Determinants of defaulting by collateral lending groups in micro financing

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(1)COPYRIGHT AND CITATION CONSIDERATIONS FOR THIS THESIS/ DISSERTATION. o Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. o NonCommercial — You may not use the material for commercial purposes.. o ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.. How to cite this thesis Surname, Initial(s). (2012) Title of the thesis or dissertation. PhD. (Chemistry)/ M.Sc. (Physics)/ M.A. (Philosophy)/M.Com. (Finance) etc. [Unpublished]: University of Johannesburg. Retrieved from: https://ujcontent.uj.ac.za/vital/access/manager/Index?site_name=Research%20Output (Accessed: Date)..

(2) Determinants of defaulting by collateral lending groups in micro financing. by. Katlego Ipeleng Modisagae. MINOR DISSERTATION submitted in partial fulfilment of the requirements for the degree. MAGISTER COMMERCII. in. FINANCIAL MANAGEMENT. in the. FACULTY OF ECONOMIC AND FINANCIAL SCIENCES. at the. UNIVERSITY OF JOHANNESBURG. SUPERVISOR: Dr Christo Ackermann CO-SUPERVISOR: Mrs Marise Mouton. November 2016.

(3) ABSTRACT The rural poor with no physical collateral typically have virtually no access to small business financing. The microfinance movement replaces physical collateral with social collateral as a means for rural poor persons to gain access to financing for their microbusinesses. Microfinance entails lending to self-formed groups of close-knit community members who are jointly liable for loans advanced to individual group members. Advantages include borrower screening by fellow group members, mutual assistance in micro-enterprises, monitoring repayment and imposing social sanctions to delinquent group members. Despite the use of group lending, Microfinance Institutions (MFIs) are still faced with the risk of default by borrowers and the absence of physical collateral means there is no recourse to borrower assets for repayment. Default on loans, which can be caused by characteristics of the lending groups themselves, has the undesirable effect of eroding the capital base of MFIs and threatening their continued existence. The main research problem is that MFIs are faced with borrower default that threaten their operational sustainability.. The main purpose of this study is to investigate the effect of group characteristics on the probability of borrower default. The characteristics of interest are: the age and gender of the borrower, group size, loan amount, instalment size, loan duration, loan cycle, location of group (rural or urban), business experience of the borrower, business savings, business assets, record of loan centre meeting attendance, family relations in a group and intra-group business risk correlation. The importance of this understanding will practically assist MFIs with insights regarding which factors to eliminate and which to enhance in the design of the groups to which they lend.. The probit regression model was used on secondary data from a loan programme at a large South African MFI. The key findings of the study indicate that probability of default decreases with larger groups, more female borrowers in a group and larger borrower savings. We also found that probability of default increases with larger loan. ii.

(4) amounts and with borrowers that have more business experience. Our recommendations to MFIs in light of the findings of our research are that the current practice in the MFI industry of lending to majority female borrowers should be maintained. Although we do not advocate specifically for increasing group sizes, we recommend that MFIs should endeavour to minimise situations where group sizes become smaller due to a member who has dropped out not being replaced speedily. The current practice of closely monitoring borrower savings records at repayment meetings should be maintained and continuously strengthened. This study found that default tends to increase with larger loan amounts and among borrowers with more business experience. We recommend that MFIs must have a feeder programme where borrowers whose businesses have become successful and larger can be passed on to bigger commercial banks instead of continuing to borrow from the MFI as part of a group lending scheme.. Keywords: Microfinance, Joint Liability Lending, Default, Probit Model.. iii.

(5) DECLARATION OF ORIGINAL WORK I, Katlego Ipeleng Modisagae, declare that this minor dissertation is my own unaided work. Any assistance that I have received has been duly acknowledged in the dissertation. It is submitted in partial fulfilment of the requirements for the degree of Master of Commerce at the University of Johannesburg. It has not been submitted before for any degree or examination at this or any other university.. ___________________. __________________. Signature. Date. iv.

(6) ACKNOWLEDGEMENTS This has indeed been a long process of learning, discovery and faith…a lot of faith. I would like to thank my family, friends, class-mates, consultants and lecturers for the motivation and support. I would also like to thank the staff at the Small Enterprises Foundation for their assistance in this project. Special mention needs to go to my supervisors (Mr. W Roets, Dr. C Ackermann and Mrs M Mouton) for their patience, advise and guidance throughout this process. To God be all the Glory!. v.

(7) Index Abstract……………………………………………………………………………………………………..….……………….ii Declaration of original work………………………………………………………………...…………….…………iv Acknowledgements…………………………………………………………..…………………………….………………v Table of contents………………………………………………………...…..…………………….………………………vi List of tables……………….……………………………………………………………………………………………….viii List of abbreviations…………………………….……………………………………………………….……………….ix. Table of Contents 1.. 2.. Chapter 1 – Introduction ................................................................................................................ 10 1.1. Introduction................................................................................................................. 10. 1.2. Background and overview of literature on loan default characteristics ........ 11. 1.3. The research problem and objectives .................................................................... 16. 2. Significance of the study............................................................................................ 17. 3. Research ethics ........................................................................................................... 18. 4. Outline of the study .................................................................................................... 19. 5. Conclusion ………………………………………………………………………………………………………………19. Chapter 2 – Literature Review ..................................................................................................... 21 2.1. Introduction................................................................................................................. 21. 2.2. Poverty in our modern-day global economy......................................................... 21. 2.3. Microfinance as a potential solution for poverty alleviation ............................ 24. 2.4. Understanding the lending model........................................................................... 25 2.4.1 The Grameen model reduces credit risk faced by MFIs .............................. 25 2.4.2 The group lending mechanism ................................................................................. 28 2.4.3 Four classical approaches of group lending ...................................................... 29. 2.5. Group characteristics and default ........................................................................... 31 2.5.1 Gender of the borrower ................................................................................................ 32 2.5.2 Group size ............................................................................................................................. 34 2.5.3 Age of the borrower ........................................................................................................ 35 2.5.4 Family relationships in a group ............................................................................... 35 2.5.5 Rural versus urban borrowers ................................................................................. 36 vi.

