Masters Thesis

1
UNIVERSITY OF LIMERICK
Ollscoil Luimnigh
KEMMY BUSINESS SCHOOL
Department of Accounting and Finance
Microfinance as a driving force for socio-economic development in the
emerging economies: Measuring its effectiveness in North India
By
Kumar Deepam
Author ID : 14079623
Programme : MSc in Financial Services
Supervisor : Dr. Antoinette Flynn
Year of completion : 2015

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UNIVERSITY OF LIMERICK
Ollscoil Luimnigh
KEMMY BUSINESS SCHOOL
Department of Accounting and Finance
Programme of Study : MSc in Financial Services
Year of submission : 2015
Author’s Name : Kumar Deepam (14079623)
Title of the Research Paper -Microfinance as a driving force for socio-
economic development in the emerging economies: Measuring its
effectiveness in North India.
Word Count : 12913
Supervisor : Dr. Antoinette Flynn
This project is solely the work of the author and is submitted in partial
fulfilment of the requirements of the Degree of MSc in Financial Services.

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Abstract
The purpose of this research is to measure the effectiveness of microfinance in the sense of
socio-economic development in the Northern part of India. The aim has been accomplished
by using the methods of statistical analysis and through the examination of primary and
secondary data. The methods of data analysis that were employed in the research
incorporated chi-square tests, independent sample t-tests and binary logistic regressions. The
data has been analysed based on the survey of 100 respondents, who were below nationally
defined poverty line in Lucknow (Major metropolitan city of North India) and areas nearby.
The survey data was divided into two parts i.e. 60% of the respondents were the non-
microfinance respondents and remaining 40% were the microfinance recipients.
Recommendations regarding the research have been based on the findings from the analysis.
Findings of the study have shown that young entrepreneurs who are below poverty line are
more likely to apply for the micro loan. This has been explained by the binary logistic
regression analysis of the whole sample. Further, the findings show that microfinance has
very low outreach in North India. This has been explained by the data from the MIX market,
level of awareness of microfinance among the non-microfinance respondents and the case
study of Nat Purva Village near Lucknow. Furthermore, the results disclosed that
microfinance recipients face difficulty while applying to micro loan due to which they also
face difficulty in paying the loan amount with interest back. This has been explained by the
chi-square test and binary logistic regression analysis of the responses from the microfinance
recipients. However, overall impact of microfinance on both poverty reduction and gender
equality is turned out to be positive. This has been explained by MFI’s major focus on
women entrepreneurs, changes in social and economic conditions of the recipients after
taking the micro loan, expenditure of the recipients on education of children, recipient’s
recommendations regarding micro loan and the ability of recipients to apply for the micro
loan again.
Key words: Microfinance, Joint liability group, Poverty reduction, Gender equality, North
India

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Acknowledgement
I would like to express my gratitude to my supervisor Dr. Antoinette Flynn for the useful
comments, remarks and engagement through the learning process of this master thesis. Also,
I would like to thank the participants in my survey, who have willingly shared their precious
time during the process. I would like to thank my loved ones, who have supported me
throughout entire process, both by keeping me harmonious and helping me putting pieces
together. I will be grateful forever for your love.

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Table of Contents
Chapter 1: Introduction...........................................................................................................................9
1.1 Definition of microfinance ............................................................................................................9
1.2 Why India....................................................................................................................................11
1.3 Why North India..........................................................................................................................11
1.4 Microfinance delivery models in North India.............................................................................12
1.5 Aims and Objectives of the research...........................................................................................13
1.6 Summary .....................................................................................................................................13
Chapter 2: Literature Review................................................................................................................14
2.1 Introduction.................................................................................................................................14
2.2 Micro Finance Loans and their uses...........................................................................................14
2.3 International Evidence................................................................................................................15
2.4 Indian Evidence ..........................................................................................................................17
2.5 Scope of Research and Possible Contribution............................................................................19
2.6 Some Possible Research Hypothesis...........................................................................................20
Chapter 3: Methodology .......................................................................................................................21
3.1 Research Philosophy and Approach...........................................................................................21
3.2 Research Strategy .......................................................................................................................21
3.3 Data ............................................................................................................................................22
3.4 Methods of data analysis ............................................................................................................23
3.5 Limitations ..................................................................................................................................24
Chapter 4: Findings and Analysis.........................................................................................................25
4.1 Analysis of the whole sample. ....................................................................................................26
4.2 Analysis of the sample of non-microfinance respondents. .........................................................28
4.3 Analysis of the sample of microfinance recipients. ....................................................................31
4.3.1 Chi- Square Test with cross-tabulation................................................................................39
4.3.2 Independent- Samples T-Test...............................................................................................45
4.3.3 Binary Logistic Regression..................................................................................................49
Chapter 5: Conclusion...........................................................................................................................52
5.1 Recommendations .......................................................................................................................54
5.2 Future Scope...............................................................................................................................55
Bibliography .........................................................................................................................................56
Appendices............................................................................................................................................63

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1. Questionnaire............................................................................................................................63
2. KBS Research Ethics Form.......................................................................................................69
3. Confirmation for Ethics Approval ............................................................................................74
4. Chi-Square Test ........................................................................................................................74
5. Independent sample T-Tests .....................................................................................................77
6. Binary Logistic Regression.......................................................................................................80
7. Custom Report Generated from MIX Market...........................................................................87
8. Mean income spent by the microfinance recipients..................................................................88

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List of Tables and Figures
Table 1: Survey Data............................................................................................................................25
Table 2: Omnibus Tests of Model Coefficients table...........................................................................26
Table 3: Variables in the Equation table ..............................................................................................27
Table 4: Cross tabulation: profession * microfinance awareness among the non-microfinance
respondents ...........................................................................................................................................28
Table 5: State wise people below poverty in North India ....................................................................29
Table 6: Active micro loan borrowers in the top MFI's of North India ...............................................30
Table 7: Percent of female borrowers in top MFI's of North India......................................................32
Table 8: Cross tabulation: gender * survey data of 40 microfinance recipients...................................32
Table 9: Cross tabulation: difficulties while applying to micro loan * microfinance services awareness
..............................................................................................................................................................33
Table 10: Cross tabulation: purpose of taking micro loan * difficulties while paying the loan amount
back.......................................................................................................................................................34
Table 11: Types of business undertaken by microfinance recipients...................................................35
Table 12: Meaning of social conditions in the opinion of microfinance recipients .............................35
Table 13: Social conditions of the microfinance recipients before and after taking micro loan..........36
Table 14: Meaning of economic conditions in the opinion of microfinance recipients .......................36
Table 15: Economic conditions of the microfinance recipients before and after taking the micro loan
..............................................................................................................................................................36
Table 16: Recommendations regarding micro loans by microfinance recipients ................................37
Table 17: microfinance adds value or not? In the opinion of the microfinance recipients ..................37
Table 18: Purpose of microfinance recipients for applying micro loan again......................................38
Table 19: Borrowers loan retention rate in top MFI's of North India ..................................................38
Table 20: Cross tabulation: difficulty faced while applying to micro loan* microfinance services
awareness apart from micro loan ..........................................................................................................39
Table 21: Cross tabulation: difficulty faced while applying to micro loan* difficulty in paying the
loan amount with interest back .............................................................................................................40
Table 22: Cross tabulation: would respondents recommend the micro loan to other people* would
respondents apply for the micro loan again ..........................................................................................41
Table 23: Cross tabulation: difficulty faced while applying to micro loan * would you apply for the
micro loan again....................................................................................................................................42
Table 24: Cross tabulation: difficulty in paying the loan amount with interest back* would
respondents recommend the microfinance loan to other people...........................................................43
Table 25: Cross tabulation: have recipients seen any variations in interest rates charged by MFI on
micro loan * difficulty in paying the loan amount with interest back...................................................44
Table 26: Group statistics.....................................................................................................................45
Table 30: Omnibus Tests of Model Coefficients .................................................................................49
Table 31: Variables in the Equation.....................................................................................................50
Figure 1: Mean percentage wise spending of income by microfinance recipients………………….. 35

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List of Acronyms
AIMS Accessing the Impact of Microenterprises
BIDS Bangladesh Institute of Development Science
BMC Bhartiya Micro Credit
BPL Below Poverty Line
CGAP Consultative Group to Assist the Poor
FOCCAS Foundation for Credit and Community Assistance
ILO International Labour Organisation
JLG Joint Liability Group
MFI Microfinance Institution
MIX Microfinance Information Exchange
NGO Non-Government Organisation
NABARD National Bank for Agriculture and Rural Development
PAC Public Affairs Committee
SME Small and Medium sized Enterprises
SHG Self Help Group
USAID United State Agency for International Development

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Chapter 1: Introduction
This thesis examines the effectiveness of microfinance in the socio-economic development
with the major focus on poverty reduction and gender equality (in the sense of women
empowerment) in Northern part of India.
1.1 Definition of microfinance
Microfinance is defined as any activity that includes the provision of small business loans,
saving accounts, money transfers, insurance and other banking services to individuals who
fall below the nationally defined poverty line with the goal of creating a socio-economic
value. According to ILO, “Microfinance is an economic development approach that involves
providing financial services through institutions to low income clients.” In India,
Microfinance has been defined by the National Microfinance Taskforce Gdrc.org (1999) as,
“Provision of thrift, credit and other financial services and products of very small amounts to
the poor in rural, semi-urban or urban areas for enabling them to raise their income levels
and improve living standards.”
Making small loans to individuals who lack access to financial services to secure traditional
credit without any collateral is known as micro loan. The organisations that provide these
services are known as MFI’s, which may operate as non-bank financial institutions, formal
micro banks; community based financial institutions or NGO’s. Microfinance differs from
conventional banks in number of ways. Table 1 outlines the major differences between
conventional banks and microfinance.

