nnewi and Onitsha. The study equally highlights the social capital that
stands out as a critical determinant to the choice of business in most communities,
especially that Nnewi is known for spare parts and Aba for textiles. Therefore, the
study departs from the economic perspective that most studies are built on to include
psychological and social benefits that contribute to existing knowledge, and stimulate
the debate on the subject.
67
CHAPTER THREE
THEORETICAL FRAMEWORK AND RESEARCH METHODOLOGY
3.1 Introduction
This chapter focused on the theoretical framework guiding the study as well as
research methods, procedures and strategies adopted to realize the objectives of this
study. This included adequate description of research design, data collection
instrument, methods of data collection and analysis.
3.2 Design of the Study
The research design for this work was essentially survey research method with the use
of structured questionnaire administered to selected enterprise clusters in three cities
of South East Nigeria viz. Onitsha, Nnewi and Aba. The instrument used
(questionnaire) consisted of four sections namely, Demographics; Finance and Credit;
Enterprise Association; and Entrepreneurs’ Perception. The questionnaire was
structured in line with the objectives of the study. The 5-point likert scale were
analysed while the average for each question was approximated to the nearest whole
number.
The generated data was tabulated for statistical and econometric analyses to
obtain results and test appropriate hypotheses. The Focus Group Discussions (FGDs)
were employed to confirm and revalidate the information analysed from the
administered questionnaires.
3.3 Data and Sources
The source of data for this study was mainly from primary sources generated through
questionnaire, FGD and personal interviews. The contents of the questionnaire were
structured from available literature with specific inputs from the Small and Medium
Enterprises (SME) center at Enugu and other micro finance institutions visited in the
course of this work. The questionnaire is presented in detail in the annex.
3.4 Population of the Study
Covering all MSEs in South East Nigeria would be cumbersome. Therefore, the
survey only covered selected industrial/enterprises clusters operating at Nnewi,
Onitsha and Aba of South-East geopolitical zone of Nigeria. The choice of the three
cities was based on factors such as geographical proximity and prevalence of cluster
of microenterprises.
68
A three stage cluster sampling was adopted in this study. A sample of primary
unit was selected from different clusters, existing in South-East and that gave rise to
the selected three cities. The second stage was the selection of sample of secondary
units which were chosen from each selected primary units. This stage resulted in the
choice of the following: A.M.E Shoe Makers Cluster for production, Omenma
Traders Cluster for trade and Global Systems Mobile Network (GSM) and Allied
Components Cluster, Aba Central for services, Nnewi Technology Incubation centre
for production, Nnewi Automobile spare parts cluster for trade, and GSM and Allied
Components Cluster in Nnewi, as well as Tinkers Dealers Cluster for production,
Building Materials Cluster for trade; and GSM and Allied Components Cluster in
Onitsha. Finally, a sample of tertiary unit was selected from each selected secondary
unit (nine selected clusters) from the three cities with the help of a sample frame from
the National Association of Small and Medium Enterprises (NASME). The lists of all
the clusters in the three cities are presented in Annex IV.
It is noteworthy that with a three stage sampling, covering a large city may be
impossible. Therefore, such city can be sub-divided into administrative units. The
total number of enterprises located within the city can be determined by first,
selecting a sample of administrative units, then, choosing a sample location within the
selected administrative units and finally, interviewing/administering a sample of
firms/enterprises at the selected location. Details of estimated number of enterprises
across the nine clusters are presented in the Table 3.1 below:
Table 3.1: Estimated Number of Enterprises across selected clusters in South-East
S/No Town/City/State Estimated Number of enterprises 1 Aba 658
2 Nnewi 456
3 Onitsha 880
Total 1994
Source: Enterprise Directory, National Association NASME 2011
3.5 Instruments for Data Collection
The study employed both questionnaires and personnel interviews:
Questionnaire: The questionnaire was designed and distributed to the respondents.
The questions were structured to enable the research obtain data in respect to the
stated objectives of the study.
69
Personal Interview: A guided structured interview was used. The questions were
designed to obtain data on certain specific issues which may not be easily available to
the general public.
Focus Group Discussion (FGD): This is a research method that involves
understanding attitudes and behaviours of the audience. It aimed at ascertaining
audience disposition towards a given issue. The study, therefore, engaged about 15-20
people per each of the selected area or city, cutting across the different sectors of the
study (production, Trade and Services). The essence of a FGD is to elicit qualitative
information from a homogenous group (Nwodu, 2006:132). The study, therefore,
employed the focus group discussion to confirm and revalidate the information got
from the questionnaires that were administered.
3.6 Determination of Sample Size
To calculate the optimum sample size, the study applied the formula used for
determination of sample size for a simple random sampling calculated at 95%
confidence level and 5% standard error.
The formula is:
n =
Where: n = Sample Size
p = Proportion of Positive Response
q = Proportion of Negative Response
ME = Error Margin
Z = Critical Z-value
N = Population size
Calculating an error margin of 2.5% to ensure a larger sample size and solving for “n”
n =
n = 540.46
70
With this outcome, the researcher used 540 as the total sample size.
Using the formula for calculating the proportionate sample size for clusters, the
sample size for the various clusters was determined. The formula is;
nh = Nh x n N
where;
Nn = cluster sample size
Nh = cluster population size
N = total population size
n = population sample size
Based on the population, the various clusters were calculated as:
Aba
naba = 658 x 540 1994
naba = 178.2 ≈ 178
Nnewi
nnnewi = 456 x 540 1994
nnnewi = 123.5 ≈ 124
Onitsha
nonitsha = 880 x 540 1994
nonitsha = 238.3 ≈ 238 The proportionate sample size for the various clusters are presented in Table 3.2
below.
Table 3.2: Sample Size of Enterprises across Clusters in South-East Nigeria S/No Town/City/State Estimated Number of
enterprises Sample Size
1 Aba 658 178 2 Nnewi 456 124 3 Onitsha 880 238 Total 1994 540 Source: Author’s calculation
71
3.7 Validity of the Research Instrument Validity refers to the degree to which an instrument measures what it is supposed to
be measuring (Akuezuilo, 2007, Udo, 2004, Osuala, 2005). This was achieved by
sending the prepared research instrument to experts for vetting in terms of relevance
to the subject matter, coverage of the content areas, appropriateness of language usage
and clarity of purpose.
3.8 Reliability of the Research Instrument
Reliability of the research instrument goes hand in hand with its validity. A research
instrument is said to be reliable to the degree that it measures accurately and
consistently, yielding comparable results when administered in a number of times
(Akuezuile, 2007, Osuala, 2005; Udo, 2004). This was achieved through test-retest
measure of the research instrument administered to 10 entrepreneurs of the clusters.
The values obtained from the surveys were computed using Spearman’s Rank
Correlation coefficient (Spearman’s rho). The Spearman’s Rank Correlation
Coefficient formula is:
p =
where p = spearman’s rank correlation coefficient
d = difference in rank xi and rank yi
n = sample size
With a correlation coefficient above 0.7, the instruments were considered to be
reliable. Validity and reliability are characteristics of good measuring research
instruments aimed at achieving research objectives and answering appropriately
research questions. For the current study, the correlation coefficient was 0.7515 which
confirms the reliability of the instrument utilized for the study (See Annex IV).
3.9 Pilot Survey
The study conducted a pilot survey where 70 of the research questionnaires were
administered randomly to the Management and Members of Staff of the Ministry of
Commerce and Industry; Small and Medium Enterprises Development Agency of
Nigeria (SMEDAN); National Association of Small and Medium Enterprises
(NASME), and selected Microfinance Banks and enterprises in clusters in Nnewi,
Onitsha and Aba.
72
Out of the 70 respondents, 60 questionnaires were correctly completed and
retrieved. The pilot survey was considered as positive response and successful. The
remaining 10, represented the ones that were rejected. They were regarded as negative
response. The percentage of responses and non-responses therefore were 86% and
14% respectively.
3.10 Theoretical Framework
This study used the theoretical framework of Mayoux (1999). It interlinks
Microfinance to Micro and Small Enterprises (MSEs) empowerment (profitability).
Mayoux (1999) identified and linked the three contrasting ‘paradigms’ which are:
financial self-sustainability paradigm; poverty alleviation paradigm; as well as the
feminist empowerment Paradigm. According to Mayoux (2000), ‘profitability’ is a
multidimensional and interlinked process of change in power relations which can
operate in different spheres of life (economic, social, political, and so on) and at
different levels like individual, enterprise, cluster, and so on’. For some authors like
Cheston and Kuhn (2002) profitability is ‘a process of change by which individual,
MSEs, or group of MSEs (cluster) with little or no power, gain the power and ability
to make choices that affect their lives and businesses’. They also pointed out three key
elements of profitability which are ‘change, choice and power’. In relation to that,
Kabeer (1999) saw MSEs profitability as ‘the process by which those who have been
denied the ability to make strategic life choices acquire such ability’. With this regard,
the study pointed out three interrelated dimensions to measure profitability as
resources, socio-economic factors and achievement. According to the study,
‘resources’ include access to capital from different sources and future claims to both
material and social resources which serve to enhance the ability to exercise choice.
The second dimension of ‘socio-economic factors refers to characteristics that
help MSEs operating within a group (cluster) to define one’s goal and act upon them.
It includes the process that affects decision making, negotiation or ‘Power within’.
And then as a result of both resources and socio-economic factors, there is a
dimension of ‘achievement’ which refers to what Kabeer quoting Sen (1985b) called
the potential that people have for living the lives they want, of achieving valued ways
of ‘being and doing’(Kabeer 1999).
Again, Afshar (1998) in defining ‘profitability or empowerment’ supported Kabeer’s
notion of socio-economic factors stating that MSEs empowerment or profitability is
73
something that cannot be done to or for enterprises but has to begin from them -
‘power within’.
For that reason, it has been found by development practitioners that building
MSEs capacity (economically, socially, and politically) is one of the prior activities
on agenda. Then, increasing MSEs especially those operating in a cluster access to
financial services through Microfinance programme has been found as one of the
tools which can lead to wellbeing improvement as well as profitability or
empowerment. But, as Swain and Wallentin (2009) mentioned, not all activities that
lead to an increase in the well-being of an MSEs are necessarily empowering in
themselves. From the same researchers’ point of view, ‘empowering activities’ are
those activities that reflect the changes that MSEs have effectively made to improve
the quality of their lives by resisting the traditions and norms that reinforce inequality.
MSEs operating in clusters are characterized by a different production
function to that of single MSE or other entities. MSEs operating in clusters are
diverse in terms of industrial organization and hence, it is plausible that there are
additional factors that impacted MSEs operating in clusters profitability in addition to
enterprise level specifics such as the source of capital. An empirical approach built on
the above theoretical predictions relevant to MSEs is useful in identifying the impact
of various funding instruments that predict profitability. Literature on MSEs devotes
considerable attention to Trade-off and Pecking Order theories of capital structure and
choices of source of capital.
