THE EFFECTS OF OUTREACH AND FINANCIAL SUSTAINABILITY OF MICROFINANCE ON POVERTY ALLEVIATION IN MOMBASA COUNTY

THE EFFECTS OF OUTREACH AND FINANCIAL SUSTAINABILITY OF

MICROFINANCE ON POVERTY ALLEVIATION IN MOMBASA COUNTY

ECN 360 - Economic Development

A MANAGEMENT RESEARCH PROJECT SUBMITTED IN PARTIAL

FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF

BACHELOR OF COMMERCE IN THE W. P. CAREY SCHOOL OF BUSINESS,

DEPARTMENT OF ECONOMICS, ARIZONA STATE UNIVERSITY, TEMPE

CAMPUS.

JULY 2019

ABSTRACT

Microfinance institutions play a key role in alleviating poverty in developing countries and

Kenya is no exception as their outreach and financial sustainability has a significant effect on

poverty alleviation. This study sought to examine the effects of outreach and financial

sustainability of microfinance in Mombasa County. There are various MFIs in this county that

have provided the marginalized communities with financial services that have reduced poverty

levels in the County. The objective of the study was to determine the effect of outreach and

financial sustainability of microfinance institutions on poverty alleviation in Mombasa County.

The study adopted a descriptive content analysis research design with a target population of 30

MFIs in the county. The sample design used in the study was convenience sampling which is a

non-probability sampling that uses subjects that are nearest and available to participate in the

study. Therefore, 8 deposits taking MFIs were chosen as the sample size and data was collected

from secondary sources covering a period of five years from 2014 to 2018.Data analysis was

done using SPSS, utilizing multivariate regression analysis. After a multivariate regression

model was applied to determine the effects of outreach and financial sustainability on poverty

alleviation, it was found that outreach, with a coefficient of -211.7559, associated t statistic of -

4.21 and a P-value of approximately 0.001, financial sustainability with a coefficient of financial

is -322833.5, associated t statistic of -5.20 and P-value of approximately 0.0001, and firm size

with a coefficient of firm size of -174.5849, associated t statistic is -2.53 and p-value of

approximately 0.001, had a significant negative effect on poverty alleviation. This meant that a

unit change in financial sustainability, firm size and outreach caused a significant change in

poverty alleviation. It was concluded that financial sustainability, outreach, and firm size has to

be intensified by MFIs in the county to realize a significant reduction in poverty levels. This

study recommended that MFIs should ensure that it reaches more clients through running

campaigns and promotions to create awareness of their services and increase their firm sizes

through establishing more branches and increasing the volumes of services. Another conclusion

was that they should maintain their financial sustainability through sourcing for more grants

from mother organizations and the government, establishing visionary leadership and evaluate

the efficacy of their investments. For further research, it suggested that future studies should

cover a wider geographic location and a larger sample size to increase generalizability and

representativeness. Also, future research could be done with a wider scope in regard to data

collection with the guidance provided by this research. Covering a wider period of about ten or

more years will help in providing an accurate picture of the situation.

iii

LIST OF ABBREVIATIONS

MFIs- Micro-Finance Institutions

ToC- Theory of Change

OSS-Operational Self-Sufficiency

FSS- Financial Self Sufficiency

USD- United States Dollar

iv 
 
TABLE OF CONTENTS 
ABSTRACT ................................................................................................................................... ii 
LIST OF ABBREVIATIONS ..................................................................................................... iii 
TABLE OF CONTENTS ............................................................................................................ iv 
LIST OF TABLES ....................................................................................................................... vi 
LIST OF FIGURES .................................................................................................................... vii 
CHAPTER ONE ........................................................................................................................... 1 
INTRODUCTION......................................................................................................................... 1 
1.1 Background of the Study............................................................................................................... 1 
1.1.1 Outreach of Microfinance ............................................................................................................................ 3 
1.1.2 Financial Sustainability ................................................................................................................................ 3 
1.1.3 Poverty Alleviation ...................................................................................................................................... 4 
1.1.4 Outreach, financial sustainability of MFIs and poverty alleviation ............................................................. 5 
1.2 Research problem ................................................................................................................................ 5 
1.3 The Research Objective ...................................................................................................................... 7 
1.4 The Value of the Study ....................................................................................................................... 7 
CHAPTER TWO .......................................................................................................................... 8 
LITERATURE REVIEW ............................................................................................................ 8 
2.1 Introduction ......................................................................................................................................... 8 
2.2 Theoretical Review ............................................................................................................................. 9 
2.2.1 Social Capital Theory .................................................................................................................................. 9 
2.3 Determinants of Poverty alleviation ................................................................................................. 11 
2.3.1 Business Expansion ................................................................................................................................... 11 
2.3.2 Resources/Income/Savings/Purchasing Power .......................................................................................... 11 
2.3.3 Housing and Shelter ................................................................................................................................... 12 
2.3.4 Healthcare .................................................................................................................................................. 12 
2.3.4 Outreach and financial sustainability of MFIs ........................................................................................... 12 
2.4 Empirical Review .............................................................................................................................. 13 
2.4.1 The Global perspective .............................................................................................................................. 13 
2.4.2 The local perspective ................................................................................................................................. 14 
2.5 Summary of Literature Review and Research Gap ........................................................................... 15 
2.5.1 The conceptual Framework ........................................................................................................................ 16 
CHAPTER THREE .................................................................................................................... 17 
RESEARCH METHODOLOGY .............................................................................................. 17 
3.1 Introduction ....................................................................................................................................... 17 
3.3 Target Population .............................................................................................................................. 18 
3.4 Sample design and Sample Size........................................................................................................ 18 
3.5 Data Collection ................................................................................................................................. 18 

v 
 
6 Reliability and Validity ..................................................................................................................... 19 
7 Data Analysis .................................................................................................................................... 19 
8. Operationalization of Study Variables ............................................................................................. 20 
CHAPTER FOUR ....................................................................................................................... 23 
DATA ANALYSIS, RESULTS AND DISCUSSION ............................................................... 23 
0 Introduction ....................................................................................................................................... 23 
1 Descriptive Statistics ......................................................................................................................... 23 
1.1 Grouped Descriptive Statistics ................................................................................................................... 23 
1.2 Descriptive statistic for Individual MFIs ................................................................................................... 24 
2 Correlation Matrix ............................................................................................................................ 29 
3 Regression Analysis .......................................................................................................................... 30 
3.1 Normality of Residuals .............................................................................................................................. 30 
3.2 Model Summary......................................................................................................................................... 31 
4 Interpretation of the Findings ............................................................................................................ 33 
4.1 Effects of firm size on poverty alleviation ................................................................................................. 33 
4.2 Effects of Outreach on poverty alleviation ................................................................................................ 34 
4.3 Effects of Financial Sustainability on poverty alleviation ......................................................................... 35 
4.4 Effects of outreach, financial sustainability and firm size on poverty alleviation ...................................... 36 
CHAPTER FIVE ........................................................................................................................ 37 
SUMMARY, CONCLUSION, AND RECOMMENDATION ................................................ 37 
0 Introduction ....................................................................................................................................... 37 
1 Summary of the Findings .................................................................................................................. 37 
2 Conclusion of the Study .................................................................................................................... 38 
3 Recommendations ............................................................................................................................. 38 
4 Suggestions for Further research ....................................................................................................... 39 
REFERENCES ............................................................................................................................ 41 
APPENDIX I ............................................................................................................................... 45 
APPENDIX II .............................................................................................................................. 46 
APPENDIX III ................................................................................. Error! Bookmark not defined. 
 
 
 
 
 

vi 
 
LIST OF TABLES 
Table 1: Operationalization of Study Variables............................................................................ 21 
Table 2: Grouped Descriptive Statistics ....................................................................................... 23 
Table 3: Descriptive Statistic for KWFT ...................................................................................... 24 
Table 4: Descriptive Statistic for KWFT ...................................................................................... 25 
Table 5: Descriptive Statistic for RAFIKI DTM .......................................................................... 25 
Table 6: Descriptive Statistic for SMEP ....................................................................................... 26 
Table 7: Descriptive Statistic for SUMAC ................................................................................... 27 
Table 8: Descriptive Statistic for Remu ........................................................................................ 27 
Table 9: Descriptive Statistic for Century .................................................................................... 28 
Table 10: Descriptive Statistic for U & I ...................................................................................... 28 
Table 11:Correlation Matrix ......................................................................................................... 29 
Table 12: Model Summary ........................................................................................................... 31 
Table 13: Analysis of Variance (ANOVA) .................................................................................. 32 
Table 14: Table of coefficients ..................................................................................................... 32 
 
 
 
 
 
 
 
 
 
 

vii

LIST OF FIGURES

Figure 1: The Conceptual Framework .......................................................................................... 16

Figure 2: Linear relationship among Variables ............................................................................ 31

Figure 3: The Effects of Firm Size on Poverty Alleviation .......................................................... 34

Figure 4: The relationship between outreach and poverty alleviation ......................................... 35

Figure 5: The relationship between financial sustainability and poverty alleviation ................... 36

CHAPTER ONE

INTRODUCTION

1.1 Background of the Study

Microfinance was first established in Bangladesh and other parts of the world, such as Latin

America in the late 1970s. According to Beatriz and Marc (2011), the term microfinance refers to

the component of the broader financial inclusion system that comprises of numerous players with

a common goal of delivering financial services at a higher quality to the low-income people. On

the other hand, other scholars such as Pedrini et al., (2016) describe microfinance as the financial

services and products that, among others, include savings schemes, loans, money transfers and

insurance for the low-income people. Further, Prakash and Malhotra (2017) define microfinance

as the way of promoting economic development, growth, and employment by providing support

to the micro-entrepreneurs and small businesses. In other words, it is a way that helps the poor

people to effectively manage their finances and take advantage of the economic opportunities

provided to them in the processes of managing related risks.