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Area Conventional Banks Microfinance
Focus Profit maximizing credit
lending firms for general
public.
Viable credit system for
economically weak people.
Customer enrolment Customers are enrolled
primarily through the
branches.
Customers are enrolled in a
stage wise strategy initiated
by village meetings, making
groups, provide trainings to
group members on financial
management and then
providing credit.
Loan size & collateral Large loan amounts with
collateral. Loan for the
people BPL is mostly 320€
and above.
Small collateral free loan
amounts. Average loan size
is of 200€. Starting with the
minimum loan amount of
40€.
Customer service Customer mostly access bank
branches for services
MFI’s access customers at
their place for services.
Source of capital Mix of both ownership and
borrowed funds
Mostly operates on borrowed
funds.
Social/educational
programs
Doesn’t include Include social/educational
programs such as health
awareness, trainings on
women empowerment, etc.
Loan collection method Customers pay the loan
amount with interest in the
form of monthly instalments
at the maturity of the
contract.
Customers pay the loan
amount with interest in the
form of weekly, semi-
monthly and monthly basis in
the form of instalments.
Table 1: microfinance vs conventional banks (Source: Avineet, 2010)

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1.2 Why India
India is chosen as a location because apart from being considered as a land of ethnic beauty,
diverse culture and integration, it is also the aboard of millions of poor’s. India is said to host
one-third of the world’s poor. According to World Bank, India falls under low-income class.
Gini coefficient (measure of income inequality) of India in 2010 was 33.9
(Data.worldbank.org, 2015). Furthermore, 24% of the population in India is living a life of
misery and below the poverty line of €1 a day (Povertydata.worldbank.org, 2015). Today, the
poor wants to break out of the poverty trap, if given a chance they can display the strength
and resilience required in breaking out of the poverty trap (Bandhanmf, 2007).
“In my experience, poor people are the world's greatest entrepreneurs. Every day, they must
innovate in order to survive. They remain poor because they do not have the opportunities to
turn their creativity into sustainable income.” - Mohammad Yunus
In emerging economies like India the structure of economy is dualistic. The rich get richer
and the poor get poorer. Gender inequality in India is another major issue, even though taking
serious measures in the fields of employment, literacy and health; gender inequality still
remains in majority of states. Employment, health and education of women are worse than
men in almost all states of India (Srivastava, 2010). In India, why North India is chosen as a
location for the study is discussed in the next section of this chapter.
1.3 Why North India
There have been significant regional differences in India since the time of its independence.
North India lags far behind of South India in terms of majority of productive factors such as
literacy, gender equality, life expectancy, infant mortality, fertility, etc. (Sridhar & Reddy,
2011). According to PAC of India, poor quality of governance, inferior leadership and
political instability has led North India far behind of South India, expanding the gap in terms
of poverty and per capita income between the both. As of 2009-10 average, weighted per
capita income of Northern India was less than half (i.e.125€) that of South India (i.e. 262€)
and in the same period average, weighted poverty rate (rural and urban population combined)
of North India was 38% against just 19% in South India (India Today, 2013). The result of
which, migration of North Indians to South India has been increased for search of work in the
recent years. These regional differences make North India as a good location for measuring

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the effectiveness of microfinance. Microfinance in North India is delivered through three
major models which are discussed in the next section of this chapter.
1.4 Microfinance delivery models in North India
North India Comprises of three major delivery models of microfinance.
1. Microfinance Institutions (MFI’s) is the chiefly followed model in North India.
MFI’s provide financial services to the economically weak people through the notion
of Joint Liability group (JLG) (Nasir, 2013). A JLG is a kind of casual group
consisting of 10-15 members who avail the micro loan either together or individually
against a mutual guarantee of paying it back with interest.
2. Grameen Bank Model was first initiated in 1983 by Mohammad Yunus in
Bangladesh. Under this model, micro loans are given to the under privileged people
for the purpose of income generation without any collateral. People pay back the loan
amount from the profits earned with very little interest. Interest earned from the loan
is then utilized to give micro loans to more people. This model has been adopted by
few MFIs of North India such as SHARE microfinance limited, CASHPOR micro
credit and Activist for social alternatives (ASA) (Nasir, 2013).
3. Self-help groups (SHG)-bank linkage program was first commenced by NABARD
in 1992 (IITK.ac.in, 2011). Under this model, initially the members were required to
form the groups of 10-15 and are encouraged to contribute their savings in the group
in the periodic manner so that the small loans from the savings can be disbursed to the
group members in need. Later these SHG’s were linked with the banks for providing
bank loans for the purpose of income generation. Recovery of these loans is made
from the group’s savings and also the new loans are disbursed to the group members.
Once these groups become substantial, they start to operate from their own with some
support from the NGO’s.

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1.5 Aims and Objectives of the research
The aim of this research is measure the effectiveness of microfinance in North India. The
objectives of the study are to:
1. Take an overview of the microfinance process followed in North India. It involves
examining the loan disbursement and collection process undertaken by the MFI’s in
North India.
2. Examine the role played by microfinance in poverty reduction in North India. It
involves examining the changes in the socio-economic conditions of microfinance
recipients after taking the micro loan.
3. Examine the role played by microfinance in promoting gender equality in North
India. It involves examining how female entrepreneurs utilise income generated from
microfinance.
4. Discuss how recipients make use of microfinance funding. It involves examining the
types of business recipients undertake after getting the micro loan and also the recipients
loan retention rate.
5. Examine public awareness of microfinance funding in North India. It involves
examining the outreach of microfinance in North India.
6. Identify problems prevailing in microfinance in North India. It involves examining
the problems related to microfinance structure in North India.
1.6 Summary
This chapter has introduced the topic and discussed briefly the purpose of the research
project. The question is whether or not microfinance has a role to play in a strategy of socio-
economic development in North India. A country overview of India and introduction to
microfinance was outlined. The aims and objectives discussed are reached using the methods
of statistical analysis and through the examination of primary and secondary data. The
methods of data analysis include chi-square tests, independent sample T-tests and
regressions. The data has been analysed from the sample of 100 respondents and
recommendations have been based on the findings from the analysis. The scope of this thesis
is limited to the operation of MFI’s in North India. The next chapter reviews the literature on
the effectiveness of micro loans. This is followed by a discussion regarding methods, findings
& analysis and the final conclusion.

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Chapter 2: Literature Review
The present chapter critically discuss the theoretical and empirical evidences on the
effectiveness of microfinance. The first part of this chapter draws the introduction on
microfinance. The second part discusses the areas in which microfinance can be used for the
welfare of the underprivileged. The third and fourth part will bring some international and
Indian evidences on the effectiveness of microfinance in the context of natural disaster,
poverty reduction, SME’s, health awareness and women empowerment. The fifth part
examines the literature gap and discusses how the research can begin to fill that gap and the
last and the final part of this chapter discusses some possible hypotheses that flow from the
literature.
2.1 Introduction
Microfinance has become a sensible means to supply crucial funding to the people who are
below nationally defined poverty line, particularly those in emerging economies that have
limited or no access to conventional means of financing (Dorado, 2001) and (Khavul, 2010).
In recent years microfinance has appeared as an indispensable industry delivering over $25
billion in micro loans to over 150 million individuals (CGAP, 2013) and (Diekman, 2007).
Access to microfinance may contribute in the accumulation of the resources; consumption
smoothening and it can reduce the vulnerability of the poor people due to illness, drought and
crop failures. It may contribute to better health, education and living of the borrower. In
addition, it may contribute to the women empowerment. Impact of microfinance surpasses
the social and economic improvement of the borrower(Hermes & Lensink, 2011).
2.2 Micro Finance Loans and their uses
Loans from MFI’s can be used by borrowers for productive purposes such as investment in
agriculture or non-farm businesses on household poverty levels. Imai, Arun, & Annim (2010)
examine the sample of 20 SIDBI partnered MFI’s and cross-sectional data of 5260
households across different regions of India. They then employed Tobit model and Heckman
sample selection model to evaluate poverty-reducing effects of access to MFI’s. From both
the models they find out that MFI’s play a crucial role in poverty reduction.

