Microfinance as a driving force for socio-economic development in emerging economies. Measuring its effectiveness in North India

Masterarbeit , 2015 , 82 Seiten , Note: A2

BWL - Wirtschaftspolitik

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.

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.

Table of Contents

Chapter 1: Introduction
1.1 Definition of microfinance
1.2 Why India
1.3 Why North India
1.4 Microfinance delivery models in North India
1.5Aims and Objectives of the research
1.6 Summary

Chapter 2: Literature Review
2.1 Introduction
2.2 Micro Finance Loans and their uses
2.3 International Evidence
2.4 Indian Evidence
2.5 Scope of Research and Possible Contribution
2.6 Some Possible Research Hypothesis

Chapter 3: Methodology
3.1 Research Philosophy and Approach
3.2 Research Strategy
3.3 Data
3.4 Methods of data analysis
3.5 Limitations

Chapter 4: Findings and Analysis
4.1 Analysis of the whole sample
4.2 Analysis of the sample of non-microfinance respondents
4.3 Analysis of the sample of microfinance recipients
4.3.1 Chi- Square Test with cross-tabulation
4.3.2 Independent- Samples T-Test
4.3.3 Binary Logistic Regression

Chapter 5: Conclusion

5.1 Recommendations

5.2 Future Scope

Bibliography

Appendices

1. Questionnaire

2. KBS Research Ethics Form

3. Confirmation for Ethics Approval

4. Chi-Square Test

5. Independent sample T-Tests

6. Binary Logistic Regression

7. Custom Report Generated from MIX Market

8. Mean income spent by the microfinance recipients

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

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.

List of Tables and Figures

Table 1: Survey Data

Table 2: Omnibus Tests of Model Coefficients table

Table 3: Variables in the Equation table

Table 4: Cross tabulation: profession * microfinance awareness among the non-microfinance respondents

Table 5: State wise people below poverty in North India

Table 6: Active micro loan borrowers in the top MFI's of North India

Table 7: Percent of female borrowers in top MFI's of North India

Table 8: Cross tabulation: gender * survey data of 40 microfinance recipients

Table 9: Cross tabulation: difficulties while applying to micro loan * microfinance services awareness

Table 10: Cross tabulation: purpose of taking micro loan * difficulties while paying the loan amount back

Table 11: Types of business undertaken by microfinance recipients

Table 12: Meaning of social conditions in the opinion of microfinance recipients

Table 13: Social conditions of the microfinance recipients before and after taking micro loan

Table 14: Meaning of economic conditions in the opinion of microfinance recipients

Table 15: Economic conditions of the microfinance recipients before and after taking the micro loan

Table 16: Recommendations regarding micro loans by microfinance recipients

Table 17: microfinance adds value or not? In the opinion of the microfinance recipients

Table 18: Purpose of microfinance recipients for applying micro loan again

Table 19: Borrowers loan retention rate in top MFI's of North India

Table 20: Cross tabulation: difficulty faced while applying to micro loan* microfinance services awareness apart from micro loan

Table 21: Cross tabulation: difficulty faced while applying to micro loan* difficulty in paying the loan amount with interest back

Table 22: Cross tabulation: would respondents recommend the micro loan to other people* would respondents apply for the micro loan again

Table 23: Cross tabulation: difficulty faced while applying to micro loan * would you apply for the micro loan again

Table 24: Cross tabulation: difficulty in paying the loan amount with interest back* would respondents recommend the microfinance loan to other people

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

Table 26: Group statistics

Table 27: Group statistics

Table 28: Group statistics

Table 29: Group statistics

Table 30: Omnibus Tests of Model Coefficients

Table 31: Variables in the Equation

Figure 1: Mean percentage wise spending of income by microfinance recipients

List of Acronyms

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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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Table 1: microfinance vs conventional banks (Source: Avineet, 2010)

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 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.

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.

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.

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 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 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 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 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 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.

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 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).

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 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.

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

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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

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

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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.

Table 3: Variables in the Equation table

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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

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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

[...]

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^[1] Barnes et al, impact of three microfinance programs in Uganda, 2001.

^[2] Simonwitz, appraising the poverty outreach of microfinance.

• Hochschule: University of Limerick (Kemmy Business School)
• Veranstaltung: MSc in Financial Services
• Note: A2
• Autor: Kumar Deepam (Autor:in)
• Erscheinungsjahr: 2015
• Seiten: 82
• Katalognummer: V310204
• ISBN (eBook): 9783668091153
• ISBN (Buch): 9783668091160
• Sprache: Englisch
• Schlagworte: microfinance, measuring, north, india