Microfinance Institutions participate in the areas of microfinance lending microloans that range as

low as $50 to amounts as large as $30,000 (Gutierrez-Nieto, Serrano-Cinca, and Molinero, 2017).

Many microfinance institutions (MFIs) provide additional services to these people, including

savings accounts and checking as well as providing other products such as micro-insurance.

Additionally, other MFIs offer their clients with business and financial education. From this

definition, it is clear that the primary goal of MFIs is to ensure that they ultimately provide

impoverished groups of people with an opportunity to become financially self-reliant and self-

sufficient. Microfinance does not only entail the banking activities but also other things such as

investments and the informal borrower’s appraisal. Further, they also provide collateral substitutes

that entail compulsory savings or group guarantees. According to Hermes, Lensink, and Meesters

(2011), microfinance institutions exist in almost all parts of the world; however, the majority of

their operations are situated in developing countries such as Kenya. It is estimated that over 500

million people across the globe have benefitted from the services offered by MFIs.

There are two theories that provide an elaboration on the effects of outreach and financial

sustainability of microfinance on poverty alleviation. One of these theories is the Social Capital

theory that was established by Hanifan in 1916 and subsequently revised to what it is today by

Bourdieu and Coleman in 1961and it describes the social relations that exist among groups and

individuals who are able to create and develop norms of mutual trust as well as forming social

networks. This ability, in return, allows them to achieve specific economic and social purposes in

society (Chen, Lee, and Chang, 2015). The second theory that anchors this study is the theory of

change that first emerged at the Aspen Institute Roundtable by a Methodist. The Methodist behind

the formation of this theory at this roundtable was Kurt Lewin in 1958. The theory of change (ToC)

refers to a method that provides an explanation on how a certain intervention or a number of

interventions are expected or intended to lead to a given development change, drawing on the

causal analysis based on the evidence available (Arnold et al, 2016). The theory provides an

analysis of why and how change is necessary and expected in the process of reducing poverty in a

given society.

In Mombasa County, poverty has been a major problem among the local population with World

Bank reporting that the County is still grappling with high levels of poverty. Rakodi, Gtabaki-

Kamau, and Devas (2015) assert that about 29.2% of the population in Mombasa County cannot

access the most basic needs because of the effect of extreme poverty that has caused intense

unemployment. Most of these people struggle to earn with the majority of them living below $1 a

day. However, according to a study conducted by Ngugi and Kerongo (2014), the levels of poverty

in Mombasa County have reduced over the years due to the intensified MFI services. This is the

factor that motivates the researcher to conduct research in this field. There have been various

researches done on MFIs and poverty alleviation in Mombasa. However, the majority of these

studies, such as the study done by Kidzuga (2018) focused on the relationship between financial

sustainability and outreach of microfinance institutions in Mombasa County, hence does not

address the effects that outreach and financial stability of microfinance institutions have on poverty

alleviation in Mombasa County. This provides a gap for this study to fill for the benefit of various

players in the economic sector in the region.

1.1.1 Outreach of Microfinance

Microfinance institutions in Kenya and other parts of the world strive to ensure that it reaches a

wider population which is also called the breadth of outreach. Hermes, Lensink and Meesters,

(2011) says it ensures that the people living in areas with high relative levels of poverty have access

to MFI’s services (depth of outreach). It includes services such as the financial services required

for both enterprise and consumption development. Quayes (2019) declares that some of the

determinants or measurements of outreach are determined by assessing the extent to which the

MFIs have succeeded in reaching out to the targeted population in the region and the degree to

which these MFIs have met their client’s financial service demands. This means that it is measured

in terms of breadth which is the number of clients and the volume of the services that MFIs served

its people or the depth which is the socio-economic level of MFI’s clients reached.

1.1.2 Financial Sustainability

Financial sustainability has become a buzz in the microfinance sector over the years. With the

continued “donor fatigue” among the rich nations financing most of the financial institutions in

Africa, there has been increasing confidence from most of the developing countries as more people

talk about the need for MFIs to stand on their own feet and be financially sustainable. Financial

sustainability, according to Chikalipah (2017), is about the ability of MFIs to be there for its clients

and beneficiaries in the long run. A model for measuring financial sustainability has to be an

effective model and it should have an ability to not only measure it but also predict financial

sustainability. An effective model should be able to correlate to the results and capital generation

and it should contain indicators that are easy to measure. It should also comprise of indicators that

are impacted by choices and decisions made by management and the board as well as being able

to be benchmarked.

Return on Assets Ratio (ROA) is used in the calculation of the financial sustainability of an MFI.

Tucker (2011) asserts that the return on assets ratio, often called the return on total assets, is a

profitability ratio that measures the net income produced by total assets during a period by

comparing net income to the average total assets. In other words, the return on assets ratio or ROA

measures how efficiently a company can manage its assets to produce profits during a period. The

ROA formula is ROA = Net Income / Total Assets. The second method is through Operational

Self-Sufficiency (OSS) which is the most basic measurement of sustainability, indicating whether

revenues from operations are sufficient to cover all operating expenses (D’Espallier and Goedecke,

2019). As with the preceding measures of returns, OSS focuses on revenues and expenses from

the MFI’s core business, excluding non-operating revenues and donations. (D’Espallier and

Goedecke (2019) suggests that by focusing on cost coverage, OSS reflects the MFI’s ability to

continue its operations if it receives no further subsidies. MFI managers should seek to achieve a

Financial Self Sufficiency (FSS) ratio greater than 100 percent. FSS can be affected by external

factors, such as the local market rate for borrowings, which can lead to annual fluctuations. FSS is

less likely to fluctuate for MFIs that have fewer subsidies and higher leverage (and smaller

adjustments).

1.1.3 Poverty Alleviation

Poverty alleviation is one of the world’s most critical challenges, and this also applies to the

contemporary Kenyan society. It is indicated that the private sector is the primary sector with a

major role to play in the creation of economic growth purchasing options and employment. Poverty

alleviation, according to Wund (2011) refers to the set of measures that are both humanitarian and

economical and are intended to live a given population permanently out of poverty. These

measures enable the poor to establish wealth for themselves as a way of ending poverty. Poverty

is highly correlated with many negative measurable aspects of standards of living and therefore

reducing poverty can have a positive impact on the lives of millions of people around the world.

One type of poverty reduction program, microfinance, has become very trendy since the success

of Grameen Bank in Bangladesh and the winning of the Nobel Peace Prize in 2006 by the bank's

founder, professor Muhammad Yunnan (Bayulgen, 2008). But, despite all the hype and good

intentions, the actual success of microfinance in poverty reduction has been somewhat limited

(Karnani, 2016). While the goal of micro financing programs is to be self-sustaining, the majority

of microfinance programs in India have remained dependent on funds from donors to cover

operating costs. According to Wund (2011), poverty alleviation is measured through the

determination of the headcount index (P0) which measures the proportion of poor people in a given

population. The other measure is done using the poverty gap index used to measure the extent to

which individuals fall below the poverty line as a proportion of the poverty line. The sum of these

poverty gaps provides the minimum cost of eliminating poverty. When this is effectively done, it

becomes possible for microfinance institutions to target poor communities and effectively reduce

poverty.

1.1.4 Outreach, financial sustainability of MFIs and poverty alleviation

A relationship exists between outreach, financial sustainability, and poverty alleviation. The

outreach of Microfinance institutions ensures that coverage of the people living in areas with high

relative levels of poverty also called the depth of outreach with financial services required for both

enterprise and consumption development. There is convincing evidence that outreach is negatively

related to the efficiency of MFIs. More specifically, Wijesiri, Yaron and Meoli (2017) found that

MFIs that have a lower average loan balance (a measure of the depth of outreach) are also less

efficient. Moreover, evidence shows that MFIs that have more women borrowers as clients (again

a measure of the depth of outreach) are less efficient (Azad et al., 2016). Therefore, MFIs have the

responsibility to ensure that it has a higher average loan balance to reach more cents and reduce

poverty. If this is not achieved, then MFIs will have failed in its mandate to reduce poverty.

