This thesis is my original work and has not been presented for a degree in any other University. No part of this thesis may be reproduced without the prior written permission of the author and/or Rongo University College.

OUMA, Robinson Omondi

MBM/1002/12

Signature: .................................. Date: ..........................................

DECLARATION BY SUPERVISORS

This thesis has been submitted for examination with our approval as University supervisors:

DR. RICHARD NYANGOSI

Senior Lecturer,

School of Business and Human Resource Development,

RONGO UNIVERSITY COLLEGE

Signature: .......................................... Date:...................................................

DR. RONALD BONUKE

Senior Lecturer,

School of Business and Economics

MOI UNIVERSITY

Signature: ........................................... Date:...........................................

DEDICATION

For efforts so precious, love so true and understanding so focused, I dedicate this work to my lovely wife, Judith Jepchumba, my son Chris Brandon Ouma for his constant troubles and joy that motivated my spirit. To my parents Mr. and Mrs. Ouma for their love and understanding and lastly my loving brother Denis Ouma for his tireless support.

The socio-economic growth and development of Migori County is to a great extent dependent on farming and small scale enterprise. Majority of the people working in these sectors are low income earners whose main source of credit facilities is the micro lending institutions. The aim of the present study was to analyse the effects of microcredit facilities on the welfare of households in Suna East Sub-County. The study focussed on the microcredit customers who got loan from the five selected microfinance institutions in Suna East Sub-County. A sample size of 306 respondents was obtained for the study using Krajcie & Morgans' table,1970. A survey was conducted to carry out the study in which questionnaires was developed to collect data from the respondents. Multiple regression analysis was used to test the proposed hypotheses of the study and to verify the association between variables. The results of the multiple regression analysis test revealed that there was a significant effect of microcredit in improving household's welfare status and living standard of the microcredit users in the Sub-County. Both descriptive and inferential statistics were used to draw the results from the study. Through descriptive analysis, the study clearly demonstrated that microcredit has played a positive role in improving the household status of customers after getting the loan. In this regard the study observed that microcredit played the positive role in changing and improving the living standards, income, diet patterns, health status and children's education of the respondents. The current study did not put into consideration the effect of respondents background characteristics on household welfare. The study recommends that emphasis on the importance of loan services on household welfare should be made and the amounts borrowed be increased so as to meet the needs of the residents, residents should be encouraged to save with the microcredit facilities so as to raise their chances of gaining support from the facilities and lastly capacity building among households should be maintained so that residents can maximize potentials within the microcredit facilities.

TABLE OF CONTENT DECLARATION i DEDICATION ii ABSTRACT iii TABLE OF CONTENT iv LIST OF ABBREVIATION AND ACRONYMS vii LIST OF TABLES viii ACKNOWLEDGEMENT ix CHAPTER ONE 1 INTRODUCTION 1 1.1. Background of the Study 1 1.2. Problem Statement 4 1.3. Purpose of the Study 5 1.4. Objectives of the Study 5 1.5. Research Hypotheses 6 1.6 Significance of the Study 6 1.7. The Scope of the Study 7 1.8. Limitations of the Study 7 1.9. Operational Definition 8 CHAPTER TWO 11 LITERATURE REVIEW 11 2.0 Introduction 11 2.1. Overview of the Problem 11 2.1.1. The Concept of Microcredit and Welfare Improvement. 11 2.1.2 Effects of Micro-credit Facilities on household welfare 12 2.2. Theoretical Framework 27 2.3. Empirical Literature Review 29 2.4. Conceptual Framework 34 CHAPTER THREE 36 3.1 Introduction 36 3.2. Research Design 36 3.3 Target Population 36 3.4 Sample size and Sampling Procedure 37 3.4.1 Sample Size 37 3.4.2 Sampling Techniques 38 3.5 Data Sources 38 3.6 Data Collection Instrument 39 3.6.1. Validity and Reliability of Research Instruments 39 3.7. Data collection procedure 40 3.8. Data Analysis 40 3.9. Ethical Considerations 40 CHAPTER FOUR 42 PRESENTATION AND DISCUSSIONS OF FINDINGS 42 4.1 Introduction 42 4.2 Response rate 42 4.3 Data Screening and Cleaning 43 4.3.1 Univariate outliers 43 4.3.2 Testing for Normality 43 4.3.3 Assumption of Linearity 44 4.3.4 Assessing Homogeneity of Variances 44 4.4 Respondents Demographic Profile 45 Table 4.4.1 Respondents Demographic Profile 45 4.4.2 Gender of the Respondents 45 4.4.3 Age of the respondents 46 4.4.4 Respondents Level of Education 46 4.4.5 Occupation of Respondents 47 4.5 Descriptive Statistics of Key Study Variables 47 4.5.1 Loans Services 48 4.5.2 Savings Services 51 4.5.3 Non-Financial Services 52 4.5.4 Capacity Building Packages 54 4.5.5 Prevailing Levels of Household Welfare among Residents of Migori County 55 4.6 Testing Formulated Hypotheses for the Study 56 4.7 Study Model 59 4.8 Discussions of the findings 60 CHAPTER FIVE 66 SUMMARY OF THE FINDINGS, CONCLUSIONS AND RECOMMENDATIONS 66 5.1 Introduction 66 5.2 Study Findings 66 5.3 Conclusions 67 5.4 Recommendations 68 5.5 Suggestions for future research 68 REFERENCES 70 QUESTIONNAIRE 78 APPENDICES 82

Kadet Kenya agency for development of enterprise and technology

KWFT Kenya Women Finance Trust

SPSS Statistical package for social sciences

AMFI Association of Microfinance Institutions

CIDA Canadian International Development Agency,

Table 3.1 Distribution of target population

Table 4.1: A Summary of the Response Rate

Table 4.2: Testing for Normality Requirements

Table 4.3: Testing for Linearity Requirements

Table 4.4 Test of Homogeneity of Variances

Table 4.5 Respondents Demographic Profile

Table 4.6 Prevailing perceptions on loan services

Table 4.7 Factors motivating respondents to take a loan

Table 4.8 Respondents’ views towards saving services

Table 4.9 Respondents Average savings on Monthly Income for Emergencies

Table 4.10 Non-Financial services

Table 4.11 Capacity Building

Table 4.12 Household welfare

Table 4.13 Model Summaryb

Table 4.14 Regression Coefficientsa

I wish to acknowledge my research supervisors Dr. Richard Nyangosi and Dr. Ronald Bonuke for the guidance and directions they gave me during the development of this study. I also acknowledge the support of my lecturers, Dr. Ambrose Kemboi, Mr. Patrick Kutoto and Mr. Emanuel Tanui for their unrelenting coaching and training which has endowed me with the competencies that have been core to the development of this study. I also acknowledge the support of my classmates with whom we have shared great knowledge in the course of our studies, their advice and support have been immensely instrumental in developing this study.

Overview

This chapter presents the background of the study, the problem statement, the purpose of the study, objectives of the study, research hypotheses, significance of the study, the scope of the study, limitations and assumptions of the study and lastly the operational definition of the significant terms which are discussed in details.

There are over 100 million people who use Micro-credit facilities around the world, of which 84% of them are women and youths, and 72% are “very poor”, (Dunford et. al., 2007). The most important objective of micro-credit facilities is to alleviate poverty.

The living standard in low income developing countries always remain crucial issue to be addressed. In many developing countries, like Bangladesh, microfinance has been used as a tool to gear up the living standard of poor people (Akram & Hussain, 2011). There is an almost global agreement now that microfinance to the poor is viewed to achieve equitable and sustainable gains for economic and social development in the twenty-first century (Akram & Hussain, 2011)..

In the past two decades, microcredit has advanced and developed into a Nobel Peace Prize winning concept for poverty alleviation (Carlin, 2006). Microcredit is seen as a solution for ending the endemic poverty canker in poor communities. It provides working capital for poor people to engage in small businesses (Rankin, 2001). One of the common features of microcredit is that it creates self-employment in non-formal sectors for income-generation. However, the fact that microcredit helps the poor out of poverty particularly in the developing world is not universally accepted. This is because there is still skepticism about the ability of microcredit to make a major dent in the poverty situation in third world countries (Elahi and Danopoulos, 2004). The main argument here is that the diverse kinds of lenders who include traditional money lenders, informal groups, and conventional banks providing specialized credit pawnshops, friends and relatives among others have different goals in providing these small loans. Some are motivated by profits, especially money lenders and thus alleviating poverty and improving the socio-economic conditions of the poor is not a major goal for them.

Despite the skepticism, microcredit has been embraced by national governments, non-governmental organizations (NGOs) and world development bodies as well as the international donor community as a means of alleviating and eventually eradicating poverty (Nissanke, 2002). According to Akudugu at al. 2012, there has been a surge in the number of microcredit institutions and organizations operating in the developing world including Asia, Africa and South America. The use of microcredit to fight poverty is supported by the assessment that access to it facilitates the adoption of modern production technologies and overall household welfare.

Since first coming to prominence in the 1970s micro-credit has come to play a very important role in the field of development, as illustrated by the launch of the Microcredit Summit in 1997. The Summit aims at reaching 175 million of the world’s poorest families, especially the women of those families, with credit for the self-employed and other financial and business services, by the end of 2015 (Microcredit Summit, 2005). World over, provision of micro-credit facilities to poor households and the youths has been considered an innovative and sustainable approach to community economic empowerment and enterprise development, mainly by mobilizing resources to more productive uses, leading to generation of income and improved livelihoods.

According to Liliana et.al (2010), there is a correlation between lack of financial access and low income. The success of some of the micro lenders working with the poor households, particularly in South East Asia, West, Central and Eastern Africa has put micro lending high on the agenda of many development agencies. In Tegucigalpa and Cholteca in Honduras in 2003, effect assessment studies revealed that 60% and 50% of micro-credit recipients had their sales and incomes increase respectively one year after receipt of credit for working capital. Agricultural Finance Cooperation Limited in 2008 in India, assessed development effect of microfinance programs. Clients reported increase in income from 76% of activities Liliana et.al (2010).

The challenge faced by most countries now, especially the developing countries, is to improve the lives of its citizens and achieve sustainable economic growth for health development. Developing countries, especially in Kenya, have been concerned about the rising unemployment, which is regarded as the main cause of urban and rural poverty. In Kenya, of the 13 million youth, less than 50% are in gainful economic activities in the formal, informal and public sectors of the economy, while majority are unemployed, (Simeyo et al., 2011). They comprise 61% of the unemployed. This trend is worrying and calls for intervention measures. Micro finance lending and associated services are one such intervention. As such, the number of micro-lending institutions has steadily increased over the last decade in Africa, and particularly in Kenya.

Migori County, like other parts of the country, has also witnessed this increase in the number of microfinance institutions over past period of time. This sharp increase in Migori could be attributed to the kind of occupation dominating the area, especially farming and small scale business. People working in these informal sectors are low income earners who do not qualify for credit facilities from the commercial banking institutions. Micro finance lending and associated services are one such intervention. However, lack of collateral and high interest rates is an impediment to access to loans from Micro finance institutions (MFIs) by the people in this sector (Mushimiyimana, 2008).