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Microfinance enables poor people to increase, protect and diversify their sources of income.
Poor people can use micro loans to set up a small business or to pay for health care or to pay
school fees for their children or to fix their leaky roof and this can be the first step in breaking
the poverty traps.
2.3 International Evidence
Becchetti & Castriota (2011) have defined the microfinance as a recovery tool after a natural
disaster. In their paper they investigated the offering of microfinance in helping people who
were affected by the tsunami in Sri Lanka in 2004. They conducted the experiment in which
they divided the microfinance borrowers into two groups. One group consist of the borrowers
who were affected by the tsunami; the other group consist of the borrowers who were not
affected by the tsunami. Based on the diversified information containing the data for both
before and after the tsunami, Becchetti and Castriota revealed that access to microfinance
before the tsunami was the main reason for the borrowers for income convergence. The
process of convergence was severely distorted due to the disaster but micro loans provided
after the tsunami played an important role in minimising the income gap between those who
were affected and those who were not. Moreover, Khandker (2007) studies the surviving
strategies embraced by the rural people during the 1998 flood in Bangladesh and examine
their impact on well-being. He also concluded that amount of micro loan borrowing was
increased in that period and had positive effect on the people in terms of level of consumption
and assets holdings.
Microfinance accounts for around 40 % of the overall reduction in moderate poverty in
Bangladesh but Khandker (2005) analyses the impact of Microfinance by using the panel data
from Bangladesh and from his study he concluded that the impact of microfinance is slightly
higher for extreme poverty in comparison to moderate poverty, at both the village and
individual level. Moreover, Chemin (2008) used the propensity score matching technique on
the same panel data from Bangladesh and shows that access to microfinance has a favourable
impact on supply of labour, expenses and education for the extreme poverty. However, the
results were contrasted by the findings of Copestake, Dawson, Fanning, McKay, & Wright-
Revolledo (2005) as they were less confident about the impact of microfinance on extreme
poverty. They studied the data from the survey which was carried out in association with a
village banking program called Promuc, in Peru in 2002 and by using combination of

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qualitative and quantitative analysis they find that moderate poor benefit most from the
microfinance rather than extreme poor.
However, Morduch (1998) from his study of the surveys of nearly 1800 household in
Bangladesh collected by the BIDS in collaboration with World Bank, found no proof to
support the claim that household with the access to microfinance programs raises their
consumption levels or increases their school enrolments for children in relative to the
households with no access to microfinance programs. Todd (1997) supported Morduch
(1998) argument by concluding that most of the microfinance borrowers use micro loans to
buy land instead of completing their proposed business for the sake of which they have taken
the micro loan.
Furthermore, Hulme (2000) from his study concluded that effective MFI’s are only located in
Bangladesh and the claims regarding MFI’s giving micro loans to the ‘poorest’ or ‘poorest of
the poor’ is unproven within the national context. Hence, micro loans are never given to the
poorest- elderly, mentally and physically challenged people. He also said in his paper that
most of the poverty focussed MFI’s in Kenya and Uganda have high percentage of clients
who are above nationally defined poverty line and 13 clients to whom he has interviewed in
1999, all of them owns a car.
Coleman (1999), and coleman (2006) was the first person to use randomized approach for
assessing the effects of microfinance. In his research he used an external event i.e. micro loan
agenda initiating microfinance in the northeast Thailand with unanticipated and random
delays. From his quasi-experimental study, he revealed that microfinance has a favourable
effect on moderate poverty only. On the other hand Karlan & Zinman (2010) studies the
impact of microfinance on SME’s investment in Manila, Philippines. The outcome from their
results was rather dispersed. One of the important findings from the result was profit from
SME’s increases generally for male and higher income enterprises. Additionally, they find
the impressive result reflecting that ‘SME’s substitute away from labour into education and
formal insurance into informal insurance.’
Further, Carolyn, Gary, & Richard (2001) concluded that households of microfinance
borrowers appear to have better health practices, nutrition’s and health outcomes in
comparison to non-borrowers. Along with the facility of micro loans some MFI’s also
provide education on health typically in the form simple and short preventive awareness on
safe drinking water, immunization, washing hands before eating, etc. Many MFI’s have

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formed partnerships with the insurance companies in order to provide health insurance to
their clients. The study of USAID-AIMS reveals that clients of the FOCCAS MFI in Uganda
receive health training on family planning, breastfeeding and preventive health. These
borrowers have better health care practices than non-borrowers. The study commissioned by
USAID-AIMS also exposes that 95 % of the borrowers involve in better nutrition and health
practices for their children compared to the 72 % of the non-borrowers.1
2.4 Indian Evidence
MFI’s in India face great deal of challenges and are subject to exploitation in the credit
market through high interest rates and lacks convenient access to credit. They need credit to
fund their working capital needs on a day-to-day basis as well as long term needs like
emergencies or other income related activities. The need for financial assistance and business
development services for the microenterprises is essential to alleviate poverty for consistent
economic growth (Ranjani, 2012). However, group lending is the major practice enrolled by
the MFI’s in order to safe guard their loans. Hence, Joint Liability Group (JLG) is the major
attribute of group lending; in practice this signifies that if person in the group is defaulted on
the micro loan then the whole group is collectively defaulted and the responsibility is then
imposed on the group to repay the micro loan with interest (Besley & Coate, 1995).
Hulme (2000) in his paper has raised the question on loan repayment rates and argues on the
fact that MFI’s have created the myth that most of microfinance recipients repay their loans
because of their entrepreneur skills. He regarded this as a complete nonsense and given the
new name to micro credit as micro debt. Hulme argues that most of the microfinance
recipients are not able to pay back their loan due to which some of them commit suicide.
Moreover, Bateman & Chang (2008) supported Hulme (2000) in their paper and examined
the impact of microfinance on rural farmers in India and reported that 1, 60,000 farmers have
committed suicide since 1997 due to the growing debt from micro loans.
On the other hand Barbora & Mahanta (2000) examine the impact of microfinance through
Self Help Groups (SHGs). They analyse the case of Rashtriya Vikas Nidhi (RVN) in Assam,
Northeast India and found that 80% of the loan takers are the people who are living in
1
Barnes et al, impact of three microfinance programs in Uganda, 2001.

18
poverty, and belonged to the age group of 8 to 50 years. They also found the program
successful with loan repayment performance of about 91%.
Further, Sapovadia (2007) reveals from his study that typical micro-finance borrowers in
India are self-employed, low-income persons and household-based entrepreneurs that lack
business skills and don’t have access to conventional banking. Micro entrepreneurs face
number of problems in getting started. Most of the time they lack the required skills to handle
the financial aspects of their business but various MFI’s development programmes in India
have helped micro entrepreneurs (who look for collateral security or those who have low
credit) in developing their business plans, providing them training support and assisting them
in setting up their business. Therefore, the study explores that successful micro entrepreneurs
adds value to the society by creating socio-economic value.
A study of SHARE MFI by Simanowitz (2003) in Southern part of India reveals that three-
fourth of the microfinance borrowers who were borrowing from the longer period have
shown substantial improvement in their economic well-being (based on ownership of
productive assets, sources of income and housing conditions) and half of the borrowers have
broken the poverty trap. 2
Microfinance is one of the crucial investments in the economic
development. Micro loans availability at the right time at right quantity and at affordable
processing fee and interest rate contribute much to the welfare of the people especially in
rural areas (Jayasheela, dinesha, & Hans, 2008).
Rai & Ravi (2011) examined the effect of microfinance on women empowerment. They
analyse the issue by using distinctive dataset consisting of around 2, 80,000 microfinance
borrowers in India; these borrowers are required to buy health insurance after getting the loan
amount. Rai and Ravi from their study shows that female borrowers of microfinance
subsequently make more use of health insurance in comparison to the non-borrowing females
who have obtained the health insurance through their husbands. This shows that access to
microfinance may empower women.
Many schemes of microfinance primarily focus on women as research shows that women are
more creative in comparison to men and have high payback ratios. Moreover, women use a
more significant part of their income for education and health of their children(Pitt &
Khandker, 1998). Thus, women play a very important role in poverty reduction. On the other
2
Simonwitz, appraising the poverty outreach of microfinance.

19
hand Goetz & Gupta (1996) argue that women are enforced to hand over the loan amount to
man, who later use the loan amount for their own purposes which in turn leads to the extra
burden on women if they are accounted for the repayment.
Bandhan MFI, which is one of the leading MFI of India provide micro loans to the
underprivileged women of West Bengal, Northeast India. These loans are used in an era of
income generating activities. Some of the interviews of women borrowers covered by
Bandhan are listed below:
(Kajal Manna, Flower Business): “Loan taken from Bandhan has been of great help to me.
Now, I can work as well as earn money. Bandhan has given me the chance to do something in
life. Now, I am improving step by step.”
(Rahima Begam, Handicraft): “I had taken microfinance loan from Bandhan and used it for
Jori work (handicraft). I spend my income for repayment of loan, which is taken from
Bandhan and also for family expenses, and education of the children. I want to be associated
with Bandhan as long as possible.
Most of the MFI’s in India ensures that micro loans are given only to the women and for
income generation purpose. A successful micro credit borrower is graduated to a micro
enterprise borrower but in the future micro enterprise borrower will become a SME borrower
(Bandhanmf, 2007).
2.5 Scope of Research and Possible Contribution
Microfinance has received much recognition in Bangladesh, Kenya, Uganda, Shri Lanka, etc.
but in India microfinance has gained attention only in Southern and North-eastern parts in
terms of both media and academics research. However, there are significant regional
differences in India. The northern part of India lags far behind of South India in terms of
majority of productive factors such as literacy, gender equality, life expectancy, infant
mortality, fertility, etc. (Sridhar & Reddy, 2011) even after this there is hardly any academic
research done in Northern part of India. Further, population of North India is almost twofold
that of South India and poverty levels are also twofold (Hindustan Times, 2011). Two major
states of North India i.e. Uttar Pradesh and Uttaranchal come under seven poorest states of
India. These seven states constitute around 53.5% of the total poor population in India and
share just 23.06% of the total microfinance outreach in India (Nasir, 2013). Moreover, only 2