On the other hand, financials sustainability of microfinance institutions is the ability of MFIs to be

there for its clients and beneficiaries in the long run. For sustainability to be achieved, outreach

must be attained by the MFIs. Abdulai and Tewari (2017) state that failure to reach more clients

within a targeted population means that there will be a low-income generation, hence the inability

to meet the client’s needs. When the client’s needs are not met, it means that the MFIs are failing

in reducing poverty among its clients. The inability to reach more clients means that poverty

alleviation measures will not cover the target population adequately (Abdulai and Tewari, 2017).

This means that, for poverty alleviation to be realized in Mombasa County, the MFIs outreach to

its target population and their financial sustainability through the continued and higher generation

of net income has to be achieved.

1.2 Research problem

Over the years, poverty alleviation has remained a significant challenge in the world and especially

in developing nations such as Kenya. There have been various measures put in place in Kenya to

ensure that, poverty levels are reduced which include the establishment and fostering of support

aids for the provision of opportunities for the poor populations and for the purpose of reducing the

existing economic inequalities. Although these measures have been put in place, the leadership

styles in the country, as well as the economic changes adopted, have become quite unfavorable to

the low-income earners leading to a continued increase in poverty level. Thomas and Thomas

Slayter (2017) assert that, a large section of the poor and marginalized are unable to obtain loans

and other banking services as well as financial literacy services from these MFIs mainly due to

complex application procedures, lack of information about the microfinance institutions as well as

the lack of collateral demanded by these institutions. It is also indicated that Mombasa County has

a poverty level of 23.6% slightly lower than the national poverty level (Thomas and Thomas

Slayter, 2017). However, in spite of these high numbers, the poverty level in the country is

estimated to have increased over the years.

According to Kenya Integrated, Household Budget Survey 2015/16 statistics provided by (former)

Planning, National Development and Vision 2030 Ministry, poverty level in Mombasa County is

estimated at 28.29 percent slightly below the national average of 45.9 percent, placing the County

among the poor counties in Kenya. Gachugia, Mulu-Mutuku, and Odero-Wanga, (2014) assert that

the rate of unemployment in the county is at 26.9 percent according to the 2009 census which

shows that a greater number of its population is living under 1 USD per day. However, despite

these levels of poverty, microfinance, according to Mumanyi (2014), is considered a key factor

fighting for the alleviation of poverty in this county since it is recognized as one of the tools that

most youth and woman have received help from and the ability to engage in sustainable

productivity activities across the county which has led to poverty reduction and improved social

welfare. Therefore, given the role played by MFIs in alleviating poverty in Mombasa County, there

is a need to research on how its outreach and financial sustainability affects poverty alleviation.

The issue of poverty alleviation through microfinance has been debated by various scholars over

time. In Kenya, for instance, various scholars have researched on the topic among MFIs in various

Counties across the country. Mutua (2017) discussed the effect of microfinance services on

poverty reduction in Mombasa County. Mutua did not discuss the issue of outreach and financial

sustainability of such microfinance institutions on poverty alleviation. Kidzuga (2018), on the

other hand, focused on the relationship between financial sustainability and outreach of

microfinance institutions in Mombasa County, hence does not address the effect of outreach of

microfinance institutions on poverty alleviation. Obeng (2017) determined the impact of micro-

credit on poverty reduction in rural areas in Mombasa County which indicated that poverty levels

have reduced in the County. Further, Maalim (2018) determined the effect of access to micro-

financing on the growth of small and medium enterprises in Thika Sub County. However, the

majority of these studies on poverty alleviation by MFIs in Kenya focused on the relationship

between financial sustainability and outreach of microfinance institutions hence they do not

address the effect of outreach and financial sustainability of microfinance institutions on poverty

alleviation in Mombasa County. This is the research gap which the current study is trying to fill

by answering the research question; what is the effect of outreach and financial sustainability of

microfinance institutions on poverty alleviation in Mombasa County?

1.3 The Research Objective

The objective of this research is to determine the effect of outreach and financial sustainability of

microfinance institutions on poverty alleviation in Mombasa County.

1.4 The Value of the Study

This study is of great importance to a number of players in the economy of Mombasa County and

the entire country. The first one is the Scholars. This study will be of concern to the education

sector in the county because it will enrich the existing body of research and knowledge. This is

because it will be an essential material for carrying out further research on the topic of poverty

alleviation, and it will also be a useful resource for future reference among scholars.

The microfinance institutions will also benefit from this research. It will be a useful research

material for the microfinance institutions since their consultants will find it as a helpful reference

material in advising their investors as well as the government on some of the practical application

of the microfinance institution’s outreach programs in Mombasa County and other counties in the

country. Moreover, those businesses that will have benefitted from the MFIs funding will be able

to understand their importance in contributing to the financial sustainability of the MFIs.

The other crucial beneficiary of this research is the regulator. This regulator is the Central Bank of

Kenya. It will benefit from this research because it will get a glimpse of some of the vital factors

that MFIs consider before undergoing expansion processes. This research will also provide basic

blueprints to the regulator in drafting its policies that will fit all the MFIs. The Central Bank will

also use the findings of this research in developing a sustainable microfinance and the integration

of microfinance into the broader financial sector.

CHAPTER TWO

LITERATURE REVIEW

2.1 Introduction

This chapter presents the empirical literature on the effect of outreach and financial sustainability

of microfinance institutions on poverty alleviation. In doing this, a review of the past studies that

relate to the effect of outreach and financial sustainability of MFIs on poverty alleviation is

provided. It also presents a review of the relevant theories of microfinance. The chapter will also

provide a summary of the literature review as well as the conceptual framework.

2.2 Theoretical Review

In the past years, there have been few studies focusing on the effects of outreach and financial

sustainability of MFIs on poverty alleviation. As most microfinance institutions continue to

blossom and spread across the globe, researchers have developed an interest in the various aspects

of microfinance instructions and how they have worked towards alleviating poverty. As a result,

multiple scholars have come up with theories that provide a systematic understanding of

microfinance activities, situations, and events that relate to the effects of outreach and financial

sustainability of MFIs on poverty alleviation. The theory discussed in this section is the theory of

change (Pandelaere, 2019). The other theory is the Social Capital theory that was established by

Bourdieu and Coleman and it describes the social relations that exist among groups and individuals

who are able to develop and develop norms of mutual trust as well as forming social networks.

2.2.1 Social Capital Theory

The social capital theory emerged in the mid-19th and century, and since then, it has presented

useful concepts in understanding how groups come together to form valuable networks. The

central concept of this theory is that an individual’s potion within a given network or group

provides a given advantage or benefit to that group that could be used for their own advantage.

The social scientists that coined this theory believed that social capital puts emphasis on the

commonality that brings strength to the communities (Lin, 2017). According to this theory, a

dimension called bonding, bridging and linking is offered that explains that the bonding and

birding of social capital refer to the creation of social relationships founded on the homogeneity

and the heterogeneity of the ethnic group membership or the social class membership respectively

(Seibert, Kraimer and Liden, 2011). The theory further states that a society characterized by strong

bonding but weak bridging social capital leads to the creation of ethnic and class boundaries.

However, those societies characterized by strong bridging and weak bonding allow them to create

social capital that is able to support the emergence of a rootless elite group. Therefore, what this

theory proposes is that for societies to have reduced levels of poverty there should be a balance

between the development of bridging social capital and bonding.

This theory is useful to this study because it presents the concept of balancing the development

of bridging social capital and bonding. It means that MFIs should strive to ensure that the target

societies are empowered through financial education and other methods to have a balance of the

two aspects. In doing this, it will be able to intensify the outreach of social capital which has to

do with the coverage at macro and micro levels. As a result, a balanced society in regard to social

capital outreach is created that will lead to poverty alleviation.

2.2.2 The theory of Change

The theory of change is an ongoing process of reflecting and exploring change and how that change

will happen as well as what it means in a given sector, group of people, and context. The theory is

also focused mainly on mapping out or the “filling in” of what is called the “missing middle

between change initiative or program and how they lead to the desired goals achieved. The theory

of change also maps out the initiatives through six stages (Connell and Kubisch, 2013). The first

stage is the identification of long term goals. The second one is called backward mapping and the

connection of the necessary requirements or preconditions important in achieving the goals and

explaining the reasons why these requirements are sufficient and appropriate. The third stage is

the identification of the underlying contextual assumptions, while the fourth stage is about

identifying the interventions that the initiative will do to elect the intended change. The fifth stage

is about the development of indicators that measures the outcomes for assessing a narrative to

determine the initiative’s performance (Connell and Kubisch, 2013). The last stage that explains

how this theory works is the sixth stage that involves drafting a narrative that explains the

initiative’s logic.