In view of the increasing microfinance services in the world targeting the poor with anticipation of an increase in positive outcomes, particularly in developing countries, as is evidenced by the efforts above; and the little information that exists about the actual effect of the micro-credit facilities on the welfare of the households benefiting from the credit schemes offered by these micro lending institutions in Migori County, this research will strive to establish the effects of microcredit facilities on the welfare of households particularly in Suna East Sub-county.

It has been observed that in Suna East Sub-County, just like in other Counties in Kenya, Microcredit has been applied as a poverty eradication strategy. It has been used to provide low-income people with small grants, micro-credits and other Microcredit services as an impetus to exploit their productivity and develop their business to help them improve their livelihoods. For a long time, Microcredit has been used as an intervention strategy to address the marginalized situation of the poor with the hope that when they access credit facilities, they would achieve socio-economic development and thereby contribute to the development of their communities and improve their welfare.

Suna East Sub-County has witnessed an increase in the number of households accessing micro-credit facilities over the past decade especially the low income earners working in the informal sector who don’t qualify for credit facilities from the commercial banking institutions. However, much as Microcredit services have existed in Migori for a period of time, there is lack of information on the good practices in the area and the exact magnitude of its effects and how the loans are accessed and utilized in order to attain socio-economic development. The fact that poverty still exists amidst the attempts of provision of Microcredit creates room for exploring how Microcredit has benefited the poor in Suna East Sub-County.

The purpose of the study is to examine the effects of microcredit facilities on the welfare of households in Suna East Sub-County.

The study will assess the effects of microcredit facilities on the welfare of households in Suna East Sub-County. It will be guided by the following objectives:

To examine the effect of loan services offered by microcredit facilities on household welfare in Suna East Sub-County.

To determine the effect of saving services offered by microcredit facilities on household welfare in Suna East Sub-County.

To investigate the effect of non-financial services offered by microcredit facilities on household welfare in Suna East Sub-County.

To examine the effectiveness of capacity building packages offered by microcredit facilities on household welfare in Suna East Sub-County.

The research hypotheses will include:

Ho1: Loan services offered by microcredit facilities have no significant effect on household welfare.

Ho2: Saving services offered by microcredit facilities have no significant effect on household welfare.

Ho3: Non financial services offered by microcredit facilities have no significant effect on household welfare.

Ho4: Capacity building packages offered by microcredit facilities have no significant effect on household welfare.

This study is premised on the fact that evaluating the effects of microcredit facilities on the welfare of households in Suna East Sub-County is crucial in understanding the extent to which these microcredit facilities can assist in uplifting the economic status and alleviating poverty among these households. This study will help in providing vital information that can be useful in redesigning and strengthening the micro-credit program in the country by the relevant entities which include Ministry of National Treasury, Ministry of Industrialization and Enterprise development, Ministry of East African Affairs, Commerce and Tourism, Culture and Arts, Ministry of Devolution and Planning among other related ministries, Microfinance institutions, Societies and individuals. Besides, it will contribute to the body of knowledge and learning especially in the field of microcredit financing.

The study will focus on the effects of microcredit facilities on the welfare of households in Suna East Sub-County. Suna East Sub-County is chosen as a research site because of the ever-increasing number of micro lending institutions in the area which is attributed to the kind of occupation dominating the area, especially farming and small scale business. People working in this informal sector are low income earners who do not qualify for credit facilities from larger financial institutions. The study will target clients of various micro-credit institutions operating within the County which include Faulu Kenya, SMEP, Opportunity International, Kadet and Kenya Women Finance Trust. These institutions offer their credit facilities to clients organized in groups or to individual clients. The data was collected during the months of August to October, 2014.

The major foreseeable limitation of the study was the unwillingness of respondents to provide truthful information, following the government’s crackdown of bogus micro-credit institutions; this could have resulted to some respondents apprehensive of providing sincere data relevant to the study. However, the researcher vividly explained the real intention of the study being premised on educating the populous on the benefits of microcredit facilities, their access and utilization. Another foreseeable limitation was that welfare status of a household is a very complex and multi-dimensional concept that cannot be easily captured quantitatively using one variable. Therefore to overcome this, the study on the welfare of households was assessed by aggregating a number of indicators including income security, food security situation, health and education securities. Yet another limitation was the difficulty and uncertainty of making a generalization of the findings across all households in the Nation at large since it shall only target a few households in Suna East Sub-County.

The study assumed that the respondents were truthful and provided unbiased and correct responses to the questions. The study also assumed that the sampled respondents adequately represented the entire target population of the study within Migori County. Lastly the researcher assumed that low income earners in Suna East Sub-County access microcredit facilities from micro lending institutions to improve their welfare.

In this section, operational definitions are presented as used within the context of this study.

Micro lending: this is the extension of very small loans (microloans) to impoverished borrowers who typically lack collateral, steady employment and a verifiable credit history. It is designed not only to support entrepreneurship and alleviate poverty, but also in many cases to empower women and improve the welfare of entire communities by extension.

Microcredit facilities: These include Small financial loans, farm inputs like fertilizers and machinery, agronomic packages and capacity building services to small scale farmers and traders to enhance their competencies to manage businesses.

Micro-credit institutions: Also referred to as micro lending or microfinance institutions, they are organizations that offer microloans that target users like micro enterprise and low-income households' utilization for income generation and enterprise development.

Food security: Access by all people at all times to enough food, both in quality and quantity, for an active and healthy life. Food security incorporates food availability and food accessibility.

Income security: this refers to a household’s ability to earn sufficient income over a long period of time. Income refers to the amount of money or its equivalent received during a period of time in exchange for labour or services, from the sale of goods or property, or as profit from financial investments. This includes the amount of savings, accumulated earnings and wages/salary amount.

Health security: It refers to the ability of a household to guarantee its members minimum protection from diseases and unhealthy lifestyles, enabling them have a state of complete physical, mental, and social wellbeing, and not merely the absence of disease or infirmity within a household.

Education security: this explains the ability of a household to send their members to educational institutions to acquire knowledge through teaching and learning. For instance, the ability of a household to meet school fee obligations and keep the children in school at all times.

Household: A person or a group of related and/or unrelated persons who live together in the same dwelling unit, who acknowledge one adult male or female as their head, and who share community life by their dependence on communal holdings as a source of income and food.

Non-financial Services: This includes services such as training services, farm inputs, , provision of health plans, women empowerment, and marketing services.

This chapter presents review of literature relevant to the study headlined within the thematic objectives of the study; the review is basically based on concepts and records related to the study from books, journals and other relevant articles. It also contains review of empirical literature, theoretical literature as well as the conceptual framework.

Over the last decade or so, we have observed a proliferation of microfinance institutions (MFIs) in developing and transitional economies as well as in some developed countries such as USA and Canada. Modeled on infamously ‘successful’ institutions such as the Grameen Bank of Bangladesh, the Badan Kredit Kecamatan (BKK) of Indonesia or Banco Sol of Bolivia, new strands of ‘innovative’ microfinance institutions have been established specifically for reaching ‘the poor’, in the field of ‘micro-enterprise finance’ and ‘poverty lending’. Drawing lessons from the widely acknowledged failure of the earlier experiments with credit interventions such as the targeted rural credit programmes based on subsidized interest rates, new microcredit programmes lean heavily towards ‘market-based solutions’, with use of concepts such as group lending and joint liability contracts modeled for different institutions, working in different environments with different poverty conditions and enterprise opportunities (Nissanke, 2002).

Known collectively as microfinance services, Microcredit facilities include micro-credit loans, inputs, micro-savings, micro-insurance, and money transfers, and have been attributed with enabling micro-entrepreneurs to build businesses and increase their income, as well as improving the general economic wellbeing of the poor. Microfinance has been credited with improving other financial outcomes such as furniture or a sewing machine, as well as non-financial outcomes such as health, food-security, nutrition, education, women’s empowerment, housing, job creation, and social cohesion (Odell, 2010).

The underlying logic is that by providing financial services to the poor, for example in the form of credit or savings, they manage their money differently, investing, acquiring productive assets, increasing their skills levels and opening new businesses. But various studies have questioned these positive impacts. Some indicate much more mixed impacts, such as benefits for the poor but not for the poorest (Copestake, Bhalotra, & Johnson, 2001;; Zaman, 2001); or helping the poor to better manage the money they have but not directly or sufficiently increasing income and empowering women. (Husain, Mukherjee, & Dutta, 2010) or that money spent on microfinance could be better used more effectively for other interventions or that a single intervention (such as microfinance) is much less effective as an anti-poverty resource than simultaneous efforts that combine microfinance, health and education. Others allude to negative impacts such as the exploitation of women, increased or at best unchanged poverty levels, increased income inequality, increased workloads and child labour, the creation of dependencies and barriers to sustainable local economic and social development (Bateman & Chang, 2011)

Microcredit should address capital investment decisions, general business management and risk management. In the world over, provision of microcredit services to the low income earners has been considered an innovative and sustainable approach to the poor for financial and micro enterprise activities empowerment leading to generation of income so as to improve their livelihoods and contribute to economic growth. Debates on extending the reach of microfinance to the very poorest people increasingly focus on savings facilities. In remote areas, mobilization and intermediation of member savings may be the crucial step before accessing external loan funds. To this end, microfinance, the provision of a wide range of financial services, has proved immensely valuable to poor people, especially the youth and women on a sustainable basis. Access to financial services has allowed many families throughout the developing world to make significant progress in their own efforts to escape poverty (Wright, 2005).

A micro-lending or micro-credit facility to poor households has received widespread international attention in the past ten years. Micro lending is therefore viewed by many as a vehicle towards poverty eradication. With more than half of the world’s population living without access to banking or other financial services (Beck, Demirguc-Kunt, & Peria, 2008; Chaia et. al, 2009), the potential market for micro-credit facilities is substantial. As the number of micro-lending organizations has expanded (Swibel, 2007), so has the supply of microcredit facilities around the world.

Over the last decades, microfinance has been promoted as an important tool for poverty reduction and the achievement of the millennium development goals. Access to affordable credit is crucial for hundreds of millions of people in poor economies who face low labour productivity on the one hand and high returns to capital on the other. Former United Nations Secretary General Kofi Annan, when launching the International Year of Microcredit in 2005, pointed out that sustainable access to microfinance helps alleviate poverty by generating incomes, creating jobs, allowing children to go to school, enabling families to obtain health care and empowering people to make the choices that best serve their needs.

Micro lending institution have been established in a number of countries, over the past decade, as a means of mitigating the key constrains of sustainable access to financial resources by low income earners. Proponents of micro lending view it as a cost effective way of building an entrepreneur culture, enhancing domestic economic capacity, reducing poverty and unemployment (Mersland and Strom, 2009). It is viewed with a lot of expectation and a potential way of propelling economic growth in developing countries. Microcredit programmes that have targeted women have been found to be effective as it ensures that the net benefits that accrue from increased income does not only help the women but that, the welfare of the family and particularly children are improved reducing the overall poverty of beneficiary families (Newaz, 2003).