3.11 Models Specification, Methods of Data Analyses and Results Evaluation Modelling for Microfinance Sources on Profitability (Objectives 1 and 2)
The argument as presented in the theoretical framework in 3.10 above informs the
present study’s focus on impact of different sources of funding on the outcome or
empowerment ― profitability. The study therefore, estimates the following basic
regression:
1 1
N Jn j
ic n ic j ic icn j
X Xα β β ε= −
Π = + + +∑ ∑ …………….………………………………
….3.1 Where outcome is the measure of profitability icΠ of MSE i located in
clusterc , with i =1-N and c =1-3 (Aba, Nnewi and Onitsha);
α is the regression constant;
74
nicX stands for micro finance source(s) variables and amount received;
jicX represents other enterprise level characteristics; and
ic i t icε ν γ µ= + + is the disturbance term with tγ as the unobservable time effect, iν is
the unobservable complete set of enterprise-specific effect and icµ is the idiosyncratic
error. sβ are the coefficients to be estimated. Due to the significant differences that
exist in the clusters, the study tested for potential cluster effects and the econometric
model is therefore expanded as follows:
11 1
N Jn j
ic n ic j ic c icn j
ic i t ic
X X Dα β β δ ε
ε ν γ µ
−− −
Π = + + + +
= + +
∑ ∑…………..……………………………….
………….3.2 In the above model, D denotes the cluster-specific dummy variables (locations of the
cluster e.g. Aba, Nnewi and Onitsha). ic i t icε ν γ µ= + + is the disturbance term with tγ
as the unobservable time effect, iν is the unobservable complete set of enterprise-
specific effect and icµ is the idiosyncratic error. Thus, apart from observed
heterogeneity ( nicX and j
icX ), the model also accounts for MSEs-specific unobserved
heterogeneity and random idiosyncratic errors. The study acknowledges the
possibility of an alternative model, where funding may be assumed to shift or to
evolve in tandem with changing market share. Although this is well-grounded in
the literature on finance, it nevertheless appears less relevant here since we are
using a single data set. Conceptually, market share fails to capture MSEs
characteristics that graduate from various informal arrangements and pre-existing
institutions. Additionally, the market share approach does not allow for changes in
MSEs profitability that may be associated with economies of scale, even if the
growth in market share outpaces the growth of MSEs size.
However, there are other controls or enterprise level characteristics that
determine how enterprises perform which include: financial supports or source of
microfinance (sc) which is the focus of this study: age of enterprise (age); educational
level of the enterprise head (edu); total number of employees (empl); enterprise sector
of activity (a dummy for the three sectors under consideration: production, trade,
services) (sec), capital stock per employee (capem), ownership structure (owns),
75
cluster location (cluloc), and the background (apprentice activity of the entrepreneur)
(soc).
The above factors have theoretical and empirical evidence on their
relationships with enterprise performance (as shown under the a priori expectation).
Enterprise performance is measured with the profit of the enterprises. Given that the
profit shows to what extent the enterprise is actually growing, high output might not
necessarily mean growth of the enterprise if the enterprise equally records high
expenses in terms of production and indirect costs. In order to translate (3.2) into an
expression suitable for econometric analysis, the study adopts an explicit functional
form model with second-order transcendental logarithmic (‘translog’) giving rise to
the following equations classified into two models:
The estimates of the above equation therefore, show the determinants of the choice of
the micro finance providers they most often go to (whether formal or informal). The
significant variables are therefore considered as the main determinants of the choice
of the microfinance source by enterprise clusters.
81
3.12 Assessment of Level of Support of Microfinance Providers for the Sustenance of Profitability of Enterprise Clutters in South-East, Nigeria (Objective 4) The fourth objective of the study aims at ascertaining the level of support of micro
finance providers for the sustenance of the profitability of enterprise clusters in South
East, Nigeria. This was done in three ways. First, the study uses percentages, rates and
pie charts to measure and show the level of support for both formal and informal
financing sources on small scale enterprises in Nigeria, by comparing the number of
those that receive credit from formal sources and those that received from informal
sources. The study then used a 5-point likert scale to measure the perception of
enterprise as regards the level of support from both the formal and informal micro
finances. The 5-point likert scale is analysed such that, the average for each question
is approximated towards the nearest whole number. Then, the approximation
constitutes one of the 5-point scales as originally stated in the question. The
approximated whole number now determines the level of involvement such that 5
show very high involvement and 1 very low involvement. Finally, the study uses
percentages and pie charts to ascertain the extent to which micro finance funds have
expanded the firm’s business.
82
CHAPTER FOUR
DATA PRESENTATION, ANALYSES AND DISCUSSION OF FINDI NGS
4.1 Introduction
This section of the study presents the analyses done with data generated from the
survey in line with the instruments of this study. The study conduct a cross sectional
survey of 540 enterprises across three enterprise clusters in Onitsha, Nnewi and Aba.
Of the 540 enterprises surveyed, 179 of these are based in Nnewi, 180 in Onitsha and
181 in Aba.
4.2 General Enterprise Characteristics and Perceptions
Listed in Table 4.1 are the mean, standard deviation, minimum and maximum values
of selected enterprise characteristics such as average age of the enterprises, average
number of employees that are administrators, average number of employees that are
in operations, average annual sales, average profit, average savings, average capital,
and average micro finance received.
Table 4.1: Summary of Enterprises Characteristics Variable Mean Std.
Deviation Minimum Maximum
Age of the Enterprise 11.3 6.5 1.0 33.0 Approximate number of employees (Administrators)
3.0 2.8 1.0 14.0
Approximate number of employees (Operations)
5.0 5.0 1.0 27.0
Average annual sales (N) 4,371,180.0 9,672,194.0 1,000.0 50,000,000.0 Average Profit (N) 1,834,141.0 4,396,383.0 35,000.0 30,000,000.0 Average savings (N) 412,742.1 1,206,031.0 1,000.0 10,000,000.0 Capital (N) 4,411,885.0 12,400,000.0 50,000.0 100,000,000.0 Average Micro financing (N)
514,984.0 14.7 10,000.0 10,000,000.0
Interest on loan (%) 23.3 376,494.7 5.0 40.0 Value of training Received
329,682.5 376,494.7 - 100,000.0
Source: Author’s
Other indicators include average interest on loan and the monetary value of the
training received. From the table above, the minimum age of the enterprise surveyed
is about 11 year old with the minimum and maximum standing at 1 year and 33 years
of existence respectively. The average age of 11.3 shows that most of these
enterprises have had the experience and may have had the need to borrow from either
83
formal or informal sources. The average number of employees that are administrators
is just 2.45, given that administrators are usually not many, though the maximum
stands at 14.
However, the average number of operatives of the enterprises is approximately 5 with
a minimum of 1 and a maximum of 27. This shows that while some of these
enterprises are small scale with only 1 or 2 employees, others are large with up to 27
operatives. This therefore, offers a good variation of enterprise as the study examines
their credit behavior and access the way it affects enterprise performance which is
measured in this study by profitability.
The enterprises sampled across the three cities equally have huge variations in
their sales, profit, average savings and capital accumulation as deduced from their
standard deviations. The standard deviations are relatively high with capital being the
highest. This emphasizes on the high inequality that exists among micro and small
enterprises in the study area. While the mean average sales is N4,371,180, the mean
average profit is N1,834,141 just as the mean average savings is N412,742.1 with the
mean average capital as N4,411,885. In the same light, the maximum value for sales
is N50,000,000 while the maximum value for profit was N30,000,000 but for savings,
is N10,000,000 and N100,000,000 for capital. Also, the mean average micro
financing is given as N514,984 with a maximum of N10,000,000 which is far lower
than the maximum capital in the study. The mean interest on loan is 23.33%; while
the mean value of training received in the form of micro financing support is
N329,682.5 in monetary terms.
In terms of highest education attended by the enterprise heads (respondents),
the distribution shows 1% with no formal education, 4.6% with primary education,
47% with secondary education and interestingly, 44% and 3.4% with tertiary
education and post graduate studies respectively. In summary, over 90% of the
sampled enterprise heads have either secondary or tertiary education while less than
7% have either primary or non-formal education.
Indicators from the general characteristics of micro and small enterprises
sampled reveals that over 95% of the enterprise heads own the enterprises solely
while less than 4% of these enterprises are jointly owned. This means that about 97%
of the enterprises own their businesses single-handedly, bearing the risk and enjoying
84
the profit. Though some of these enterprises have expanded with many employees,
they remain the sole risk bearers and managers of the business.
In terms of the sectoral compositions of these sampled enterprises, though
majority are sole proprietors, they are equally distributed into different sectors of
production that are classified into three groups namely, production, trade and services.
While 61% of these sampled enterprises are under the trade sector, 11% and 37.2%
are under production and services sectors respectively. It is also observed that some of
the enterprises in the production sector are equally in the trading sector and/or the
service sector. It is therefore evident that more than half of the enterprises are
interested in trading, while the production and service sectors are not much exploited.
Similarly, the distribution in terms of specific activities involved suggests that
based on the type of activity practiced, a greater percentage of the enterprises are
somehow involved in trading only (about 45%), with the next most exploited sector
being the textiles with about 14%, followed by Automobile and furniture and wood
work by 9% each. On the other hand, only 1% of the enterprises are in the chemicals
and plastics sector as well as the wood/paper and pulp industry while 2% are involved
in plants and machineries. However, the survey covers other types of activities like
the shoes and leather products, constituting 5% of the study, foundries,
metals/fabrication is 5%, food is 6% as well as several other types of activities.
It is also observed that though these enterprises are from different sectors of
production and economic activities, they all face the need to borrow and have had
different types of assistance from formal micro financial operatives. Credit assistance
constitutes 67%, technical support 8%, being a financial guarantor 16.4% while
financial advisory services assistance constitutes 1.2%. It is therefore evident that
micro financial institutions are more convenient with giving out credit than any of the
other forms of financial assistance.
Looking at the extent at which the credit source is generally perceived to be
reliable, it is revealed that only 7% believe that their credit source is reliable to a very
low extent and 19% to a low extent. Also18% of the respondents from the sampled
enterprises perceives that credit source is reliable to a high extent while 16%
perceives such reliability to a very high extent. On the average, the study concludes
85
based on this finding (average) that the respondents generally agree that their various
credit sources are reliable.
In terms of distribution of the enterprises that have received credit from
formal, informal and from both sources, the frequency reveals that more enterprises
patronize the informal sources of financing by about 55% while enterprises who
received credit from formal Micro Finance Institutions (MFIs) are about 34%. About
11% of the respondents receive credit from both formal and informal sources.
Challenges faced by these enterprises in terms of borrowing include request for the
loan, requirement, protocol/procedure, interest on the loan and the tenure for payment.
However, it is worth noting that the type and magnitude vary between the formal and
informal sources of finance. Details of such challenges faced by enterprises while
accessing credit as observed during the Focused Group Discussion (FGD) are
presented in Table 4.2 below.
Table 4.2: Perceived Challenges faced by enterprises in accessing micro finance Formal Informal
Challenges %age of the sample
Challenges %age of the
sample Borrowing is costly 83 Can’t afford large credits 66 Request of collateral 76.8 Not reliable 32.3 Request of surety 33.4 So many phone calls 26 High interest rates 72 Takes time to build trust 37.6 Protocol 58.4 Short repayment periods 71 Not straight forward/corny 27 Lack of confidentiality 43.3 Time taking 47 The owner can easily request at anytime 27
Source: Author’s
Analysis of the above table suggests that borrowing credit from formal financial
institutions generally has its advantages and disadvantages from the borrowers’
experience. The challenge faced by the entrepreneurs as highlighted by the
respondents during the FGD is that borrowing from formal institutions is costly with
83% supporting this. Also, 76.8% of the respondents that receive formal credit show
that the collateral requested by formal institutions is the greatest challenge faced. In
addition, the request for surety is a major challenge and set back to borrowing from
formal institutions. 72% of the respondents that receive credit from formal institutions
agree that high interest rate is equally a challenge. Other constraints include protocol
at 58%, being corny and time constraints to finally get the loan. The study therefore,
86
notes the most predominant ones to be the cost of borrowing, collateral, high interest
rates and protocol, wherein more than half of the respondents that receive credit from
formal institutions perceive these as challenges.