This theory’s concepts inform this study by providing guidelines on how MFIs can go about

making changes to their initiatives and adopting useful initiatives that can bring change in

Mombasa County. For instance, the various stages explained in this theory help MFIs in the County

to come up with educational initiatives that could teach the poor populations how to take credits

for capital. For instance, through the steps provided, it could create outreach programs that

emphasize these people to make loans and save in the MFIs and engage in investment activities

such as in viable business. Additionally, the program could teach them how to manage businesses

to get more returns on their investments. In doing this, more people will get credit, invest, and save

in the MFIs hence creating financial sustainability leading to reduced poverty. Further, this

theory’s concepts will ensure that MFIs in Mombasa County will connect and articulate their work

to the bigger goal of poverty alleviation and spot the potential risks in their change programs

through the sharing of the underlying assumptions in each and every step.

2.3 Determinants of Poverty alleviation

The fundamental goal of the majority of MFIs is to reduce the poverty levels within the target

population. Poverty alleviation, according to Wund (2011) poverty alleviation refers to the set of

measures that are both humanitarian and economical and are intended to live a given population

permanently out of poverty. According to Hussain and Hanjra (2014), MFIs, in the process of

reducing poverty, sets initiatives and programs that provide loans, savings plans, among other

initiatives for their clients. For them to measure their performance there should be key

determinants of poverty alleviation within the target population.

2.3.1 Business Expansion

Business expansion is a vital determinant of poverty alleviation. Due to the scarcity of finances

among most individuals, they cannot expand their businesses beyond certain levels. However,

since these households have other competing needs, their finances are likely to be channeled to

these competing needs and rather than expanding their businesses (Jenkins and Thomas, 2012).

Therefore, the ability of households to expand their businesses while still meeting their competing

needs indicates that poverty levels in such a household have been reduced considerably.

2.3.2 Resources/Income/Savings/Purchasing Power

Most households in poor communities have fewer resources, lower-income, and fewer savings. A

decline in the proportion of the people in the target population living on less than the international

poverty line of USD 1.90 per day indicates decreasing poverty levels. Also, Marmot (2015) says

that a decline in the poverty level in a household means that such a household is able to save in

MFIs and invest at the same time. According to Jenkins and Thomas (2012), the other determinant

is the increased purchasing power per household within the target population or higher per capita

expenditures in the households. This will show that poverty has reduced among the families in the

poor or targeted region. Jenkins and Thomas, (2012) asserts that increased productivity and

incomes among the population target will indicate reduced poverty levels, a crucial aspect that

most MFIs should use in determining whether their initiatives are reduced poverty or not

2.3.3 Housing and Shelter

Poverty in urban areas is a significant cause of the inadequate shelter that results from lack of

income. Lack of finances forces most of the urban dwellers to rent houses that are cheaper and in

poor conditions while others are forced to build informal or illegal houses which are more

affordable and convenient to them (World Bank, 2013). However, an increase in the number of

households in with quality housing and access to high quality rented houses indicates reducing

levels of poverty within a target population.

2.3.4 Healthcare

Improved health in a society is a crucial factor not only in the process of boosting the peoples’

productivity levels and income but also in enhancing the most quality life. Health is one of the

most basic needs in the Maslow hierarchy of needs, and the ability to access better healthcare

services is a step closer to a better living (Marmot and Wilkinson, 2016). The presence of better

health centers and reduced health-related problems in a community is a key factor in poverty

reduction. The ability of County-based programs to educated families empowers them to seek

informed health interventions.

2.3.4 Outreach and financial sustainability of MFIs

The outreach and financial sustainability are key determinants of poverty alleviation in a society.

Since the MFIs play a critical role in poverty reduction, its ability to reach more households with

its financial services determines the level of poverty in such a community (Marmot and

Wilkinson, 2016). Therefore, if MFIs reach as many poor people as possible within a target

population, the level of poverty is likely to reduce among such populations due to access to

microcredit that is helping in enterprise start-up. Marmot and Wilkinson (2016) adds that the

financial sustainability of MFIs, on the other hand, means that they have the ability to provide

services to the target population for a longer period of time. Therefore, if poor households are

able to access credit in the long-term, they are able to access capital to expand their business and

generate more income, hence reducing poverty. This means that poverty reduces if MFI’s

achieved financial sustainability.

2.4 Empirical Review

There are numerous studies that have been conducted across the world that investigate the effect

of outreach and financial sustainability of the MFIs on poverty alleviation. Imai, Arun, and Annim

(2010) assert that across the globe, the lack of access to credit is one of the primary causes of

impoverishment in most developing nations. However, Shastri (2009) explains that this situation

has changed in recent decades since the poor populations have acquired access to small credit

lending programmers provided by microfinance institutions. This has been the trend both locally

and internationally among numerous countries. This section of the paper provides an international

perspective of the effects of outreach and financial sustainability of MFIs on poverty alleviation.

2.4.1 The Global perspective

Poverty alleviation initiatives through the Microfinance Institutions in most developing countries

such as India, Indonesia, Pakistan, among others, has intensified over the past ten years. Studies

conducted by Premchnader (2013) indicated that the discovery of the lending groups led to the

formation of the microfinance institutions in India. He adds that in the past decade the program

has been introduced in many developing nations. Another study by Meyer (2010) found out that

between the years 1997 and 2009, the number of MFIs globally increased from 712 to 9,333

million and the number of its beneficiaries increased from 13.5 million to 213.3 million with the

82% of them being women. These people could not access credit before, and their ability to access

it has led to reduced poverty in most developing economies. In Bangladesh, for sentence, MFIs

such as the Grameen Bank has reported an increase in the number of members from 2.4 million in

the year 2000 to 8.2 million with an outstanding loan of $825 million by the year 2015. Generally,

the number of MFIs in countries such as Cambodia, India, and others has registered remarkable

outreach.

Mosley and Hulme (2018) found out that the impressive performance of most of the MFIs across

the globe is the fact that most have a high repayment of over 95%. This means that MFI’s lending

to the underprivileged borrowers that have no credit histories or that has no history to post

collateral is one of the financially sustainable assets to the MFIs which has helped in the poverty

alleviation in most countries. Studies by Hiatt and Woodworth (2016) indicated that the financial

sustainability of MFIs continues to grow with a broader client foundation and it is viewed as vital

for its ability to access mainstream financial sources to intensify poverty alleviation.

2.4.2 The local perspective

In Kenya, MFIs continue to play a critical role in poverty alleviation through their outreach and

financial sustainability. Studies conducted by Suri and Jack (2016) found that in Kenya, the

poverty incidences are amongst the lowest in the East African region when compared with other

countries such as Uganda and South Sudan. However, Ravallion (2017) contrasts by stating that

despite poverty levels being lower in East Africa, the poverty rates in the country remain relatively

high in comparison to other lower-middle-income countries such as Rwanda. This, therefore,

proves that there is more to be done by MFIs through outreach and financial sustainability to

alleviate poverty in the country.

Microfinance institutions in Kenya have played a crucial role in alleviating poverty among lower-

income households. The youth in the country, between the age of 15-35 years is about 14 million

a large proportion of the country’s population, and out of these, over 50% are unemployed

(Ministry of Youth and Sports, 2009). This level of unemployment is quite worrying. Nevertheless,

Suri and Jack (2016) indicate that the Youth Enterprise Development Fund established by the

government in 2006 has become a significant source of capital for most youth in the country. MFIs

have also allowed youth in the country to access soft loans. However, the problem is high-interest

rates and lack of collateral that has impeded the access of more youth to such loans (Obama, 2017).

Mburu et al., (2017) found that despite such barriers, the Youth Enterprise Development Fund

established by the government through MFIs has allowed the majority of the youth to access loans

with no collateral. This has promoted the growth of MFIs as well as other financial intermediaries.

The issue of poverty in Kenya is considered an issue that the private sector should play a key role

in its alleviation. Mutua (2017) found that microfinance services play a key role in poverty

reduction in Mombasa County as it provides poor communities with capital. According to him,

poor people have benefited from the services of MFIs and have been able to create small

enterprises that cater for their household needs. Kidzuga (2018), on the other hand, researched the

relationship between financial sustainability and outreach of microfinance institutions in Mombasa

County and found that outreach and financial sustainability function together in reducing poverty.

Financial sustainability and outreach depend on each other and every private sector organization

should consider it in its mandate. Obeng (2017) determined the impact of micro-credit on poverty

reduction in rural areas in Mombasa County which indicated that poverty levels have reduced in

the County due to soft loans, savings services, and advice on financial uses among other services

needed by the poor people.