Proponents of microcredit have also found that, the position and bargaining power of women with access to credit have been found to be improved since their cash is channelled to the family (Newaz, 2003). According to Elahi and Danopoulos (2004), microcredit can perhaps help avoid poverty among some poor people but not all the poor. This is confirmed by the findings of Kay (2002) that microcredit does not work in isolation and that it may not be effective in low population density and self-contained areas where there is insufficient cash-based market activity. Other critics have also pointed out that, though microcredit can reduce vulnerability, it has not been able to lift women out of poverty or demonstrated any significant impact as a result of some limitations which make it impossible to transform social relations and the structural causes of poverty (Kay, 2002).

Fay (2005) notes that assets are at the core of households’ survival strategies. Assets help the poor to meet their needs in future, enhance wealth improvement and reduce exposure to external shocks. They also minimize the consequences of external shocks. The poor are excluded from the formal financial markets hence they accumulate their savings through semi-durable and durable assets. Assets accumulation is therefore made possible by allowing the poor to have access to financial. Owuor (2009) empirically examined the impact of micro-finance on smallholder farmers in Kenya using Propensity Score Matching. He found that smallholders’ participation in micro-finance credit (MFC) improves their income by a range of between US$ 200.00 and US$ 260.00 per hectare in a single production period. However, participation in the Micro-Finance Credit (MFC) among smallholder farmers was constrained by low literacy levels, gender, differentials in asset endowment, poor road infrastructure and maintenance of indigenous group structures.

The available evidence indicates that in many cases microcredit has facilitated the creation and the growth of businesses. It has often generated self-employment, but it has not necessarily increased incomes after interest payments. In some cases it has driven borrowers into debt traps. There is no evidence that microcredit has empowered women. In short, microcredit has achieved much less than what its proponents said it would achieve, but its negative impacts have not been as drastic as some critics have argued. Microcredit is just one factor influencing the success of a small businesses, whose success is influenced to a much larger extent by how much an economy or a particular market grows.

The available evidence indicates that, compared to the number of microloans advanced, microcredit has facilitated the creation and the growth of a tiny number of businesses. Going further, the extremely high failure rate of most informal microenterprises often leaves the average individual micro-entrepreneur worse off into the longer run, when household assets, land and housing have to be sold off (often under duress) to repay an outstanding microloan. In addition, new poverty-push micro-entrepreneurs also take business away from already struggling microenterprises, which reduces the turnover in existing businesses, and so also net income. Taking both downside effects into account, this generally means that there is no NET positive impact arising from the application of microcredit. This is especially the case in the poorest locations where (by definition) there has always been very little demand from local people for the simple goods and services provided by the typical informal microenterprise that microcredit helps create.

Rashmi Dyal-Chand (2005) asserted that, at first glance, the goal of micro lending is exciting and innovative: By making small loans to help impoverished people start small businesses, micro lenders appear to turn those who are marginalized by mainstream banks into successful entrepreneurs. United States department of agriculture (USDA) with a goal of reducing the prevalence of very low food security among low-income households suggested changes in nutritional assistance policies and programs (Nord, 2007). The study suggested that information about the composition, location, employment, education, and other characteristics of households with very low food security may provide important insights to guide these policy changes and improve the food security of economically vulnerable households. Hence achieving the food security objective may depend not only on improving the effectiveness and accessibility of nutrition assistance programs, but also on improving other key household circumstances.

Recently, practitioners have begun to increasingly acknowledge the importance of savings mechanisms. Research has even found that most people prefer savings to credit (Hirschland 2005). Furthermore, small loans are not always appropriate for poor women. A loan becomes a debt, and the poor often face a crisis if an expected source for repayment evaporates. Therefore, borrowing is often much riskier than saving. Because starting a new business is risky and sustainable providers of credit cannot afford to lose money, credit is generally not used to start a new business but rather to expand an existing one. Therefore, most people must rely on savings to start up new business ventures. Savings enables future investment, by giving access to lump sums of money. These large sums of money can be used for investment opportunities, for life cycle events, such as marriages, funerals or for emergencies. Savings can also be used to smooth consumption (Hirschland 2005).

Furthermore, while borrowers pay interest, savers can earn interest. Finally, although not everyone is creditworthy or is willing to take such risk, all people are deposit worthy and want to develop assets. Savings clearly offers substantial benefits and correspondingly, in general, savings programs have been shown to have a positive impact on participants. Dupas and Robinson (2009), who used a unique study design that controlled for potential biases while allowing for the use of simple regression analysis, find that access to a formal savings account has substantial positive impacts on women’s productive investment levels and expenditures, and also makes women less vulnerable to shocks from illness.

Access to credit can lead to an increase in labour supply to finance an investment or the purchase of durable goods which were out of reach before due to savings and borrowing constraints. This is an area where different evaluations of microcredit have very different results, ranging from a worrying increase in labour supply for teenagers in Augsburg et al. (2013). This insight is useful for understanding recent research on microfinance. Growing empirical evidence suggests that savings products can be valuable for generating income and for reducing poverty (Dupas and Robinson, 2013)

It is on this premise that Eneji et al. (2013), observed that rural dwellers need agricultural credit to a large extent to enable them invest in different types of economic ventures. Rural development involves taking into consideration the health (water supply, sanitation and hygiene), education food, poverty and rural economics and other social activities like security, transport and communication services. Majorly, rural development as conceived by the rural dweller involves all avenues engaged by the rural communities to improve their economic earnings and their livelihoods. This will increase their earning capacity and consequently their standard of living. In most rural communities, the major economic mainstay of the rural dwellers is agriculture.

Dupas and Robinson (2010) conducted a randomized field experiment in western Kenya in which they offered a random sample of poor daily income earners (primarily micro--‐entrepreneurs who sold goods in the market or operated bicycle taxis) the chance to open an interest--‐free savings accounts in a local village bank without depositing the required minimum balance of approximately $10. By significantly lowering the barrier to acquire a savings account for some in the sample and not for others, the authors were able to test the impact of having savings accounts on those in the treatment group. The accounts paid no interest and charged withdrawal fees of close to $0.40 and so offered a de facto negative interest rate, but the accounts were the only formal savings option available in the area.

Accordingly to Dupas and Robinson (2010), there was a wide variation in uptake and the intensity of account usage. Though fully 92% took up the offer, 39% made no deposit in 6 months. That said, 43% of those with accounts used them more than twice and some used them intensively. This rate of take up and active use seems high, especially given the high withdrawal fees. This high level of take up and use is in itself evidence that many individuals believed the accounts were useful and was higher than take up in recent experiments where credit products were offered to poor clients. Those offered the accounts accumulated savings of $37 on average, including those with zero balances, and those who made one deposit or more accumulated$71 on average.

For women as well, there was no evidence that the bank based savings crowded out informal saving through savings clubs or via investments in livestock which means the bank based savings were a net increase. This was not true for the men, who tended to save less through clubs and livestock and thus did not measurably increase total savings (this indicates the men were probably not as constrained with their existing options as the women.) The authors analyze the data using statistical regression techniques and find that, though women and men differ widely in their usage behaviour, gender is not as good a predictor of high levels of deposits as was being involved in savings group (mostly women join the groups) or having more livestock.

The study by Dupas and Robinson (2010), had the limitation of sample size comprising of only 279 households, all of whom were micro--‐entrepreneurs in the same town using the same bank branch in Western Kenya. It could be argued that the results occurring here may not occur in other settings or when savings accounts are given to other livelihood segments. On the other hand, the authors collect data from the women on a weekly basis, increasing the level of detail and likely the accuracy of the data. Microcredit may be a powerful tool to fulfil the demand of fund. Microfinance has proved its value in many countries as a weapon against poverty and hunger (CIDA, 2012).

But major problem for the developing countries is that most of the women are illiterate, they don’t know how to finance, how to produce a product, where to sell the product etc. Since they don’t know how to utilize their money properly so they are always afraid of borrow money. This is why they have no significant contribution to developing and under developed countries on GDP. At first they need to build up their capacity. Capacity building refers to the activities that improve one’s ability to realize his/her goals or to do his/her job more effectively (Linnell, D., 2003).

According to these writers, small-scale farmers are poor because they cultivate small hectares of land, produce low output and as such their income is low which in turn constrains farm expansion and the acquisition of new technologies (Oruonye and Musa, 2012). Some observers have raised questions as to who actually uses the loans issued to the women borrowers. It has been asserted “that Microcredit programs have worked further to incapacitate and subordinate women” (Obayedullah, 2000). There are two extreme viewpoints. Women are highly disadvantaged in our male dominated society. They have long been living in extreme poverty, massive health problems, ignorance and illiteracy. Bringing about basic changes in their situation will depend on multi-sectoral interventions.

The common agents for human capacity building are training, coaching, consulting, academic education, referrals. Developing awareness level might be helpful increasing the leading and motivating capability. Awareness level may be increased from short training on micro or small entrepreneurship, weekly or monthly interaction with group members or branch managers. Training may also be increased the institutional operating cost. Although from the study it is found that there is no significant difference of monthly income between trained group and non-trained group, but there is significant impact of training on creating employment opportunity. The borrowers who had pre credit training more than 66% of them are hiring people from outside of their family.

Linnell (2003) notes that capacity building can be in context of any process within an organization, such as improvement of governance, leadership, mission and strategy, administration (including human resources, financial management, and legal matters), program development and implementation, fundraising and income generation, diversity, partnerships and collaboration, evaluation, advocacy and policy change, marketing, positioning and planning. Hence, capacity building can be concluded as enhancing capacity attributes of an individual or community (such as knowledge, physical or social infrastructure and competencies), to sustainably change to reach higher level of performance, effectiveness, and service level.

Since loan size is very small, weekly monitoring is mandatory so more employee is required for the microfinance institutions. Due to this reason interest rate is higher than other conventional banking interest. Besides these, training for borrower before credit might be further increased significantly the operating cost of NGOs’. To reduce institutional operating cost, NGOs might accept micro-entrepreneurship or small entrepreneurship concept. Training would be provided only to the selective potential borrowers and loan size should be increased significantly according to one’s potentiality. Potentiality might be assessed by ones pre-education, pre-economic activities, pre-experience, utilization of past loan etc. For example, if training is provided to dress maker on how to sell, where to sell, how to expand business etc. then the potential borrower can make more employment opportunity for the poor and the poorest of the poor people. increasing employment opportunity, income and GDP. Financial institutions should increase the size of loan according to the borrower’s potentials so that one can employ ones full potentials and can make employment opportunity for the poor people. Difficulties in accessing credit in rural areas of developing economies adversely affect farm output (Petrick, 2004) farm investment (Carter & Olinto, 2003) and farm profits ( Foltz 2004).

Osei-Mensah and Adams (2009) found that micro credit had significant and positive impact on both labour force and output of farmers. Dong, Lu and Featherstone (2010) indicated that rural credit is a necessity for improving farm profits and improving the living standards of rural communities in developing countries. The writers found that by removing credit constraints, the income of farmers would improve considerably. Ibrahim and Bauer (2013) mentioned that the most significant interventions provided by microfinance institutions in the support of agriculture are the supply of improved seedlings, fertilizer and cash loans. Dong, Lu and Featherstone (2010) indicated that rural credit is a necessity for improving farm profits and improving the living standards of rural communities in developing countries. The writers found that by removing credit constraints, the income of farmers would improve considerably. Ibrahim and Bauer (2013) mentioned that the most significant interventions provided by microfinance institutions in the support of agriculture are the supply of improved seedlings, fertilizer and cash loans.