On the other hand, the greatest challenge faced by informal micro financial
institutions is the short repayment period. About 71% of the respondents perceive that
informal institutions usually give them a very short repayment period that is usually
not even enough to make profits from the loan. The next challenge is the inability to
lend huge sums of money or give out large credits as 66% of them see it as a
challenge. Closely followed, is the lack of confidentiality as most of these informal
financial institutions are the lender’s circle of friends and made known to everyone,
all the financial transactions that have been made. Other challenges include the time it
takes to build trust and reliability, the impromptu request for credit and its interest and
close monitoring to ascertain proper usage of the credit.
The OLS estimation results show that the overall model is statistically
significant. F-statistics is used to test the significance of the model - whether or not
there is a significant relationship between the dependent and the independent
variables. In the above regression equations, F calculated (13.73, 11.03 and 10.78) are
greater than table F table value (4.08) and hence, the study concludes that there is a
significant relationship between the dependent variable (profitability) and the
independent variables. Furthermore, the F-value probability of 0.000 which is less
than 0.05 shows that, the model is significant at the standard 5% significant level.
The square of the coefficient of determination R2 or the measure of goodness
of fit is used to judge the explanatory power of the explanatory variables on the
88
dependent variables. The R2 denotes the percentage of variations in the dependent
variable accounted for by the variations in the independent variables. Thus, the higher
the adjusted R2, the more the model is able to explain the changes in the dependent
variable due to changes in the independent variables. In the above regression results,
the adjusted R2 are 0.8482, 0.8427 and 0.8293 for formal, informal and both
microfinance sources respectively which implies that, there are 84.82%, 84.27% and
82.93% explanation of the variation in the dependent variable by the independent
variables for formal, informal and both microfinance sources respectively. This
indicates a perfect fit of regression line. T-statistics which appeared in parenthesis are
used to determine the level of significance for each variable coefficient(s) in the three
equations as appeared in the three columns with variables significant at different
critical levels 0.01 (***) or 1%, 0.05 (**) or 5% and 0.10 (*) or 10%, and
insignificant when there is no star sign.
A look at the individual coefficients for formal source of microfinance (column 1)
shows that the significant determinants of profit include, age of the enterprise, level of
education of enterprise head, number of employees, ownership and ratio of capital to
employees. The indicator for social capital proxied by membership of different cluster
groups was not significant in formal microfinance source impact on profitability. Age
of the enterprise has a negative effect on profitability which suggests that for formal
microfinance source, higher age may not be an asset. Production is the control group
for the sector effect and the results suggest that trade and services fared better than
production in determining the enterprise profit. Similarly, Nnewi is the control for
cluster city effect with the results suggesting a non-significant for Onitsha and a
negative significant for Aba. This implies that Aba clusters effect fared less than
Nnewi in determining the profitability.
A look at the individual coefficients for informal source of microfinance
(column 2a) reveals that the significant determinants of profitability include, age of
the enterprise manager, level of education, number of employees, ownership, ratio of
capital to employees as well as the indicator for social capital proxied by membership
of different cluster groups. Here, age of the enterprise manager has a positive effect
on profitability which suggests that for informal microfinance source, higher age is an
added advantage. Production is the control group for the sector effect and the results
89
suggest that trade and services fared better than production in determining the
enterprise profit just as in the formal source. Similarly, Nnewi is the control for
cluster city effect with the results suggesting a significant cluster effect for Onitsha
and Aba though negative, implying that Nnewi cluster had overall better effect in
determining the profitability of enterprises within the cluster than Onitsha and Aba in
both formal and informal micro finance sources. This suggest that generally there may
be better collaboration among enterprises in different groups in the clusters in Nnewi
than in Onitsha and Aba.
Similarly, the individual coefficients for both sources of microfinance (column
2b) reveal that the significant determinants of profitability include, age of the
enterprise manager, level of education, number of employees, ownership and the ratio
of capital to employees. The indicator for social capital proxied by membership of
different cluster groups is not significant. Age of the enterprise manager here has a
positive effect on profitability which suggests that, for enterprises using both sources
(formal and informal microfinance), higher age is an added advantage. Production is
the control group for the sector effect and the results suggest that trade and services
fared better than production in determining the enterprise profit just as in the formal
source. Similarly, Nnewi is the control for cluster city effect with the results,
suggesting a significant cluster for Onitsha and Aba though negative, implying that
Nnewi cluster had better effect in determining the profitability of enterprises within
the cluster than Onitsha and Aba that use both formal and informal sources of
microfinance.
From the three equations, sector and city with the exception of Onitsha for the
formal source are considered as important determinants of profitability of the
enterprises. However, due to their categorical nature, they are examined as dummy
variables wherein, production is considered as the omitted category against trade and
services for sector, and Nnewi is considered as the omitted category against Onitsha,
and Aba for the city in which the enterprise is located. The results suggest that
enterprises involved in trade marginally contribute more to profit when compared to
those in the services and production sectors and are better when they use formal
microfinance source. This shows that enterprises involved in trade receive more
incremental profits than those in the service sector and finally, those in the production
90
sector. This could be as a result of the gestation period of the enterprises in the
production sector as it may take longer time for some enterprises still expanding to
meet up with operational costs. While for the city or location effect, Nnewi
enterprises fare better than Ontisha and Aba in terms of location contribution to profit
for all sources. The results suggest that enterprises within clusters in Nnewi are likely
to make more profits than enterprises within clusters in Onitsha while enterprises
within clusters in Ontisha are more likely to make more profit than their counterparts
in Aba when they use informal source of microfinance.
Labour equally shows positive and significant effects on the profit of
enterprises within the clusters that receive credit from both formal and informal
sources. The ratio of capital to labour is also a significant determinant of the profit of
enterprises that receive credit from all the two sources (formal, informal or both).
The fact is that the relationship the enterprise has with the borrower (social
capital) did not significantly affect the profit of the enterprise when the source of
microfinance is formal but it was not so when it is an informal source. The informal
results corroborate with the cluster advantage of the entrepreneur. The advantage of
each enterprise being in a cluster and becoming members of different capital
associations does significantly improve profits of that enterprise.
It is worthy of note that the first and second objectives are to ascertain the impact of
formal and informal financial credit on the profitability of enterprises that receive it.
The variable used to proxy this is the sum total of credits received from financial
institutions that year regressed on the rate of return or the profit for that year. The t-
value for the formal and informal credit sources are (3.9393) and (8.990) and they are
both greater than 1.96 while the p-values are 0.012 and 0.009 respectively. Also, the
positive coefficients for both sources suggest that there is a positive relationship
between formal and informal credits and the return on investments of enterprises that
receive them within the clusters. In fact, from the coefficient, we can infer that as
credit increases by N1, the return on capital for enterprises that receive them,
increases significantly by N0.11, N0.529 and N0.306 or 11k, 53k and 31k for formal,
informal and both sources respectively.
91
4.4: Determinants of the choice of the microfinance Source by Enterprise clusters in South East of Nigeria (Objective 3 and Model3) To ascertain the determinants of choice of microfinance source, the study employs
two methods; first, by estimating multinomial logit regression that investigates the
determinants of the choice of the microfinance provider, and second, by analyzing the
perception of determinants of the choice of the microfinance source. The logit
regression uses binary dependent variable due to the qualitative nature of the study.
The dependent variable is a categorical variable and is designed such that 1 represents
enterprises that receive (proxy for choice) formal credit while 0 represents informal
credit. The significant determinants of profitability include amount of credit needed,
gender of the enterprise head, age of the enterprise head, level of education of the
enterprise head, interest rate, reliability, training, protocol extent, discrimination of
sectors, and length of repayment period offered. Indicators of social capital and sector
are regressors to the regressand, that is, the choice of the micro financial provider.
The logit estimation results are presented Table in 4.4 below.
Table 4.4: Determinants of the choice of micro financial sources for enterprises
Dependent variables Marginal effects Odds ratio TRADE 2.0435 4.70076 (3.35)*** SERVICES 3.08779 1.01485 (3.98)*** LnLEN 0.8031 2.232561 (3.87)*** LnSOC 0.0138 2.98628 (-4.11)*** _cons -18.1842 (-4.03)*** Sample size s 539 Pseudo R2 0.6311 (0.0012) Chi-square 214.15 (0.0027) Log likelihood -308.564 Source: Author’s Absolute value of z statistics in parentheses, * significant at 10%, ** significant at 5% and *** significant at 1%. Omitted categories in the dependent variables are the (comparison enterprises who did not borrow credit)
Estimation results in the above table show an overall significance given by the
probability of chi-square to be 0.0000 which is less than 0.05 hence, significant at 5%
significant level. This is evident as the probability chi-square calculated (214.15) is
greater than the probability of chi-square tabulated (4.574) with 11 degrees of
freedom. The Pseudo R2 in this non-linear model is often considered to be usually low
and it constrains this model for that characteristics. However, the Pseudo R2 of the
model estimated above is still relatively high at 0.6311.
The significant determinants for the choice of the microfinance source as shown in the
table above include amount or volume of credit needed, age of enterprise head,
distance to microfinance facility, relationship with the microfinance provider,
problematic extent of protocols, interest rate, length of repayment period offered,
sector discrimination and the social capital component. On the other hand, the non-
significant determinants include gender of the enterprise head, training offered by the
provider and level of education. Nevertheless, the positive determinants are the age of
enterprise head, reliability of the provider, problem extent of protocol, interest rate,
93
length of repayment period offered, cluster advantage and social capital while the
negative determinants are amount or volume of credit needed and training, though
training was not significant.
Given the complicated and unfriendly nature of the marginal effect, the study
estimates odds ratio of the logit model that is equally presented in the above table.
The odds ratio is, however, the antilog of the logit and is less than 1 when the
marginal effects is negative and, greater than 1 when the marginal effect is positive.
For a unit increase in the amount or volume of credit needed by the entrepreneurs, the
odds in favour of choosing informal sources over formal sources decrease by 0.6464
or 36.4%. This variable is statistically significant given its probability value in terms
of the amount or volume of credit needed. However, enterprises prefer formal
sources.
The relationship with the credit provider equally and significantly determines
the choice of the credit source. The positive coefficient suggests that a unit increase in
the extent of relationship with the credit provider increases the odds in favour of
choosing an informal credit source. Training is not a significant determinant of the
choice of credit source, though units increase on the training received decreases the
odds in favour of choosing an informal source by 0.9684 (3.2%). Therefore, the odds
in favour of choosing formal sources also increased, though not significantly.
The extent of protocol as a problem is equally a significant determinant of the
choice of credit source among enterprises in the South East of Nigeria. The absolute
z-value is 3.66 which is greater than 1.96 hence, a unit increase in the extent of
protocol as a problem increases the odds in favour of an individual choosing an
informal credit provider. This is expected a priori given that; there exist more
protocol in the formal sector than in the informal sector. The extent to which the
credit providers discriminate on specific sectors of activities does not significantly
determine the choice of the credit source, though the odds are in favour of choosing
formal sectors by 0.319 or 68.1%.
Interest rate and the length of repayment period are both significant
determinants of the choice of credit source by the entrepreneurs. A unit increase in the
extent to which the respondents perceive interest rate as a problem increases the odds
94
in favour of choosing a credit provider by 1.1449 while a unit increase of length of
repayment period increases the odds in favour of choosing an informal source for
credit provision.