2.5 Summary of Literature Review and Research Gap

The chapter presented a review of the literature on the effects of outreach and financial

sustainability of microfinance on poverty alleviation. The theory of social capital showed that

society has a strong bond that helps in developing social networks necessary for the achievement

of economic and social purposes. These networks create balanced societal development and MFI’s

outreach and financial sustainability. Premchnader (2013) indicated that the poverty level in the

world has reduced over the last decade since the emergence of MFIs in Bangladesh and other parts

of the world. Imai, Arun, and Annim (2010) assert that across the globe, the lack of access to credit

is one of the primary causes of impoverishment in most developing nations. Another study by

Meyer (2010) found out that between the years 1997 and 2009, the number of MFIs globally

increased from 712 to 9,333 million and the number of its beneficiaries increased from 13.5 million

to 213.3 million with the 82% of them being women. In the local context, Suri and Jack (2016)

found that in Kenya, the poverty incidences are amongst the lowest in the East African region

when compared with other countries such as Uganda and South Sudan. It was also found that the

levels of poverty in Kenya are worse among the youth. However, Suri and Jack (2016) indicate

that the Youth Enterprise Development Fund established by the government in 2006 has become

a significant source of capital for most youth in the country. MFIs have played a key role in

allowing the youth in the country to access soft loans; however, the problem is high-interest rates

and lack of collateral that has impeded their access loans and other services.

There has been remarkable growth of MFIs in Kenya, which has impacted the livelihood of most

of the poor households in the country. Mutua (2017) discussed the Effect of microfinance services

on poverty reduction in Mombasa County. Kidzuga (2018) focused on the relationship between

financial sustainability and outreach of microfinance institutions in Mombasa County. Obeng

(2017) determined the impact of micro-credit on poverty reduction in rural areas in Mombasa

county which indicated that poverty levels have reduced in the county. Maalim (2018) determined

the effect of access to micro-financing on the growth of small and medium enterprises in Thika

Sub County. The researches above did not address the issue of financial sustainability and the

outreach of microfinance institutions in alleviating poverty in Mombasa county while Maalim

(2018) research on a different County. However, the majority of these studies on poverty

alleviation by MFIs in Kenya focused on the relationship between financial sustainability and

outreach of microfinance institutions hence they do not address the effect of outreach and financial

sustainability of microfinance institutions on poverty alleviation in Mombasa County. This is the

research gap which the current study is trying to fill by answering the research question; what is

the effect of outreach and financial sustainability of microfinance institutions on poverty

alleviation in Mombasa County?

2.5.1 The conceptual Framework

The conceptual framework below shows the interplay between the independent variable,

dependent variable, and the control variable.

Figure 1: The Conceptual Framework

Independent variables

Control variables

Firm Size

Microfinance

Outreach and

Financial

Sustainability

Poverty Alleviation

Dependent variable

Source: The researcher (2019).

This conceptual framework, the independent variables include the outreach and financial

sustainability of microfinance. The dependent variable is poverty alleviation while the control

variable includes individuals and groups.

CHAPTER THREE

RESEARCH METHODOLOGY

3.1 Introduction

The chapter is organized in this manner: First, the research design is discussed, followed by the

target population, the sample design and the data collection are discussed and finally the reliability

and validity as well as the data processing, presentation, and analysis.

3.2 Research design

A research design is defined as the method used in collecting and analyzing data with the intention

of achieving the research’s objectives (Mugenda and Mugenda 1999). In this research, the

approach used involved a small number of electronic sources which prompted the use of qualitative

content analysis, meaning that the design will be descriptive. Content analysis research is a

technique employed in such a way that valid and replicable inferences can be made by the

interpretation and the coding of textual material (Lewis, 2015). The method works in a way such

that it identifies words, characters, phrases, sentences or themes within texts such as books, essays,

and chapters of textbooks, speeches, newspaper headlines, articles, conversations, and advertising,

historical documents among others. Neuendorf (2016) says, in general, it is all about a description

of the secondary sources employed. In this study, the chosen sources from the most credible

sources represented the entire sources on the internet concerning the effects of outreach and

financial sustainability of microfinance on poverty alleviation in Mombasa County

3.3 Target Population

The target population refers to the entire group of individuals or objects understudy to the survey

data will be used in making inferences (Neuman, 2016). It is essential to understand that research

is generally of benefit to the population. The population includes 30 microfinance institutions

operating in Mombasa County. In this research, the focus of the research was based on the

electronic secondary sources generated from the internet and the University Library that addressed

the topic on the effects of outreach and financial sustainability of microfinance on poverty

alleviation in Mombasa County.

3.4 Sample design and Sample Size

Sample design is defined as a definite plan used in obtaining a sample from a given set of

population. It is also referred to as the procedure or the technique that a researcher uses in selecting

items for the sample (Bourke, 2014). In this study, the sample design that will be used is

convenience sampling which is a non-probability sampling that uses subjects that are nearest and

available to participate in the study (Bourke, 2014). The researcher selected deposit-taking MFIs

from the target population of MFIs which were 8 out of the 30 available in Mombasa County. The

reason why the deposit-taking MFIs are because they have more contact with clients which is a

measure of outreach and the amount, as well as the frequency of deposits from clients, are

indicators of their financial position. Therefore the total sample size is 8 MFIs and this sample size

is considered adequate.

3.5 Data Collection

Data collection refers to the process in which the measurement, as well as the gathering of

information from the variables of interest to the researcher, is done (Sullivan-Bolyai, Bova and

Singh, 2014). It is always done in a systematically established manner which enables the researcher

to gather answers to the research question, test the hypotheses of the study, and conduct an

evaluation at the end of the study. In this study, the most relevant sources will be collected relating

to the effects of outreach and financial sustainability of microfinance on poverty alleviation in

Mombasa County. Since each of the electronic sources will have varied information concerning

the topic, the researcher will use each of them and compare their results for better and informed

data collection for the research. The type of data used in this study will be secondary data drawn

from secondary sources, which include factual data from MFIs, the perceptions of the local people

on microcredit and figures on poverty levels in Mombasa County. The study will cover a period

of five years which is 2014 to 2018.

3.6 Reliability and Validity

Reliability is a significant aspect of the research process, as it shows how vital the information

provided could be relied on. Potter and Levine‐Donnerstein, (2009) say in content analysis, the

reliability of the extracted information over time measures its reliability. However, in most cases,

the issues of reliability are not discussed in this ethos of analysis. Even though this is the case, it

is possible to measure reliability by determining the stability of the method. It is done by recording

the data by various experts and comparing the results. If the results show similarities, then the

method is reliable or stable. However, the issue of human nature among the researchers always

affects reliability. Human beings are bound to make errors hence the errors generated by human

faults can be minimized in content analysis and not eliminated. Therefore, 80% is the acceptable

reliability margin (Potter and Levine‐Donnerstein, 2009). In this study, reliability will be measured

through internal consistency where the researcher will check the consistency of data from the

sources reflect the same underlying construct. Since the researcher used secondary sources in

catering data for this study, the validity test used is face validity. Face validity is a simple form of

validity where you apply a superficial and subjective assessment of whether or not your study or

test measures what it is supposed to measure (Potter and Levine‐Donnerstein, 2009). Therefore, in

applying this validity test, the researcher skimmed the surface of the results generated in order to

form an opinion on whether the data generated best portrays the phenomenon under study.

3.7 Data Analysis

In this research, the research will extract data from the secondary sources that answer the research

question. The modes of presentation will include tables and figures such as charts and graphs. The

effects of outreach and financial sustainability of microfinance on poverty alleviation will be

measured from the analysis of findings and data from the secondary sources. After the data is

generated through content analysis, Statistical Package for Social Sciences (SPSS) 20.0 was used

to analyze data. Sprinthall and Fisk (2013) state that SPSS helps in generating tables which can

help in making ease interpretation and assisting in making conclusion and recommendations.

Analyzed data were then summarized using frequencies and percentages and presented in tables.

The percentages and frequencies used to explain, discuss and interpret research findings obtained

conclusion and recommendations. The analysis done is as per the research objectives. To contain

the data to manageable size descriptive statistics are used as well as to provide insights into the

pattern of the trend of the data (Sprinthall & Fisk, 2013).

The relationships between the variables of this study are statistically treated using multivariate

regression analysis. This statistical technique is employed given that the study’s model has more

than one variable and also the relationship existing among these variables is assumed to be a

linear relationship.

From the regression model the following regression equation is derived:

Y= β0 + β1X1+ β2X2+ β3X3+ε

Where;

Y= Poverty alleviation

ε = Error term

β0 is the intercept of the model.

X1 Outreach, X2=Financial sustainability, and X3= Firm size

β1, β2, β3 are the coefficients of the model.

3.8. Operationalization of Study Variables

The table presented below shows how the variables have been operationalized. Table 3.1 shows

the variables, components and how they will be measured.