Microcredit plays an important role in agricultural development. One element of an effective strategy for poverty reduction is to promote the productive use of farm inputs. This can be done by creating opportunities for raising agricultural productivity among small and marginalized farmers. Microcredit is particularly relevant to increasing productivity of rural economy, especially agricultural productivity in such an environment where economic growth is occurring. Microcredit may enable small and marginalized farmers to purchase the inputs they need to increase their productivity, as well as financing a range of activities adding value to agricultural output (Nosiru & Omobolanle 2010)

Adil & Badar (2003) conducted a research to examine the impact of microcredit on agricultural production, poverty status, income, consumption and savings of the farmers in Dera Ghazi Khan Region. The results indicated positive changes in agricultural production, poverty status, income, consumption, saving and farm expenditure after the utilization of credit. Data showed that there was a positive relationship between credit size and income, home consumption, saving and farm expenditure. A recent study indicated that the yield (per hectare) of users of micro credit is 1.21 times higher than the non-users and both the users and non-users displayed inefficiency in major resources uses (Miah et al. 2006).

The impact of microcredit on health of borrowers is a subject of much controversy. Proponents state that it reduces poverty through higher employment and higher incomes. This is expected to lead to improved nutrition and improved education of the borrowers' children. Some argue that microcredit empowers women. In the US and Canada, it is argued that microcredit helps recipients to graduate from welfare programs and improve their health status. Microcredit has evolved over the years and does not only provide credit to the poor, but also provide other services including savings, insurance, remittances and non-financial services such as financial literacy training and skills development programmes. These services have direct bearing on education among the resource poor families world over (Armendáriz de Aghion and Morduch 2005, 2010).

Shimamura and Lastarria-Cornhiel (2010) evaluated the impact of agricultural credit programme participation on children's school attendance in rural Malawi. Their paired-site sampling survey reveals that credit uptake decreased school attendance by young girl children. This finding raises concerns that young girl children are exploited as child labour, either at home or in the field, when working adults become more involved in income generating activities financed by credit. The data, however, do not show clear evidence for young girls staying at home to do household chores or working in the fields in households that obtained credit, but instead find simultaneous occurrence between attending school and taking responsibilities for domestic chores by young children. It would appear, therefore, that credit uptake delays the realization of this concurrence among young girl children and leads to delayed school enrolment.

Same way, Holland and Wang (2001) explored the promises and perils associated with the impact of microfinance on children's educational outcomes. The goal of this discussion was to ensure that the pervasive spread of microfinance to all parts of the globe is accompanied by benefits to children's educational outcomes. Another study was done for exploring the impact of microcredit on household’s children education by Maldonado and González-Vega (2008). Within a random-utility framework, a model of household consumption, investment in education and borrowing suggests determinants at the individual, household and regional levels of the probability of schooling gaps. Using data from two surveys of households of clients of microfinance organizations in Bolivia, regression models examine determinants of schooling gaps. Inferences about otherwise positive microfinance impacts identify potential negative effects of increased child-labour demand, which challenge usual assumptions and pose dilemmas for policymakers (Maldonado and González-Vega, 2008).

Hazarika and Sarangi (2008) examined the effect of household access to microcredit upon work by 7-11-year old children in rural Malawi. Given that microcredit organizations foster household enterprises where in much child labour is engaged for discovering whether access to microcredit might increase work by children. It is found that, in the season of peak labour demand, household access to microcredit, measured as self-assessed credit limits at microcredit organizations, raises the probability of child work in households with average landholdings and retail sales enterprises (Hazarika and Sarangi, 2008). Data from Malawi shows that micro-credit significantly decreases primary school attendance among borrowers’ children, leading to a repetition of primary grades in young boys and delayed or lack of enrolment for young girls (Shimamura &Lastarria-Cornhiel, 2009).

The strongest studies find somewhat mixed evidence for a direct impact on education of micro-credit users. In the Karlan et al. (2012) randomized evaluation in Ghana, Malawi and Uganda, there was no significant increase in education expenditure in any of the countries. However, there was an increase in respondents reporting having used money from income generation activities for education expenditure in Uganda, and in using loans from savings groups for education in both Ghana and Uganda. In Ghana, there was a significant increase in primary school enrolment for both boys and girls, and in secondary school enrolment for boys, attributable to the presence of savings groups. However, this result lost its statistical significance when a different way of estimating change between the baseline and endline was used. In Burundi, Bundervoet et al. (2011) found that there were large increases in education spending across the board, but significantly larger increases for those who were members of the VSLA group. In the Mali study by BARA and IPA (2013), there was no significant impact on school enrolment or expenditure.

Abebe and Selassie (2009) report that mothers more often sent their children to school after joining the WORTH programme in Ethiopia than before. They attributed this most commonly to increased awareness about education resulting from the programme; only 4% said it was partly or wholly due to their income increasing. Thus it seems to be other aspects of that programme, rather than the savings group, that have the best claim to being causal factors in increased school enrolments. The evaluation of WORTH in Uganda (Swarts et al., 2010) finds that WORTH members provided more support to their children than non-WORTH members, for instance helping them with homework and paying fees for extra tuition at school. Again, however, other programme components such as literacy training may have been more important

Some studies asked participants directly whether they thought education had improved or worsened over time and what reasons they thought were responsible. CARE (2012), in Rwanda, finds that 15% of participants felt that access to education for children in their household had significantly improved, and 33% felt it had slightly improved, and most of these attributed the change to savings group membership. There was no significant increase in educational expenditure, but the net enrolment rate in primary education increased from 71 to 76% among households that were members of the group at baseline, and in secondary education from 6.3 to 7.6%. (The study does not present any comparison between members and non-members). The study by Anyango et al. (2006, 2007) in Tanzania finds that only 6% of members thought that education (“for self or children”) had improved since they had joined the programme. By comparison, 21% said their housing had improved, and 20% that their income or business had improved.

Allen (2009a) finds a drop in the reported number of male children per household who were unable to attend school due to lack of money among savings group members in Tanzania, but an increase in the proportion of female children who were unable to attend. However this finding is particularly difficult to interpret because of the very small numbers involved (fewer than 10 children), reliance on recall data, not accounting for possible changes in the number of school-age children per household, and lack of statistical tests. The study also reports that 45% of savings group members, and 30% of control group respondents, claimed that there had been improvements in school attendance or performance, or in attitudes towards education, since the savings groups had started (2005-2008).

A theoretical framework is a collection of interrelated ideas based on theories. It is reasoned set of prepositions, which are derived from and supported by data or evidence. It accounts for or explains phenomena. It attempts to clarify why things are the way they are on theories (Kombo and Tromp, 2006).

This thesis borrowed from the Restriction of Opportunities Theory of Poverty (ROTP) pioneered by Arjun Appadurai in 2004 and developed upon by Dipkanar Chakravarti in 2006. ROTP posit that poverty is cause by unstable environmental conditions and lack of social and economic capital. The theory emphasized the influence of human environment on people’s daily lives; and since people’s lives are condition by their environment, the individual’s daily decisions/actions are dependent upon what is present or what is not in the environment. As the poor continue to navigate within the environment of poverty, he/she develops fluency within the environment, but a near illiterate in the larger society or environment (Chakravarti, 2006).

Lack of capacities could cause an individual to enter the environment of poverty. This implies that, an individual who is poor lack adequate capacities with which to change his/her position. The capacity to inspire is paramount in this regard; the individual through social interactions develops aspirations that would change his/her socio-economic environment. It suggests that, a person’s aspiration is conditioned by his/her environment. It therefore holds that, the better one is placed in his/her environment, the more chances he/she has to not only aspire but to fulfil his/her aspiration (Appadurai, 2004).

ROTP posit that the capacity to aspire required practice in a stable environment; and since the environment of poverty is unstable. The unstable life of poverty as defined by unstable environment, often limits the poor’s aspiration to basic necessities of life such as food, cloth and shelter; and this reinforces lowered aspiration levels and could significantly obstruct change of environment or condition. It implies that the way out of poverty is to expand the aspiration horizon of the poor, to escape the reinforcement that perpetuate the poor in the environment of poverty. It entails creating programmes or making policies that provide the poor with an arena that enables he/she to practice and boost his/her aspiration. It includes designing schemes that enables the poor to meet his/her basic needs; and motivate him/her to higher aspirations (Appadurai, 2004; Chakravarti, 2006). ROTP is relevant to this study in that, microfinance credit scheme is belief to be meeting human basic necessities of life and is creating positive environment for high aspirations among beneficiaries across the world. The theory thus supports the very foundations upon which this study is involved—investigating the social value of microcredit facilities amongst poor families by examining the real effects of microfinance facilities on the welfare of households in Suna East Sub-County.

Despite the apparent success and popularity of microfinance, no clear evidence yet exists that microfinance programmes have positive impacts (Armendáriz and Morduch 2005; 2010). Coperstake et al., (2001) on assessing the impact of micro credit in Zambia had three objectives. The first was to identify the individual characteristics of the loan recipients such as gender, relative poverty and age of business; and to estimate the program’s depth of outreach. The second was to identify and estimate the direct impact of loans on borrowers, their businesses and their households. The third objective was to identify indirect effects of the programme. The study drew upon three sources of data: a questionnaire-based sample survey of program participants, secondary survey data drawn from the wider population of businesses and households and a set of qualitative focus group discussions and key informant interviews. The randomly selected sample for the study was from three groups.

The findings of the study by Coperstake et al., (2001) were that those who graduated from their first to a second loan on average experienced significantly higher growth in their profits and household income, as compared with otherwise similar business operators. These borrowers also diversified their business activities more rapidly. However, some borrowers became worse off, particularly among the 50 per cent or so who left the program after receiving only one loan. Qualitative enquiry suggests the trend to be due to rigid group enforcement of fixed loan repayment schedules without regard to income fluctuations arising from ill health, theft, job loss, and fluctuating demand.

Analysis by Diagne and Zeller (2001) on the determinants of household access to and participation in informal and formal credit markets in Malawi and much of the analysis was devoted to measuring the effect of access to formal credit on the welfare of rural households. On considering the patterns of access to formal and informal credit, it was established that poor households whose assets consists mostly of land and livestock but who wish to diversify into nonfarm income-generating activities may be constrained by a lack of capital, as both sectors of the market do not grant them access to credit (ibid). It thus follow that the benefits of access to credit for smallholder farmers depend on a range of agro ecological and socioeconomic factors, some of which are time-variant and subject to shocks such as drought. The full potential of credit access in increasing the welfare of the poor can only be realized if coupled with adequate investments in hard and soft infrastructure as well as investment in human capital.

Ahmad et. al (2004) in their study on the role of micro finance in alleviating rural poverty, they describes that the concept of micro financing is now in place to play a vital role in alleviating poverty both in urban as well as in rural areas of the country. It was found that the microcredit scheme was efficiently serving the poor, helping them to get rid of poverty and improve their living standard.