Social capital component is equally a significant and positive determinant of
the choice of the credit provider, and the odds in favour of choosing an informal credit
source is on the increase. The fact that an enterprise enjoys such cluster advantage due
to the location of the firm significantly affects the choice of the credit source. And
such positive sign of the cluster advantage shows that the odds increase in favour of
choosing the informal sector for every unit increase for those with a cluster advantage.
This is expected, given that social capital component are more predominant in the
informal sector, and more importantly, it improves the confidence the provider has in
the borrower.
Surprisingly, education is not a significant determinant of the choice of the
credit provider. This suggests that it is not on the basis of education that the
enterprises choose where to get credit from. A unit increase in the educational level,
however, reduces the odds in favour of choosing an informal source by 6.2%. Sector
is considered as a categorical variable and so the production sector is omitted and
used as a reference category for trade and services. The result for both categories is
significant and positive, suggesting that the odds in favour of choosing a provider
increases for enterprises in the trade and service sectors when compared to the
production sector.
In other words, there exist significant determinants of the choice of
microfinance sources by enterprise clusters in South East, Nigeria and, these
determinants include: the amount or volume of credit needed, relationship with the
microfinance provider, problematic extent of protocols, interest rate, length of
repayment period offered, social capital component including cluster advantage. It is
equally noteworthy that factors such as age of the enterprise, interest rate, relationship
with the microfinance provider, extent of protocol including collateral availability,
being engaged in trade and services, the length of repayment period and the social
capital dimension (membership of different cluster groups that embark on cash
contributions hence somewhat give financial assistance) have odds ratio that are
95
higher than one (1). This implies that these are the main factors that affect enterprises
in the selected clusters from moving from formal to informal microfinance sources.
The likelihood of moving from formal to informal are highest with enterprises
engaged in trade as well as relationship with the microfinance provider, social capital
and extent of protocols.
Analysis of the perception of determinants of the choice of the microfinance
sources using some selected factors as depicted in Figure 4.1 below shows that
respondents perceive that the quick response is the most deterministic factor for their
micro financing choice.
Figure 4.1: Perception of determinants of choice of microfinance choice
Source: Author’s Evidence from the above figure shows that 41% of the sample opine that their choice
for credit source depends on quick response, 27% of the sample perceive interest rate
as a significant determinant of microfinance sources, 17% says it depends on the
reliability of the credit source to choose their source of micro financing, 9% of them
choose a particular credit source because they are favoured by the credit supplier
based on the cluster in which they are while only 6% of the respondents choose a
particular credit supplier because they have a relationship with the provider.
4.5 Assessing the level of support of Microfinance providers for the sustenance of profitability of Enterprise (Objective 4) The fourth objective of the study is to assess the level of support of microfinance
providers for the sustenance of profitability for enterprises that use both formal and
96
informal sources in enterprise clusters in South East, Nigeria. This objective is
examined from three perspectives. First, the study investigates the perception of the
extent to which micro financing has been supportive to the enterprises of formal and
informal recipients. Also, it examines the level of support using the likert scale and
lastly, it examines the extent to which microfinance providers have expanded their
businesses.
To examine the perception of the extent to which micro financing has been
supportive to the enterprises that receive credit from formal sources, the study uses
the chart below which is extracted from the questionnaire for demonstration.
Figure 4.2: Extent of microfinance support perceived from formal and informal sources
Source: Author’s
In examining the extent to which microfinance support enterprises that receive
funds from formal microfinance providers, the chart above shows that 53% of the
recipients from formal sources perceive that microfinance providers support them
averagely. Only 7% believe that microfinance providers support them to a very high
extent and 26% to a high extent, while 7% perceive that microfinance providers
support them to a very low extent, and 7% to a low extent. On the average, the study
states that the recipients of formal credit generally agree that microfinance providers
support them averagely.
In assessing the extent to which microfinance providers support enterprises that
receive funds from informal microfinance sources, the chart above shows that 18% of
97
the recipients from informal sources perceive that microfinance providers support
them averagely. Up to 24% believe that they support them to a very high extent and
21% to a high extent, while 16% perceive that microfinance providers support them to
a very low extent, and 21% to a low extent.
To show the level to which the respondents perceive that the micro financial funds
have been supportive, the study uses a likert scale for both formal and informal
sources. As stated above, the 5-point likert scale is analysed such that, the average for
each of the sources is approximated toward the nearest whole number. Then, the
approximation constitutes one of the 5-point scales as originally stated in the question.
The approximated whole number now determines the level of involvement such that
‘5’ shows very high involvement and ‘1’, very low involvement. The results are
therefore shown below.
Table 4.5: Average Perception of Micro Financial Support from Micro Financial
Sources for Enterprises in South East, Nigeria
Variable Obs Mean Std. Deviation Approximation of the mean
Conclusion
Formal Sources
266 3.198795 0.9225779 ≈ 3 Average
Informal Sources
272 3.661832 1.306656 ≈ 4 High extent
Source: Author’s
Analysis of Table 4.5 above clearly shows that, while the respondents on the
average perceive that formal micro financial institutions support enterprises in South
East, Nigeria, enterprises that receive funds from informal micro financial institutions
perceive that the institutions have supported them to a high extent.
Finally, to examine the extent to which funds have expanded businesses in the
sector, the study employs the doughnut chart below.
98
Figure 4.3: Perceived extent to which funds have expanded business
Source: Author’s
In examining the extent to which microfinance funds have expanded
businesses of small scale enterprises as perceived by the respondents, a doughnut
chart is used to show the percentage representative for each level or extent. The chart
above suggests that 25% of the sample perceive that the funds expanded their
businesses averagely. Only 9% believe that microfinance funds expanded their
businesses to a very low extent, and 11% to a low extent. While 38% perceive that
microfinance funds expanded their businesses to a high extent, 17% perceive that the
funds have expanded their businesses to a very high extent. On the average, the study
states that the respondents generally agree that microfinance funds have expanded
their businesses significantly.
4.6 Tests of Hypotheses
The study recalls the following research hypotheses as presented in their null forms
thus:
1. There is no significant impact of the formal microfinance sources on the
profitability of enterprise clusters in South East of Nigeria,
2. There is no significant impact of the informal microfinance sources on the
profitability of enterprise clusters in South East of Nigeria,
3. There exist no significant determinants (i.e. amount, interest, extent of
protocols including collateral availability, relationship with the provider) of
the choice of microfinance sources by enterprise clusters in South East,
Nigeria.
99
4. There is no high involvement of the microfinance providers for the sustenance
of profitability of enterprise clusters in South East Nigeria.
Decision Rule for Hypotheses Testing:
The stated hypotheses are tested at 0.05 level of significance. The null hypothesis is
rejected if the probability (p-value) at which the t-value for hypotheses 1 and 2 or the
z-value for hypothesis 3 is significantly less than the chosen level of significance,
otherwise, the alternative hypothesis will be accepted. In other words:
1. If the calculated t-value for the variable coefficient for hypotheses 1 and 2 is >
1.96, the study does not accept the null hypothesis, and accepts the alternate
hypothesis.
2. If the calculated z-value for the variable coefficient for hypotheses 3 is > 1.96,
the study does not accept the null hypothesis, and accept the alternative
hypothesis.
3. If the calculated approximation value of the mean is 3≥ in the 5 likert scale,
the study does not accept the null hypothesis, and accept the alternative
hypothesis.
Hypothesis 1 and 2:
The t-value for the formal and informal credit sources are (3.9393) and (8.990) and
they are both greater than 1.96 while their p-values are 0.012 and 0.009 respectively
which are less than 0.05 hence, we reject the null hypothesis which implies that
formal and informal sources of microfinance significantly affect the profitability of
the enterprises that receive them. Also, the positive coefficients for both sources
suggest that there is a positive relationship between formal cum informal credits and
the return on investments of enterprises that receive them within the clusters. In fact,
from the coefficient, we can infer that as credit increases by N1, the return on capital
for enterprises that receive them, increases significantly by N0.11, N0.529 and
N0.306 or 11k, 53k and 31k for formal, informal and both sources respectively.
The above findings mean that we do not accept the first and second null hypotheses of
the study. In other words, the study concludes that there is significant impact of the
formal and informal microfinance sources on the profitability of enterprise clusters in
South East of Nigeria. In summary, the first and second null hypotheses of the study
100
were rejected and hence, formal and informal sources of microfinance significantly
affect the profitability of the enterprises that receive them in the clusters of South
East, Nigeria.
Hypothesis 3
The third hypothesis of the study states that, exist no significant determinants (i.e.
amount, interest, extent of protocols including collateral availability, relationship with
the provider) of the choice of microfinance sources by enterprise clusters in South
East, Nigeria. From the study findings, the amount or volume of credit needed (5.58),
relationship with the microfinance provider (2.88), problematic extent of protocols
including collateral requirement (3.66), interest rate (4.35), length of repayment
period offered (3.87), social capital component including cluster advantage (-4.03) are
clearly significant determinants of the choice of microfinance sources by enterprise
clusters in South East, Nigeria. This is because these variables all have the absolute
value of their z-value > 1,96 hence, the third null hypothesis of the study is equally
rejected.
In other words, the study concludes that, there exist significant determinants of
the choice of microfinance sources by enterprise clusters in South East, Nigeria and,
these determinants include: the amount or volume of credit needed, relationship with
the microfinance provider, problematic extent of protocols, interest rate, length of
repayment period offered, social capital component including cluster advantage.
Hypothesis 4
The fourth null hypothesis says there is no high involvement of the microfinance
providers for the sustenance of profitability of enterprise clusters in South East
Nigeria. Unlike the above three hypotheses, this hypothesis can only be accepted
rejected based on the decision rule around the approximation value of the mean being
3≥ in the 5 likert scale. Evidence from table 4.5 which shows the average perception
of micro financial support from micro financial sources for enterprises in South East,
Nigeria shows that both formal (~3) and informal (~4) microfinance sources have
mean values at either 3 or above. This implies that the fourth null hypothesis is
rejected and the study concludes that there is high involvement of the microfinance
providers both formal and informal in sustaining profitability of enterprise clusters in
South East Nigeria.
101
4.7 Discussion of Findings
Findings of the statistical analysis from the respondents show that a great proportion
of the heads of the enterprise are educated as more than 94% have a minimum of
secondary education. This means that, on the average, the respondents to these
questions have the basic knowledge of the formalities or processes of borrowing from
formal or informal sources. That is, the study assumes that about 94% can read and
write. The role of education is not really an issue as it is not a significant determinant
of the choice of the microfinance provider as shown in Table 4.4 above. Also, 97% of
the respondents are sole proprietors meaning that the risks are very high for most of
these enterprises as they are owned and controlled by individuals, thereby leaving the
fate of the business on the welfare of the individuals.
A greater part of the micro and small enterprises (MSEs) that were
interviewed are involved in trading and other service sectors, with very few in the
production sector. This means that most of the enterprises are not involved in
converting raw materials to semi-finished or finished products which is one of the
major indicators of a fast growing economy or the age of high mass production. This
could be explained by several reasons. First, it could be explained by the fact that the
gestation period is very short for traders, and they only need to buy and sell and make
gains. On the other hand, enterprises in the production sector wait for a longer time
for the production to take place, including packaging and some other sub-processes
before it gets to the market, and finally gets converted into liquidity/cash. Some banks
tend to prefer traders as well as those in the service sectors that are predominantly
consultants/contractors who service and repay their loans easily than those in the
production sector who may last for months or even years before recording profit on
their investments let alone the loans.