Table 1: Operationalization of Study Variables

Variable

Nature Of

Variable

Components and

Indicators

Scale of

Measurement

Supporting

literature

Outreach and

Financial

Sustainability

Independent

Variable

 Number of people

using the series

(Depth of reach).

 Cost to users

 Width of outreach

(Volume of

services offered)

 Length of

sustainability

 Flexibility of

repayment

 Donor

involvement

 Profitability

 Return on Assets

Ordinal

Outreach

measured by the

volume of the

services that

MFIs served its

people or the

depth which is

the socio-

economic level of

MFI’s clients

reached (Quayes

(2019).

Financial

Sustainability is

measured by the

Return on Assets

which determines

how efficiently a

company can

manage its assets

to produce profits

during a period.

The ROA

formula is ROA

= Net Income /

Total Assets.

(D’Espallier and

Goedecke, 2019;

Tucker, 2011).

Poverty

alleviation

Dependent

variable



 Level of

household debts

 Headcount Index

 Level of income

 Poverty gap index

Ordinal

According to

Wund (2011),

poverty

alleviation is

measured through

the determination

of the headcount

index (P0) which

measures the

proportion of

poor people in a

given population.

The other

measure is done

using the poverty

gap index used to

measure the

extent to which

individuals fall

below the poverty

line as a

proportion of the

poverty line

(Wund, 2011).

Firm Size

Control

Variables

 Total Assets

 Number of outlets

 Number of

employees

Ordinal

According to

Shalit and Sankar

(2017), the total

assets, the

number of

employees and

revenue per

employee, as well

as the number of

firm’s outlets,

determines its

size.

CHAPTER FOUR

DATA ANALYSIS, RESULTS AND DISCUSSION

4.0 Introduction

This chapter presents the empirical findings obtained from the collected data. The study helps to

analyze the effects of outreach and financial sustainability of microfinance on poverty alleviation

in Mombasa County. The general objective of this study was to determine the effect of outreach

and financial sustainability of microfinance institutions on poverty alleviation in Mombasa

County. It presents the analyzed data, results and discussion.

4.1 Descriptive Statistics

This section provides the data trends as collected by the researcher from the secondary sources.

The data collected was on Outreach of 8 MFIs in Mombasa County, their financial sustainability,

their size, and poverty alleviation.

4.1.1 Grouped Descriptive Statistics

This section shows the overall mean, standard deviation, minimum and maximum variable data.

Table 2: Grouped Descriptive Statistics

Variable | Obs Mean Std. Dev. Min Max

---------------------------------------------------------------------------------------------------------

Financial sustainability | 40 .72925 .1191075 .57 .96

Outreach | 40 438.95 116.7083 271.7 750.3

Firm Size | 40 375.2025 154.6655 230.4 820.9

Poverty Alleviation | 40 276989.2 22674.66 239096 301402

Source: Research data (2019)

From the table above, the mean for financial sustainability for the whole MFIs is 0.72925, the

mean for outreach is 438.95, and the mean for firm size is 375.2025 while the mean for poverty

alleviation data is 276989.2. The standard deviation for financial sustainability, outreach, firm

size, and poverty alleviation are 0.1191075, 116.7083, 154.6655 and 22674.66 respectively. The

minimum data for financial sustainability, outreach, firm size, and poverty alleviation are 0.57,

271.7, 230.4 in 2014 and 239096 in 2018 respectively. Finally, the maximum data for financial

sustainability, outreach, firm size, and poverty alleviation are 0.96, 750.3, 820.9 in 2018 and

301402 2014 respectively.

4.1.2 Descriptive statistic for Individual MFIs

4.1.2.1 Faulu DTM

Table 3: Descriptive Statistic for KWFT

--------------------------------------------------------------------------------------------------

ID1 = Faulu

Variable | Obs Mean Std. Dev. Min Max

-------------+------------------------------------------------------------------------------------

Financial Sustainability | 5 .662 .0828855 .57 .75

Outreach | 5 342 53.57238 290 420

Firm Size | 5 257.16 15.3536 230.4 266.4

Poverty alleviation | 5 276989.2 25032.15 239096 301402

- ----------------------------------------------------------------------------------------

Source: Research data (2019).

From the table above, the mean for financial sustainability for Faulu is 0.662 the mean for

outreach is 342, and the mean for firm size is 257.16 with respective standard deviation of

0.0828855, 53.57238 and 15.3536 respectively. The minimum data for financial sustainability,

outreach and firm size are 0.57, 290, and 230.4 in 2014 respectively. Finally, the maximum data

for financial sustainability, outreach and firm size are 0.75, 420, and 266.4 in 2014 respectively.

4.1.2.2 KWFT DTM

Table 4: Descriptive Statistic for KWFT

ID1 = KWFT

Variable | Obs Mean Std. Dev. Min Max

-------------+---------------------------------------------------------------------------------------------------

---

Financial Sustainability | 5 .648 .0356371 .6 .68

Outreach | 5 687.54 45.11068 632.6 750.3

Firm Size | 5 733.42 86.81392 590.2 820.9

Poverty Alleviation | 5 276989.2 25032.15 239096 301402

Source: Research data (2019)

From the table above, the mean for financial sustainability for KWFT is 0.648 the mean for

outreach is 687.54, and the mean for firm size is 733.42. The standard deviation for financial

sustainability, outreach and firm size are 0.0356371, 45.11068 and 86.81392 respectively. The

minimum data for financial sustainability, outreach and firm size are 0.6, 632.6, and 590.2 in

2014 respectively. Finally, the maximum data for financial sustainability, outreach and firm size

are 0.68, 750.3 and 820.9 in 2014 respectively.

4.1.2.3 RAFIKI DTM

Table 5: Descriptive Statistic for RAFIKI DTM

ID1 = RAFIKI

Variable | Obs Mean Std. Dev. Min Max

-------------+-------------------------------------------------------------------------------------------------

Financial Sustainability | 5 .734 .0167332 .72 .76

Outreach | 5 383.74 44.45704 312 432.2

Firm Size | 5 293.1 12.56483 273.5 302.3

Poverty alleviation | 5 276989.2 25032.15 239096 301402

Source: Research data (2019)

From the table above, the mean for financial sustainability for RAFIKI is 0.734 the mean for

outreach is 3883.74, and the mean for firm size is 293.1. The standard deviation for financial

sustainability, outreach and firm size are 0.0167332, 44.45704 and 12.56483 respectively. The

minimum data for financial sustainability, outreach and firm size are 0.72, 432.2, and 302.3 in

2014 respectively. Finally, the maximum data for financial sustainability, outreach and firm size

are 0.76, 432.2, and 302.3 in 2018 respectively.

4.1.2.4 SMEP DTM

Table 6: Descriptive Statistic for SMEP

ID1 = SMEP

Variable | Obs Mean Std. Dev. Min Max

------------------------------------------------------------------------------------------------------------------

Financial Sustainability | 5 .586 .0151658 .57 .61

Outreach | 5 514.36 35.0937 472.5 561.9

Firm Size | 5 472.52 40.50188 402.1 500.9

Poverty Alleviation | 5 276989.2 25032.15 239096 301402

Source: Research data (2019)

From the table above, the mean for financial sustainability for SMEP is 0.586 the mean for

outreach is 514.36, and the mean for firm size is 472.52. The standard deviation for financial

sustainability, outreach and firm size are 0.0151658, 35.0937 and 40.50188 respectively. The

minimum data for financial sustainability, outreach and firm size are 0.57, 472.5 and 402.1 in

2014 respectively. Finally, the maximum data for financial sustainability, outreach and firm size

are 0.61, 561.9 and 500.9 in 2018 respectively.

4.1.2.5 SUMAC DTM

Table 7: Descriptive Statistic for SUMAC

ID1 = SUMAC

Variable | Obs Mean Std. Dev. Min Max

------------------------------------------------------------------------------------------------------

Financial Sustainability | 5 .632 .0148324 .61 .65

Outreach | 5 386.08 33.11543 342.3 428.1

Firm Size | 5 310.92 9.923054 300.3 321.5

Poverty Alleviation | 5 276989.2 25032.15 239096 301402

Source: Research data (2019)

From the table above, the mean for financial sustainability for SUMAC is 0.632 the mean for

outreach is 386.08, and the mean for firm size is 310.92. The standard deviation for financial

sustainability, outreach and firm size are 0.0148324, 33.11543 and 9.923054 respectively. The

minimum data for financial sustainability, outreach and firm size are 0.61, 342.3 and 300.3 in

2014 respectively. Finally, the maximum data for financial sustainability, outreach and firm size

are 0.65, 428.1 and 321.5 in 2018 respectively.