(8) 2.5.6 Availability of alternative sources of credit for the borrower ................ 36 2.5.7 Formalised group rules and group training ...................................................... 37 2.5.8 Borrower’s level of savings ......................................................................................... 37 2.5.9 Borrower’s prior business experience and current business income 38 2.5.10 Borrower’s level of education ................................................................................... 38 2.5.11 Business risk correlation among group members ........................................ 38 2.5.12 Loan size, repayment instalment and repayment period.......................... 39 2.5.13 Borrower’s record in attending loan centre meetings ................................ 40. 3. 2.6. Main propositions ...................................................................................................... 40. 2.7. Conclusion .................................................................................................................... 41. Chapter 3 – Research Methodology ............................................................................................ 42 3.1. Introduction................................................................................................................. 42. 3.2. Research strategy ....................................................................................................... 42 3.2.1 Research paradigm.......................................................................................................... 42 3.2.2 Sampling approach .......................................................................................................... 43. 3.3. Data collection............................................................................................................. 46. 3.4. Data analysis................................................................................................................ 49 3.4.1 Descriptive statistics for independent variables............................................ 49 3.4.2 Model of analysis .............................................................................................................. 50 3.4.3 Validity of the analysis instrument ........................................................................ 52 3.4.4 Reliability of the analysis instrument................................................................... 54. 3.5 4. Conclusion .................................................................................................................... 54. Chapter 4 – Results ........................................................................................................................... 56 4.1. Introduction................................................................................................................. 56 4.1.1 Reliability of the analysis instrument................................................................... 56. 4.2. Quantitative analysis of data for the Micro-Credit Programme (MCP) borrowers .................................................................................................................... 57 4.2.1 Descriptive analysis of the independent variables for the MCP programme .......................................................................................................................... 57 4.2.2 The probit model for MCP ........................................................................................... 60. 5. 4.3. Discussion of results .................................................................................................. 62. 4.4. Conclusion .................................................................................................................... 64. Chapter 5 – Findings, conclusion and recommendations................................................... 65 5.1. Introduction................................................................................................................. 65. 5.2. Rationale for undertaking this research................................................................ 65 vii.

(9) 5.3 Summary of the research ........................................................................................... 65 5.4. Recommendations ...................................................................................................... 68. 5.5. Limitations of the study............................................................................................. 69. 5.6. Opportunities for further research ......................................................................... 69. 5.7. Final conclusion .......................................................................................................... 69. References.................................................................................................................................................... 71 Bibliography ................................................................................................................................................ 80. List of Tables Table 3.1. Outstanding loans and total borrowers of South African MFIs reporting to MIX-market .................................................................................................. 45. Table 4.1. Reliability of the instrument: Cronbach’s Alpha Test ................................ 56. Table 4.2. Summary statistics for the MCP programme .............................................. 58. Table 4.3. Result of probit model for the MCP programme......................................... 60. Table 4.4. Marginal effects of the probit model on the MCP programme .................. 61. Table 5.1. Assessment of attainment of research objectives ..................................... 66. Table 5.2. Summary of marginal effects ........................................................................ 67. viii.

(10) List of abbreviations IFC. International Finance Corporation. ILO. International Labour Organisation. MCP. Micro-Credit Programme. MIX. Microfinance Information Exchange. MFI. Microfinance Institution. OLS. Ordinary Least Squares. PWR. Participatory Wealth Ranking. SEF. Small Enterprise Foundation. TCP. Tshumisano Credit Programme. UN. United Nations. WDB. Women’s Development Bank. ix.

(11) 1. Chapter 1 – Introduction 1.1 Introduction According to the World Bank’s 2011 Poverty Headcount Ratio indicator, 46.8% and 24.5% of the people in Sub-Saharan Africa and South Asia respectively live on under US$1.25 a day (World Bank, 2011). The situation in South Africa is also concerning; according to the 2011 census, the country’s population is reported as 51.8 million citizens with a poverty headcount of 56.8% (Statistics South Africa, 2012); the country’s unemployment rate as measured in the third quarter of 2014 is 25.4%, (Statistics South Africa, 2014). The 2008 / 2009 Living Conditions Survey carried out by Statistics South Africa indicates that approximately 26.3% of the country’s people were living on under R305 a month (measured between September 2008 and August 2009)(Statistics South Africa, 2011). The amount of R305 a month is termed in the report as the ‘food poverty line’ and defined as ‘the amount of money that an individual will need in order to consume the required energy intake’. The same report indicates that, when the international poverty line of US$1.25 a day is used, 10.7% of the population will fall under the poverty line. There is a dichotomy in that microfinance has a mandate to lend to the poor. This money can be used by the borrowers to fund the individual micro-enterprises that they (borrowers) have created and to lift themselves out of poverty. On the other hand, microfinance institutions (MFIs) must manage the collection of these debts carefully if they want to remain in existence. Collateral lending groups (also referred to as joint liability groups) help MFIs to reduce credit risks (the risk that the borrower will default on the borrowed funds) that they are faced with. Collateral lending requires that the borrower form a group with fellow borrowers where each borrower’s loan is guaranteed by fellow group members and where no future loans can be granted to any group member unless all members in the group have paid their outstanding loans (Stiglitz, 1990; Ghatak, 1999; Faridi, 2011). Group members are responsible for the screening, selection, monitoring, mutual support and payment enforcement of fellow group members. These activities 10.

(12) performed by fellow group members invariably reduce the costs associated with the lending activity on the part of the lender (Bhatt & Tang, 2002). The use of collateral lending groups with joint-liability is commonly referred to as the ‘Grameen model’ because of the pioneering efforts by the Grameen Bank of Bangladesh in designing group lending as a practice in the microfinance industry. Through the use of joint liability, collateral lending groups reduce the credit risk faced by MFIs while at the same time creating an opportunity for rural poor persons to gain access to credit. Poor rural persons, who are the typical clients of MFIs, are often credit-constrained due to their lack of physical collateral and the resulting high level of credit risk that this poses to the lender (Kugler & Oppes, 2005). The lack of collateral and the high credit risk renders it impractical for conventional financial institutions like retail banks to extend credit to the rural poor (Ross & Savanti, 2005) The purpose of this study is to identify, through a literature review, those characteristics of collateral lending groups that are most associated with default behaviour and then to determine statistically which of the identified characteristics are predictors of loan default. Secondary MFI data in South Africa will be used in order to understand which characteristics must be avoided by MFIs when designing lending groups. A great deal of effort is required to construct well designed joint liability groups and related lending contracts. Well-designed group lending schemes will ensure that group lending does indeed meet the expectation of limiting the risk of default faced by the lender. An understanding of the group factors which are highly associated with default behaviour will enable MFIs to avoid the prevalence of such factors among its joint liability groups and by so doing, reduce the probability of default. Low default rates will help to ensure the sustainability of MFIs and their ability to continue providing credit to the rural poor.. 1.2 Background and overview of literature on loan default characteristics. The probability of the repayment of a microfinance loan advanced to a customer is influenced by a wide variety of factors. According to Olomola (2000), default could be induced by factors related to external shocks like a disaster occurring in a borrower’s. 11.