There have been major reviews examining impacts of microfinance. These reviews concluded that, while other inspiring stories purported to show that microfinance can make a real difference in the lives of those served, rigorous quantitative evidence on the nature, magnitude and balance of microfinance impact is still scarce and inconclusive (Armendáriz and Morduch 2005;2010). Overall, it is widely acknowledged that no well-known study clearly shows any strong impacts of microfinance (Armendáriz and Morduch 2005, p199-230). Because of the growth of the microfinance industry and the attention the sector has received from policy makers, donors and private investors in recent years, existing microfinance impact evaluations need to be re-investigated; the claims that microfinance successfully alleviates poverty and empowers women must be scrutinised more carefully.

Weiss et. al (2003) reviewed the evidence of the microfinance impact on poverty in Asia and subsequently Weiss and Montgomery (2005) provided an update including studies using Latin American data. They reviewed only more “rigorous studies” and did not cover studies using qualitative or participatory approaches. Weiss and Montgomery (2005) summarized their review by saying that the conclusion from the early literature, that whilst microfinance clearly may have had positive impacts on poverty it is unlikely to be a simple answer for reaching the core poor, remains broadly valid. Reaching the core poor is difficult and some of the reasons that made them difficult to reach with conventional financial instruments mean that they may also be high risk and therefore unattractive microfinance clients.

Meyer (2002) reached a similar conclusion. Surveying available evidence for Asian countries, he concluded that while access to microcredit seems to have an overall positive effect on income and education, results differ substantially across countries and programs both in magnitude and statistical significance and robustness. Bebczuk and Haimovich (2007) used household survey data on poor households from a number of Latin American countries to undertake their analysis. They found that credit increased labour income in a statistically and economically significant manner. Access to credit increased the hourly labour income of poor individuals compared with a similar population without access to credit by 4.8 times (Bolivia at 10% level of significance), 12.5 times (Guatemala at 1% level of significance), and 4.5 times (Haiti at 5% level of significance). The impact was sensitive to the size of the loan. They found that, in Guatemala, a 10% increase over the average amount of credit translates into an increase in hourly labour income of 4.7 times to the average income of credit borrowers and 6.2 times for those without access to credit

According to Maldonado and González-Vega (2008) in their study exploring the impact of microcredit on household’s children education by a random-utility framework, a model of household consumption, investment in education and borrowing suggests determinants at the individual, household and regional levels of the probability of schooling gaps. Using data from two surveys of households of clients of microfinance organizations in Bolivia, regression models examine determinants of schooling gaps. Inferences about otherwise positive microfinance impacts identify potential negative effects of increased child-labour demand, which challenge usual assumptions and pose dilemmas for policymakers.

Jehanzeb (2008) conducted the study on the effects of agricultural credit on farm productivity and the income of the small farmer as a result of the credit provided by Zarai Tarraqiati Bank of Pakistan. Farming was the main occupation of both respondents. The result reveals that the credit advanced by ZTBL in the study area has made (a) positive effect on the area of wheat and maize which show some improvement on living standard. Abhijit et al. (2010) studied the Miracle of microfinance with Evidence from a randomized evaluation, find that the introduction of Microcredit in Hyderabad, India, supports households borrowing and investment and support the creation and expansion of small businesses. Dupas & Robinson (2009) in their study Savings Constraints and Microenterprise Development: Evidence from a field experiment in Kenya, when examined closely, report evidence of a number of positive impacts of microfinance on the lives of poor clients. Dupas and Robinson studied the effect of the introduction of savings accounts on business investments in Kenya and find that formal savings accounts increase business investment in Kenya.

Akram & Hussain (2011) conducted the study to assess the contribution of microfinance in raising the living standard of low income people of District Okrara- Pakistan. Borrowers of microfinance from major microfinance institutions operating in the district Khushhali Bank Limited (KBL), Tameer Micro Finance Bank (TMB) and The First Micro Finance Bank (FMB) were studied. Positive impact of microfinance on income level and customers’ satisfaction level about the services of microfinance institutions were observed. Dean et. al (2011) examined the Expanding Microenterprise Credit Access using randomized Supply Decision to Estimate the Impacts in Manila, Philippines and find that the expansion of microcredit to a new population in Manila leads to an increase in business profits for male borrowers only but has no overall effects on income or poverty. Therefore, it is of interest to engage more with evaluation techniques and to understand their limitations, so that more reliable evidence of impact can be provided in order to lead to better outcomes for the poor ( Duvendack et al (2011).

Ibrahim and Bauer (2013) mentioned that the most significant interventions provided by microfinance institutions in the support of agriculture are the supply of improved seedlings, fertilizer and cash loans. According to Abhijit et al. 2014 in their study on the Miracle of microfinance, Evidence from a randomized evaluation, Small business investment and profits of pre-existing businesses increased, but consumption did not significantly increase. Durable goods expenditure increased, while “temptation goods” expenditure declined. They found no significant changes in health, education, or women’s empowerment. Two years later, after control areas had gained access to microcredit but households in treatment area had borrowed for longer and in larger amounts, very few significant differences persist.

Collectively these findings suggest that over relatively short time periods, microfinance had positive impacts on business investments and outcomes but did not have impacts (positive or negative) on broader measures of poverty and social well-being. There have been attempts in the past to study Microcredit and Micro lending but much focus has been on the impact of micro-credit facilities in poverty alleviation, especially in Kenya. Mixed results regarding impact on income and expenditure have been found. Some studies show a significant, positive impact on beneficiaries while others show no significant impact. Not much has been done to find out the effects of these microcredit services on the welfare of the households in Suna East Sub-County using the four indicators; income security, education security, health security and food security to determine their effects on the well-being of the households, therefore this research addresses these gaps.

Conceptual Framework is a set of broad ideas and principles taken from relevant field of enquiry and used to structure subsequent presentations. Conceptual framework involves forming ideas about relationships between variables in the study and showing these relationships graphically or diagrammatically (Mugenda & Mugenda, 2003)

The conceptual framework explains the direct and indirect effects of microcredit on welfare of the household through direct credit facilities offered by the micro lending institutions. The credit facilities offered are aimed at uplifting the welfare of the households by engaging in income generating activities. The change in household welfare status will be manifested through changes in credit amount, savings, income levels, education, food and health security situation, asset accumulation, better shelter and health status (dependent variables). However, the actual change in the level of welfare will be determined by a number of extraneous variables beyond the control of the client and/or the lending institution. Such variables include poverty level, household size, number of household dependants, inflation rate, level of education, business risk and government controls. This interrelationships illustrated in Figure 2.1

Welfare of Household Income security Food Security Health Security Education Security Wages/salary amount Microcredit facilities Loan services Saving Services- Nonfinancial Services Capacity building packagesIndependent variables Dependent variables

Figure 2.1: Diagram of Conceptual Framework

METHODOLOGY

This chapter discusses the research design, target population, sample size and sampling procedure, data collection instruments, their piloting, validity and reliability, as well as administration of the instruments. Data analysis techniques and ethical considerations are also discussed.

Research design is the arrangement of conditions for collection and analysis of data in a manner that aims to combine relevance to the research purpose with economy in procedure, Kothari (2004). The researcher used Descriptive Survey research design in carrying out the study in Suna East Sub-County. Survey Research Design seeks to obtain information that describes existing phenomena by asking individuals about their perceptions, attitudes, behaviour or values, Mugenda & Mugenda (2003).

The target population of the study constituted the households within Suna East Sub-County which have accessed micro-credit facilities within major micro-finance institutions in Suna East Sub-County over the last 5 years. Suna East is a Sub-Couty of Migori County located in the Western part of Kenya. According to the 2013 Annual Report on the Microfinance Sector in Kenya, Suna East Sub-County had a total of 1465 households accessing micro-credit facilities. This population was distributed amongst the five major micro-finance institutions in Migori County, which included Agrinfo (211 households), Kenya Women Finance Trust (473 households), Smep (402 households), Kadet (176 households) and Opportunity (203 households). Table 3.1 shows the distribution of target population in Suna East Sub-County with regard to micro-finance institutions and their respective households accessing micro-credit facilities.

Table 3.1 Distribution of target population

Source: Annual Report on the Microfinance Sector in Kenya (2013)

Using Krejcie & Morgans', 1970 table for determining the sample size from a given population (see annex 1), the sample size for the study was 306 respondents drawn from each household. These households exhibited homogenous characteristics with reference to their social, economic, and political, activities as well as their environmental and geographical space. This homogeneity made it appropriate to use Krejcie & Morgan table to determine the sample size from a population of 1465 households.

Krejcie& Morgan table was calculated using the following formula:

s = X 2NP(1− P) ÷ d2 (N −1) + X 2P(1− P).

s = required sample size.

X2 = the table value of chi-square for 1 degree of freedom at the desired confidence level (3.841).

N = the population size.

P = the population proportion (assumed to be .50 since this would provide the maximum sample size).

d = the degree of accuracy expressed as a proportion (.05).

The researcher used simple random sampling technique to select the respondents to question. Moore & McCabe (2005) define simple random sampling technique as the selection of a sample of size n consisting of n individuals from the population, chosen in such a way that every set of n individuals had an equal chance of being selected. The researcher therefore randomly numbered the entire 1465 households and a sample size of 306 was obtained. The researcher then administered a questionnaire to every sampled household.

Primary data was collected through administration of a structured questionnaire to the selected respondents. In a structured questionnaire, the questions, their wordings and sequence were fixed and identical for all the respondents. This had the advantage of eliciting standard answers to questions, making it possible for comparisons to be made between sets of data and eliminating errors arising out if inconsistency. Secondary data was also collected to supplement the primary data; this data was collected from documented information on micro-credit institutions and household welfare. Sources of this information included government offices, books, journals, theses, periodicals, and other publications.

The paper utilized both qualitative and quantitative data. Quantitative data were collected by use of questionnaire. The first part of the questionnaire consisted of background information of the respondents and the second part consisted of the questionnaires on various services offered by these microcredit institutions. Data on households’ savings and expenditure were also collected by the use of closed ended questionnaire and a 5-point Likert scale where clients were to indicate their level of agreement. Using a well structured questionnaire the researcher personally administered the research instruments to the sampled population and same collected on the very day. Explanation was done to respondents who had difficulties in understanding the questionnaire.

Validity is the ability of research instruments to measure what they purport to measure (Mugenda & Mugenda 2003).The researcher ensured the instruments were sufficiently formatted and the content capable of measuring what they purport to measure with regard to set objectives of the study; the researcher also sought the advice from the supervisor, research experts, colleagues and microfinance experts to ensure the instruments were suitable and valid. Bowling (2009) views reliability in quantitative research as synonymous to dependability, consistency, reproducibility or replicability over time, over instruments and over groups of respondents. To ascertain the reliability of data instruments, the researcher used the split-half technique in which the questionnaires were administered to a group of 10 non-sampled respondents at the same period of time in order to estimate how well the questions checking the same concepts yielded the same results. The questionnaire schedules were then separated into evenly numbered and odd numbered questions and results noted, scored and correlated to ascertain reliability coefficient where suggested reliability level at 0.80 and above was accepted.

The researcher personally administered the structured questionnaire schedules to the respondents and recorded down their responses with the guidance of the questionnaire schedules for analysis and interpretation of data.

