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Optimal microfinance loan size and poverty reduction amongst female entrepreneurs in Pakistan Samia Mahmood
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Finance, Accounting, Systems and Economics Department, Business School, University of Wolverhampton, Wolverhampton, UK
Javed Hussain Business School, Birmingham City University, Birmingham, UK, and
Harry Z. Matlay Business School, University of the West of Scotland, Hamilton, UK Abstract Purpose – The purpose of this paper is to explore the impact of microfinance loans on poverty reduction amongst women entrepreneurs in Pakistan. The authors set out to establish whether there exists an optimal loan size to attain the objectives of women entrepreneurs and poverty reduction in this country. Design/methodology/approach – This exploratory study is based upon an empirical investigation of 123 semi structured interviews as well as in-depth, semi structured interviews with a sub sample of ten women entrepreneurs who secured microfinance loans for their new or established enterprises. Findings – Emergent results show that access to finance is important for female entrepreneurs and helps them realise their potential as entrepreneurs. An optimal, poverty reduction, microfinance size has been identified. A range of entrepreneurial characteristics were found to be critical to the success of women led enterprises in general and to poverty reduction amongst their families in particular. Research limitations/implications – This research focuses upon a relatively small sample of female entrepreneurs operating in the Pakistani economy. Although the results could be relevant to women entrepreneurs in other developing countries, caution should be exercised when attempting to generalise these finding to other contexts. Originality/value – Emergent results make a contribution to research on women entrepreneurship in general and optimal microfinance loan size in particular. Keywords Pakistan, Education, Microfinance, Family health, Household income, Poverty reduction, Women entrepreneurship Paper type Research paper
Introduction The global shift in gender dynamics indicates that “women capital” is increasingly important for the socio-economic and political development of emerging economies. This proposition is supported by Minnite et al. (2005) who claim that women’s entrepreneurial activities are central to promoting regional development and economic growth in both industrially developed and developing countries. It is therefore imperative for governments in emerging countries, such as Pakistan, to offer favourable financial and economic environments for women entrepreneurs (Roomi and Parrott, 2008). It should be noted, however, that in emerging economies women entrepreneurs often lack collateral and therefore access to microfinance loans and related support (Kobeissi, 2010). In response to this widespread disadvantage, various development initiatives programmes were introduced over the years to mitigate this gender-related barrier to entrepreneurship. Amongst these, the most popular and accessible is microfinance.
Journal of Small Business and Enterprise Development Vol. 21 No. 2, 2014 pp. 231-249 r Emerald Group Publishing Limited 1462-6004 DOI 10.1108/JSBED-03-2014-0043
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In its various forms, the concept of microfinance has been around for centuries, but more recently its apparent success in various countries has added to its growing popularity. Importantly, microfinance institutions (MIs) provide modestly sized loans to women who do not have access to formal finance (Haque and Harbin, 2009). Generally, microfinance is used to support income generating activities that provide exit and/or “breakout” strategies from poverty and various forms of discrimination. It is widely recognised that poverty is a complex, interlinked and involved phenomenon that cannot be considered in isolation or measured in terms of monetary value alone. According to United Nation Development Program (2008, p. 13) “[y] lack of access to essential resources goes beyond financial hardship to affect people’s health, education, security and opportunities for political participation”. Poverty is traditionally defined as lack of income, assets and/or resources, but recent studies recognise that it also includes issues related to dignity and autonomy. Assessing poverty is a challenge and qualitative approaches are often used to identify individuals’ own criteria and to develop strategies and solutions for poverty reduction. This approach to poverty (Cagatay, 1998, p. 6) has “far reaching implications for analysing the general nature of poverty as well as the relationship between gender inequalities and overall poverty levels”. The United Nation Developing Programme (2008) measurement of human poverty focuses on capabilities, such as clean water, health services and levels of literacy. This approach attempts to reconcile capability with absolute and relative poverty. Therefore, a linkage between