(13) life. Some causes of default are factors under the direct control of the client, like a decision to use borrowed funds for personal consumption expenditure instead of investing in the micro-enterprise venture. Some factors contributing to default are linked to the MFI, for example, procedural delays in loan application processing and disbursements can cause cash flow difficulties for the borrower’s micro-enterprise (Olomola, 2000). Of particular interest in this study are factors, or more specifically the attributes or characteristics, related to the collateral group under which loans are advanced to the borrower. The design of a lending group in terms of the attributes characterising the group has an effect on the probability of default by the individual members of the group and indeed by the group as a whole. The attributes discussed in the reviewed literature can be summarised according to the following five themes: (i) borrower-related attributes (gender, age, effect of education on mobility and discipline in attending loan centre meetings); (ii) business skills-related attributes (business experience, prior business training by the MFI, effect of education on conducting business enterprise and business income); (iii) financing-related attributes (savings, alternative sources of credit); (iv) loan contract-related attributes (loan size, instalment size, loan cycle, repayment period, instalment collection frequency); (v) borrower group-related attributes (group size, family relationships, group setting – urban versus rural, business risk correlation). . Borrower-related attributes (gender, age, effect of education on mobility and discipline in attending loan centre meetings). Gender is one of the attributes that has been extensively studied by researchers. Females are found to be reliable repayers because their generally limited access to financing causes them to place greater reliance on future loans from the MFI (Armendariz & Morduch, 2005 cited in D’Espallier, Guerin & Mersland, 2011). In addition, females are found to be generally mutually supportive of each other, to like working in groups more than males (Musona & Coetzee, 2001) and to be more reactive to pressure from loan officers to repay (D’Espallier et al., 2011). Studies have, however, been conducted where MFIs with a predominantly male client base have managed to achieve good repayment rates (Richman & Fred, 2010). This then challenges the prevalent notion that males are likely to default. 12.

(14) Observations made regarding the age factor are that younger borrowers generally conduct micro-enterprises as a short-term activity while waiting for better employment prospects. Younger borrowers are more mobile, migrating from rural settings to urban areas for better jobs and a better social life (Oke, Adeyemo & Agbonlahor, 2007). Mobility is also related to education levels. Higher levels of education also increase employment prospects and the level of mobility of borrowers, resulting in higher dropout rates from the MFI and consequential default (Olomola, 2000). The attendance of loan centre meetings (where each group’s repayment performance is announced) is an important feature of most MFI group lending contracts in that a client’s fear of public humiliation is used to dissuade him / her from default. Thus, a client’s attendance of meetings is important and associated with higher repayment rates (Olomola, 2000). However, frequent meetings increase transaction costs for both the lender and the borrower and account for some of the drop-outs. The time spent attending meetings can be used productively in the microenterprise (Fischer & Ghatak, 2010). . Business skills-related attributes (business experience, prior business training by the MFI, effect of education on conducting business enterprise and business income). Borrowers with better levels of education make better business decisions, run better businesses and are thus better placed to repay (Bhatt & Tang, 2002). Borrowers with more business experience and prior business training by the MFI are better positioned to run better micro-enterprises, to be more successful in doing so and to consequently become better repayers (Roslan & Karim, 2009). Borrowers generating more business income are also better repayers (Gomez & Santor, 2003). . Financing-related attributes (savings, alternative sources of credit). Borrowers with limited or no alternative sources of credit are more reliable in repayment as their lack of other financing sources makes them dependent on the MFI’s loan (Kritikos & Vigenina, 2005). Borrowers with higher savings have a large resource base for emergency expenditure and are thus less likely to divert microenterprise funds for personal use in cases of disaster. Larger savings in a way also indirectly serve as collateral for the lender and can be used to settle the loan during 13.

(15) hard times. As a result, larger savings are associated with higher levels of repayment (Olomola, 2000; Ross & Savanti, 2005). However, the South African context is characterised by low levels of savings by households generally (Masilela, n.d.) and some of the bad savers still remain reliable in meeting monthly repayment obligations for their varying levels of unsecured lending. The Q3 2014 Consumer Credit Index Report issued by TransUnion (2014), a reputable local credit bureau agency, indicates that South African households are heavily indebted. Their estimated national household debt to financial institutions to disposable income is 73.5%. In compiling their Credit Index, 56.5 million consumer accounts were measured and only 3.6 million accounts were one month or more in arrears. . Loan contract-related attributes (loan size, instalment size, loan cycle, repayment period, instalment collection frequency). Default is often associated with larger loan amounts, bigger repayment instalment amounts and later loan cycles (all members of the group should have repaid amounts borrowed to them before another round / cycle of loans is given to them) (Armendáriz & Morduch, 2010). Larger loan amounts tempt borrowers to invest in riskier ventures (Madajewicz, 2004). Group dynamics in later loan cycles are different from initial loan cycles in that the levels of business success (and hence the riskiness) of group members may be different to such an extent that less successful members with lower loan amounts feel exploited when having to guarantee the larger loans of more successful members (Paxton, 1996 cited in Kritikos & Vigenina, 2005). More frequent collection of repayment instalments is widely associated with better repayment rates (Fischer & Ghatak, 2010). The economic realities of microfinance customers is such that there is an ever present temptation to use micro-enterprise profits towards day-to-day living expenses instead of making repayments. Frequent repayments instil some fiscal discipline and reduce the temptation faced (Yunus & Jolis, 2003 cited in Fischer & Ghatak, 2010). . Borrower group-related attributes (group size, family relationships, group setting – urban versus rural, business risk correlation). According to Abbink, Irlenbusch and Renner (2006), bigger group sizes create room for increased free-riding by group members who do not want to apply themselves in 14.

(16) their micro-enterprises. In-group coordination can be better achieved in smaller groups (Ghatak & Guinnane, 1999 cited in Abbink, et al., 2006) but larger groups have the advantage of having more voices to speak against a misbehaving member. Larger groups, however, can also find themselves in situations where each member neglects their monitoring and disciplinary duties under the presumption that these are performed by other group members. Despite all these factors, some large groups have been found to manage to maintain decent repayment rates (Guttman, 2007). Rural communities are typically more close-knit and better placed to impose social sanctions on defaulting members. Coupled with limited access to credit, rural borrowers are more likely to repay than urban borrowers (Kugler & Oppes, 2005). However, the South African context has urban townships with very close-knit communities placing them in a better position for reliable repayment. Borrowers tend to become less stringent when performing the screening function on relatives; thus having relatives in the same group is associated with higher levels of default (Sharma & Zeller, 1997 cited in Hermes, Lensink & Mehrteab, 2006). Microenterprises conducted as family-run businesses using MFI loans do in some instances have the extensive involvement of other family members who are themselves not MFI clients. Some of these family-run businesses do still, however, manage to achieve good repayment rates. Diversification of business risk could be perceived as a superior option where group members have formalised insurance agreements where members will assist a member who experiences business losses and that member will repay them later. Ahlin (2007) concludes that borrowers prefer group members with similar business risk because if one borrower fails, fellow group members are also likely to fail and will thus not be held liable for repayment. In other words, "groups anti-diversify in order to lower liability for their partners" (Ahlin, 2007). The author rightfully notes that this homogenous matching in terms of business risk in a group defeats the purpose of joint liability groups and places the lender in high risk should all businesses run by a group fail. This may prompt lenders to try to encourage business risk diversification while at the same time letting the groups to self-select in order to have homogeneity in terms of borrower (individual) risk.. 15.