Also, trading seems more lucrative and does not need a very large capital base
to start-up/expand, and so, its reflection on the loans requested are favourable to the
Microfinance Institutions (MFIs) and therefore, encourages them to give out loans
with the expectations that they will also pay back within a short period. Results
suggest that microfinance institutions may have preferred those in the service sector to
those in the production sector. This can be attributed to the quick gain expected in the
service sector unlike the production sector that takes lots of time to mature.
102
Finally, the production sector is mostly risky in this part of the globe as they
depend on several other factors to be productive. In addition, given the poor
investment climate in Nigeria coupled with the lack of government intervention in
case of a recession, most microfinance institutions shy away from giving out credits to
enterprises in the production sector. Average micro finance source to this sector is
11.6% from the result of the survey.
The most practical way that microfinance providers support enterprises is by
giving actual credit or loans. The enterprises do not benefit up to 20% of the other
forms of microfinance assistance that constitutes technical support, financial
guarantors and financial advisory. There are, however, several other cheaper and
efficient means by which micro financial institutions can assist their customers in
securing future loans. Some of them are training and technical support. From the
statistics also, the study notes that a greater percentage have received credits more
from informal sources than formal sources. This could be explained by the fact that,
most informal sources are closer to the people and understand their peculiar needs vis-
à-vis the nature of the businesses they are engaged in. This may also explain why the
distance to MFIs is a significant determinant of microfinance source as seen in Table
4.4 above.
The challenges faced by entrepreneurs in receiving credit from formal sources
are quite different from those they faced from the informal sources. Entrepreneurs that
borrow from the formal sources face challenges such as high cost of borrowing,
request for collateral, and sureties, high interest rates, tiring protocol/bureaucracy,
corny and usually time constraints. On the other hand, entrepreneurs that receive
assistance from informal sources face challenges such as inability to lend out large
credits, unreliability, receiving so many phone calls from the lenders, taking time to
build trust with the lender, giving short repayment periods and lack confidentiality.
These challenges are also highlighted during the focus group discussions as the major
hindrances to accessing credit from formal and informal institutions.
4.7.1 Discussion on Objective One
The first specific objective is to assess the effect of formal microfinance sources on
the profitability of enterprises in South East, Nigeria. The findings show that formal
103
sources significantly and positively affected the profitability of its recipients. The
study, therefore, accepts the hypothesis and concludes that, there is a significant
differential impact of the formal microfinance sources on the profitability of
enterprise clusters in South East of Nigeria. This is expected a priori as the credit
taken is usually intended to expand the business and so, should ordinarily reflect on
the profit of the enterprise. This result is similar to that of Nimoh, Kwasi and Tham-
Agyekum (2011) who examined the effect of formal credit on the performance of the
poultry industry in urban and peri-urban Kumasi of the Ashanti region in Ghana. They
found that, formal credit has a positive effect on the net income of large-scale poultry
farmers in the urban and peri-urban Kumasi.
The other significant determinants of profitability of firms that receive formal
credit are capital, education, sectors (trade and services), labour (number of
employees) and age of enterprise head as well as cities of operation (Aba and Nnewi
only). Social capital including cluster advantage and the city of Onitsha are not
statistically significant determinants of the enterprise profit. The significance of the
determinants is expected a priori for most of the variables.
Capital and labour are equally significant and positive as shown in Table 4.3.
They are both considered important factors and determinants of output as well as
profit as theoretically shown on most theories of the firm and evident in numerous
empirical researches. The age of the enterprise depicts experience in the field. The
older an enterprise becomes, the better it gets at, in minimizing its cost and finding
newer strategies of maximizing it profit thereby, enhancing its efficiency. On the
other hand, relationship with providers and the cluster advantage (social capital) are
not significant determinants of the enterprise profit. This is not surprising as formal
institutions have discrete directives and work with the minimum requirements, such
that the relationship with the providers and the cluster advantage (social capital) do
not have any room for favouritism.
4.7.2 Discussion on Objective Two
On the other hand, the second objective seeks to ascertain the effect of informal
microfinance sources on the profitability of enterprises in South East, Nigeria. Hence,
the study concludes that there is a significant differential impact of the informal
104
microfinance sources on the profitability of enterprise clusters in South East of
Nigeria. The results are very similar to the model that assesses the effect of formal
sources on the profitability of its recipients. The total annual average credit from
informal sources equally, significantly and positively affects the profitability of its
recipients as expected a priori.
Though enterprises that receive credit from informal sources complain about
the inability to raise huge funds, such firms have the advantage of being able to
borrow as many times as possible with fewer protocols as requested by the formal
credit providers. The sum total by the end of the year might, therefore, be enough to
impact on the profitability of the enterprises as is the case in the study. Also, the other
determinants that significantly affect the profits or the return on investment are
capital, labour (number of employees), age and cluster advantage (social capital) as
well as level of education of the enterprise head, sector and city of operation.
This finding is consistent with the result of the study by Loca and Kola (2013),
which used qualitative and quantitative tools to show that lending practices have a
positive effect on entrepreneurial activities in increasing employee salaries, job
creation or generating employment and profit margin of enterprises in Albania. These
are in line with the results of the findings of this study that shows that formal and
informal credits are significant determinants of profitability for enterprises in the
South East, Nigeria. Several other studies show similar findings. An example is
Wanambisi and Bwisa (2013) who used descriptive statistics and logistic regression to
demonstrate that, the amount of loans is significantly and positively related with
performance of MSEs in Kitale Municipality.
4.7.3 Discussion on Objective Three
In assessing the third objective, the study finds that the significant determinants for
the choice of micro financial sources as shown in Table (4.4) above are: the amount or
volume of credit needed, relationship with the credit provider, problematic extent of
protocols, interest rate, length of repayment period, the cluster advantage (social
capital component) and the categories of the sectors. The non-significant determinants
are: training offered by the provider, discrimination on sectors, gender and education.
105
Most of the significant variables are expected a priori as is evident in other empirical
and theoretical literature.
An example is seen in Olowe et al. (2013) who investigated the impact of
microfinance on MSEs growth in Ibadan metropolis of Nigeria. The results showed
that high interest rate, collateral security and frequency of loan repayment could
cripple the expansion of MSEs in Nigeria. These are also the challenges that were
noted in accessing credit in the South East, especially in accessing credit from formal
channels. The present study, therefore, notes that the most predominant ones are the
cost of borrowing, collateral, high interest rates and protocol, wherein more than half
of the respondents receiving credit from formal institutions perceive these as
challenges. On the other hand, short repayment periods, inability to lend huge sums of
money, lack of confidentiality, much time to build trust, unreliability, impromptu
request for credit and its interest and then so many phone calls are the challenges
faced in accessing credit from the informal sector.
The amount or volume of credit is in favour of formal institutions given that,
they are in the best position to give out large loans. So, the higher the amount or
volume of the credit needed, the greater the odds in favour of choosing a formal credit
provider.
The relationship with the microfinance provider and the extent to which the
protocol and interest rates are problematic are both positive and significant. It implies
that the odds in favour of choosing formal sources increase with their units increase.
This is because the burdensome protocol/bureaucracy and high interest rates have
plagued formal institutions for a long period of time and have become one of the
reasons for which some small scale enterprises choose informal institutions over
formal institutions.
Also, the extent to which the length of the repayment period is offered is
equally a positive and significant variable. Hence, it increases the odds in favour of
choosing the informal source over the formal source, given that it is a challenge for
both the formal and informal institutions. However, it apparently affects the formal
institutions more than the informal institutions. The trade and service categories of the
sectors of activity are positive and significant relative to the production sector. Hence,
106
they equally increase the odds in favour of choosing from the informal sector. This
could be explained by the fact that, most entrepreneurs in the trade and service sector
need smaller amounts or credits more frequently, thus, they patronize informal credit
providers, unlike the production sector.
The results of the logit regression of this study depict that the significant
determinants for the choice of the microfinance sources are the amount or volume of
credit needed, relationship with the microfinance provider, problematic extent of
protocols, interest rate, length of repayment period offered, the cluster advantage
(social capital) and the trade and service categories of the sectors. On the other hand,
the non-significant determinants are gender, training offered by the provider,
discrimination on sectors and education. Essien et al. (2013), which examined both
formal and informal credit sources and the role of social capital to small scale agro-
based enterprise in the Niger Delta region of Nigeria, is the closest to the present
study. Their results reveal that gender, age, and social capital are significant
determinants of informal credit while gender, education, age, size and collateral are
significant determinants of formal credit. While this study examines the determinants
of choosing between formal and informal credit, Essien et al investigate the
independent determinants of formal and informal credit. Though the results are
different, Essien et al suggest that education is a determinant for both formal and
informal credit which is not the case in this study.
4.7.4 Discussion on Objective Four
The last objective is to assess the level of support of microfinance providers for the
sustenance of profitability of enterprise clusters in South East, Nigeria. The analysis
shows that formal credits support enterprises that benefit from them averagely while
informal credits support their beneficiaries to a high extent. This means that informal
credit sources support micro and small enterprises much more than the formal
sources. In agreement with these findings is the study by Akinbola et al. (2013) who
examined the extent to which micro financing and marketing techniques have
contributed to entrepreneurial development of the customers of ten microfinance
banks located in Ojo Local Government Area (LGA) of Lagos State. Their result
suggests that microfinance banks have contributed significantly to the entrepreneurial
development in Nigeria. Again, Suberu et al. (2011) assess the impact of
107
microfinance institutions on small scale enterprises in Nigeria and showed that,
majority of the small scale enterprises acknowledged positive contributions of
microfinance institutions’ loans towards promoting their market excellence and
overall economic company competitive advantage.
This is equally confirmed by the focus group discussions that were held in
these clusters as the informal sectors could give credit faster and frequently more than
the formal sectors. This submission is, however, paradoxical to one of the principal
challenges faced by enterprises that benefit from them as they stated that the inability
to give out large loans is problematic. Nevertheless, this could be explained by the
fact that, though the informal credit providers may not be able to provide huge sums,
they are more likely to give out as many credits as possible. The credits may make a
significant impact in the long term.
The submission above is consistent with Babajide (2011), who investigated
the effects of micro-financing on micro and small enterprises (MSEs) in South West,
Nigeria and the results suggest that, micro financing enhances the survival of micro
and small enterprises but it is not sufficient for growth and expansion of such micro
and small enterprises. Also, the study shows that micro-financing is not financially
effective and practiced in Nigeria as many MFB’s grant more individual loans than
group based loans, thereby increasing their running cost and putting their portfolio at
risk. Though, the study was done in South-South, Nigeria while the present study
focused on the South East, Nigeria, the findings of both studies are similar and
consistent.
108
CHAPTER FIVE
SUMMARY, POLICY RECOMMENDATIONS AND CONCLUSION
5.1 Summary of Findings
The study was motivated by the fact that micro enterprises are referred to as the arm
of the industry that could be used to reach out to relatively low scale investors and
develop the home industries of any economy. In Nigeria, it could be said to be the
‘sleeping drug of the sleeping giant’ given that a revamp of the micro enterprises
would expand the businesses to boost the manufacturing sector, increase production,
increase exports and then lead a nation to a stage of high mass production. The study
examined the effectiveness of the microfinance sources on the profitability of
enterprise clusters in South East, Nigeria. In order to achieve the central aim, the
study had the following specific objectives: to assess the effect of formal
microfinance sources on the profitability of enterprise clusters in South East of
Nigeria, to ascertain the effect of informal microfinance sources on the profitability of
enterprise clusters in South East of Nigeria, to examine the determinants (i.e. amount
or volume, interest, process, accessibility, product/ sector concentration, connection
with provider) of the choice of the microfinance source by enterprise clusters, and to
assess the level of support of microfinance providers for the sustenance of
profitability of enterprise clusters in South East, Nigeria.