gender inequality and poverty is established, with a focus on differences in education, health, life expectancy and socially constructed constraints on the entrepreneurial choices of various groups, such as women or lower castes. Women’s deprivation is an important aspect in the study of poverty alleviation due to the size of the population and the critical role they play in the “up-skilling” and “empowerment” of future generations. Women encounter many more dimensions of poverty because of gender inequalities in distribution of income, access to credit, control over property or earned income, gender biases in labour markets and social exclusion (Cagatay, 1998). These factors are more prevalent in emerging economies and to a lesser extent in developed economies. Lucy et al. (2008), in their study of Bangladesh, reported that all citizens of this country suffer from poverty, but women and children bear most of the burden as they face discrimination in health, nutrition, education, employment and political participation. Women are also “time poor” (i.e. time committed to raising a family) and much of their work is unpaid, yet such an activity is essential for the well-being, social care and empowerment of future generations. To gain an insight into the link between poverty and economic growth, Morrison et al. (2007) have developed a complex poverty measurement framework. Accordingly, a given level of male earnings leads to improvements in women’s productivity, earnings and children well-being, which in turn results in poverty reduction and economic growth. An increase in female earnings stimulates short-term growth, reduces current poverty and stimulates long-term economic growth, which reduces future poverty through higher consumption expenditures and savings ratios. To capitalise and harness entrepreneurial efforts, development programmes explicitly inculcate women’s participation to achieve economic success. Specifically, access to credit is essential (Cagatay, 1998), to enable women to gain a foothold on the economic ladder and help them uplift their families’ well-being. Credit will only be helpful if it is used in business and pilferages are mitigated. This paper examines the impact of
microfinance loans upon poverty reduction amongst female entrepreneurs in Pakistan. The authors set out to establish whether there exists an optimal loan size to attain the objective of poverty reduction in this country. Conceptual and contextual issues To reduce poverty in most of the developing world and in some areas of developed countries requires strategies and development programmes that promote self-reliance and entrepreneurship. In this context, microfinance can make a significant contribution towards poverty reduction through the facilitation of entrepreneurship and new venture creation (Mawa, 2008). This perspective on microfinance is reflected in various empirical studies. Morris and Barnes (2005) investigated three microfinance programmes in Uganda and found that these contributed to a reduction in financial vulnerability through diversification of income sources and accumulation of assets. The positive impact of microfinance programmes in Uganda included the addition of new products and services, improved and/or expanded enterprise activities and niche markets, reduced cost of inventory purchases and increase in sales. Most commonly cited examples of success in microfinance relate to Bangladesh, but some critics argue that the presence of microfinance in this country is limited to a few small areas and that pilferage is mostly mitigated through external injections of finance. Chemin (2008) reported that participants of microfinance programmes in Bangladesh achieved 3 per cent additional income for expenditure, than similar non-participants in this type of initiatives. He reported positive impact of microfinance on supply of labour in both male and female respondents. Chowdhury et al. (2005) showed that the impact of Bangladesh microcredit programmes tended to be short lived. Improvements associated with microcredit were associated with lower objective as well as subjective measure of poverty, a strong impact for about six years, thereafter benefits leveled off and disappeared altogether. Khandker (2005), using panel data from Bangladesh, showed that microfinance contributed to annual poverty reduction in just over half of the 3 per cent sample of microfinance participants. The benefits of microfinance spillover to the wider community, manifested through local income and expenditure, exhibited a multiplier effect and promoted local economic growth. There are some empirical studies specific to Bangladesh which report more positive microfinance results for women than for men. For instance, Pitt and Khandker (1998) examined three groups of respondents selected from microfinance programmes in Bangladesh and found an increase in the annual consumption expenditures of the participants. Most microfinance programmes aim to help poor people, particularly women, to become entrepreneurs (Haque and Harbin, 2009) by