20
MFI’s out of top 50 MFI’s of India are located in Northern part of India (Cresil, 2009). Due
to these significant regional differences, the researcher has picked North India as a location
for measuring the effectiveness of micro loans.
2.6 Some Possible Research Hypothesis
H1: Microfinance has positive impact on poverty reduction in North India. Due to
collateral free loans provided by MFI’s, poor people will get the opportunity to start their
own business and reflect their entrepreneur skills. Therefore, there is a possibility that they
will improve their economic conditions and break the poverty trap.
H2: Microfinance promotes gender equality in the sense of women empowerment in
North India. As discussed in the literature that ‘MFI’s in India mainly targets female
entrepreneurs who are BPL’. Therefore, there is a possibility that women get the opportunity
to show their entrepreneurial skills and may contribute major portion of their earnings in the
welfare of their family to reflect gender equality against males in their family.
H3: Microfinance recipients face difficulty while applying to micro loan. As argued in the
literature that ‘micro entrepreneurs face number of problems in getting started’. Therefore,
there can be the possibility that people BPL face difficulty while applying to micro loan.
H4: MFI’s have difficult loan collection method. As argued in the literature that ‘most of
the micro entrepreneurs are not able to repay their loan amount with interest back’. Therefore,
there can be the possibility that MFI’s have difficult loan collection method.
H5: Microfinance borrowers have high loan retention rate. As discussed in the literature
that’ micro entrepreneurs who are borrowing from the long period are successful in breaking
the poverty trap’. Therefore, there can be the possibility that micro entrepreneurs apply for
the micro loans again and again and reflect high loan retention rate
H6: Many North Indian residents who are BPL are unaware of MFI’s and service such
institution offer. Population of North India is 543 million and majority of the rural
population who are BPL is illiterate. So, there may be the possibility that many people BPL
are not aware of MFI’s and services such institutions offer.

21
Chapter 3: Methodology
This section aims to explore the methodological tools and instruments that are implemented
in the research project for fulfilling the aims and objectives. The section explores various
subs –sections such as philosophical posture of the study, approach to the research, data
collection methods, research strategy and methods of data analysis.
3.1 Research Philosophy and Approach
The research has been approached using positivism philosophy of science which uses both
the principles of deductivism and inductivism (Bryman & Bell, 2008). It generate hypothesis
that can be tested using statistical tools and instruments and that thereby allow justification of
laws to be analysed (deductive approach). Knowledge is primarily achieved through the
collection of relevant facts that provide building blocks for laws (inductive approach). This
philosophy of science is different from interpretivism philosophy of science which is more
qualitative in nature (more inductive) and relies heavily on the analysis of existing text
(human action) rather than objects that deemed to act on it in order to develop a meaningful
reality (Bryman & Bell, 2008). According to Saunders, Lewis & Thornbill (2009)
interpretivism is associated more with the human beings rather than objects such as cars and
machines.
The choice of positivism philosophy of science in this research project can be clarified by the
need to test available theories on the effectiveness of the micro loans in emerging economies
or to reject alternative hypothesis (research hypothesis) using quantitative analysis.
According to Bryman & Bell (2008) interpretivism philosophy of science will take the
research project primarily in qualitative direction because this philosophical posture is more
concerned to the subjective meaning of the social action rather than testing.
3.2 Research Strategy
Surveys, Microfinance Information Exchange (MIX) and case study have been selected as the
key strategies for the research project. One of the main advantages of case study is that it
allows inductive approach by focusing on the context of the issue and supplements the
research with qualitative information (Robson, 2002). In this research project, people below

22
nationally defined poverty line have created the context in which effectiveness of micro loans
in North India was investigated.
However, the case study alone would not be sufficient to explore the effectiveness of micro
loans, primary data is required to execute this. According to Bryman & Bell (2008) and
Saunders, Lewis & Thornbill (2009), survey is the most successful strategy for working with
primary data. It implies that data can be collected from the respondents through
questionnaires, interviews or other observations. In this research project, questionnaires are
preferred over interviews because former can be analysed more quantitatively, scientifically
and objectively in comparison to interviews
Data collected from the surveys allow deductive approach and can be used with statistical
tools and techniques to report quantitative information in the research project (Saunders,
Lewis & Thornbill, 2009). To enrich this data, custom report generated from MIX market has
been used as a source of information in sourcing the statistics used in this research. Further
details of data are described in the following section of this chapter.
3.3 Data
This research was granted by the “Kemmy Business School research Ethics committee” (see
appendix 3). For primary data, structured questionnaire was prepared and distributed in
Lucknow (capital city of Uttar Pradesh and one of the major metropolitan cities of North
India) and areas nearby to 100 respondents who were below nationally defined poverty line.
Lucknow is chosen as a location for the research study because it is considered as the second
happiest city of India (The Times of India, 2015) and doing the research on the effectiveness
of micro loans in this city on poverty will be worthwhile. Out of 100 respondents that were
below nationally defined poverty line, 40 of them were the successful microfinance recipients
of Bhartiya Micro Credit (BMC) and 60 were the respondents that don’t use microfinance.
This facilitated the acquisition of relevant data from the two different sources.
First part of the questionnaire was designed to separate these 60 respondents from the 40
respondents in order to reveal the awareness of microfinance among the 60 non-
microfinance respondents in North India. From second part onwards the questionnaire was
specifically for the 40 successful microfinance recipients of BMC (see appendix 1).

23
The research project is also based on the secondary data in the form of custom report of five
largest MFI’s in North India, namely the Cashpor Micro Credit, Pahal financial Services,
Sonata Finance Private Limited, Ujjivan Financial Services and SV Credit Line Private
Limited (SVCL) generated by MIX (see appendix 7). It also includes an interesting case
study of Nat Purwa village of North India related to gender inequality which is later
discussed in the next chapter.
Apart from these data’s, following documents have been analysed for additional secondary
data required in the research:
1. Books and articles related to microfinance and development in the areas of
research.
2. Annual Reports, Press releases, Newsletters and Organisational charts
within microfinance.
3.4 Methods of data analysis
The data collected from the surveys is reported with the help of frequency tables that
reflected a breakdown of responses and helped in estimating the percentages. Information
gathered from the custom report generated by MIX is also presented in synchronisation with
the analysis resulted from the survey data. Several statistical methods in IBM SPSS version
20 have been used for the in depth analysis of the survey data in order to test the research
hypothesis and to reach the aims and objectives of the research project. The methods include:
Chi-Square Tests with cross tabulation: are used to find statistically significant association
between two categorical variables using cross tabulation and comparing p value of the result
to the alpha level (Which is commonly 0.05). If the p value is<= 0.05 then variables are
significantly associated and reject the Null Hypothesis and accept the Research Hypothesis. If
the p value is > 0.05 the variables are not significantly associated and retain the Null
Hypothesis and reject the Research Hypothesis (Statistics.laerd.com, 2015).
Independent- Samples T-Tests: are used to find significant difference in the mean
percentage between two variables by considering dependent variable (measured on a
continuous scale) as the test variable and independent variable (two categorical) as the
grouping variable. In the result, if p value under Levene’s Test is <= 0.05 then it violates the
assumption of equal variance and p value under T-Test for equal variance not assumed was

24
considered. Conversely, if p value under Levene’s Test> 0.05 then it accepts the assumption
of equal variance and p value under T-Test for equal variance assumed was considered to
find the significant difference in the mean percentage between the two variables
(Statistics.laerd.com, 2015).
Binary Logistic Regressions: are used for assessing the impact of number of factors
(independent variables) on the likelihood of the dependent variable. For example, difficulty
faced by the people in paying the micro loan amount with interest back to the MFI can be
considered as dependent variable and to test its likelihood age, number of children, economic
conditions after micro loan, etc. can be considered as independent or predictor variables.
3.5 Limitations
The research project is limited to the number of people that could be surveyed. It was very
difficult to get 100% response ratio in the population of 543 million people (Population of
North India) and only a proportion of people who were invited to participate in the surveys
could actually participate. Out of 150 potential respondents who had been invited, only 100
make through it. Hence response ratio is 66.66%.
The next limitation concerns the number of successful microfinance recipients i.e. 40
respondents limits to only one MFI i.e. BMC. However, there are several other MFI’s in
North India but due to the time constraints; it wasn’t possible to invite microfinance
recipients from other MFI’s to participate.
The final limitation concerns the quality of responses from the respondents. The research
project doesn’t guarantee against the respondents bias and fallacy. Since majority of the
questions in the questionnaire were constructed by using the Likert scale (McLeod, 2015)
there is a possibility that respondents could underreact or overreact to certain questions.