The study employed multiple regression techniques, logit regressions and
descriptive analysis to attain these objectives. The statistics showed that a greater
proportion of the samples were more of trade and services than the production sector.
Of these enterprises, more of them (about 55%) received credit from informal sources
than the formal sources. The results of the first and second objective showed that
formal and informal credits were significant determinants of the profit of the
enterprises or return on investment. However, other significant determinants included
capital, labour and age for both formal and informal sources. The cluster advantage
(social capital) was equally a significant determinant of the profit of enterprises that
was used as a proxy for performance. The results of the logit regression suggested
that, the significant determinants for the choice of the microfinance sources were the
amount or volume of credit needed, reliability, problematic extent of protocols,
109
interest rate, length of repayment period offered, the cluster advantage (social capital)
and the trade and service categories of the sectors.
To achieve these objectives, the study further analysed the perception of the
entrepreneurs to establish what were considered significant determinants. The
respondents perceived that the most deterministic factor for their choice of micro
financing was the credit provider that gave them quick response, followed by the
interest rate, reliability, and finally the relationship with the provider (social capital).
Finally, the study used descriptive analysis to show that, formal credits
supported the enterprise recipients much more than the informal credits. But both of
them supported the enterprise to a reasonable extent. Also, the credits generally
expand the enterprises averagely, so the credits could be encouraged and the access
smoothened to cover a larger span.
5.2 Policy Implications of Findings
A specific policy issue from the first two objectives is that formal microfinance
sources significantly and positively affected the profitability of its recipients but not
as much as the informal sources for enterprise clusters in South East of Nigeria. This
is expected a priori as credit taken is usually intended to expand the business and so,
should ordinarily reflect on the profit of the enterprise. Other determinants crucial for
policy is the high impact of social capital including cluster advantage. There is the
need for policy direction to tap from such social capital including cluster advantage. It
is equally necessary for microfinance banks to begin to come closer to their clients as
the study found that relationship with credit providers and the cluster advantage
(social capital) are not significant determinants of the enterprise profit when such
enterprise is using the formal microfinance source and vice versa.
Another policy question from the finding is why has Nnewi performed better
than Onitsha and Aba? Are there inherent qualities and strategies that need to be
harnessed in order for Aba and Onistha to measure up with Nnewi?
The study also found that the amount or volume of credit needed, relationship
with the service provider, problematic extent of protocols, interest rate, length of
repayment period, the cluster advantage (social capital component) and the categories
110
of the sectors are all determinants for choosing a particular source. It is equally
important to note that any positive improvement on the part of policy makers on any
of these variables sway enterprise from informal sources to formal sources and vice
versa. Also, the extent to which the length of the repayment period is offered is
equally a positive and significant variable. Hence, it increases the odds in favour of
choosing the informal source over the formal source, given that it is a challenge for
both the formal and informal institutions. However, it apparently affects the formal
institutions more than the informal institutions. The trade and service categories of the
sectors of activity are positive and significant relative to the production sector. Hence,
they equally increase the odds in favour of choosing from the informal sector.
Findings from the last objective means that informal credit sources support
micro and small enterprises much more than the formal sources. This is equally
confirmed by the focus group discussions that were held in these clusters as the
informal sectors could give credit faster and frequently more than the formal sectors.
This submission is, however, paradoxical to one of the principal challenges faced by
enterprises that benefit from them as they stated that the inability to give out large
loans is problematic. Nevertheless, this could be explained by the fact that, though the
informal credit providers may not be able to provide huge sums, they are more likely
to give out as many credits as possible. The credits may make a significant impact in
the long term.
5.3 Policy Recommendations
The findings of this study have, to a large extent, revealed what most micro and small
enterprises (MSEs) face and equally provided empirical evidence to help inform
policies that address their situation. Some of these include;
i) The main weaknesses of accessing formal credit are the amount or volume of
credit, interest rate and its tenure. These can only be bridged by the Central
Bank of Nigeria and development institutions through interventions such
as grants, donors, and/or soft loans. The recent N220 billion for micro and
small scale enterprises by the CBN should be focused on the micro
enterprises as was originally designed.
111
ii) Accessing credit in the formal sector is equally seriously plagued by
documentation and burdensome protocol in an effort to reduce the number
of bad loans and divergence of credit given. This challenge can be
minimized if banks empower their branches to move closer to the sectors
and clusters in order to exploit better, the social capitals that exist amongst
these clusters. By this policy, specific credit could be granted to micro and
small enterprise within the sector using their social capital dynamics as
collateral.
iii) The study equally recommends that, as the microfinance banks are relocating
to these sectors and clusters using the cluster advantage, they should be
supported in any form from the regulatory authorities. This is consistent
with the objectives of the rural banking scheme of the 1970s that is no
longer in operation. The scheme provided that, a minimum of 45% of total
deposit liabilities of bank branches located in local areas be given to the
location as credit facilities.
iv) Credits can therefore be given on the basis of social capital and group
dynamics to the informal sectors that act as the backup for securities. Once
the fear for physical and tangible security is not there, it would encourage
enterprises to borrow and create more confidence in formal financial credit
providers.
v) Formal microfinance providers should develop products with less emphasis on
physical and tangible securities as collateral and should rely more on their
social dynamics, discipline and trust, to avail them credit facilities within
their locations.
vi) The study recommends that Microfinance banks should move closer to the
clusters in order to exploit the social capital and group dynamics that exist,
and should be supported always by the regulatory authorities.
5.4 Contribution of this Study to Knowledge on the Subject Matter
The findings of the study are consistent with existing literature on the subject matter
and align with empirical findings earlier mentioned in Chapter Two. It, however,
makes additional contribution to knowledge on the subject by revealing the positive
impact of both formal and informal microfinance sources on the profitability of MSEs
in the South East. It goes further to reveal the differential impact of these sources on
112
each of the economic sectors (production, trade and services) within the clusters.
Although both formal and informal sources affect profitability of MSEs significantly,
the study reveals that microfinance providers shy away from the production sector,
hence granting only 11.6% of total credit to this sector within the period covered by
the study.
This finding is instructive and explains why despite the positive contribution
of microfinance sources to the profitability of MSEs over the years, the production
sector has not witnessed any significant growth. It, therefore, means that there is still a
huge gap in the financing profile of the production sector, hence a call for a robust
and dedicated model of financing to galvanize the production sector of the MSEs.
The computation of odds ratio in the study revealed major factors and the
magnitude at which factors such as age of the enterprise manager, interest rate,
relationship with the microfinance provider, extent of protocol, being engaged in trade
and services, the length of repayment period and the social capital dimension
(membership of different cluster groups that embark on cash contributions hence
somewhat give financial assistance) have odds ratio that are higher than one (1). This
implies that these are the main factors that affect enterprises in the selected clusters
from moving from formal to informal microfinance sources. The likelihood of moving
from formal to informal are highest with enterprises engaged in trade as well as
relationship with the microfinance provider, social capital and extent of protocols.
Some studies may have found few of these factors as key to the choice of
microfinance sources but this study went beyond that to estimate the odds ratio which
is quite useful to every policy maker.
Additionally, the study goes beyond the economic benefits (i.e. profitability)
to reveal the psychological and social benefits and the spread mechanism of micro
financing sources on MSEs in the clusters. These benefits come in the form of social
capital existing within the clusters which could be used to cushion or mitigate the
collateral gap in financing these enterprises for growth and sustainability. The focus
of the study on major enterprise clusters in the cities of South East like Aba, Nnewi
and Onitsha further reveals why certain businesses are easily associated with certain
communities, like Nnewi is associated with spare parts business, and Aba with textile
businesses in the South East economy.
113
With these findings, it is possible to develop a micro financing model for
MSEs to align with the social dynamics and capital as a substitute for collateral
instead of relying heavily on physical asset from operators which discourages them
from seeking financing assistance from the providers whenever in need.
5.5 Suggestions for Further Research
This study has been able to add value to existing literature, but more importantly to
stimulate further debate on the subject under consideration. The role of micro
financing is very significant in developing countries and even more significant in
Nigeria given the size of her informal sector and the number of small scale
enterprises. This study could equally be carried out in other economies and countries
as there is the need to continually improve the impact of micro financing on the
performance/profitability of MSEs.
Further studies could equally examine other aspects of social capital and group
dynamics in considering other ways in which they can be exploited as means of
enhancing securities and reducing risks. Other clusters could equally be examined to
investigate to what extent the clusters can be an advantage to micro financial
institutions. Other methodologies could equally be used to verify if they adheres to the
findings of this study in an effort to appreciate better the recommendations.
5.6 Conclusion
This study was motivated by the slow state of manufacturing as it was deduced to be
caused by the inability of domestic enterprises to thrive and grow into manufacturing
giants. This led the study to evaluate the effectiveness of the microfinance sources on
the profitability of enterprise clusters in South East, Nigeria, paying particular
attention to Onitsha, Aba and Nnewi industrial clusters. Amongst several findings, the
results showed that formal and informal credits were significant determinants of firm
profitability in South East, Nigeria. While the results of the logit regression suggested
that, the significant determinants for the choice of the microfinance sources are the
amount or volume of credit needed, reliability, problematic extent of protocols
including collateral availability, interest rate, length of repayment period offered,
relationship with the credit provider including cluster advantage (social capital) and
concentration on the trade and service categories of the sectors.
114
The findings further showed that the respondents perceived that, the main
factor for their choice of micro financing is the credit provider who provided loans
quickly. This was followed by the interest rate, reliability and the relationship with the
provider (social capital). And finally, the study used descriptive analysis to show that,
though both the formal and informal credit providers supported the firm at least
averagely and the credits generally expanded the enterprises averagely, formal credits
supported the enterprise recipients much more than the informal credits.
Therefore, within the limits of the scope and coverage of the study, the
findings were consistent with the objectives of the study. The study is confident that
the research is an interesting and worthy exercise and, thereby presents the report as a
contribution to the knowledge base on the subject matter.
115
REFERENCES
Adam, G. (2007), Role of Microfinance Institutions in Actualization of MDGs. Paper delivered at the induction ceremony of Institute of Chartered Economists of Nigeria (ICEN) in Port Harcourt
ADB (2005), Microfinance Development Strategy Update. Manila: Asian
Development Bank. Adebayo, A. A. (1997), “The Role of NGOs in Poverty Alleviation: A Case Study of
Farmers Development Union” Poverty Alleviation in Nigeria, selected papers for the 1997 Annual Conference of the Nigerian Economic Society.
Adebayo A. and Alayende T. (2001), The Impact of Government Poverty Alleviation
programs on Entrepreneurship development in Nigeria, Ibadan: Research Report Development Policy Centre.
Adelaja, M. A. (2005), “Enhancing the Microfinance Sector for sustainable
Development in Nigeria.” Seminar Paper CBN Launching of Microfinance Policy, Regulatory & Supervisory Framework for Nigeria.
Aderibigbe, J. O. (2001). “The role financial sector in poverty Reduction” .Bullion
CBN Economic & Financial Review, 39(4). Afshar, H. (1998) Women and Empowerment. Illustrations from the Third World,
New York, 1-210 Akinbola O. A., Ogunnaike O. O. and Tijani A. A., (2013). “Micro financing and
entrepreneurial development inNigeria; the mediating role of marketing”. Arabian Journal of Business and Management Review, 1(6): 7-20.