The responses were classified into themes and sub themes for ease of analysis using both quantitative and qualitative techniques. The researcher sought to analyse, describe and interpret data based on research objectives and hypotheses, and present the data in form of frequencies, tables, percentages and explanatory notes. Change in the household's welfare was measured on a five- point range likert scale basing on the various indicators. The Statistical Package for Social Sciences (SPSS) was used to conduct the data analysis. Descriptive statistics (frequencies, means and standard deviations) were used to explore existing services offered by microcredit facilities. Multiple regression analysis was used to test the formulated hypotheses and deduce the effect of microcredit facility services on household welfare.

While undertaking the study, the researcher considered such ethical issues as keeping the confidentiality of all the information from the respondents, protection of the respondents’ identities, and their rights to exercise their freedom of thought. The researcher also maintained high moral decorum and intellectual integrity and ensured that any attempts that could jeopardize the security and confidentiality of data were eliminated during and after the study. And to avoid individual exposure, the study reported the data as a pool instead of individual data sets.

The analyses used data compiled from household surveys of residents living in Suna East Sub-County. First the response rate was assessed for the respondents issued with the questionnaires. This was then followed by an analysis of the respondent’s demographic profile. Descriptive statistics were used to analyze the structured sections of the questionnaire. All data were entered into SPSS version 18.0. Data screening was then conducted according to guidelines set out by Tabachnick and Fidell (2007). This included assessment of missing data, outliers, normality and testing basic assumptions of multiple regression analysis.

Data for compilation of this study were collected from respondents drawn from households in Suna East Sub-County. Out of a sample size of 306, a total of 283 respondents representing 92.5% returned their questionnaires completely filled. Twenty three questionnaires were partially filled and were therefore discarded.

Table 4.1: A Summary of the Response Rate

Source: Survey Data (2014)

In order to analyze and interpret the data adequately, the 283 completed questionnaires were edited, coded and processed. Results of the analyses are presented in the following sections.

The quality of data was first examined before embarking on descriptive and inferential analysis. Data was examined for missing values, outliers, normality and testing basic assumptions of multiple regression analysis.

Univariate outliers are cases with unusual values for single variables (Tabachnick and Fidell, 2007). Using standardized scores, no univariate outliers were identified for any of the microcredit facility variables (all standardized scores were within the interval -3.0 to 3.0 recommended by Steven’s (2002). Similarly, no outliers were detected for the household welfare variable. Consequently, all the 283 cases were retained for further analyses in the current study.

Normality was assessed using measures of skewness and kurtosis (Tabachnick and Fidell, 2007). The distribution was considered normal if skewness and kurtosis values fell within the interval -2.0 to 2.0. As shown in Table 4.2, the skewness and kurtosis values for all variables were within the acceptable interval. Normality assumptions were therefore met.

Source: Survey Data (2014)

Pearson’s product moment correlation coefficients were used to examine the assumption of linearity. Results displayed in Table 4.3 indicate that there were positive associations among predictor variables. The linearity assumption was not violated.

Using Levenne statistic for equality of variances, homogeneity of variances was assessed. The study revealed that the assumption of homogeneity of variances was not violated Table 4.4. None of the Levenne statistic was significant (Tabachnick and Fidell, 2007).

Source: Survey Data (2014)

Analysis of respondent’s demographic profile centred on establishing respondent’s gender, age, level of education and occupation. Table 4.5 presents a summary of respondents’ demographic profile.

Source: Survey Data (2014)

Microcredit facilities are designed not only to support entrepreneurship and alleviate poverty, but also in many cases to empower and uplift the entire communities, particularly women by extension. In many communities women lack stable employment histories that traditional lenders tend to require and therefore lack the capacity to borrow conventional loans. It was therefore necessary to examine the gender distribution of the respondents in order to control for the possible influence of gender on the final results.

Results of the gender distribution shown in Table 4.5 reveal that a majority (78.8%) of the respondents were female. Considering that the study targeted households, it is possible that women were easily found either at the group meetings or at their business places as opposed to men. This explains the variation in gender among respondents.

Age as a demographic characteristic was analyzed across 3 age brackets. Respondents were asked to indicate whether their age was below 30yrs, between 30 and 40 years, or 41 years and above. Results presented in Table 4.5 indicate that most of the respondents (45.5%) were aged below 30 years; 31.8% were aged between 30 and 40 years; and 23.7% were aged above 41 years. These results imply that the study sample comprised across section of the residents of Suna East Sub-County and took care of the diverse interests of youth and elderly. Consequently, the findings would reflect the views of both the youth and elderly.

The inclusion of Education level as a demographic characteristic was informed by findings of a previous studies where he states that due to low literacy levels most microcredit traders are unable to differentiate the loan products offered by the microcredit institutions, additionally most of these services are offered in banking jargons, as a result most traders are discouraged from applying for the loans. There was therefore a need to control for the possible influence of education household welfare.

Three categories were used to assess the level of education among respondents. Respondents were asked to indicate their level of education from among; secondary and below, tertiary or degree. Results of the level of education analysis presented in Table 4.5 reveal that a majority (49.1%) of the respondents were of secondary school level or below. Only a small proportion (23.0%) was graduates. The large proportion of respondents who were of secondary school and below vindicates the need for micro credit facilities that can be used to facilitate economic activities among household.

Personal occupation is the key characteristic for an individual’s living standard, a good occupation gives space for ones savings and affordability of basic needs, in the current study, occupation was included to control respondents’ occupation in examining the effects of microcredit facilities on the welfare of households. Table 4.2 above reveals that 40.3% of the respondents were farmers, respondents with professional occupation represented 25.8% of sample respondent; business dependent respondents occupied 23.3% of the respondents while other occupations covered 10.6% of the sample respondents.

Descriptive statistics were used to explore the prevailing levels of key study variable within the study area. In particular, frequency distributions, means and standard deviations were used to describe loan services, saving services, non financial services, capacity building packages, and household welfare.

Objective one of this study sought to examine the effect of loan services on household welfare. It was therefore necessary first to establish the descriptive statistics among respondents that would warrant loan services. Four items were used to examine the prevailing perceptions on loan services among residents in the Sub-County. First, respondents were asked to indicate the highest amount they had ever borrowed from the microcredit institutions. Second, they were asked to indicate the source of daily meals in the household. Third, they were asked to state the average percentage of monthly earnings spent on healthcare and education. Fourth, respondents were asked to indicate the extent to which selected potential benefits of loan services motivates application of loans.

When asked the highest amount of cash ever borrowed from a microcredit institution, results presented in Table 4.6 reveal that a majority (53.4%) of the respondents indicated an amount of between Ksh5001 and Ksh10,000. This was closely followed by those who had borrowed between Ksh10,001 and Ksh. 20,000 (38.2%). Only 2.5% reported to have borrowed above Ksh20,000. These results confirm that a majority of residents in Suna East Sub-County are keen on borrowing small amounts of money that can suitably be accessed from microcredit facilities. The implication is that most of them are small scale traders looking for extra capital for their enterprises; or those out to offset certain payments.

On the question of the source of daily household meals, two key sources were identified. Farming was cited by 48.8% of respondents as the major source of daily meals in households. Another key source of household daily meals was purchases made from the market (45.2%). The finding that farming constitutes the key source of daily household meals confirms the need for microcredit facilities that can help inject capital into the farming through loan services.

When asked to indicate the average monthly spending on health and education, a majority (60.1%) revealed that they spend 41% to 60% of their monthly earning on health and education; while 35% indicated that they spend 21% to 40%. These results imply that most residents in Suna East Sub-County spend so much on health and education and often find microcredit facilities useful to their requirements.

Table 4.6 Prevailing perceptions on loan services

Source: Survey Data (2014)

The extent to which potential benefits of loan services motivates residents of Suna East Sub-County to apply for loans was analyzed using means and standard deviation. Potential benefits of loan services were measured using 8 items reflecting benefits of loan services. Responses were elicited on a 5-point scale ranging from 1-very low extent to 5-very high extent.

Results presented in Table 4.7 indicate that residents in Suna East Sub-County appear to be highly motivated to take loans owing to the potential benefits accruing from use of loan money. The mean response scores on all items were approximately 4.00 and standard deviation values less than or equal to 1. This shows consistency among responses which reflect high extent of motivation. In particular, respondents tended to be highly motivated by among others; the urge to make home improvement (M=4.22, SD=0.869); ease of access of top up loan (M=3.96, SD=1.071); relaxed initial conditions and procedures (M=3.95, SD=0.882); short time taken before approval (M=3.91, SD=1.015); extra capital for business (M=3.80, 0.667); and ability to repay (M=3.72, SD=0.60).

Table 4.7 Factors motivating respondents to take a loan

Source: Survey Data (2014)

These statistics imply that the potential benefits that loans provide play a key role in motivating residents of Migori County to take loans. Many of them yearn to improve their homes, top up their loans, settle medical bills and pay school fees among other needs. The availability of microcredit facilities enables them to achieve all these.

The second objective of the current study focused on determining the effect of saving services on household welfare. Saving services were measured using a total of 8 items. First, respondents were asked to indicate their agreement or disagreement with the items which were selected to reflect saving services. Responses were elicited on a 5 point scale (1- strongly disagree, 2- disagree 3- uncertain 4- agree 5- strongly agree).

Results displayed in Table 4.8 below show respondents’ views towards saving services offered at their respective microcredit institutions. The mean score to all items approximated 4.00, which was coded to imply agreement. In particular the results show that respondents tended to agree that microcredit savings have made basic needs affordable and accessible (M = 4.36, SD = 0.76); that savings reduce vulnerability to economic stress and external shocks (M = 3.89, SD = 0.78), that compulsory saving encourages saving habit (M=3.88, SD=0.71). The variable with the least mean response score was that savings act as an insurance for emergencies (M = 3.59 SD = 0.80).

Source: Survey Data (2014)

These results indicate that residents of Suna East Sub-County appreciate the importance of saving services and embrace the existence of microcredit facilities within the County.

Second, respondents were asked to indicate the average monthly savings made on income so as to take care of emergencies. Frequencies and percentages were used to analyze responses made to this item. Table 4.9 presents the summary statistics for this item.

Table 4.9 Respondents Average savings on Monthly Income for Emergencies

Source: Survey Data (2014)

Results displayed in Table 4.9 reveals that a higher proportion (47.0%) of the residents of Suna East Sub-County save on average between 21-40% of their monthly income for emergency purposes; 30.0% save on average below 20% of their monthly income for emergency; while 16.3% save on average 41-60% of their monthly income for emergency. These results show that residents can only afford to save a small proportion of their income for emergency. This argues the case for the need of more microcredit facilities to empower residents and encourage them to make savings that can be useful in emergencies.

Objective three of the current study sought to investigate the effect of non-financial services offered by the microcredit facilities on household welfare. As a result 6 items were used to measure non financial services offered. Respondents were asked to indicate their level of agreement as to whether or not non-financial services offered have had an effect on their livelihoods. Responses were elicited on a 5-point scale (1- strongly disagree, 2- disagree 3- Uncertain 4- Agree 5- Strongly agree). These responses were then analyzed using means and standard deviations, the mean response scores for all the items was approximately 4.00, which indicates that the majority of the respondents tended to agree that non-financial services have had an effect on their livelihoods. In addition, the standard deviations were very small showing in responses recorded.