(17) 1.3 The research problem and objectives Group lending has been identified as a key mechanism that can be used to reduce the probability of default when lending to the rural poor who lack collateral (Hermes et al., 2006). Despite the joint liability model being in extensive use in many countries, the model has been used to lesser proportions in South Africa. Similarly, the studies that have been undertaken to investigate the model in a South African context are limited and, to the researcher’s knowledge, no extensive studies on the effect of group characteristics in South Africa were detected. To this end, this study’s contribution will be in the form of increasing the understanding of group characteristics in reducing the probability of default. To this end the research problem is formulated as follows: MFI clients are considered highly risky by commercial banks and collateral group lending is intended to reduce the credit risk faced by MFIs when lending to such borrowers. Despite the use of group lending, MFIs are still faced with the risk of default by borrowers and the absence of physical collateral means there is no recourse to borrower assets for repayment. Default on loans, which can be caused by characteristics of the lending groups themselves, has the undesirable effect of eroding the capital base of MFIs and threatening their continued existence. The main research problem is that MFIs are faced with borrower default that threaten their operational sustainability. To this effect, this study will address the following main research question: Which group characteristics are predictors of loan default for collateral lending groups? In order to assist in answering the main research question, the following objectives will be addressed: . Identify through a literature review the most prominent group lending characteristics which could result in loan default; and then to. . determine which of the identified group characteristics are predictors of loan default through the use of the probit regression model. The probit model is a suitable type of regression model where the dependent variable is a 16.

(18) dichotomous variable. The detailed research design and methods applied in order to achieve the stated research objectives are discussed in Chapter 3. In this study, good groups (groups which are on schedule with payments) are compared to groups that are in arrears, regardless of the length of period of arrears. The study is quantitative in nature and the probit regression model is used to analyse secondary data obtained from the Small Enterprise Foundation (SEF), a leading and reputable South African MFI that has been engaged in lending to the poor since 1992. SEF was specifically selected through purposive sampling due to the relevance of its attributes to this study (the use of joint liability groups, serving the rural poor, majority of female clients, long operational experience in the microfinance industry in South Africa and the availability of reliable data on group loans).. 2 Significance of the study Group lending has been identified as an effective way of reducing the risk of default on microloans. Therefore, an understanding of the factors that lead to good rates is essential for MFIs. According to Godquin (2004) good repayment rates have the following benefits: they help ensure the sustainability of MFIs and their critical services to poor persons; help reduce the level of interest that the MFIs charge to borrowers which would in turn make microloans more accessible to an even larger number of poor borrowers; encourage donors to continue with the supply of funds to the MFIs and increase the overall profitability of MFIs and reduce their reliance on government or donor aid agencies. A further important factor about this particular study is that it indicates the group dynamics of the Grameen model in a firmly South African setting. The Grameen model is not as widely used in South Africa as it is in some other African economies and in other developing countries internationally. To the researcher’s knowledge, no direct study that investigates group characteristics has been undertaken in South Africa and the absence of an understanding of joint liability groups may be a contributor to the limited use of microfinance in South Africa.. 17.

(19) 3 Research ethics Any research project invariably involves ethical questions which need to be dealt with carefully in order to conform to ethical research practice (Saunders, Lewis & Thornhill, 2009). This research project involves using the information of individuals who are former and existing clients of SEF. The confidentiality of clients’ personal information is thus an important matter. To this end, it was made clear to SEF that the names, identity numbers or any other information that may lead to the identity of the borrowers being discovered would not be disclosed. SEF was also notified that they reserve the right to withhold any information whatsoever at their sole discretion and to later request that any information already disclosed must not be published or must be discarded. All SEF information was stored and processed in a manner that ensures that data security and confidentiality is strictly maintained (through the use of passwords). All communication with SEF personnel has been conducted in a polite and professional manner. The purpose of requesting the data and the manner in which the data was to be used was clearly and honestly communicated to SEF. All telephonic and face-to-face interviews (carried out at the initial stages of the research project to gain an understanding of the organisation and its operations) that were scheduled with SEF personnel were conducted at times that were convenient to them and in due consideration of their work responsibilities. No misconception was created with SEF regarding any possible ways that the research project could benefit the organisation. All costs associated with this research project were self-funded and thus the absence of a sponsor means there are no ethical issues relating to the involvement of a sponsor. A copy of this research report was also provided to the SEF for perusal prior to submission for assessment; this afforded SEF the opportunity to identify any misstatements of fact relating to their organisation and its operations. A written agreement was entered into between the researcher and SEF as the hosting organisation. The agreement contains standard terms and conditions that SEF normally provides to external researchers conducting research at the organisation. The key terms contained therein are that the researcher must provide SEF with the research proposal prior to commencement of research fieldwork; the researcher must provide SEF with a copy of the final research resport prior to 18.

(20) submission for assessment; meetings with staff and clients must be scheduled in advance and must coincide with already existing branch meetings were clients are to be interviewed. The researcher has complied with all the terms and conditions as set out in the research agreement. Admittedly, the avoidance of bias in analysing and reporting on research findings can become a difficult issue to the researcher. However, the presence of bias discredits research findings (Saunders et al., 2009). Therefore, all necessary efforts were made to ensure that research data was objectively assessed and reported.. 4 Outline of the study The remainder of this document is structured as follows: a detailed review of the literature on joint liability lending and default characteristics is conducted in Chapter 2. The chapter also contains a detailed discussion on the Grameen model of group joint liability lending, an overview of the microfinance industry in the modern-day global economy as well as a discussion of the significance of the present study. This is followed by a description of the research methodology in Chapter 3, which also addresses the important issue of ethical considerations. Chapter 4 contains the quantitative testing of the data collected for the study and a discussion of the test results while Chapter 5 contains the concluding remarks and mentions future research areas which are not specifically addressed in the study.. 5 Conclusion The aim of this chapter was to provide the background to the stated research problem, the formulation of the main research question and study objectives. Poor rural persons in South Africa and in many other countries in the world are faced with the problem of severely limited access to financial services, especially access to loans. The collateral group lending practice enables social collateral to be used in place for physical collateral that poor persons often lack; this then creates greater access to loan capital. MFIs who are providers of loan capital through collateral lending groups need to achieve good repayment rates in order to remain financially sustainable and to continue providing loans to borrowers. Default by customers on their loans is 19.