Akinboyo, O. L. (2007). “Microfinance Banks: Unlocking the potentials of Micro-
business Activities of the Nigerian Rural Economy”. Bullion CBN, 31(1). Akuezuilo, N. A. (2007). Research and Statistics in Education and Social Sciences.
Methods and Applications. Awka: Nuel Centi Publishers and Academic Press Ltd.
Ali, M., Peerlings, J. and Zhang, X. (2012). Clustering as an Organizational Response
to Capital Market Inefficiency: Evidence from Micro-enterprises in Ethiopia,
https://www.dartmouth.edu/~neudc2012/docs/paper_59.pdf Amagwu, F. I. (2006). “Implications of Micro Credits to Industrial Clusters in the
Nigerian Economy (A Case Study of South Eastern Nigeria)”. A proposal Presented at a Forum in Enugu, on Industrial Clusters Development and the Nigerian Economy.
116
Amobi, I. C. (2006). “Unleashing of Industrial Clusters for Growth and Prosperity in South East Nigeria”. A Paper Presented at a Seminar Organized by the Enugu Form and African Institute of Applied Economics in Enugu.
Anyanwu, C. M. (2004). “Microfinance Institution in Nigeria: Policies, Practices and
potentials”.CBN Bullion, 4(2). Anyanwu, C. M. (2004). “Micro Finance Institutions in Nigeria: Policy, Practice and
Strategy”. Journal of Social Development in Africa, 19. Anyanwu, J. C. (1994). “Women’s education and the use of bank credit in Nigeria;
Challenges for the twenty-first century,” Journal of Social Development in Africa, 9(2).
Babajide A. A. (2011). “Effects of micro-financing on micro and small enterprises
(MSEs) in South west Nigeria”. Being a Ph.D thesis of the Department of Banking and Finance, School of Business, Covenant University.
Baker, S. (2006). Sustainable Development: Rutledge Introductions to environmental
series, London, Taylor and Francis Company Barnes, C. and Erica K. (1999). “An Assessment of the Impact of Zambuko’s
Microenterprise Program in Zimbabwe: Baseline Findings”. Working Paper, Management Systems International (MSI).
Bergeron, G.S., Morris, S., & Bengas, J.M.M. (1998). “How reliable are group
informant ratings? A test of food security rating in Honduras”. Discussion Paper FCND. Washionton DC.
Boudeville, J. R. (1964). Les espaces économiques. Presses University, Paris. 128 p. Brautigam, D. (1997). “Substituting for the State: Institutions and Industrial
Development in Eastern Nigeria”. World Development, 25, (7):1063-1080. CBN (2003). Manual of Operation for Community Banks, Abuja: CBN, July 21. Central Bank of Nigeria (2006). Monthly Report. July, Available at www.cenbank.org Central Bank of Nigeria (2008).Monthly Report. July, Available at www.cenbank.org Cheston, S & L. Kuhn (2002) Empowering Women through Microfinance. Draft
publication sponsored by UNIFEM, USA, 1-47 Chibundu, E. (2006). “How Nigerian SMEs can grow the Economy”. Vanguard
Newspaper Sept 29, p46. Conroy, J.D. (2003). The Challenges of Micro financing In Southeast Asia. Singapore:
Institute Of Southeast Asian Studies.
117
Cull, R. J., Demirgüç-Kunt, A., & Morduch, J. (2007). “Financial Performance and Outreach: A global Analysis of Leading Micro Banks.” The Economic Journal.
De Crombrugghe, A., Tenikue, M., & Sureda, J. (2008). “Performance Analysis for a
Sample of Microfinance Institutions in India.” Annals of Public and Cooperative Economics, 79(2), 269-299.
Economic Performance Review (2006). Published by National Planning Commission
& National Bureau of Statistics Nigeria – Abuja April – July. Ellul, A. (2005). External Governance and Debt Agency Costs of Family Firms,
Research Paper Series, Kelley School of Business, Indiana University. Eng, L.L & Mak, Y.T. (2003). Corporate governance and voluntary disclosure,
Journal of Accounting and Public Policy, 22: 325–345. Essien U. A., Arene C. J. and Nweze N. J. (2013). “An investigation into credit
receipt and Enterprise Performance among small scale Agro based enterprises in the Niger Delta region of Nigeria”. International Journal of Agricultural Management and Development, 3(4): 245
Eyiuche, A. C. (2005). Economic Problems & Development Programmes and Policies
in Nigeria. Enugu: Diamond Publications. Ezeh J.A (1999). Fundamentals of Small Business Management. Enugu: Glanic Ventures. Fama, E. F. & French, K. R. (2002). Testing Trade‐Off and Pecking Order
Predictions About Dividends and Debt, Review of Financial Studies, Vol. 15 (1): 1-33.
FCND (2001). “An Operational Tool for Evaluating Poverty, Outreach of
Development Policies and Project”, Discussion Paper of Food consumption and Nutrition Division International Food Policy Research Washington June.
Federal Republic of Nigeria (2004). A one day focus group Consultative workshop on
NEEDS. Office of the Economic Adviser to the president Nigeria Abuja. Frank, M. Z. & Goyal, V. K. (2000). Testing the Pecking Order Theory of Capital
Structure (December 7, 2000). EFA 0157: AFA 2001 New Orleans. Available at SSRN: http://ssrn.com/abstract=243138 or http://dx.doi.org/10.2139/ssrn.243138
Godwin U. (2007). “Setting up Micro Finance Banks” in Daily Sun, Thursday,
November 15. Gujarati, D. N. (2004). Basic Econometrics. India: The McGraw-Hill Companies. Hartungi, R. (2007). “Understanding the Success Factors of Micro-Finance Institution
in a Developing Country”. International Journal of Social Economics, 34(6): 388-401.
118
Humphrey, J. and Schmitz, H., (2003).Governance in Global Value Chains. Local Enterprises in the Global Economy: Issues of Governance and Upgrading, Cheltenham: Edward Elgar Press.
IUCN (1980). The World Conservation Strategy: Living Resource Conservation for
Sustainable Development, prepared for International Union of the Conservation of the Nation (IUCN) and World Wildlife Fund (WWF)
Jensen, M. C. & Meckling, W. H. (1976). Theory of firm: Managerial behavior,
agency costs and capital structure, Journal of Financial Economics, 3(4): 305–360.
Kabeer, N. (1999) Resources, Agency, Achievements: Reflections on the Measurement
of Women's Empowerment. Development and Change 30: 435-464. Kessey K. D. (2014). “Micro credit and the promotion of small and medium
enterprises in informal sector of Ghana: Lessons from Experience”. Asian Economic and Financial Review, 4(6):768-780.
Kim, Y. H., & Kim, H. H. (2008). “Development and validation of evaluation
indicators for a consortium of institutional repositories: A case study of collection”, Journal of the American Society for Information Science and Technology, 59(8), 1282.
Kpakol M.L. (2005). “The role of Microfinance in Poverty Alleviation.”Seminar
Paper. CBN Launching of Microfinance Policy, Regulatory & supervisory framework for Nigeria. Dec.
Kudiabor, C.D.K. (1974). "Policy Objectives and Strategies for Integrated Rural
Development in Ghana," in Rural Development in Ghana. Ghana Universities Press, Accra, Ghana, 26-32.
Kushnir, K., Mirmulstein, M. L. and Ramalho, R. (2010). Micro, Small, and Medium Enterprises Around the World: How Many Are There, and What Affects the Count? MSME Country Indicators 2010, The World Bank/IFC, http://www.ifc.org/wps/wcm/connect/9ae1dd80495860d6a482b519583b6d16/ MSME-CI-AnalysisNote.pdf?MOD=AJPERES Lasuen, J. R. (1969). On Growth Poles, Urban Studies 6(2), pp. 137161. Loca S. and Kola F. (2013). “Microfinance and enterprises – Case of Albania”.
European Scientific Journal, 9(22): 122-143. Maduagwu, A. (2000). “Growing up in Oguta: The Economics of Rural Poverty in
Nigeria”. Available atwww.africaeconomicanalysis.org Malmberg, A. (1996), ‘Industrial geography: Agglomeration and local milieu’,
Progress in human Geography, 20(3): 392-403.
119
Malmberg, A. (1997), ‘Sticky places in slippery space, economic geography’, Economic Geography, 72: 293-313.
Mano Y., Iddrisu A., Yoshino Y., and Sonobe T., (2011). “How Can Micro and
SmallEnterprises inSub-Saharan Africa Become MoreProductive? The Impacts of ExperimentalBasic Managerial Training”. GRIPS Discussion Paper, 11(06).
Markusen, A. (1996), Sticky places in slippery space: A typology of industrial
districts, Economic Geography 72, 293–313. Mayoux, L. (1999) Questioning Virtuous Spirals: Micro-Finance and Women's
Empowerment in Africa. Journal of International Development 11: 957-984. Mayoux, L. (2000) Micro-Finance and the Empowerment of Women. A review of the
key issues: 2-31. McCulloch, N. and Bob, B. (2000). “Simulating the impact of Policy upon Chronic
and Transitory Poverty in Rural Pakistan.” Journal of Development Studies. 36 (6).
Mergos, G., Papadaskalopoulos, A., Christofakis, M., Arseniadou, I. and Kalliri, A.
(2004). Economic characteristics and development strategy of insular Greece. Athens: Academy of Athens.
Mersland, R., & Strøm, R. O. (2007). “Performance and corporate governance in
microfinance institutions”. From, http://mpra.ub.uni-muenchen.de/3888/. Modigliani, F., and Miller, M. H. (1958). “The cost of capital, corporate finance and
the theory of investment.” The American Economic Review, 48:261-297. Modigliani, F., and Merton H. Miller, (1963). Corporate income taxes and the cost of
capital: A correction. The American Economic Review, 53:433-443. Mpuga, P., 2004. Demand for Credit in Rural Uganda: Who Cares for the Peasants? A
Paper Presented at the Conference on Growth, Poverty Reduction and Human Development in Africa Centre for the Study of African Economies March 21-22. http:www.worldbank, org/wbp/impact/practice/annex1_2.pdf
Mpuga, P., 2008. “Constraints in Access to and Demand for Rural Credit: Evidence in
Uganda”. A Paper for Presentation during the African Economic Conference (AEC), 12-14 November, 2008, Tunis, Tunisia
Myers, Stewart C.; Majluf, Nicholas S. (1984). "Corporate financing and investment
decisions when enterprises have information that investors do not have". Journal of Financial Economics 13 (2): 187–221
Nadvi, K., (1996). ’Small Firm Industrial Districts in Pakistan’, Doctoral Thesis, Institute of Development Studies, University of Sussex
Nadvi, K. and Schmitz, H., (1999). “Clustering and Industrialisation: Special Issue.”
World Development, 27(9).
120
Nadvi, K., (1999a). “The Cutting Edge: Collective Efficiency and International Competitiveness in Pakistan.” Oxford Development Studies, 27(1).
Nadvi, K., (1999c). “Collective Efficiency and Collective Failure: The Response of
the Sialkot Surgical Instrument Cluster to Global Quality Pressures.” World Development, 27(9).
Nadvi, K., (2003).The Effect of Global Standards on Local Producers: A Pakistani
case study. Cheltenham: Edward Elgar Press. Nimoh, F., Kwasi A., and Tham-Agyekum, E. K., (2011). “Effect of formal credit on
the performance of the poultry industry: The case of urban and peri-urban Kumasi in the Ashanti Region”. Journal of Development and Agricultural Economics, 3(6): 236-240.