As shown in Table 4.10, respondents tended to agree that skills training services offered by the microcredit institutions have are beneficial (M = 4.72, SD = 0.49); that provision of farm inputs by the microcredit institutions takes care of farming needs (M = 4.33 SD = 0.87); that non financial services changes community sanitary dimensions (M=4.29, SD=0.85); that health care plans offered by microcredit institutions guarantees health insurance (M=4.28, SD=0.85); that women empowerment is realized (M=4.26, SD=0.73); and that marketing services are easily accessed (M=4.16, SD=0.70).

Source: Survey Data (2014)

These results reveal that microcredit facilities within Migori County offer services such as training services, farm inputs, community sensitization, provision of health plans, women empowerment, and marketing services. These services offered through microcredit facilities usually facilitate residents in their affairs. From training, to farm inputs and sanitary awareness, non financial services have had an influence on the livelihood of residents in the County. This underscores the diverse contributions that microcredit facilities can make to a community.

The fourth objective of this study sought to examine the effectiveness of capacity building packages offered by microcredit facilities on household welfare. The study conceptualized that capacity building has a direct effect on household welfare. Accordingly, 6 items were employed to measure capacity building. Respondents were asked to indicate their level of agreement or disagreement with the items selected to reflect utility of capacity building packages offered by microcredit facilities.

Responses were elicited on a 5 point scale (1-strongly disagree, 2- disagree 3-undecided 4-agree, 5-strongly agree). The mean response scores for all items were approximately 4.00, indicating that respondents tended to agree that capacity building packages offered by the microcredit facilities within the County were beneficial to them. More particularly, respondents tended to agree that training services help in reaching out to poorer individuals (M=4.22, 0.70); that they occasionally get invited for informational sessions (M=4.14, SD=0.67); that Capacity building services facilitate kinship development (M=4.11, 0.84); that microcredit facilities have leadership training components built in them (M=3.94, SD=0.80); and that microcredit firms provide appropriate skills to utilize finances (M= 3.78, SD=0.76); they were however not sure whether improved farm productivity is attributed to microcredit facilities (M=3.39, SD=0.96). Table 4.11 below provides a summary of these results.

Table 4.11 Capacity Building

Source: Survey Data (2014)

These results vindicate the role of microcredit facilities in building the capacity of residents in Migori County. Through capacity building packages, poor individuals are reached and imparted with appropriate skills both for going about with their concerns as well as in utilizing finances.

Household welfare was conceptualized as the dependent variable in the current study. Eight indicators were used to measure household welfare. Respondents were asked to indicate the extent to which microcredit facilities have improved their household welfare in terms of the given indicators. Responses were elicited on a 5-point response scale (1=greatly weakened, 2=weakened, 3=undecided, 4=improved 5=greatly improved).

Results presented in Table 4.12 show that mean response scores for all the items was approximately 4.00. This implies that respondents were of the view that their welfare in terms of the analyzed indicators had improved. In particular respondents indicated that their welfare had improved in terms of among others; clothing (M=4.24, SD=0.44); food (M=4.01, SD=0.61); physical mobility (M=3.95, SD=0.71); ownership of Assets (M=3.93, SD=0.74); children care (M=3.88, SD=0.69); medical care (M=3.74, SD=0.84); provision of educational expenses (M=3.61, SD=0.84); and home improvement (M=3.54, SD=0.60).

Source: Survey Data (2014)

The results suggest that household welfare for most residents in Suna East Sub-County has improved. There seems to be a general improvement in most indicators of household welfare which include among others; clothing, food, physical mobility, ownership of assets; children care; medical care; and home improvements. The improvement in household welfare could be attributed to microcredit facilities which through several services are empowering residents in several income generating activities such as farming which is reported as the main income generating activity among residents.

The main purpose of this study was to examine the effect of microcredit facilities on household welfare of residents in Suna East Sub-County. Consequently, four hypotheses were formulated to guide the study. Multiple regression analysis was used to test these hypotheses. Multiple-regression was used since several microcredit services were affecting household welfare simultaneously. It was therefore necessary to examine the influence of each service while holding others constant.

First the regression model was run to examine the strength of the proposed model. Results of the model summary presented in Table 4.13 reveal that microcredit services account for up to 87.3% of the variance in household welfare (R square=0.873). Besides, the Durbin-Watson statistic (1.452) indicates that the model residuals are uncorrelated. The model was therefore found to be quite powerful in predicting household welfare.

Source: Survey Data (2014)

4.6.1 Testing the effect of Loan Services offered by Microcredit facilities on Household Welfare

Research Hypothesis Ho1 postulated a lack of effect of loan services offered by microcredit facilities on household welfare. Results of the multiple-regression coefficients presented in table 4.13 below show that loan services offered by microcredit facilities are significant predictors of household welfare (β=0.691, p<0.01). The large t value of 24.833 implies that loan services are the major microcredit facilities services in predicting household welfare, as a result of these the hypothesis was rejected.

The implication of these results is that loan services have a positive effect on household welfare. The standardized coefficient β=0.691 reveals that an increase of 1 standard deviation in loan services has the potential to increase household welfare by 0.691 standard deviations. Consequently, loans offered by microcredit facilities could be responsible for the observed improvement in household welfare among residents in Suna East Sub-County.

4.6.2 Testing the effect of saving services offered by Microcredit Facilities on Household Welfare among Residents of Suna East Sub-County

Research hypothesis Ho2 posited that saving services offered by microcredit facilities have no effect on household welfare. Results in Table 4.13 revealed that saving services positively and significant predict household welfare (β= 0.277, p<0.01) and thus the hypothesis was rejected. This implies that a 1 standard deviation increase in saving services was likely to result in an increase of 0.277 standard deviations in household welfare. The implication of these results is that utilization of saving services offered by microcredit facilities in Suna East Sub-County is having a positive impact on household welfare.

4.6.3 Testing the Effect of Non financial Services offered by Microcredit facilities on household welfare among residents of Suna East Sub-County

Research hypothesis Ho3 posited that non financial services offered by microcredit facilities in Suna East Sub-County do not have a significant effect on household welfare of residents in the Sub-County. Results of the standardized coefficients presented in Table 4.13 revealed that non financial services offered by microcredit facilities are positive and highly significant predictors of household welfare (β=0.147, p<0.01). The implication is that an increase of 1 standard deviation in non financial services was likely to result in a 0.147 standard deviations increase in household welfare and therefore the hypothesis was rejected.

4.6.4 Testing the Effect of Capacity Building Packages on Household Welfare among Residents of Suna East Sub-County

Research hypothesis Ho4 postulated a lack of significant effect of capacity building packages offered by microcredit facilities on household welfare of residents of Suna East Sub-County. Results of the standardized coefficient revealed that capacity building packages were significant predictors of household welfare (β=0.084, p<0.01). The hypothesis that capacity building packages have no effect on household welfare was therefore rejected. The implication of these results is that through capacity building packages, microcredit facilities are able to empower residents to better manage their affairs and hence improve their household welfare.

The study therefore established that household welfare is a function of microcredit facilities services that include loans, savings, non financials, and capacity building packages. The researcher therefore suggested the following multiple regression model for prediction of household welfare among households in Suna East Sub-County.

Household Welfare= 0.691 loan services +0.277 Savings + 0.147 non financial + 0.084 capacity building

4.8.1 Assessing the influence of Loan Services on Household Welfare

The study found out that microcredit facilities through loan services have positive and significant effects on household welfare. This is achieved through improvements on clothing, food, physical mobility, ownership of assets, children care, medical care, provision of education expenses and homes among others.

The finding that loan services are positive and significant predictors of household welfare supports a plethora of findings (Beck, Demirgns-Kunt, & Knight, 2008; Hietalaliti & Linden, 2006; Hassain & Knight, 2008; Khandker, 2001; Odell, 2010). According to these findings, microfinance which is equivalent to loan services has been credited with improving other financial outcomes such as furniture, food-security, nutrition, education, housing, and social cohesion. The finding further supports findings by Wright (2005), that access to financial services has allowed many families throughout the developing world to make significant progress in their own effort to escape poverty.

The relevance of microfinance in empowering communities is further highlighted in other studies. Coperstake et al (2001) in a study assessing the impact of micro credit in Zambia found out that repeated taking of loans has a positive influence on profits and household income. In support of this notion, Ahmad, Nareed and Ghafoor (2004) noted that microcredit scheme was efficiently serving the poor, helping them to get rid of poverty and improve their living standard. In addition, Johanzeb (2008) in a study of effects of agricultural credit on farm productivity and the income of the small farmer productivity reveals that credit advanced by microcredit institutions made positive effects on the welfare of the farmer’s productivity and living standards. The findings in the current study are further highlighted in several other studies. In another study, R. Bebczuk and F. Haimovich (2007) noted that credit services increases labour income for poor individuals and that the impact is usually related to the size of loan taken.

4.8.2 Effect of savings services offered by microcredit on household welfare

The study findings that saving services positively and significantly predict household welfare support the findings which highlight the importance of microcredit facilities in savings (Beck, Demirguc-Kunt, & Peria, 2008; Chaia et. al, 2009). According to these findings, more than half the world’s population are living without access to banking or other financial services and therefore the market for microcredit facilities are substantial.

The finding further supports the findings by Armendáriz de Aghion and Morduch (2005, 2010) that other services provided by microcredit facilities such as saving have a direct bearing on education among the poor families world over. In a study on saving constraints and microenterprise development, Pascaline Dupas & Jonathan Robinson (2009) found that savings have a positive impact on the lives of the poor clients. In particular, they found that formal saving accounts increase business investment.

Concurrently, some studies have questioned the impacts of microcredit saving services. For instance Husain, Mukherjee & Dutta (2010) argues that microcredit facilities help the poor to better manage the money they have by providing saving services but not directly or sufficiently increasing their income and empowerment. Dupas and Robinson (2010) conducted a randomized field experiment in western Kenya in which they offered a random sample of poor daily income earners (primarily micro--‐entrepreneurs who sold goods in the market or operated bicycle taxis) the chance to open an interest--‐free savings accounts in a local village bank without depositing the required minimum balance of approximately $10.

The study done by Dupas and Robinson (2010) revealed that there was no evidence that the bank based savings crowded out informal saving through savings clubs or via investments in livestock which means the bank based savings were a net increase. This was not true for the men, who tended to save less through clubs and livestock and thus did not measurably increase total savings .Dupas and Robinson (2010) analyzed the data using statistical regression techniques and found that, though women and men differ widely in their usage behaviour, gender is not as good a predictor of high levels of deposits as was being involved in savings group (mostly women join the groups) or having more livestock.

4.8.3 Effect of Non-financial services offered by microcredit facilities on Household welfare

An examination of the effect of non-financial services on household welfare among residents of Migori County revealed that services such as, provision of farm inputs, and community sensitization among others positively and significantly predicts household welfare among residents. Thus, on the availability of non-financial services many of the respondents felt that the accessibility of these services warrants the usefulness of the services in their lives.