taking risks and support enterprise start-ups. A value chain programme targeting poor women in Pakistan benefitted more than half of participants and their engagement in enterprise led to broader empowerment in community groups, changing family relationships and participation in the wider society (see Jones et al., 2006). Critics, however, argue that poverty is not reduced by microfinance and that it burdens the poor with additional debt. Coleman (1999) conducted a study on microcredit programmes of northeast Thailand and found only an insignificant impact upon physical assets, savings, production, sales, productive expenses, labour time and expenditures on health care and education. Furthermore, in a later study, Coleman (2006), concluded that microcredit programmes were biased towards better off applicants. He found a positive impact on the household welfare of the richer committee members and no significant impact on the average members of MIs. Similarly, Duong and Izumida (2002),
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conducted a study on rural development microfinance in Vietnam and concluded that banks were rationing credit on the basis of reputation, collateral and the amount of credit applied. Not surprisingly, these microfinance programmes only benefitted the better off applicants and not the very poor. Some argue that access to microfinance by very poor individuals, including women, acted as a barrier to new business formation. Hermes and Lensink (2007) reported that although microfinance has a positive impact on economic development, it has not reached the poorest of the poor. They suggested that microfinance could only become an effective tool to fight poverty if it reached the poorest borrowers first. Critics of microfinance suggest that MIs have to distinguish between “marginally poor” and “very poor” (Sengupta and Aubuchon, 2008) in order to examine real impact on the recipients of credit. Microfinance loan providers’ drive to minimise bad debts can, in practice, exclude the very poor from borrowing (Weiss et al., 2003) and fail to target the poorest and most needy applicants (Chemin, 2008). Methodological approaches employed to study the impact of microfinance have often been criticised, due mainly to access problems encountered in reaching the poor in society. In addition, definitional problems also result in bias barriers and sample selection difficulties. Pitt and Khandker’s (1998) study was criticised on the basis that lowland holdings constraint of less than half an acre was not strictly enforced in the sample and led to biased results (see Weiss et al., 2003). Furthermore, Morduch (1998) reworked his research sample and, by using simple comparisons that took into account bias not controlled in previous work, found no impact of microfinance on consumption or increase in educational achievement of applicants’ children. Pitt (1999), however, upon re-examination of his work, confirmed earlier positive findings, as reported in Pitt and Khandker (1998). Chemin (2008) criticised Pitt and Khandker’s (1998) results for not enforcing the eligibility criteria of land holding for borrowing as well as Morduch’s (1998) findings for not accounting for non-random programme placements. Helms (2006) argued that microfinance can only serve a limited number of clients and many potential customers remained disappointed. The author further noted that “[y] microcredit is not appropriate for the destitute and hungry who have no reliable income or means of repayment [y] in many cases, small grants, infrastructure improvements, employment and training programs, and other nonfinancial services may be more appropriate for destitute people” (Helms, 2006, p. 33). Mosley and Rock (2004), from their study of six African MIs, suggested that the main advantage of microfinance rested upon the intention to reach and benefit vulnerable, non-poor, the working poor or the entrepreneurial poor. Microfinance initiatives might also benefit the extremely poor indirectly through labour markets, as it enables them to become employees of successful microfinance entrepreneurs. In addition, their human capital would increase and this would result in a commensurable rise of expenditure on education and health. Microcredit facilities could only have a positive effect on income generating activity if the external environment is also conducive to entrepreneurial intention and conversion. The loan to women may not be successful if familial and social conditions suppress the independence and mobility of women, and forbids them to start a new business (Sinha, 2005). In developing nations, family obligations and gender role expectations often act as hurdles for would be women entrepreneurs. Some forms of entrepreneurship, however, give women the opportunity and ability to combine domestic roles with new venture creation and small business management (Scott, 1986; Orhan and Scott, 2001). Similarly, entrepreneurship can enable women to mitigate