(21) problematic in that it erodes the capital base of the MFI and negatively affects its ability to continue providing loans to borrowers. Group characteristics and their contribution to default are an area of interest in this study. In this study, the aim is to identify through detailed literature review those group characteristics that may have an association with default and to statistically examine this association through the use of the probit regression model. The contribution from this research is to provide guidance to MFIs on which group factors to limit (because of their negative effect on repayment) and which to encourage (because of their positive effect on repayment).. 20.

(22) 2. Chapter 2 – Literature Review 2.1 Introduction This chapter commences with a review of poverty as a problem in our modern-day global economy. The scale of poverty in the world and in South Africa specifically is described using quantitative data from reports by the World Bank, the United Nations (UN), and amongst others, the International Finance Corporation (IFC). Microfinance is considered as one of the possible solutions to poverty alleviation. Bearing in mind that microfinance comes with the associated credit risks that stem from lending to the poor without collateral, the role of the Grameen model as a credit risk mitigation tool is discussed. The discussion on risk mitigation is enhanced by separate discussions about the intricate workings of the Grameen model and about the four classical models of group lending. The bulk of this chapter focuses on group characteristics that may lead to default on loans advanced to lending groups. This culminates in the identification of specific group characteristics that are investigated in the rest of this study and will form the basis of the statistical analysis.. 2.2 Poverty in our modern-day global economy Poverty still remains one of the greatest challenges facing the modern-day world. Despite many developments and advances in the global economy, in technology and its capabilities to introduce efficiencies in economic activities, the global community has still not managed to reduce the poverty and suffering of the world’s poorest to acceptably low levels. According to the World Bank’s 2011 Poverty Headcount Ratio indicator, 46.8% and 24.5% of the people in Sub-Saharan Africa and South Asia respectively live on under US$1.25 a day (World Bank, 2011).. The United Nations issued a report in 2012 that describes progress made on the Millennium Development Goals targets. The data included in the report indicates that, in addition to the 47% of people living in extreme poverty in Sub-Saharan Africa, 28% of the people in developing regions also live in extreme poverty. These figures are as 21.

(23) measured in 2008. In the introduction to the report, the UN’s Secretary General Mr Ban Ki-Moon highlights that the UN estimates that in 2015 almost 1 billion people worldwide will be living in extreme poverty (less than US$1.25 a day). The report also cites a study conducted by the International Labour Organisation (ILO) which indicates that out of all the people in the world living in extreme poverty, 456 million of them are actually employed (United Nations, 2012). The situation in South Africa is also concerning; the country’s population is reported from the 2011 census as 51.8 million citizens with a poverty headcount of 56.8% (Statistics South Africa, 2012); the country’s unemployment rate measured in the third quarter of 2014 is 25.4% (Statistics South Africa, 2014). The 2008 / 2009 Living Conditions Survey carried out by Statistics South Africa indicates that approximately 26.3% of the country’s people were living under R305 a month (measured between September 2008 and August 2009) (Statistics South Africa, 2011). The amount of R305 a month is termed in the report as the ‘food poverty line’ and defined as ‘the amount of money that an individual will need in order to consume the required energy intake’. The same report indicates that, when the international poverty line of US$1.25 a day is used, 10.7% of the population fall under the poverty line. The world’s poor are still faced with the challenge of a lack of access to financial services. The IFC’s (2012) report on their Microfinance Operations in Africa mentions that over 3 billion people in developing countries do not have access to financial institutions and that only between 5% and 25% of households in Sub-Saharan Africa have a formal relationship with a financial institution. The report further mentions that Sub-Saharan Africa’s MFIs constitute only about 2% of the world’s MFIs. The IFC correctly notes in the same report that ‘improved financial services are needed most in Africa’s poorest economies and countries emerging from conflict’. Microfinance Information Exchange (commonly referred to as ‘MIX’) is a non-profit organisation that collects, analyses, consolidates and reports on information about activity in the microfinance sectors across the globe. According to the MIX website (MIX, 2011), as at 28 September 2011, there were 92.2 million microfinance borrowers across the world served by approximately 2 000 MFIs reporting to MIX with a total gross loan portfolio of US$65.2 billion. The sheer scale of demand for microfinance services is a glimpse of the important role that MFIs play in creating 22.

(24) access to financial services for the poorest members of the global community. It is, however, important to note that only those institutions that voluntarily report their information are included in the MIX data set and thus the MIX statistics do not purport to cover the entire global microfinance industry. The mismatch in the reported microfinance borrowers (even after accounting for borrowers not captured by MIX statistics) and the number of people living in extreme poverty as indicated by the various statistics in the preceding paragraphs strongly suggests that there is even greater need for microfinance services. The issue of financial access in South Africa is also significant and is continuously receiving government attention. The importance of the issue of financial access in the country is captured in the following quote taken from an address made by Mr Pravin Gordhan (then Minister of Finance) at the Alliance for Financial Inclusion Global Policy Forum in Cape Town (Gordhan, 2012:3): In South Africa, financial inclusion plays a vital role in the on-going transformation and development of our society, and our desire to improve the lives of our people. In our efforts to boost economic growth, improve economic opportunities and promoting equality of opportunity, financial inclusion is of vital importance. The ability to use a transactional account to purchase goods and services, a savings account to preserve wealth, credit to increase productive capacity or improve the quality of life, and to use insurance services as a bulwark against unforeseen events and risks, can go a long way in facilitating a better life for the poor. The microfinance industry does of course have a pivotal role to play in the quest to ensure that the many poor persons across the globe have access to ethical lending services. This helps in protecting the vulnerable poor from highly unethical practices that are particularly prevalent across the developing world. The practices include, according to Mashigo (2012), the charging of exorbitant interest rates, the use of violent mechanisms by the lender to ensure repayment, the lending of high loan amounts where clients cannot realistically be expected to afford to repay (Kelly-Louw, 2008), the retention of critical items (like the borrower’s identity document) as a form of security, etc. Due to their desperation to access funds, the vulnerable poor often find themselves borrowing from these unethical lenders (sometimes referred to as ‘loan sharks’) and as a consequence, get subjected to the afore-mentioned abusive practices (Mashigo, 23.