25
Chapter 4: Findings and Analysis
This chapter reflects the analysis of the sample using SPSS statistical tools and instruments.
As discussed in the data section of the methodology, sample consists of total 100 respondents
that were below nationally defined poverty line. Out of which 40 respondents were the
microfinance recipients of BMC and remaining 60 were the non-microfinance respondents
(Table 1).
Table 1: Survey Data
Frequency Percent
Valid Non-microfinance respondents 60 60.0
Microfinance recipients 40 40.0
Total 100 100.0
The chapter is divided into three parts. First part puts spotlight on the of the whole sample
using binary logistic regression analysis to find which factor makes a significant contribution
on the likelihood that respondents will apply for micro loan. Second part focuses on the
analysis of 60 non-microfinance respondents with the help of the data from the MIX and an
interesting case study of Nat purva village to describe the outreach of microfinance in North
India. Final part of the chapter focuses specifically on the analysis of the 40 microfinance
recipients with the help of frequency tables, cross tabulations, data from MIX, chi-square test,
independent sample t-test and binary logistic regression to explore the effectiveness of micro
loans in North India

26
4.1 Analysis of the whole sample.
Binary Logistic Regression using Enter method was performed on the whole sample of 100
respondents to assess the impact of number of factors on the likelihood that respondents will
apply for the micro loan. The model contained four independent variables or predictor
variables i.e. (1) age groups (i.e., under 35, over 35), (2) gender (i.e., male, female) (3)
marital status (i.e., married, non-married), (4) children (i.e., yes, no).
The full model (from the Omnibus test of model coefficients in Table 2) containing all
predictors was statistically significant, X2
(4, N=100)= 45.060, p< .001 indicating that the
model was able to distinguish between the respondents who applied the micro loan and the
respondents who did not applied the micro loan (Kirkpatrick & Feeney, 2013).
Table 2: Omnibus Tests of Model Coefficients table
Chi-square df Sig.
Step 1 Step 45.060 4 .000
Block 45.060 4 .000
Model 45.060 4 .000
The model as a whole was a good model as p>0.05 in Hosmer and Lemeshow Test and is
explained between 36.3% (Cox and Snell R square) and 49.0% (Nagelkerke R square) of the
variance in the status that respondent will apply for micro loan (Statisticalhorizons.com,
2015), and correctly classified 78% of the cases (See appendix 6.1). As shown in the Table 3,
only one of the predictor variables made a unique statistically significant contribution to the
model i.e. age-groups, recording an odds ratio of 3.8. This indicated that respondents who
are under 35 age-groups (young entrepreneurs BPL) are over 3.8 times more likely to
apply for micro loan than those who are over 35 age-groups, controlling for all other
factors in the model.

27
Table 3: Variables in the Equation table
B S.E. Wald df Sig. Odds ratio/ Exp (B)
Step 1a
(1) Age groups 1.323 .606 4.761 1 .029 3.755
(2) Gender -21.367 7843.903 .000 1 .998 .000
(3) Marital status -.639 .725 .776 1 .378 .528
(4) Children -1.051 .908 1.341 1 .247 .350
Constant .105 .355 .087 1 .768 1.110

28
4.2 Analysis of the sample of non-microfinance respondents.
In the sample of 60 non-microfinance respondents, more than 90% of the people who were
below nationally defined poverty line were not aware of the MFI’s and the services such
institutions offer (Table 4). This is because majority of the poor’s in North India are illiterate
and hardly able to understand anything when these services are advertised. These people are
often engaged into some part time work or into the same profession (which is continuing
from the time of their ancestors). Part time work primarily includes labour work, home maid,
etc. and its allocation only depends on the requirement. It is completely uncertain that a part-
time work of the person will last till next day.
Table 4: Cross tabulation: profession * microfinance awareness among the non-microfinance respondents
Microfinance awareness Total
No Yes
Profession Own business 15 0 15
Labor work 16 0 16
Home maid 10 2 12
Cook 3 2 5
Washing clothes 3 0 3
Smith 1 0 1
Carpenter 1 0 1
Painter 3 0 3
Driver 0 1 1
Cobbler 3 0 3
Total 55 5 60
In case of emergencies, these people have no option left except to go to the local money
lenders which charge very high interest rates that further forms the barrier in microfinance
awareness among these people.
Moreover, some respondents in the sample were also engaged in the business of prostitution
for the sake of traditional practice and poverty and were not aware of microfinance.
Following case study of Nat Purva village (which is just1 hour drive from Lucknow, Uttar
Pradesh) will help to understand this issue

29
Prostitution for the sake of traditional practice and poverty: case of Nat Purva village.
In the sample of 60 non-microfinance respondents as shown in (Table 4), 15 people who are
reflecting their own business are the female respondents who are engaged in the business of
prostitution. These females are forced into prostitution by their family members (primarily
brothers and fathers) to earn for living for the sake of 400 years old traditional practice
(Scoop Whoop, 2015). Earlier this business was limited to the village only but now the girls
(as young as 11 years old) are sent to the places like Mumbai, Dubai, etc. (Aljazeera, 2013).
Major source of income in this village comes from prostitution. Whatever these females earn
in their youth is taken away by their brothers and fathers and after that when they become old
they are considered of no use (Video volunteers, 2010).
“At least 30% of the women in this village are still sex workers. If you want to see progress,
you should be able to offer them an alternative way of earning their livelihood”- Ram babu
The major cause of prostitution in North India is poverty and gender inequality (Youth Ki
Awaaz, 2011). Funding options available within MFI’s may be proved beneficial in these
cases (ZDNet, 2013) but the irony is that these people are not even aware of it.
Low outreach of microfinance
According to Government of India Planning Commission (2013), Uttar Pradesh, which is the
biggest state of North India, is the poorest state in the whole India reporting alone 59.8
million people BPL (Table 5).
Table 5: State wise people below poverty in North India
States of North India People BPL (Million)
Uttar Pradesh 59.8
Haryana 2.9
Delhi 1.7
Jammu & Kashmir 1.3
Uttaranchal 1.16
Punjab 2.3
Himachal Pradesh 0.56
Total 67.5
Source: Government of India Planning Commission (2013)

30
Total people BPL in North India reported in the period 2012 was 67.5 million and in the
latest data generated from MIX, number of active micro loan borrowers in the top MFI’s of
North India was just 2.46 million (Table 6) reflecting very low outreach of microfinance in
North India.
Table 6: Active micro loan borrowers in the top MFI's of North India
Top MFI’s of North India Active micro loan borrowers (million)
1) Cashpor Micro Credit 0.65
2) Pahal Financial Services 0.05
3) Sonata Finance Private Limited 0.28
4) SVCL 0.18
5) Ujjivan Financial Services 1.3
Total 2.46 million
Source: MIX Market (2013)
Moreover, two major states of North India i.e. Uttar Pradesh and Uttaranchal come under
seven poorest states of India. These seven states constitute around 53.5% of the total poor
population in India and share just 23.06% of the total microfinance outreach in India (Nasir,
2013).

31
4.3 Analysis of the sample of microfinance recipients.
As discussed in the first chapter, microfinance delivery through MFI’s is the chiefly followed
model in North India (Singh, n.d.) and it is important to understand the loan disbursement and
collection process undertaken by the MFI’s before beginning with the analysis of the sample
of 40 microfinance recipients.
Loan disbursement and collection process
Micro loans are disbursed through the notion of JLG consisting of 10-15 members in North
India. Each group has a president, cashier and a secretary and each of them is charged with
specific responsibilities. Loan processing fees (which is usually 2%) and insurance premium
is mandatory to be paid by each member of the group and is collected by the cashier during
the disbursement process. Cashier hands over the collected amount to the president of the
group. President then verify the amount received with the sanctioned amount and hands over
the collected amount to the loan officer of the respective MFI. Loan officer then issues the
receipt to the members for the cash received and disbursed the sanctioned amount to each
member of the group by explaining them the terms and conditions of the loan. Loan officer
also explains the significance of demand promissory note, the disbursement voucher and the
loan card to the members. Each members of the group is then required to sign the demand
promissory note and disbursement voucher to acknowledge the receipt of their loan.
After disbursement process, weekly meetings take place in one of the borrower’s house.
During the meetings, the microloan borrowers pay their weekly instalments to the cashier of
the group which then hands over the amount to the president of the group. President verifies
the amount and hands over it to the loan officer. The important thing to be noted in this
process is that the loan is disbursed to the group and has to be repaid by the group (JLG). In
addition, the members also discuss the various socio-economic issues during the meetings. If
everything runs well, a micro loan borrower is graduated to micro enterprise borrower (high
loan amount) in order to expand their business.
Analysis of the sample is presented from the next section onwards.

32
Micro Loans are only limited to female entrepreneurs
MFI’s in North India majorly targets women because women are considered to be more
genuine borrower of micro credit than man. Women are considered to be a good investment
by MFI’s because they tend to invest more in education, healthcare, etc. and thereby are more
capable of improving their family’s welfare (About Microfinance, 2015). Table 7 lists the top
five MFI’s of North India by percent of female borrowers in the year 2013.
Table 7: Percent of female borrowers in top MFI's of North India
Top MFI’s of North India Percent of female borrowers
1) Cashpor Micro Credit 100%
2) Pahal Financial Services 99.62%
3) Sonata Finance Private Limited 100%
4) Ujjivan Financial Services 99.95%
5) SVCL 100%
As a result all 40 microfinance recipients of BMC in the sample comes out to be the females
(Table 8)
Table 8: Cross tabulation: gender * survey data of 40 microfinance recipients
Survey data Total
Non-microfinance respondents Microfinance recipients
Gender Male 23 0 23
Female 37 40 77
Total 60 40 100

33
Difficulty of language barrier while applying to micro loan turns into the lack of
awareness of other microfinance services
Majority of microfinance recipients have low education levels which makes them difficult to
communicate with the loan officer while applying to micro loan. For this reason, loan officers
are also not able to explain them the policies and other bonus services provided by their
respective MFI’s such as trainings on women empowerment and voluntary insurance services
like life/accident and health insurances.
In the sample of 40 microfinance recipients, 21 recipients who faced the difficulty of
language barrier while applying to micro loan were also not aware of other microfinance
services provided by MFI’s apart from micro loan (Table 9).
Table 9: Cross tabulation: difficulties while applying to micro loan * microfinance services awareness
Microfinance services awareness
apart from micro loan
Total
No Yes
Types of difficulties while
applying to micro loan
Language barrier
(verbal + Written)
20 1 21
High Interest rates 2 0 2
Loan processing fee 3 0 3
Total 25 1 26
Difficult loan collection method
Weekly loan collection method through instalments imposed by MFI’s in North India forms
major difficulty especially for the recipients who have taken the loan for the agricultural
purposes as they can only generate income from micro loans during they harvest their crops
at the time of cropping season. Moreover, a week time is too less to generate profit from any
business. Hence, it hampers the growth of both MFI’s and its clients in North India (Nasir,
2013).
In the sample of 40 microfinance recipients, 25 respondents faced difficulty in paying the
loan amount with interest back due to weekly loan collection method (Table 10).