Nwodu, L. C. (2006). Research in Communication and Other Behavioural Sciences:
Principles, Methods and Issues. Enugu: Rhyce Kerex Publishers. Ocholah, R. M. A., Ojwang C., Aila F., Oima D., Okelo S. and Ojera P. B., (2013).
“Effect of micro finance on performance of womenowned enterprises, in Kisumu City, Kenya”. Greener Journal of Business and Management Studies, 3(4): 164-167.
Okeke, B.C. (2007). “Preparation for Entrepreneurship and Entrepreneurial
opportunities in Industrial Technical Education in Contemporary Nigeria.”Public Lecture Delivered at FCE(T) Umunze.
Okonjo-Iweala, N. (2005). “The Role of Government in Microfinance Development
in Nigeria." CBN Seminar Paper on Launching of Microfinance Policy, Regulatory and supervisory framework for Nigeria. Dec.
Okonkwo, M.C. (1996). “Small Scale Industries: Foundation for National
Development”. Occasional Paper delivered at Abuja RMRDC and Techno-Expo. Oladeji, S.I. and Abiola.A.G. (1998). “Poverty Alleviation with Economic Growth
strategy: Prospects and Challenges.” NJSS, 40(1). Olowe F. T., Moradeyo O. A. and Babalola O. A. (2013). “Empirical Study of the
Impact of Microfinance Bank on Small and Medium Growth in Nigeria”. International Journal of Academic Research in Economics and Management Sciences, 2(6): 116-124.
Osotimehin K. O., Jegede C. A., Akinlabi B. H. and Olajide O. T. (2012). “An
Evaluation of the Challenges and Prospects of Micro and Small Scale Enterprises Development in Nigeria”. American International Journal of Contemporary Research, 2(4): 174-185.
Osuala, E. C. (2005). Introduction to Research Methodology. Onitsha: Africana–First
Publishers Limited.
121
Otero, M. (1999). Bringing Development Back into Microinance. Journal of Microfinance, Vol. 1, No. 1, 8-19.
Otu, M.K., Ramlal, P., Wilkinson, P., Hall, R.I., & Hecky, R. E. (2011),
Paleolimnological evidence on effects of recent cultural eutrophication during the last 200 years in Lake Malawi, East Africa, J. Great Lakes Res., 37:61-74.
Peattie, L. (1987). “An Idea in Good Currency and how it grew: the Informal
Sector.”World development, 15(7). Perroux, F. (1950). The Domination Effect and Modern Economic Theory, Social
Research: An International Quarterly, Volume 17, No. 2 (Summer 1950): 188-206
Petridou, E., & Glaveli, N. (2008). “Rural women entrepreneurship within co-
operatives: training support.”Gender in Management: An International Journal, 23(4): 262-277.
Putnam, D. R. (1993). Making Democracy Work: Civic Traditions in Modern Italy.
New Jersey: Princeton University Press. Remenyi, J. and Quinones, B. (2000). Microfinance and Poverty Alleviation: Case
studies from Asia and the Pacific. New York: Prentice-Hall. Robinson, M. (2001). The Microfinance Revolution: Sustaining Finance for the Poor.
Washington D.C.: World Bank and Open Society Institute. Roodman, D. (2009). “What Do We Really Know about Microfinance’s Impact?”.
Decisions and the Interaction with Payout Decisions: Empirical Evidence from Brazil.
Scott, A. (1998). New Industrial Spaces: Flexible Production Organization and
Regional Development in North America and Western Europe, London: Pion. Suberu O. S., Aremu O. S. and Popoola (2011). “The Impact of microfinance
institutions on the development of smallscale enterprises in Nigeria”. Journal of Research in International Business Management, 1(8): 251-257.
Soubbtina, T. P. (2004), Beyond Economic Growth: An Introduction to Sustainable
Development, Second Edition, Washington D. C.: The World Bank. Swain, R.B. and F.G. Wallentin (2009) Does Microfinance Empower Women?
Evidence from Self - Help Groups in India. International Review of applied economics 23(5): 541-556.
122
Thapa, G. (2007). “Sustainability and Governance of Microfinance Institutions: Recent Experiences and Some Lessons for Southeast Asia”. Asian Journal of Agriculture and Development, 4(1), 17-37.
Todaro, M. P. and Smith, S. C. (2009), Economic Development, Tenth Edition,
Essex: Pearson Education Limited Udo, G. O. (2004). A Guide to Modern Research Methods. Enugu: Institute for
Development Studies. IUNCDF, (1997). “Micro-Finance: Nigeria Country Report. United Nation Capital
Development Fund”, http://www.uncdf.org/english/micro-finance/reports/country _feasibility/
UNDP (2007). Human Development Report 2007 – 2008.Washington D.C.: United
Nations. UNIDO, (2002). Corporate Social Responsibility: Implications for small and medium
enterprises in developing countries. Vienna: UNIDO. UNIDO, (2003). A Path out of Poverty: Developing rural and women
entrepreneurship. Vienna: UNIDO. UNIDO (2006). SME Cluster and Network Development: Principles and Practices.
Enugu: UNIDO. Wanambisi A. N. and Bwisa H. M. (2013). “Effects of Microfinance Lending on
Business Performance: A Survey of Micro and Small Enterprises in Kitale Municipality, Kenya”. International Journal of Academic Research in Business and Social Sciences, 3(7): 56-67
Wang, G.Y. (2010). The Impacts of Free Cash Flows and Agency Costs on Firm
Performance, Journal Service Science and Management, 3: 408-418. Wellalage, N.H. (2012). An Empirical Investigation of Agency Costs and Ownership
Structure in Unlisted Small Businesses, New Zealand Journal of Applied Business Research, 10(2).
World Bank (2003). Rural and Micro Finance Regulation in Ghana: Implications for
Development and Performance of the Industry, Africa Region Working Paper Series No. 49, http://www.worldbank.org/afr/wps/wp49.pdf
Zaman, H. (2000). “Assessing the Poverty and Vulnerability Impact of Micro-Credit
in Bangladesh: A case study of BRAC”. URL:www.worldbank.org/html/dec/Publications/Workpapers/wps2000series/wps2145/wps2145.pdf
123
ANNEX I: QUESTIONNAIRE ON MICRO AND SMALL ENTERPRIS ES (MSEs) Institute for Development Studies, University of Nigeria, Enugu Campus, Enugu. May, 2014 Dear Respondent, This is a pubic survey questionnaire which is aimed at identifying and collecting data on the problems, concerns and issues that affect the operations and performance of our Micro and Small Scale Enterprises (MSSEs). Your kind and objective e-response will significantly contribute towards reducing if not totally removing the problems militating against this all-important sub-sector of our economy. In order to ensure confidentiality, do not put down your name on the questionnaire but please answer the questions as honestly and objectively as possible. Section A: Demographic Characteristics 1. (a) Study Area
Name of Area ………………………………………………………………….. Town/Village: ………………………………… LGA ……………………………. State: …………………………… Geopolitical Zone: …………..………………. (b) Identification of Enterprise Name: …………………………………………………………………………….. Address: …………………………………………………………………………..
2. How long has the Enterprise/Firm been in operation? (Years) ………………….. 3. What is the highest level of education of the enterprise head? No formal education______ Primary education____ Secondary education ________Tertiary Education (Degree, OND, HND, etc.)_______ Post graduates________
4. Is this firm owned by a sole proprietor? Yes……………No…………….
5. Were you an apprentice before? Yes……………No…………….
5. Total Number of employees: Managerial and Administrative ……….…...
Operatives ……..……...
6. In which sector is this enterprise?
Production…….…Trade…………...Services….………
7. Type of activity
i. Food [ ]
ii. Textiles, Clothing & Garments[ ]
iii. Oil & Gas [ ]
iv. Wood/Paper/Pulp [ ]
v. Furniture and wood work [ ]
vi. Chemicals and Plastics [ ]
vii. Automobile [ ]
viii. Foundries, Metals/Fabrication[ ]
124
ix. Shoes and Leather Products [ ]
x. Plants and machineries [ ]
xi. Agro Processing [ ]
xii. Solid Minerals (Mining) [ ]
xiii. Bio Fuels [ ]
xiv. Petro Chemicals [ ]
xv. Community-based craft [ ]
xvi. Quarrying [ ]
xvii. Trading [ ]Others (specify) ……………………
122
Section B: Finance, Credit and Association
8. What is the value of your sales on the average?
………………….……………………Naira
9. How much is the average annual profit of this enterprise? ……….…………………
10. How much is the average annual savings of this enterprise? ………….…………
11. What is your estimated capital at present? …………….………………………
12. Which of these forms of micro financial support have you received most? (����)
Credit……. Technical support ………. Financial guarantor ……… Financial leaving
13. How much credit have you received from micro finances?
S/N Questions Responses 1. What is your name Sir/Madam? 2. What is your profession? 3. What position do you occupy? 4. How long have you been in your profession? 5. Are you aware of Micro Finance Bank(s) (MFB) within the location? 6. What is the closest MFB to your business location? 7. Have any of them assisted you to access finance? 8. If ‘Yes’ what is the impact of such assistance on your business? 9. How do you access the assistance, as a business person or group (cluster)? 10. Is this assistance on a regular basis or once in a while? 11. Do you think your group (i.e. clusters) have also benefited? 12. How far has assistance impacted on your business and the cluster? 13. Has there been any increase in your business activities and benefits since you
started accessing formal MFB loans?
14. What other support services are available to you as a business and a cluster? 15. How regular are these support services? 16. What form of collateral do you pledge? 17. Does the group have any influence on the offer and acceptance of financial
assistance to you and/or the cluster?
ANNEX III: GUIDE QUESTIONS FOR THE FOCUS GROUP DISC USSIONS 1) What are the various ways through which microfinance sources affect
profitability of enterprises?
2) To what extent has their assistance improved your profitability?
3) Do microfinance institutions prefer giving support to individuals or the cluster
as a whole?
4) Do you prefer formal or informal sources of micro financing?
5) Why or why-not?
6) What are the key determinants for micro financing from formal sources?
7) What are the key determinants for micro financing from informal sources?
8) What are the key constraints for micro financing from formal sources?
9) What are the key constraints for micro financing from informal sources?
10) Do microfinances privilege some sectors of activity than others?
11) Does one need to have a personal or family relationship with your credit
supplier to access credit?
12) How reliable is your credit supplier?
13) How much does the growth of your enterprise depend on microfinancing?
14) What policy options could be incorporated to improve profitability and
output?
ANNEX IV: ABA, NNEWI AND ONITSHA CLUSTERS DIRECTORY
S/No Name of Cluster
1. A.M.E. Shoe Makers Cluster
2. Omemma workers/traders Cluster
3. Building materials/Allied Cluster
4. Aba Leather product/Garments common facility center 18 industrial road Aba
5. National Board for technology incubation center
6. Nkwo Ngwa Allied workers Cluster
7. Aba North Shoe Plaza Cluster
8. Ugwu Mango Furniture Cluster
9. Aba belts makers Cluster, Ugwu mango-Ariaria
10. ATE Bags makers Cluster
11. Trunk box manufacturers Cluster
12. Pionerering shoe manufacturers Cluster
13. Cluster of shoe parts dealers
14. Timber and Allied market
15. Nigerian Automobile Technicians Cluster
16. Asa Nnentu motor spare parts Cluster
17. Factory Road Crunchies
18. GSM and Allied components Aba central
19. Aba woodworkers Cluster(Town ship unit) St. Georges