(25) 2012). Furthermore, the unethical lenders have little interest in the improvement of the lives of the borrowers; theirs is essentially a money-making quest. This often leads to borrowers getting trapped by loans in a never-ending cycle of debt (Mashigo, 2012). Regulated MFIs lend at rates that are much lower than those of loans sharks (Goodwin-Groen, 2002), do not lend recklessly (more than what the borrower can afford to repay), use legal and ethical means to collect repayment and are concerned with social performance management (ensuring that their services do improve the lives of their borrowers) (Di Leo, 2012).. 2.3 Microfinance as a potential solution for poverty alleviation MFIs were created to serve the poorest of the poor through the provision of much needed financial services. The services provided include microcredit, savings facilities, micro-insurance and other similar services designed to meet the needs of MFI clients (Microfinance Gateway, 2011). The client base targeted by MFIs typically consists of persons who are poor, not formally employed, have been without formal employment for lengthy periods of time and are mostly based in remote rural areas. According to Armendáriz and Morduch (2010), commercial financial institutions typically find serving this particular market to be an expensive and loss-making venture. The costs associated with reaching remote villages and offering large volumes of low-value loans and products would makes serving this client base unprofitable from a commercial perspective. This then results in such clients being excluded from access to basic banking products such as savings accounts, microloans, micro-insurance and other basic financial service products (Naveen & Veerashekharappa, 2011). MFIs were thus established mainly as non-profit organisations that mostly relied on donor funds or government subsidies to carry out their operations. The mandate of these institutions broadly entailed the provision of financial services to poor communities found primarily in rural areas (Faridi, 2011; Lutzenkirchen, 2012). The rationale for wanting to enable the poor to have access to such services is that access to microfinance services is regarded as a useful tool in the process of propoor development (developing the lives and economic situations of poor persons and communities). The provision of microfinance services to poor communities has been 24.

(26) dubbed as one critical element that, when properly applied, can contribute significantly to improving the lives of the poor (Dehejia, Montgomery & Morduch, 2005). In particular, the provision of microloans to poor clients with the intention of assisting them to establish and maintain micro-enterprise ventures is one of the celebrated features of microfinance. These micro-enterprises enable microloan clients to generate income and improve living standards for themselves and their families (Armendáriz & Morduch, 2010). From a credit risk perspective, however, the provision of loans to poor clients is problematic. This is because these clients do not have collateral or regular employment income that can be used to settle loans and, more often than not, do not have a verifiable credit history that can be partly used as a predictor of future repayment behaviour. Roslan and Karim (2009) also make the observation that those prospective clients who already have a micro-enterprise at the time of approaching the MFI for a microloan would typically not have proper financial records for their micro-enterprises.. 2.4 Understanding the lending model 2.4.1 The Grameen model reduces credit risk faced by MFIs. To address the problem of the absence of collateral and to overcome the information asymmetry problem (that of not having sufficient information to assess the creditworthiness of prospective clients), a popular lending practice known as the ‘Grameen model’ was developed. Under this model, loans are not granted to independent individual clients; instead clients are required to be part of a borrowing group with other individuals who are also borrowers. A borrowing group typically consists of five members. Key requirements regarding the formation of a borrowing group are that clients self-select fellow group members and group members are normally people from the same village, community or other social grouping and are thus people who know each other well (Armendáriz & Morduch, 2010). Under the group lending model, each individual in the group receives a microloan but the group members are jointly liable for each individual’s loan. In cases where a particular member fails to repay his / her loan, the other group members would not 25.

(27) qualify for further loans until they have settled their own loans and that of the member who has defaulted (Faridi, 2011). Furthermore, the size of subsequent loans granted to borrowers increases with each loan cycle. This dynamic incentive of progressive lending is intended to make the prospect of receiving a subsequent loan attractive to the borrowers (Armendáriz & Morduch, 2010). By allowing community members (who know each other well) to select fellow group members, the MFI is effectively transferring the credit risk screening function to the group members. Furthermore, because group members stand as surety for any member who defaults, they have an incentive to monitor fellow group members to ensure that they do not default on their loans (Ghatak, 1999; Naveen & Veerashekharappa, 2011). The Grameen model was pioneered by Professor Muhammad Yunus of the Grameen Bank in the mid-1970s in rural Bangladesh (Armendáriz & Morduch, 2010). The term ‘Grameen Bank’ itself means ‘Village Bank’ (Yunus, 2013). The model has since gained a lot of popularity because of its perceived strength in limiting the probability of loan defaults (by transferring the credit risk screening and borrower monitoring from the MFI to the borrowers themselves). Today, the microfinance industry has expanded to enormous proportions, serving millions of poor, credit-constrained persons across the globe. To recognise Professor Yunus’ and the Grameen Bank’s pioneering efforts, both were jointly awarded the Nobel Peace Prize in 2006. The 2006 Nobel Prize occurred just a year after the United Nations declared 2005 as the International Year of Microcredit (Ahlin, 2007). Other pertinent features of the Grameen model are that individual loan values are generally small (e.g. average loan of R1 500 per client) and repayments occur on a more frequent basis (mostly occurring weekly) than is normally the case in commercial bank loans. Loan values are initially very low and increase with each loan cycle that the client completes (progressive lending). The collection of loan repayment amounts on a weekly basis (or other frequent bases) is perceived to instil some ‘fiscal discipline’ in the borrowers. This helps limit the borrowers’ temptation to divert the repayment amounts to day-to-day living expenses (Yunus & Jolis, 2003 cited in Fischer & Ghatak, 2010).. 26.

(28) Weekly loan repayments are done at loan centres where the repayment performance of each group and each client are announced (Ghatak, 2002). A loan centre is a common administrative meeting place where several groups assemble for such activities as the disbursement of loans by the MFI’s loan officers, the collection of repayment instalments, the approval of new groups, etc. The intention with collecting repayment instalments at loan centres is to use a client’s fear of public humiliation to shape positive repayment behaviour (Kugler & Oppes, 2005). The majority of MFIs prefer to disburse production loans (loans intended to assist the client to finance a micro-enterprise) instead of consumption loans (loans used to finance daily living expenses and acquisition of non-productive assets) (Bond & Rai, 2002). One matter that is of paramount interest in the Grameen model discussion is how Professor Mohammed Yunus himself explains the issue of joint liability. In a public lecture delivered at the University of Johannesburg on 3 October 2013, Professor Yunus indicated a key discrepancy in how the Grameen model has been widely interpreted in academic literature. He indicated that the Grameen model, as practiced by the Grameen Bank itself, does not operate on joint liability lending, as widely understood. The Grameen Bank’s model does require borrowers to form a group of five members and that the five members must self-select and know each other well. He indicated that the group operates as a key social structure where members can support each other not only in running their individual micro-enterprises but also in achieving certain social goals. These social goals are defined by the Grameen Bank as the ‘16 decisions’ and include among them objectives like achieving good nutrition, good domestic dwellings, good health, good sanitation, environmental cleanliness, social justice, education and other social benefits for the members and their families (Grameen Bank, 2013). He indicated that fellow group members are not specifically required to pay the loan of a member who defaults. Although the Grameen Bank does not make use of the joint liability element as indicated by Professor Yunus, many other entities described in literature that use the Grameen model have a joint liability element to the group. The SEF in South Africa also uses the Grameen model with a joint liability element.. 27.