34
Table 10: Cross tabulation: purpose of taking micro loan * difficulties while paying the loan amount back
Types of difficulties while paying the loan
amount back
Total
In the loan collection Method which includes
weekly repayment system
Purpose of taking
micro loan
Start-up business 13 13
Develop existing business 3 3
Agricultural/livestock
business
9 9
Total 25 25
Education of children is the primary concern for the microfinance recipients
Microfinance recipients spent major portion of their income (generated by micro loan) on
education of children as MFI’s play a crucial role in causing awareness about the importance
of education in the society and its future benefits in the economic growth of the nation. As a
result, mean income spent on education of children from the sample of 40 microfinance
recipients comes out to be 41% (see figure 1 and appendix 8)
Figure 1: Mean percentage wise spending of income by microfinance recipients
Education of
children
41%
Lodging
28%
Food & Utilities
17%
Savings
14%
Mean income spent on

35
Recipients are involved in very small and low-budget lucrative businesses and reflect
positive change in their socio-economic conditions after taking micro loan.
Recipients take micro loans to primarily start low-budget and high returns businesses like
artesian work, flower business, farming business, vegetable business, etc. (Table 11) and
reflect positive change in their socio-economic conditions.
Table 11: Types of business undertaken by microfinance recipients
Frequency Percent
Valid Artesian Work 15 37.5
Flower Business 7 17.5
Tea stall 4 10.0
Farming business 12 30.0
Vegetable business 1 2.5
Egg stall 1 2.5
Total 40 100.0
In the opinion of recipients in the sample, social conditions mainly stand for improvement in
standard of living and education of their children. (Table 12)
Table 12: Meaning of social conditions in the opinion of microfinance recipients
Frequency Percent
Valid Improvement in standard of living and education of children 29 72.5
Improvement in standard of living 5 12.5
Improvement in standard of living and wedding of my daughters 3 7.5
Education of children 2 5.0
Improvement in standard of living, education of children and making
contacts
1 2.5
Total 40 100.0
85% of the total 40 microfinance recipients have reported better social conditions after taking
the micro loan (Table 13).

36
Table 13: Social conditions of the microfinance recipients before and after taking micro loan
Social conditions after taking the
microfinance loan
Total
Worse Better
Social conditions before taking the
microfinance loan
Worse 6 34 40
Total 6 34 40
In the opinion of recipients in the sample, economic conditions generally stand for being
productive, profit making and strong financial conditions (Table 14)
Table 14: Meaning of economic conditions in the opinion of microfinance recipients
Frequency Percent
Valid Being Productive 13 32.5
Profit Making 26 65.0
Strong Financial Conditions 1 2.5
Total 40 100.0
More than 90% of the total 40 microfinance recipients reported better economic conditions
after taking the micro loan (Table 15).
Table 15: Economic conditions of the microfinance recipients before and after taking the micro loan
Economic conditions after taking the
microfinance loan
Total
Worse Better
Economic conditions before taking the
microfinance loan
Worse 3 37 40
Total 3 37 40
Recipients will recommend the micro loan primarily to the women entrepreneurs
95% of the total 40 microfinance recipients will recommend the micro loans to other people
(Table 16). Recipients will recommend the microloan mainly to women recipients as in their
opinion they are more responsible compared to men and are considered as most under
privileged in the society. However, they are right; women in North India who are BPL

37
generally remain in a disadvantaged segment of the society and have less opportunities then
males. They are simply considered as housewife’s and birth giving machines by most of the
males in rural areas (gender inequality). Through microfinance, these recipients can get the
opportunity to reflect their business skills in the society and to set the example for gender
equality in the sense of women empowerment.
Table 16: Recommendations regarding micro loans by microfinance recipients
Microfinance adds value
In the sample of 40 microfinance recipients, 95% agree that microfinance and its services add
value in their life (Table 17).
Table 17: microfinance adds value or not? In the opinion of the microfinance recipients
Frequency Percent
Valid Disagree 2 5.0
Agree 38 95.0
Total 40 100.0
whom you will recommend and why Total
Women
recipients,
because they
are more
responsible
compared to
men
Women
recipients,
because they
are considered
most under
privileged in
the society
Neighbors,
because I want
that everyone
should be aware
of microfinance
in my society
Relatives,
because they
are financially
weak and have
no capital to
invest for the
startup
Would you
recommend
the micro
loan to other
people?
Yes 17 15 5 1 38
Total 17 15 5 1 38

38
Therefore for this reason, microfinance recipients will apply for micro loan again either for
the development of their existing business or to set up another business (Table 18).
Table 18: Purpose of microfinance recipients for applying micro loan again
For what purpose you will apply the microloan again? Total
Development of existing
business
To set up another
business
Would you apply for the micro
loan again?
Yes 30 7 37
Total 30 7 37
According to the Wall Street Journal (2014), the total funding requirement for the
microfinance recipients in India in 2012 was $158 billion but they only get access to $ 42
billion from authorized lenders.
Hence, weighted average, micro loan borrower’s loan retention rate reported from the top
MFI’s in North India is 85.97% (Table 19)
Table 19: Borrowers loan retention rate in top MFI's of North India
Top MFI’s of North India Borrowers Loan Retention Rate
1) Cashpor Micro Credit 85.95%
2) Pahal Financial Services N/A
3) Sonata Finance Private Limited 85.80%
4) SVCL 82.02%
5) Ujjivan Financial Services 90.11%
Weighted Average 85.97%
Further, in depth analysis of the sample of 40 microfinance recipients has been presented
from the next section onwards. The methods of statistical analysis that were employed in the
research incorporated chi-square tests, independent sample t-tests and binary logistic
regression.

39
4.3.1 Chi- Square Test with cross-tabulation
Chi-Square Test is used in the research project to find statistically significant association
between two categorical responses from the microfinance recipients using cross-tabulation in
SPSS, p value of the result is then compared to the alpha level (Which is commonly 0.05) to
accept or reject the null hypothesis.
1) Is there any relationship between the recipients who faced difficulty while applying
to micro loan and the recipients who are aware of other microfinance services apart
from micro loan?
Table 20: Cross tabulation: difficulty faced while applying to micro loan* microfinance services awareness apart from
micro loan
Microfinance services awareness apart
from micro loan
Total
No Yes
Difficulty faced while applying
to micro loan
No Count 0 14 14
Expected
Count
8.8 5.3 14.0
Yes Count 25 1 26
Expected
Count
16.3 9.8 26.0
Total Count 25 15 40
Expected
Count
25.0 15.0 40.0
The relation between the recipients who faced difficulty while applying to micro loan (i.e.,
no, yes) and the recipients who are aware of other microfinance services (i.e., no, yes) was
significant, X2
(1, N = 40) = 35.897, p <.05 (see appendix 4.1), rejected the null hypothesis
and accepted the research hypothesis i.e. the observed and expected count of both the
variables is far different (Table 20). The final result signifies that recipients who have
difficulty while applying to micro loan are also not aware of other microfinance services
apart from micro loan in comparison to the recipients who do not have difficulty while
applying to micro loan.

40
to micro loan and the recipients who faced difficulty in paying back the loan amount
with interest back?
Table 21: Cross tabulation: difficulty faced while applying to micro loan* difficulty in paying the loan amount with
interest back
Difficulty in paying the loan amount
with interest back?
Total
No Yes
Difficulty faced while applying
to micro loan
No Count 13 1 14
Expected
Count
5.3 8.8 14.0
Yes Count 2 24 26
Expected
Count
9.8 16.3 26.0
Expected
Count
15.0 25.0 40.0
The relation between the recipients who have difficulty while applying to micro loan (i.e., no,
yes) and the recipients who faced difficulty in paying the loan amount with interest back (i.e.,
no, yes) was significant, X2
(1, N = 40) = 28.161, p <.05 (see appendix 4.2), rejected the
null hypothesis and accepted the research hypothesis i.e. the observed and expected count of
both the variables is far different (Table 21). The final result signifies that recipients who
faced difficulty while applying to micro loan also faced difficulty in paying the loan
amount with interest back in comparison to the recipients who do not faced difficulty
while applying to micro loan.