4.1.2.6 Remu DTM

Table 8: Descriptive Statistic for Remu

-> ID1 = Remu

Variable | Obs Mean Std. Dev. Min Max

-------------+---------------------------------------------------------------------------------------------------

---

Financial Sustainability | 5 .772 .0238747 .74 .8

Outreach | 5 392.72 38.34849 341.6 441.7

Firm Size | 5 310.44 17.82044 291.7 337.3

Poverty Alleviation | 5 276989.2 25032.15 239096 301402

Source: Research data (2019)

From the table above, the mean for financial sustainability for Remu is 0772 the mean for

outreach is 392.72, and the mean for firm size is 310.44. The standard deviation for financial

sustainability, outreach and firm size are 0.0238747, 38.34849 and 17.82044. The minimum data

for financial sustainability, outreach and firm size are 0.74, 441.7 and 337.3 in 2014 respectively.

Finally, the maximum data for financial sustainability, outreach and firm size are 0.8, 441.7 and

337.3 in 2018 respectively.

4.1.2.7 Century DTM

Table 9: Descriptive Statistic for Century

ID1 = Century

Variable | Obs Mean Std. Dev. Min Max

-------------+--------------------------------------------------------------------------------------

Financial Sustainability | 5 .876 .0114018 .86 .89

Outreach | 5 393.26 97.05366 271.7 513.3

Firm Size | 5 279.1 32.44403 232.9 316.3

Poverty Alleviation | 5 276989.2 25032.15 239096 301402

Source: Research data (2019)

From the table above, the mean for financial sustainability for Century is 0.876 the mean for

outreach is 393.26, and the mean for firm size is 279.1. The standard deviation for financial

sustainability, outreach and firm size are 0.0114018, 97.05366 and 32.44403 respectively. The

minimum data for financial sustainability, outreach and firm size are and 0.86, 271.7 and 232.9

in 2014 respectively. Finally, the maximum data for financial sustainability, outreach and firm

size are 0.86, 513.3 and 316.3 in 2018 respectively.

4.1.2.8 U & I DTM

Table 10: Descriptive Statistic for U & I

ID1 = U & I

Variable | Obs Mean Std. Dev. Min Max

-------------+---------------------------------------------------------------------------------------------

Financial Sustainability | 5 .924 .0270185 .89 .96

Outreach | 5 411.9 55.67616 347.3 488.1

Size | 5 344.96 31.88892 307.8 382.7

Poverty Alleviation | 5 276989.2 25032.15 239096 301402

Source: Research data (2019)

From the table above, the mean for financial sustainability for U & I is 0.924 the mean for

outreach is 411.9, and the mean for firm size is 344.96. The standard deviation for financial

sustainability, outreach and firm size are 0.0270185, 55.67616 and 31.88892 respectively. The

minimum data for financial sustainability, outreach and firm size are 0.89, 347.3 and 307.8 in

2014 respectively. Finally, the maximum data for financial sustainability, outreach and firm size

are 0.96, 488.1 and 382.7 in 2018 respectively.

4.2 Correlation Matrix

Table 11:Correlation Matrix

Correlations

Poverty

Alleviation

Financial

sustainability

Outreach

Firm

Size

Poverty

Alleviation

Pearson

Correlation

-.670*

-.703**

-.541*

Sig. (2-tailed)

.025

.003

.024

Financial

Sustainability

Pearson

Correlation

-.670*

-.394*

-.365*

Sig. (2-tailed)

.025

.012

.043

Outreach

Pearson

Correlation

-.703**

-.394*

-.236

Sig. (2-tailed)

.003

.012

.051

Firm Size

Pearson

Correlation

-.541*

-.365*

-.236

Sig. (2-tailed)

.024

.043

.051

*. Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

From Table 11, the correlation coefficient between poverty alleviation and financial

sustainability is -.670 since the P-value associated with this coefficient is .025 which is less

than .05. This suggests that financial sustainability has a negative significant effect on poverty

alleviation. Similarly, outreach has a negative significant effect on poverty alleviation since the

correlation coefficient between these variables is -.703 with a p-value of.003. The correlation

coefficient between firm size and poverty alleviation is -.541 with a p-value of .024 suggesting

that firm size has a negative significant effect on poverty alleviation.

4.3 Regression Analysis

The researcher conducted a multivariate regression analysis so as to determine the effect of

outreach and financial sustainability of microfinance institutions on poverty alleviation in

Mombasa County. Multiple regressions are statistics that allows the researcher to predict a score

of one variable on the basis of their score on several other variables. The main purpose of

multiple regressions is to learn more about the relationship between several independent or

predictor variables, a control variable and a dependent or criterion variable.

4.3.1 Normality of Residuals

The researcher wanted to check whether the assumption of normality was met. Normal Q-Q plots

were employed to test for this assumption. The scatter plot below indicated the presence of

multivariate normality in the data population of the four variables. The assumptions of normality

were met since the scatter points lay within the 450 line.

Figure 2: Linear relationship among Variables

Source: Research data (2019).

4.3.2 Model Summary

Table 12: Model Summary

Model Summaryb

Model

R Square

Adjusted R Square

Std. Error of the Estimate

.885a

.783

.778

20275.878

a. Predictors: (Constant), Size, Financial Sus, Outreach

b. Dependent Variable: Poverty alleviation

Source: Regression Analysis (2019)

From Table 11 R-square which measures the variation of the independent variable that is

explained by independent variables is 0.7833. 78.33% of the variation in poverty alleviation is

explained by outreach, financial sustainability and firm size.

Table 13: Analysis of Variance (ANOVA)

ANOVAa

Model

Sum of Squares

Mean Square

Sig.

Regression

43105010939

14368336980

34.95

.001b

Residual

14800003756

411111215.4

Total

57905014695

a. Dependent Variable: Poverty alleviation

b. Predictors: (Constant), Firm Size, Financial sustainability, Outreach

Table 13 shows Table 13 shows the overall model was a good fit since F(3,29) =34.95 with a p-

value less than 0.05.

Table 14: Table of coefficients

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

Sig.

Std. Error

Beta

(Constant)

670870.5

46024.33

14.58

.000

Financial Sustainability

-322833.5

62135.04

-.086

-5.20

.000

Outreach

-211.7559

50.32267

-1.355

-4.21

.000

Firm Size

-174.5849

68.87468

-1.088

-2.53

.017

a. Dependent Variable: Poverty alleviation

Source: Research Data (2019)

Source: Regression Analysis of Research Data (2019)

After multivariate regression analysis was done, the above panel regression was generated from

the data set. From the panel regression analysis, we can deduce the following model:

Y=670870.5-211.7559 X1 –322833.5X2 -174.5849X3+e

4.4 Interpretation of the Findings

The study sought to determine the effects of outreach and financial sustainability of microfinance

on poverty alleviation in Mombasa County. A multivariate regression model was applied to

determine the effects. The findings, according to the regression model are discussed in this

section.

4.4.1 Effects of firm size on poverty alleviation

Since the coefficient of firm size is -174.5849 with a standard error of 68.87468 and its

associated t statistic is -2.53 whose p-value is approximately 0.0001 which is less than 0.05 we

reject the null hypothesis and conclude that firm size has a negative significant effect on poverty

alleviation at 5% level of significance. This, therefore, shows a negative relationship between

firm size and poverty alleviation such that if the size of a firm increases, the poverty level

reduces within the targeted population. These results are in accordance with Nanayakkara and

Mia (2016) who found out that the larger the size of microfinance institutions, the higher their

ability to reduce poverty because it provides more access to credit. Further, Nanayakkara and

Mia (2016) adds that the larger the size of MFIs, the larger the sizes of loans offered which can

be accessed by a large number of poor people in a given population hence increasing capital for

small enterprise start-ups crucial in reducing poverty among households.

The effects of firm size on poverty alleviation among the 8 MFIs in Mombasa County are

indicated by the figure below.

Figure 3: The Effects of Firm Size on Poverty Alleviation

Source: Research Data (2019)

4.4.2 Effects of Outreach on poverty alleviation

Since the coefficient of outreach is -211.7559 with a standard error of 50.32267 and its

associated t statistic is -4.21 whose P-value is approximately 0.0001 which is less than 0.05 we

can reject the null hypothesis and come to the conclusion that outreach has a negative significant

effect on poverty alleviation at 5% level of significance. It means that when outreach intensifies,

poverty reduces within the target population where the MFIs operate. For instance, in Mombasa

County, if MFIs intensify their outreach, more people are served with an increased volume of

services, hence reducing poverty. This relationship proves Annim (2018) and Quayes (2019)

assertions that higher the intensity of outreach or the extent to which the MFIs succeed in

reaching out to the targeted population in the region and the degree to which these MFIs meet

their client’s financial service demands, the higher the degree of reducing poverty among these

clients. The Figure below shows the relationship between outreach and poverty alleviation

among the 8 MFIs in Mombasa County.