(29) 2.4.2 The group lending mechanism The formation of borrowing groups with joint liability and a threat of future denial of credit are intended to operate as ‘social collateral’ which serves as a substitute for physical collateral while at the same time helping to overcome the information asymmetry problem (Conning, 2000 cited in Naveen & Veerashekharappa, 2011). Clients are jointly liable for unpaid loans of fellow group members in the case of default and each group member is also assumed to find it important to receive further loans to refinance his / her micro-enterprise. It is therefore in each member’s best interest to select fellow group members who are considered to be good with making their loan repayments as and when they become due. Because the clients have detailed knowledge about their neighbours with whom they intend forming a borrowing group, it is a far easier exercise for them to assess the reliability of fellow group members in making loan repayments than it is for the MFI. The use of information residing with individuals in communities overcomes the information asymmetry problem (Ghatak, 1999). When clients make use of the information that they have about their community members to self-select fellow group members, a process of ‘assortative matching’ typically occurs. This is a process whereby a good applicant will not want to be in a group with a bad applicant as this will increase his / her cost of having to repay the loan of a fellow group member who has defaulted. This process culminates with ‘good’ applicants being paired with applicants of a similar risk profile and ‘bad’ applicants being paired with ‘equally bad’ applicants (Armendáriz, 1999 cited in Kugler & Oppes, 2005). However, there still remains the risk that, with the process of assortative matching, a group may be formed that consists only of risky (bad) clients. To mitigate the risk of this happening, MFIs also often require that each new group must be approved at loan centre level before loans can be disbursed. During the group formation stage, a process of peer-screening takes place when the clients use local information to assess potential fellow group members. Without the peer-screening function and faced with the information asymmetry problem, the MFI would have to resort to adverse selection. This is a practice of charging universal high interest rates to compensate for the fact that the MFI cannot differentiate between low credit risk and high credit risk clients (Armendáriz & Morduch, 2010). 28.

(30) Once the borrowing group is in existence, a process of peer-monitoring and peerenforcement needs to continually take place in order to overcome various moral hazards. Peer enforcement recognises the fact that group members, because of their close social associations with one another, are able to institute several social sanctions against group members who are in default (Bond & Rai, 2002). Typical moral hazards include the risk that the client may divert the loan funds to other purposes other than the micro-enterprise operations or that the profits generated from the micro-enterprise may be diverted into other causes instead of repaying the microloan (Simtowe & Zeller, 2006). Moral hazards also include the risk that the applicant may not apply their best efforts in conducting their micro-enterprise and thus create the risk that not enough profits will be generated to cover loan and interest repayments (Armendáriz & Morduch, 2010). Again, group members are incentivised by joint liability and the risk of not getting future loans to effectively monitor each other and to assist each other to ensure that every group member can meet their loan repayment obligations. The combination of the above social factors (the screening of fellow borrowers, careful selection of fellow group members, the ability of group members to impose social sanctions on members in default and the fear of public humiliation of members not repaying) results in the ‘social collateral’ which serves as a collateral substitute for physical collateral (Bond & Rai, 2002).. 2.4.3 Four classical approaches of group lending Four leading historical papers on microfinance provide interesting insights into the operation of the group lending mechanism. The 1990 paper by Stiglitz and the 1994 paper by Banerjee, Besley and Guinnane both consider joint liability lending from a moral hazard perspective. Besley and Coate’s 1995 paper considers joint liability lending under conditions of limited contract enforcement while Ghatak’s 1999 paper considers adverse selection and its impact on joint liability lending.. Stiglitz argues that, when borrowing individually, borrowers are tempted to choose riskier projects that would enhance business returns. However, when a borrower is in a joint liability contract, fellow group members are there to ensure that each project 29.

(31) chosen is of a reasonable risk profile. Stiglitz (1990) notes that the lender does not normally have direct means of ensuring that the borrower uses good discretion and puts the borrowed funds into good use. This then means that the borrower can subject the borrowed funds to abnormally high levels of risk and, in so doing, compromise his / her ability to repay the borrowed funds. Stiglitz notes that this problem can be solved through the creation of joint liability groups. This results in the monitoring function being performed by a fellow group member and, because of the very fact of joint liability, that fellow group member pays a penalty where they do not perform the monitoring function appropriately. The prospect of receiving future loans from the lender acts as an incentive that further encourages group members to carry out their monitoring functions. Banerjee et al. (1994), similarly to Stiglitz, also view joint liability lending from a moral hazard perspective. Their paper analyses joint liability groups by considering two alternate views that may explain the effectiveness of group lending. The first view is the peer-monitoring view that was explored by Stiglitz above (granting fellow group members incentives to monitor each other and imposing a penalty where monitoring is not performed effectively). The alternate view is a sociological view that recognises the severity of social sanctions that members can impose on a member who defaults and hamper their prospects of obtaining further loans. Similarly to Stiglitz, they also attribute the strength of group lending to the members’ ability to effectively monitor each other. Besley and Coate (1995) focus on repayment decisions made by borrowers. They do this by creating repayment games where the participant’s decision to repay the loan or not is observed and the influencing factors are noted. In their repayment game, they observe repayment decisions made by individual borrowers and also by joint liability borrowers. A further element that they consider is the effect of social collateral on the decision to repay. As Besley and Coate (1995:2) note: Under an individual lending contract, all the borrower has to fear, if he defaults, is the penalties that the bank can impose on him. Under group lending, he may also incur the wrath of other group members. If the group is formed from communities with a high degree of social connectedness, this may constitute a powerful incentive device, since the costs of upsetting other members in the community may be high.. 30.