41
3) Is there any relationship between the recipients who will recommend the micro loan
to other people and the recipients who will apply for micro loan again?
Table 22: Cross tabulation: would respondents recommend the micro loan to other people* would respondents apply
for the micro loan again
Would you apply for the
micro loan again?
Total
No Yes
Would you recommend the microfinance
loan to other people?
No Count 2 0 2
Expected
Count
.2 1.9 2.0
Yes Count 1 37 38
Expected
Count
2.8 35.2 38.0
Total Count 3 37 40
Expected
Count
3.0 37.0 40.0
3 cells (75.0%) have expected count less than 5 (see appendix 4.3) which is much greater
than 20%. This signifies that it violates the assumption of chi square (Stattrek.com, 2015) and
in this case we cannot conclude significant or not significant relationship between the two
variables. However, in this case likelihood ratio will be considered to determine the
relationship. Therefore, from the (appendix 4.3), we can conclude that there is a relationship
between the recipients who will recommend the micro loan (i.e., no, yes) and the recipients
who will apply for micro loan again (i.e., no, yes) because likelihood ratio (1, N=40) =
12.062, p<0.05 have rejected the null hypothesis and accepted the research hypothesis i.e.
observed and expected count is far different (Table 22). The final result signifies that
recipients who will recommend the micro loan to other people will also apply for the
micro loan again.

42
to micro loan and the recipients who will apply for micro loan again?
Table 23: Cross tabulation: difficulty faced while applying to micro loan * would you apply for the micro loan again
Would you apply for the micro
loan again?
Total
No Yes
Difficulty faced while applying to
micro loan
No Count 0 14 14
Expected
Count
1.0 13.0 14.0
Yes Count 3 23 26
Expected
Count
2.0 24.1 26.0
Total Count 3 37 40
Expected
Count
3.0 37.0 40.0
relationship. Therefore, from the (appendix 4.4), we can conclude that there is no
relationship between the recipients who faced difficulty while applying to micro loan (i.e.,
no, yes) and the recipients who will apply for micro loan again (i.e., no, yes) because
likelihood ratio (1, N=40) = 2.714, p>0.05 retains the null hypothesis and rejected the
research hypothesis i.e. observed and expected count is almost same (Table 23). Hence, we
cannot conclude that recipients who faced difficulty while applying to micro loan will
apply for the micro loan again but from the results of the cross tabulation, we can see
that majority of the recipients who faced difficulty while applying to micro loan will
apply for the micro loan again.

43
5) Is there any relationship between the recipients who faced difficulty in paying the
loan amount with interest back and the recipients who will recommend the micro
loan to other people?
Table 24: Cross tabulation: difficulty in paying the loan amount with interest back* would respondents recommend the
microfinance loan to other people
Would you recommend the
microfinance loan to other people?
Total
No Yes
Difficulty in paying the loan
amount with interest back?
No Count 0 15 15
Expected
Count
.8 14.3 15.0
Yes Count 2 23 25
Expected
Count
1.3 23.8 25.0
Total Count 2 38 40
Expected
Count
2.0 38.0 40.0
relationship. Therefore, from the (appendix 4.5), we can conclude that there is no
relationship between the recipients who faced difficulty in paying the loan amount with
interest back (i.e., no, yes) and the recipients who will recommend the micro loan to other
people (i.e., no, yes) because likelihood ratio (1, N=40) = 1.943, p>0.05 retains the null
hypothesis and rejected the research hypothesis i.e. observed and expected count of both the
variables is almost same (Table 24). Hence, we cannot conclude that recipients who faced
difficulty in paying the loan amount with interest back will recommend the micro loan
to other people but from the observed count in the cross tabulation, we can see that
majority of the recipients who faced difficulty in paying the loan amount with interest
back will recommend the micro loan to other people.

44
6) Is there any relationship between the recipients who have seen variation in interest
rates and the recipients who faced difficulty in paying the loan amount with interest
back?
Table 25: Cross tabulation: have recipients seen any variations in interest rates charged by MFI on micro loan * difficulty
in paying the loan amount with interest back
Difficulty in paying the loan
amount with interest back?
Total
No Yes
Have you seen any variations in interest
rates charged by your MFI on micro
loan?
No Count 7 12 19
Expected
Count
7.1 11.9 19.0
Yes Count 8 13 21
Expected
Count
7.9 13.1 21.0
Expected
Count
15.0 25.0 40.0
The relation between the recipients who have seen variation in interest rates (i.e., no, yes) and
the recipients who faced difficulty in paying the loan amount with interest back (i.e., no, yes)
was not significant, X2
(1, N = 40) = 0.07, p >.05 (see appendix 4.6) retains the null
hypothesis and rejected the research hypothesis i.e. observed and expected count of both the
variables is almost same (Table 25). Hence, we cannot conclude that recipients who have
seen variation in interest rates charged by MFI’s also faced difficulty in paying the loan
amount with interest back.

45
4.3.2 Independent- Samples T-Test
Independent Sample T-Test is used in the research to find significant difference in the mean
percentage between two variables by considering dependent variable (measured on a
continuous scale) as the test variable and independent variable (two categorical) as the
grouping variable.
1) Is there a significant difference in the mean percentage of income generated by
recipients from micro loan that is spent on food and utilities for the recipients
having children and the recipients having no children?
Table 26: Group statistics
Children N Mean Std.
Deviation
Std. Error
Mean
Percentage of income generated from
micro loan is spent on food and utilities
No 3 30.0000% 0.00000% 0.00000%
Yes 37 15.6757% 8.34684% 1.37221%
Under Levene's Test for Equality of Variances p value is less than the alpha level i.e. 0.026<=
0.05 (see appendix 5.1) indicating that variance between the two groups i.e. having children
and not having children are not the same and violates the assumption of equal variance. So,
for t-test for equality of means we have to use the second line in the table i.e. equal variance
not assumed (see appendix 5.1).
The results of independent t-test were significant, t (36) =10.439, p=0.000 i.e. p value < 0.05
(see appendix 5.1) have rejected the null hypothesis and accepted the research hypothesis,
indicating that there is statistically significant difference between the mean percentage of
income generated from micro loan which is spent on food and utilities from the two groups
i.e. having children (M=15.7%, SD=8.3%, N=37) and not having children (M=30%, SD=0%,
N=3) (Table 26). This signifies that recipients without children spent more on food and
utilities (live more healthy life) in comparison to the recipients with children.

46
recipients from micro loan that goes in savings for the recipients having children
and the recipients having no children?
Children N Mean Std.
Deviation
Std. Error
Mean
Percentage of income generated from
micro loan goes in savings.
No 3 26.6667% 5.77350% 3.33333%
Yes 37 12.9730% 5.19875% 0.85467%
Under Levene's Test for Equality of Variances p value is greater than the alpha level i.e.
0.885> 0.05 (see appendix 5.2) indicating that variance between the two groups i.e. having
children and not having children are the same and for t-test for equality of means we have to
use the first line in the table i.e. equal variance assumed (see appendix 5.2).
The results of independent t-test were significant, t (38) =4.361, p=0.000 i.e. p value < 0.05
income generated by recipients from micro loan that goes in savings from the two groups i.e.
having children (M=12.97%, SD=5.1%, N=37) and not having children (M=26.6%,
SD=5.7%, N=3) (Table 27). This signifies that recipients without children are able to
save more in comparison to the recipients with children as they don’t have other
expenses like education of children, healthcare of children, etc.

47
recipients from micro loan that goes in savings for the recipients who are
married and the recipients who are not married?
Married and
non-married
N Mean Std.
Deviation
Std. Error
Mean
Percentage of income generated
from micro loan goes in savings.
Married 33 12.7273% 5.16764% 0.89957%
Non-married 7 20.0000% 8.16497% 3.08607%
0.270> 0.05 (see appendix 5.3) indicating that variance between the two groups i.e. married
and non- married are the same and for t-test for equality of means we have to use the first line
in the table i.e. equal variance assumed (see appendix 5.3).
The results of independent t-test were significant, t (38) =-3.042, P=0.004 i.e. p value < 0.05
income generated from micro loan which goes in savings from the two groups i.e. married
(M=12.7%, SD=5.2%, N=33) and non-married (M=20% SD=8.2%, N=7) (Table 28). This
signifies that married recipients tend to invest major portion of their income generated
by micro loan on their family and are able to save less in comparison to non-married
recipients.

48
4) Is there a significant difference in the mean percentage of income generated from
micro loan that goes in savings for the recipients who faced difficulty while
applying to micro loan and the recipients who didn’t faced any difficulty while
applying to micro loan?
Difficulty faced while
applying to micro
loan
N Mean Std.
Deviation
Std. Error
Mean
Percentage of income
generated from micro loan that
goes in savings.
Yes 26 13.2692% 5.46668% 1.07210%
No 14 15.3571% 7.71220% 2.06117%
0.129> 0.05 (see appendix 5.4) indicating that variance between the two groups i.e. having
children and not having children are the same and for t-test for equality of means we have to
use the first line in the table i.e. equal variance assumed.
The results of independent t-test were not significant, t(38)=-0.996, P=0.326 i.e. p value
>0.05 (see appendix 5.4), indicating that there is no statistical significant difference between
the mean percentage of income generated from micro loan which is goes on savings from the
two groups i.e. recipients who faced difficulty while applying to micro loan (M=13.3%,
SD=5.46%, N=26 )and recipients who don’t faced any difficulty while applying to micro loan
(M=15.3%, SD=7.7%, N=14) (Table 29). This signifies that income generated by
recipients from micro loan that goes in saving from the two groups i.e. recipients who
faced difficulty while applying to micro loan and recipients who don’t faced any
difficulty while applying to micro loan is more or less same.