childcare cost and assist them to combine domestic chores with enterprise activities (Minniti and Arenius, 2003). Greater domestic involvement, could be perceived negatively by lenders, with the result that access to finance would be ultimately denied. Businesses supported through microfinance initiatives can have lower barriers to entry, yet financial, social and cultural factors might restrict entrepreneurial women from starting and developing high-growth businesses (Shaw, 2004). This would suggest a need for training for would be women entrepreneurs (Brixiova, 2010) and using microcredit to help them maximise their income generation potential. Training in business management and networking was found to be helpful in promoting entrepreneurship (Karlan and Valdivia, 2011). Interestingly, Banjeree et al. (2010) argued that microfinance was successful in creating and expanding small businesses, but no effect was found, in the short run, on health, education and the empowerment of women entrepreneurs. It should be noted that the specialist literature on microfinance is still evolving and that the ensuing debate has produced conflicting results on the role of MIs in alleviating poverty amongst women entrepreneurs and their families. Clearly, microfinance offers benefits and challenges wider social dynamics that emerge when access to finance is facilitated for women entrepreneurs (cf. Hermes and Lensink, 2007) Therefore, a case can be made for more empirically rigorous research in the area of microfinance, in order to study its effects on poverty alleviation through women led entrepreneurship. Specifically, it would be beneficial to investigate microfinance impact in a particular region, from direct interaction with the borrowers and lenders of such programmes, to identify the actual impact that it has on poverty reduction for women entrepreneurs and their families. In this context, Pakistan is the sixth most populated country in the world, with a population of 169.9 million, of which 23 per cent is living below the poverty line, on less than $1.25 a day. Up until 2007, efforts to reduce poverty were having some positive impact, but the recent worldwide economic and political crises have negated much of the earlier improvements in poverty reduction (Economic Survey of Pakistan, 2009-2010; Alkire and Santos, 2010)[1]. Poverty amongst women remains a cause for concern for government as well as the international community: 55.5 per cent of women are living below the poverty line (Goheer, 1999, p. 2). They experience greater barriers to break out from the poverty trap, due to market inefficiencies, which are further compounded by extant social, religious and cultural norms. To break this cycle of poverty, microfinance is often considered to be an effective strategy to enable poor and vulnerable women to engage with entrepreneurial activity. A recent State Bank of Pakistan (2005) quarterly report, offered its own model of evaluating the performance of microfinance providers. Thus, microfinance is considered to represent an effective tool to fight poverty through enabling individuals to engage in self-employment and new venture creation. MIs tend to target women as the poorest segment of the society, which helps to enhance position through entrepreneurship. The logic of the proposed approach is that female participation in new venture creation can lead to an improvement in gender equality and has a positive impact on the status of women within a family decision making process. This can enhance the social status of women entrepreneurs and indirectly contribute to lower birth rates and increased family well-being. Thus, the use of microcredit to reduce poverty and enhance local economic growth appears to have gained wither recognition in both developed and developing countries.
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Conceptual framework This study examines how MIs impact on the well-being of women entrepreneurs and which factors contribute towards the success of those who benefit from this type of loan. For the study of poverty reduction and entrepreneurial success, the authors classify poverty with entrepreneurship into three phases. The first phase is the “Failure Phase”, characterised by limited vision due to poverty clouds, as depicted in Figure 1. The women were in this phase, before accessing the microfinance facility and discovering/converting entrepreneurial opportunities. The second phase is the “Improvement Phase”, resulting from enterprise and related empowerment. This provides a broader vision, as the result of women entrepreneurs accessing microfinance and acquiring relevant attributes and entrepreneurial skills. MIs provide finance, trainings, product knowledge and assist with the establishment of business networks and peer mentoring facilities. Individually and cumulatively, these factors tend to propel women entrepreneurs towards the “Success Phase”. Figure 1 outlines these three phases. The research questions that this research seeks to answer are: RQ1. Does microfinance help women entrepreneurs with limited entrepreneurship prospects to exit poverty (Phase I)?