(32) The writers conclude that although group lending is a good repayment incentive (because of the insurance effect that borrowers offer each other), it may also lead to a bad repayment equilibrium where all members in a group strategically default even if some individuals would have repaid had they not been part of a group. The writers also observe that the addition of potential social sanctions (by fellow group members) makes joint liability a superior lending model. In the final classical paper, Ghatak (1999) considers adverse selection and its effect on joint liability lending. Joint liability lending is considered to be a superior lending contract type because the lender is able to exploit the information that community members have about each other. The process of self-selection into groups compels community members to use information they have about each other to form groups. This results in positive assortative matching where safe borrowers only want to be in a group with other safe borrowers. Ultimately, this enables the lender to extend loans to borrowers who would otherwise not have been able to secure such loans as individuals.. 2.5 Group characteristics and default At an operational level, group joint liability lending is widely perceived to be a successful invention and this is mainly due to the fact that many MFIs across the world have been able to achieve excellent repayment rates. To this end, a wide range of studies have been conducted to understand the reasons why these MFIs have managed to achieve excellent repayment rates, or inversely, what are the factors that may lead to default on microloans. These studies are discussed below.. Olomola (2000) categorises the factors that may lead to default as falling into four groups: borrower-related causes, loan-use related causes, lender-related causes and external factors. An example of borrower-related causes would be a borrower falling sick and his or her illness leading to default while an example of loan userelated causes would be the diversion of borrowed funds to consumption expenses. An example of lender-related causes would be late pay-out of approved loans by the MFI creating a cash flow constraint in the borrower’s micro-enterprise and leading ultimately to default. External factors could for example include natural disasters that affect the business of the borrower, consequently leading to default. 31.

(33) In addition to Olomola’s four categories above, there are also factors related to the design of the loan contract itself such as the loan amount and the repayment period of the loan (Roslan & Karim, 2009) as well as factors relating to the structural design of the borrowing group. A review of the literature on factors related to the design of the group reveals a number of group characteristics that have a varying effect on the probability of repayment. The wide-ranging factors include items like the size of the group itself in terms of number of members, the gender of borrowers, the level of education of group members, the age of group members, the size of the loan taken by borrowers, the record of attendance of loan centre meetings, etc.. 2.5.1 Gender of the borrower The gender of borrowers is probably the most widely researched characteristic in the group characteristics mentioned above (Maclean, 2010; D’Espallier et al., 2011; Faridi, 2011; Perez, 2012).This is related to the fact that most MFIs proudly publicise the fact that the majority of their clients are females. As already indicated in sections above, SEF in South Africa states in its annual report for the year ended 30 June 2014 that its client base during each financial year over the period July 2009 to June 2014 was consistently composed of 99% females. This practice is also similar in other parts of the world, as indicated in the 2011 study by D’Espallier et al. in which a global data set collected for an 11-year period covering 350 MFIs located in 70 countries was used. An analysis of their data set indicated that 73% of the clients served by the MFIs concerned were females.. One of the main reasons for aiming microfinance services at female borrowers is that practitioners are mostly of the view that females are more likely to make economic choices that will ultimately benefit the family more than males would. As primary caregivers, women are more inclined than males to spend on the welfare of children (Young, 2010). Other reasons are that females are often poorer than males, are often paid less in job markets and have lower chances of accessing employment opportunities than males (Faridi, 2011). Females often contribute lower levels of income to the family and, as a result, have lower bargaining and decision-making power in the family unit. The granting of microcredit would increase their income contribution to the family, thereby helping to achieve gender equality by increasing 32.

(34) the bargaining and decision-making powers of female borrowers (D’Espallier et al., 2011; Faridi, 2011). The above factors are often seen as legitimate reasons, from a development economics perspective, for targeting microfinance and other development tools more towards females than males. Furthermore, female borrowers are perceived as being more reliable in repaying their microloans than male borrowers and hence microfinance schemes would largely target female clients in a quest to keep default rates lower. This is, for example, consistent with the 2009 findings of Opoku et al. (cited by Richman & Fred, 2010) that an increase in the level of female clients improves repayment and retention rates for the MFI. Female borrowers are more reliable in making microloan repayments for several reasons. Firstly, women have less access to credit facilities than men (Bhatt & Tang, 2002). This then means that they would generally place greater value on the ability to receive any future credit. This incentive motivates female borrowers to make scheduled loan repayments in order not to be denied future credit by the MFI. This view is supported by the results of a study by Bhatt and Tang (2002). The study was conducted in the United States where state welfare grants are widely available to socio-economically vulnerable females. The availability of state welfare grants presents another avenue where female grant recipients can access funds and lower their incentive to make MFI microloan repayments. As a second reason, female borrowers are found to be less aggressive in taking business risks, meaning that they will mostly invest borrowed funds in safer microenterprise ventures and consequently be able to meet repayment obligations (D’Espallier et al., 2011). The third reason for females’ superior loan repayment performance is that, as found by Musona and Coetzee (2001) using a focus group discussion methodology, males do not like working in groups, especially with women in the group. The dislike of working in groups exhibited by male borrowers would increase default and drop-out rates. A further reason contained in Bhatt and Tang (2002) is that women are more supportive of each other in times of difficulty, meaning that they are able to exploit the ‘mutual support’ feature of joint liability groups. Women’s support of each other in times of difficulty means that they stand a better chance of surviving difficult times 33.

(35) and thus continuing to make loan repayments. D’Espallier et al. (2011) bring another interesting dimension connected to the behavioural aspect of female borrowers. The authors note that female borrowers are more sensitive to pressure exerted by loan officers and are thus more likely to make repayments when pressured to do so by loan officers. To further explore the gender effect, Richman and Fred (2010) noted that the scales in the MFIs that they studied in Ghana were reversed because the majority of MFI clients appeared to be males. Richman and Fred thus decided to measure the effect that a larger male client-base has on the sustainability of an MFI. Their findings were in contrast to the notion expressed above that females are better repayers. Their econometric tests applied to survey data from MFIs in Ghana revealed that an increase in male clients leads to an improvement in repayment rates. This then creates a situation of conflicting views regarding the gender repayment differences.. 2.5.2 Group size The size of the borrowing group has also received a fair amount of attention in academic research on microfinance. Stiglitz (1990) suggests that when a member who is part of a large group defaults, the individual contributions by the remaining members to cover the amount in default would be insignificant. In other words, larger groups have a better insurance effect than smaller groups. This therefore means that members of a large group do not have a strong incentive to monitor fellow group members as the cost to each of them in the event of a fellow group member’s default is low. Abbink et al. (2006) also make similar observations that larger groups have a better insurance effect. In the same research article, Stiglitz notes the possibility that larger borrowing groups can find themselves in a situation where each member thinks that the other members will carry out the enforcement function and no enforcement ends up taking place. This would then lead to a collectively weakened peer monitoring mechanism in a group. Smaller groups, however, have the advantage that in-group coordination can be achieved more easily than in larger groups (Abbink et al., 2006). An alternative view is that larger groups may have the benefit of having more voices to speak against a misbehaving member and this may well be an aid to improved repayment.. 34.

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