Figure 4: The relationship between outreach and poverty alleviation

Source: Research Data (2019

4.4.3 Effects of Financial Sustainability on poverty alleviation

Since the coefficient of financial is -322833.5 with a standard error of 62135.04 and its

associated t statistic is -5.20 whose P-value is approximately 0.0001 which is less than 0.05 we

can reject the null hypothesis and come to the conclusion that financial sustainability has a

negative significant effect on poverty alleviation at 5% level of significance. This can be

interpreted that if the financial sustainability of any of the 8 firms is increased, it will have a

negative effect on poverty alleviation such that its increase will cause a decrease in poverty

alleviation. This means that for poverty to reduce there should be an increase in financial

sustainability. According to Chikalipah (2017), an increase in the financial sustainability of MFIs

leads to the creation of a sustainable microfinance industry that continues to grow with a wider

client base and is often viewed as crucial for its access to mainstream sources of finance as well

as reducing poverty. Therefore, there is a need for MFIs to increase financial sustainability to

reduce poverty at the same time. The figure below shows the relationship between financial

sustainability and poverty alleviation among the 8 MFIs in Mombasa County.

The relationship between financial sustainability and poverty alleviation

Figure 5: The relationship between financial sustainability and poverty alleviation

Source: Research Data (2019

4.4.4 Effects of outreach, financial sustainability and firm size on poverty alleviation

Since the coefficients of outreach, financial sustainability and firm size were all negative and

their associated t statistic were negative and whose P-values were approximately 0.0001 which is

less than 0.05, the null hypothesis was rejected and the researcher concluded that financial

sustainability, outreach, and firm size had negative significant effect on poverty alleviation at 5%

level of significance. This, therefore, meant that an increase in two independent variables and the

control variable causes a significant reduction in poverty. For poverty to reduce in Mombasa

County there should be an increase in microfinance size, outreach, and financial sustainability.

For the regression analysis, the figure below was generated that shows the poverty trends for the

past four years as induced by the activities of the 8 MFIs in the county.

CHAPTER FIVE

SUMMARY, CONCLUSION, AND RECOMMENDATION

5.0 Introduction

This chapter provides a summary of the research findings, provides a conclusion based on the

research findings, provides recommendations and suggestions for further research.

5.1 Summary of the Findings

The objective of this study was to determine the effect of outreach and financial sustainability of

microfinance institutions on poverty alleviation in Mombasa County through determining how

outreach, financial sustain inability, and firm size play a role in influencing the reduction of

poverty in the county.

The data analysis demonstrated that the outreach of microfinance institutions play a key role in

alleviating poverty in Mombasa County. It indicated that an increase in outreach among the 8

MFIs understudy could lead to a significant reduction in poverty in the county. Outreach ensures

that MFIs reach a wider population which is also called the breadth of outreach. If MFIs offer

services to more people within the targeted region and population and they increase the volume

of services offered to the people, then, it means that more households will access credit, savings,

financial advises among other services offered by MFIs that could reduce poverty.

In regard to financial sustainability, the research findings indicated that finical sustainability had

a significant negative effect on poverty alleviation in Mombasa County. It showed that for

poverty to reduce among the people in the region there is a need for microfinance institutions to

be there for its clients and beneficiaries in the long run. In doing so, MFIs must ensure that it

serves more clients and it makes enough income from the services to be able to serve them for a

longer period while adding value to their lives.

The other finding was that firm size also played a key role in poverty alleviation in the county. It

indicated that the larger the size of an MFI, the greater the ability to reduce poverty. The findings

also indicated significant negative effects by firm size on poverty alleviation in the county it

gains a higher ability to reduce poverty because it provides more access to credit, more financial

services and it reaches more clients within the target population.

5.2 Conclusion of the Study

The research findings led the researcher to the conclusion that the outreach and financial

sustainability of microfiche helps has a significant effect on poverty alleviation in Mombasa

County. Microfinance Institution’s size in terms of its total assets gives it the ability to reach

more clients, provide more services to more clients within a given population more than

relatively smaller microfinance institutions. Therefore, larger MFIs have the ability to reach

more people making it efficient in its objective to reduce poverty in a given population. It is

paramount that most MFIs strives to increase its size over time by ensuring that it generates more

revenue that will help in increasing its size and the ability to achieve its objectives.

Additionally, out of this research’s findings, it becomes clear that financial sustainability is at the

heart of every MFI both in ensuring that it survives in the market as well as allowing it to meet

its objectives. Every MFI strives to remain relevant and be able to sustain itself financially apart

from getting support through donors. It has to ensure that its activities are profitable enough to

sustain its activities while meeting the needs of the poor people such as providing affordable

interest rates. This will help in reducing poverty in a long-term basis.

Further, outreach proved to be an important aspect of Microfinance institutions in Mombasa

Country. The research findings indicated a negative relationship between outreach and poverty

alleviation. This relationship proves that for MFIs’ impact in Mombasa County; they should

strive to provide more services such as loans, savings, financial pieces of advice and other

services to a larger number of poor people. Even thigh poverty trends from this research’s data

showed a decline in poverty levels in the County, there is a need to ensure that more people get

these services.

5.3 Recommendations

From the results of this study, it was clear that firm size, outreach, and financial sustainability are

crucial in reducing poverty and even though these MFIs have played a key role in reducing

poverty in the county, there is still a need to intensify outreach, financial sustainability and size

of firms to ensure that the intensity of poverty eradication is increased. Therefore, microfinance

institutions in Mombasa County have to ensure that it carries out promotions and campaigns to

create awareness of their services to reach out to more clients by increasing the volume of their

services and ensure that their financial statuses are sustainable enough to allow it to provide

better services on a long term basis.

This study also recommends that for MFIs to maintain their financial sustainability, they should

further attract new customers through promotions as this would help them in improving their

outreach which in turn will help in improving financial performance and profitability and

lowering operating costs hence boosting the overall quality of the MFIs in the county. They

should also source for more grants from other organizations and the government, establish

visionary leadership and evaluate the efficacy of their investments (Mwangangi, 2017).

Another recommendation based on the results of this study is that MFIs should open more

branches countrywide. During data collection, the researcher found that there are few MFIs in

Mombasa County when compared to counties such as Nairobi and Uasin Gishu counties.

Increasing the number of MFIs in Mombasa County will provide services closer to the people

and hence increase the number of customers. The study showed that access to that to credit

among people in Mombasa is still limited and thus access to credit has to be strengthened.

Finally, a positive correlation between financial sustainability and outreach implies MFIs could

reach more clients which could help them in their social mission and sustainability.

5.4 Suggestions for Further research

This study was done with a small sample size of 8 microfinance institutions in Mombasa County,

a small section of the country. This aspect brings concern when it comes to replicating the results

of the study to other parts of the country because the results may not be a replica of what can be

perceived of other parts of the country and other contexts in the world. Therefore, this study was

limited in regard to generalizability and representativeness. Therefore, the researcher

recommends that a wider researcher that reflects the issues of the effects of outreach and

financial sustainability of MFIs in the whole country could help in resolving the issue of

generalizability. Further research done on a bigger scale with large sample size could shed more

light on how microfinance activities impact on poverty alleviation on the poor people in Kenya

(Mutua, 2017).

Secondly, in this study, the researcher confined to the research data from secondary sources from

within a range of the past five years which makes its scope a little narrower and it may not give a

completely clear picture of the situation of poverty in Mombasa County. A suggestion on this is

that further research could be done with a wider scope in regard to data collection with the

guidance provided by this research. Covering a wider period of about ten years and increasing

the number of MFIs understudy will help in providing an accurate picture of the situation.

Further, Munthe-Kaas, et al., (2019) reliable sources such as government websites, trusted

organizations such as NGO’s websites, are credible in conducting secondary research and this

could help future studies on the effects of outreach and financial sustainability of MFIs on

poverty alleviation in Mombasa County in future.

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APPENDIX I

Names of MFIs in the Study

A-Faulu Deposit Taking Microfinance Mombasa Main Branch

B- Kenya Women Finance Trust Deposit Taking Microfinance Mombasa CBD Branch

C- Rafiki Deposit Taking Microfinance Mombasa Main Branch

D- SMEP Deposit Taking Microfinance Mombasa Main Branch

E- SUMAC Deposit Taking Microfinance Mombasa Main Branch

F- Remu Deposit Taking Microfinance Mombasa CBD Branch

G- Century Deposit Taking Microfinance Mombasa Branch

H- U & I Deposit Taking Microfinance Mombasa Branch

exe

edad

FRED

Graph

c D

E F

Financial

Sustainabity

Dataof

MFIs

Mombasa

County

Messured

using

Retum

Assets

Ratio

‘Sourcecf

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Peto

2014

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‘2016

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microfinance

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117.

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APPENDIX II

Raw Data Collected

THE EFFECTS OF OUTREACH AND FINANCIAL SUSTAINABILITY OF MICROFINANCE ON POVERTY ALLEVIATION IN MOMBASA COUNTY

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