These findings are consistent with findings by Diagne and Zeller (2001). According to these authors, poor households whose assets consist mostly of land and livestock can only benefit if they access credit to small holder farmers through hard and soft infrastructure. Difficulties in accessing credit in rural areas of developing economies adversely affect farm output , farm investment and profit (Carter & Olinto, 2003; Foltz 2004)

The findings are also in agreement with Osei-Mensah and Adams (2009) who found that micro credit had significant and positive impact on both labour force and output of farmers. Dong, Lu and Featherstone (2010) indicated that rural credit is a necessity for improving farm profits and improving the living standards of rural communities in developing countries. The writers found that by removing credit constraints, the income of farmers would improve considerably. Ibrahim and Bauer (2013) mentioned that the most significant interventions provided by microfinance institutions in the support of agriculture are the supply of improved seedlings, fertilizer and cash loans. Nosiru & Omobolanle (2010) found that microcredit plays an important role in agricultural development. One element of an effective strategy for poverty reduction is to promote the productive use of farm inputs.

This can be done by creating opportunities for raising agricultural productivity among small and marginalized farmers. Microcredit is particularly relevant to increasing productivity of rural economy, especially agricultural productivity in such an environment where economic growth is occurring. Microcredit may enable small and marginalized farmers to purchase the inputs they need to increase their productivity, as well as financing a range of activities adding value to agricultural output. Therefore this study concludes that non-financial services complements the rest of micro-finance services to realize the positive effects on user since these non-financial services sharpens personal skills that lead to positive behavioural change that influence successful realization of the general microfinance programs

4.8.4 Effect of Capacity building packages offered by microcredit facilities on household welfare

Analysis of the effect of capacity building packages offered by microcredit facilities on household welfare revealed that capacity building packages such as training services, seminars and interactive sessions positively and significantly predict household welfare.

These findings reflect findings by Linnell (2003) who found that capacity building can be in context of any process within an organization, such as improvement of governance, leadership, mission and strategy, administration (including human resources, financial management, and legal matters), program development and implementation, fundraising and income generation, diversity, partnerships and collaboration, evaluation, advocacy and policy change, marketing, positioning and planning. Hence, capacity building can be concluded as enhancing capacity attributes of an individual or community (such as knowledge, physical or social infrastructure and competencies), to sustainably change to reach higher level of performance, effectiveness, and service level.

Frankish (2003) identifies a number of dimensions for community capacity and includes; financial capacity (resources, opportunities and knowledge), human resources (skills, motivations, confidence and rational abilities), and social resources (networks, participation structures, shared trust and bonding). Microcredit may be a powerful tool to fulfil the demand of fund. Microfinance has proved its value in many countries as a weapon against poverty and hunger (CIDA, 2012).

But major problem for the developing countries is that most of the women are illiterate, they don’t know how to finance, how to produce a product, where to sell the product. Since they don’t know how to utilize their money properly so they are always afraid of borrow money. This is why they have no significant contribution to developing and under developed countries on GDP. At first they need to build up their capacity. Capacity building refers to the activities that improve one’s ability to realize his/her goals or to do his/her job more effectively (Linnell, D., 2003)

The findings are in agreement by the study done by Backer (2000) who found that one of the core components for effective capacity building is the competence base of the change agent. The study found that the most effective capacity-building services are those that are offered by well-trained providers (both foundation staff and expert service providers) and requested by knowledgeable, sophisticated ‘consumers’ – the managers and board members of non-profit organisations.

The purpose of this study was to examine the effect of microcredit facilities on household welfare of residents of Suna East Sub-County. This chapter presents the summary, discussions and implications of the findings of the study. The first section provides a summary and discussion of the study findings in line with the research objectives. The second section presents conclusions drawn from the findings and the final section provides implications and recommendations of the study.

Objective one sought to examine the effect of loan services offered by microcredit facilities on household welfare. First the study found out that a majority of residents of Migori County mainly borrow amounts ranging from Ksh. 5,000 to Ksh. 10,000 which microcredit facilities can easily loan out. Second, using regression analysis, the study established that loan services have a positive and significant effect on household welfare of residents of Suna East Sub-County. In this regard, households have seen improvements in clothing, food, physical mobility, ownership of assets, children care, medical care, provision of education expenses and home improvement among others.

The second objective sought to determine the effect of saving services offered by microcredit facilities on household welfare. The study found out that saving services positively and significantly predict household welfare. The study further established that residents of Suna East Sub-County can only afford to save a small proportion of their income.

The third objective sought to investigate the effect of non-financial services offered by microcredit facilities on household welfare. The study established that among non-financial services offered by microcredit facilities in Suna East Sub-County are: workshops, provision of farm inputs, community sensitization, provision of health plans, women empowerment and offering marketing services. The study further found out that these non-financial services are positive and significant predictors of household welfare among residents of Suna East Sub-County.

The fourth and final objective of the current study sought to examine the effectiveness of capacity building packages offered by microcredit facilities on household welfare. First, the study revealed that residents were receptive of capacity building packages offered to them and which the study identified to include; training services, seminars and interaction sessions. Second, the study established that capacity building packages offered by microcredit facilities in Suna East Sub-County were positive and significant predictors of household welfare.

The study therefore revealed that household welfare is a function of services offered by microcredit facilities and could be modelled as; Household welfare = f (loan services, saving services, non-financial services and capacity building packages). The study revealed that this model could predict up to 87.3% of the variance in household welfare.

In view of the findings discussed above, the following conclusions were made; The microcredit facilities are used by members of Suna East Sub-County to access loans so that they can improve their welfare in terms of food, clothing, medical care and educational expenses but the amounts borrowed however are quite minimal to make lasting impacts. Secondly the microcredit facilities play a critical role in the household welfare through their savings services. The amount saved however remains a very small proportion of resident’s income. Thirdly the facilities are utilized for their potential to offer non-financial services that impact positively on household welfare. These include provision of farm inputs, community sensitization and, women empowerment and lastly the facilities impact positively on the welfare of households in Suna East Sub-County through capacity building packages. Through seminars, trainings and interactive sessions, households are empowered to be self reliant

In view of the conclusions drawn above that microcredit services improves the loans improves household welfare, emphasis on the importance of loan services on household welfare should be made and the amounts borrowed be increased so as to meet the needs of the residents. In order to encourage saving habits among the borrowers, residents should be encouraged to save with the microcredit facilities so as to raise their chances of gaining support from the facilities which will also enables them to quality for large amounts of loans. Another way to help borrowers who may not be able to handle financial services well is to enhance provision of non-financial services. Further rigorous training in the form capacity Building among households should be maintained so that residents can maximize potentials within the microcredit facilities.

The current study did not put into consideration the effect of respondents background characteristics on household welfare. It is recommended that future studies look into the mediating/ or moderating effect of background characteristics on the relationship between microcredit services and household welfare. Lastly in order to enhance external validity, future studies should consider replicating the study in contexts with diverse/ different environmental settings.

Abhijit, Duflo, Glennerster & Kinnan (2014) “The Miracle of microfinance, Evidence from a randomized evaluation.

Abhijit, Esther Duflo, Rachel Glennerster, and Cynthia Kinnan. (2010). “The Miracle of Microfinance? Evidence from a Randomized Evaluation,” the Abdul Latif Jameel Poverty Action Lab at MIT and the Center for Microfinance at IFMR (mimeo).

Hello:

I am a Master of Business and Management student at Rongo University College, conducting research on Effects of microcredit facilities on the welfare of households in Migori Sub-Count, Migori County as a partial fulfilment of the requirements for the award of Masters Degree in Business Management. You are kindly requested to respond to this questionnaire in the best way possible. Information from this research will help develop a comprehensive understanding of the subject matter, advice stakeholders and form basis for further research.

Your response will remain confidential and will only be used for analysis and evaluation.

Thank you.

Background Information

Gender: (a) Male (b) Female

Age: (a) Below 30 yrs (b) 31-45 yrs (c) Above 45 Years

Level of Education: (a) Secondary and Below (b) Tertiary Institute (c) Graduate

Occupation: (a) Farmer (b) Business (c) Professional (d) Other (specify)

Kindly tick any microcredit institutions that you have known been for the last 5 years.

Agrinfo. (c) KWFT (e) SMEP

Kadet (d) Opportunity

Questions on Microcredit Services

Reasons for getting the credit facility.

Business (c) Health (e) Household items

Education (d) Marriage (f) Other Specify

Which microcredit facilities did you get from the institution?

Monetary Loans (c) Training and extension (e) Other (specify)

Farm inputs (d) Marketing Services

What is your major economic activity/source of income

Farming (c) Salaried

Business (d) Other (Specify)

What is the level of the monthly income of your family/household?

Below 5,000 (c) 10,001-20,000

5001- 10,000 (d) Above 20,000

Kindly rate on a scale of 1 to 5, how these microcredit facilities have/would contribute to your household’s income security?

What is the major source of food for your household?

Farming (c) Gifts

Business (d) Other (Specify)

What average percentage of your monthly earnings do you spend on food for your household?

Below 20% (c) 41-60%

21-40% (d) 61% and above

On a scale of 1-5, kindly rate how these microcredit facilities have helped your household improve its food security over the last 5 years?

What is the major strategy your household employs to ensure adequate health for its members?

Hospital treatment (c) Preventive measures

Over the Counter drugs (d) Other (Specify)

What average percentage of your monthly earnings do you spend in enhancing the health of your household

Below 20% (c) 41-60%

21-40% (d) 61% and above

Kindly rate, on a scale of 1-5, how these microcredit facilities have enhanced the health status of your household over the last 5 years?

How many members of your household pursue or have pursued their education over the last 5 years?

What average percentage of monthly earnings do you spend on your household education?

Have you ever received any microcredit facilities to help you cater for the educational expenses of your household over the last 5 years? (a) Yes (b) No

On a scale of 1- 5, indicate your level of agreement on savings services offered by the microlending institutions.

On a scale of 1-5, kindly rate how these microcredit facilities have improved your household’s ability to manage its educational expenses over the last five years?

On a scale of 1- very low to 5-very high, indicate what motivates you to take a loan

On a scale of 1- 5, indicate your level of agreement on savings services offered by the microlending institutions.

APPENDIX I

KREJCIE & MORGAN’S TABLE FOR DETERMINING SAMPLE SIZE FOR A GIVEN POPULATION

N S N S N S

10 10 220 140 1200 291

15 14 230 144 1300 297

20 19 240 148 1400 302

25 24 250 152 1500 306

30 28 260 155 1600 310

35 32 270 159 1700 313

40 36 280 162 1800 317

45 40 290 165 1900 320

50 44 300 169 2000 322

55 48 320 175 2200 327

60 52 340 181 2400 331

65 56 360 186 2600 335

70 59 380 191 2800 338

75 63 400 196 3000 341

80 66 420 201 3500 346

85 70 440 205 4000 351

90 73 460 210 4500 354

95 76 480 214 5000 357

100 80 500 217 6000 361

110 86 550 226 7000 364

120 92 600 234 8000 367

130 97 650 242 9000 368

140 103 700 248 10000 370

150 108 750 254 15000 375

160 113 800 260 20000 377

170 118 850 265 30000 379

180 123 900 269 40000 380

190 127 950 274 50000 381

200 132 1000 278 75000 382

210 136 1100 285 1000000 384

Note:-

‘N’ is people size.

‘S’ is sample size.

Source: Krejcie and Morgan, 1970