49
4.3.3 Binary Logistic Regression
Binary Logistic Regression using Enter method was performed in the research project to
assess the impact of number of factors on the likelihood that recipients would report that they
had difficulty in paying the micro loan with interest back. The model contained eight
independent variables or predictor variables i.e. (1) difficulty while applying to micro loan
(i.e., yes, no), (2) marital status (i.e., married, non-married), (3) children (i.e., yes, no), (4)
number of children, (5) percent of income spent on education of children, (6)percent of
income spent on lodging, (7)percent of income spent on food and utilities and (8) percent of
income that goes in savings.
The full model (from the Omnibus test of model coefficients in Table 30) containing all
predictors was highly statistically significant, X2
(8, N=40) = 40.776, p< .001 indicating
that the model was able to distinguish between the respondents who reported or didn’t
reported difficulty while applying to micro loan (Kirkpatrick & Feeney, 2013).
Table 30: Omnibus Tests of Model Coefficients
Chi-square df Sig.
Step 1 Step 40.776 8 .000
Block 40.776 8 .000
Model 40.776 8 .000
The model as a whole was a good model as p>0.05 in Hosmer and Lemeshow Test and is
explained between 63.9% (Cox and Snell R square) and 87.1% (Nagelkerke R squared) of the
variance in difficulty status (Statisticalhorizons.com, 2015), and correctly classified 97.5% of
cases (See Appendix 6.2). As shown in the (Table 31) only two of the independent variables
made a unique statistically significant contribution to the model (difficulty while applying to
micro loan and percent of income spent on food and utilities). The strongest predictor of
reporting a difficulty in paying the loan amount with interest back was difficulty while
applying to micro loan, recording an odds ratio of 14981.5. This indicated that recipients
who faced difficulty while applying to micro loan were over 14981.5 times more likely to
report the difficulty in paying the loan amount with interest back than those who did
not faced difficulty while applying to micro loan, controlling for all other factors in the
model.

50
The odds ratio of 0.52 for percentage of income spent on food and utilities is less than 1,
indicating that for every additional percent of income spent on food and utilities
respondent were 0.52 times less likely to report the difficulty in paying the loan amount
with interest back, controlling for other factors in the model.
Table 31: Variables in the Equation
B S.E. Wal
d
d
f
Sig
.
Odds Ratio/ Exp(B) 95% C.I.for EXP(B)
Low
er
Upper
Ste
p
1a
1
Difficul
ty while
applyin
g to
micro
loan
9.61
5
3.52
4
7.44
2
1 .00
6
14981.525 14.9
80
14983475.7
79
2
Marital
status
4.09
4
2.74
2
2.23
0
1 .13
5
59.996 .278 12941.686
3
Childre
n
-
4.68
5
7.52
9
.387 1 .53
4
.009 .000 23639.353
4
Number
of
children
.845 2.32
5
.132 1 .71
6
2.329 .024 221.976
5
Percent
of
income
spent
on
educati
on of
children
-.534 .287 3.47
5
1 .06
2
.586 .334 1.028
6
Percent
of
income
spent
-.377 .223 2.84
9
1 .09
1
.686 .443 1.063

51
on
lodging
7
Percent
of
income
spent
on food
and
utilities
-.652 .318 4.20
1
1 .04
0
.521 .279 .972
8
Percent
of
income
recipien
ts save
-.553 .465 1.41
2
1 .23
5
.575 .231 1.432
Consta
nt
45.4
81
27.8
78
2.66
2
1 .10
3
5653659971911109000
0.000

52
Chapter 5: Conclusion
On the above findings, we observed that microfinance in North India is delivered mainly via
MFI’s and only to the female entrepreneurs who are below poverty line (BPL), through the
concept of Joint Liability Group (JLG) and supports the argument of Besley & Coate (1995)
in the literature that micro loans are disbursed and collected by the MFI’s through the notion
of JLG i.e. if one person in the group is defaulted on the micro loan then the whole group is
collectively defaulted and the responsibility is then imposed on the group to repay the micro
loan with interest (objective 1).
From the regression analysis of the whole sample, we observed that under 35 age group
(young entrepreneurs BPL) are over 3.8 times more likely to apply for micro loan than those
who are over 35 age group. However, few problems were encountered with the MFI’s in
North India (Objective 6). The MFI’s have very low outreach against the people BPL and
supports my sixth hypotheses that many people BPL are unware of MFI’s and service such
institutions offer. More than 90% of the non-microfinance respondents in the sample were
unware of the micro financing activities. Further, some respondents in the sample were
involved in the business of prostitution due to poverty and were unware of microfinance
services. Moreover, Top MFI’s of North India have reported only 2.46 million active micro
loan borrowers against the total of 67.4 million people BPL (objective 5).
Sapovadia (2007) argued in the literature that microfinance recipients face number of
difficulties in getting started supports my third hypothesis that microfinance recipients face
difficulty while applying to micro loan. 52% of microfinance recipients in the sample
reported difficulty of language barrier while applying to micro loan and due to which they
were also not unware of other services provided by MFI’s apart from micro loan. This is also
been proved by the chi square test. However, the results from independent t test shows that
this difficulty status has no relation with the savings i.e. recipients who face difficulty while
applying to micro loan are able to save almost same amount of income (generated by micro
loan) in comparison to the recipients who didn’t face any difficulty while applying to micro
loan.
Research also supports my fourth hypothesis that microfinance recipients faced difficulty in
paying the loan amount with interest back as 62.5% of the microfinance recipients in the
sample reported the difficulty of weekly loan repayment system through instalments to MFI’s

53
as week time is too less to generate profit from any business primarily for those who have
taken the loan for agricultural purpose as they can only generate profit during the cropping
season. Further, Chi square test and regression analysis have disclosed one important finding
that microfinance recipients who face difficulty while applying to micro loan also face
difficulty in paying the loan amount with interest back. However, no one in the sample gets
defaulted on the loan amount and opposes the argument of Hulme (2000) in the literature that
most of the microfinance recipients are not able to pay back their loan.
Yet, the overall impact of microfinance on poverty reduction and gender equality (in the
sense of women empowerment) turned out to be positive and supports my first and second
hypotheses in the research that microfinance promotes gender equality and has positive effect
on poverty reduction. As argued by Pitt & Khandker (1998) in the literature that MFI’s
majorly targets women entrepreneurs because women are more responsible compared to men
and spent significant part of their income on education and health care of their children. The
research supports this argument as the findings from the analysis reported that all the
microfinance recipients in the sample were female entrepreneurs who were BPL and they
spent a weighted, average of 41% of their earnings on the education of their children.
Further, females use MFI funding to start small budget lucrative businesses (objective 4) and
reflect positive change in their socio-economic conditions. More than 85% of the females in
the samples have reported positive change in their socio-economic conditions after taking the
micro loan (objective 2). Results from the independent sample t-test also reported that
married females tend to invest major portion of their income for the welfare of their family.
Moreover, results from the chi square test reported that microfinance recipients i.e. women
entrepreneurs will recommend the micro loan to other women entrepreneurs and will also
apply for the loan again either for the development of their existing business or to a start new
business. Therefore, for this reason top MFI’s of North India have reported an average loan
retention rate of 86% by the borrowers which supports my fifth hypothesis that micro loan
borrowers have high loan retention rate. These findings clearly reflect that microfinance has
played key role in poverty reduction and gender equality in the sense of women
empowerment in North India (Objective 3).
Finally in my view, microfinance in North India have few gaps in their functioning, though it
has played a key role in the poverty reduction, women empowerment and boosting the living
standards of the underprivileged. If few shortcomings mentioned above will be eliminated

54
from the MFI’s in North India, it would have direct affirmative impact on the economy of
India, lead to pronounced productivity and boost the living standards of the millions of poor.
5.1 Recommendations
 MFI’s can use network marketing strategy in order to increase its outreach in North
India. For example, they should give incentives (like zero loan processing fee in the
next loan) to the active micro loan borrowers for recommending the micro loan to the
underprivileged.
 MFI’s should deploy flexible loan collection method and it should differ from
business to business. For example, if the applicant has taken the loan for agricultural
purpose, his/her loan repayment through instalments should start during the cropping
season.
 MFI’s should take initiative in providing basic education to the micro loan borrowers,
at least to the level where borrower can read or write. This will reduce the difficulty
of language barrier (both verbal and written) for the borrowers while applying to
micro loan.
 Loan officers should use presentations and videos in the native language of the JLG
for explaining them the terms and conditions of the micro loan and other services
provided by MFI’s apart from micro loan so, that the borrowers can understand each
and every small things about their debt and utilise other bonus services provided by
MFI’s apart from micro loan.
 Management of MFI’s should deploy effective research strategy to find out the
females wo are involved in the business of prostitution due to poverty and reach them
to provide the rehabilitation services, funding etc. to kick start their new journey.
This will have direct impact in bringing the socio-economic change in North India.
 MFI’s should also consider male entrepreneurs who are BPL as the part of their
funding as many males BPL in North India are engaged in temporarily labour work
and looks for alternative way of earning. This will have the direct impact on the
economy of the country.

55
5.2 Future Scope
The Present research underlines the effectiveness of micro financing activities on the basis of
the sample of 100 respondents and top MFI’s of North India. Therefore, large sample size
considering the potential respondents and all the MFI’s of North India can be taken into
account for further analysis

56
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