First Phase: Failure Poverty Clouds Vision is limited due to poverty clouds Poverty limits the entrepreneurial and prospects ideas
Impact: •
Good ideas are not fully exploited or conceived
•
Immediate need of shelter
Second Phase: Improvement Poverty clouds starts to lift up Start to have broader vision and learned from experience • • • •
Client education Product knowledge Training from MFI Budgeting and marketing
Impact: • • •
Better health Better children’s education Business experience
Third Phase: Success Poverty reduction and success
Figure 1. Phases of poverty reduction with entrepreneurship
Clear vision of entrepreneurial ideas Poverty reduction by entrepreneurship
Impact: • • •
Financial Inclusion Business Networks Increase in household income
RQ2. Does microfinance assist women entrepreneurs to improve and built entrepreneurial attributes and skills (Phase II and III)? RQ3. What is the role of microfinance loan size in reducing poverty and developing entrepreneurial attributes and skills for female entrepreneurs? To answer these research questions, three hypotheses are developed: H1. An increase in the size of microfinance loan secured by women entrepreneurs leads to an increase in the income of their family. H2. The increase in the size of microfinance loan leads to an increase in expenditure on children’s education. H3. Larger sized microfinance loans result in better health and nutrition for women entrepreneurs and their families. There are many definitions for entrepreneurs, but for the purpose of this research study, the woman entrepreneur is one who takes risks to start a new income generating activity (new enterprise) or invest in an already establish income generating activity (established enterprise). The concept of poverty incorporates many factors, such as: income, consumption, assets, health and education. In quantitative research, however, only the income, health and education of the family are taken into consideration. It should be noted that microcredit is disbursed only to one woman in a family, and only those women who used these loans to set-up a microenterprise are studied in this research. Furthermore, the impact of microfinance is investigated on the basis of the income, health and education of their family, because women are considered to benefit the family through the productive use of microfinance loans (see Morrison et al., 2007). Research sample and methodology In order to determine the impact of microfinance for women entrepreneur borrowers, this exploratory study was carried out using a questionnaire administered by a woman researcher, to overcome cultural and gender barriers. The questionnaire was designed to gather both qualitative and quantitative data, by using a range of open and closed questions. In total 123 useable questionnaires were collected on women entrepreneurs who benefitted from a microfinance facility offered by three MIs, for the stated purpose of starting and developing their enterprises. The quantitative analysis, using a SPSS software package, was designed to analyse the impact of microfinance on poverty reduction by examining increases in income, family health and education. The data analysis was carried out using binary logistic regression. The open-ended responses to questions were recorded and analysed using inductive qualitative analysis. To explore in detail the connection between microfinance and poverty reduction through new venture creation and enterprise development, a qualitative approach was also carried out, by interviewing ten women entrepreneurs. The semi-structured interviews were carried out in order to gain an in-depth understanding of relevant, microfinance-related factors and their influence upon these entrepreneurs’ family circumstances. These ten women either lived below or just above the poverty line. The geographic scope of this study was limited to participants from four districts of the Punjab region, in Pakistan. Punjab is a relatively effluent region in
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Pakistan, where women are more likely to engage in entrepreneurial activities. All the interviews were conducted in the local language, and focused on income levels before microfinance, number of family members, education, business type, business experience, securing microfinance and related training, business networks, peer monitoring, product knowledge, budgeting and finance. There are some limitations attributable to this research study. First, it is a static, “snap shot” type of research, which captures certain aspects of reality at the time of the survey (see Johnson and Loveman, 1995). Second, it is possible that some responses were biased, due to the sensitive nature of questions and issues of trust or the reluctance of respondents to disclose their experiences to an outsider. Therefore, caution must be exercised when attempting to generalise the emergent results of this study. Binary logistic model For the purpose of this research, the equation for simple liner regression of the straight line equation is: Yi ¼ a0 þ b1 X1i þ ei
ð1Þ
where a0 is the Y intercept, b is the coefficient, X is the independent variable and ei is a residual term. To analyse the completed questionnaires, a binary logistic regression model is used. The logistic regression is the prediction of the probability of Y occurring, given the known values of X (cf. Field, 2009). The logistic model equation with P (Y ) the probability of Y occurring, e the base of natural logarithms, bn regression coefficient of variable Xn is: P ðY Þ
1 1þ
eða0 þb1 X1i þb2 X2i þþbn Xni Þ
ð2Þ
The dependent variables “increase in income/family health/children education after microfinance loan” is taken as binary variables where income/health/education increase takes value of 1 and the value is 0 for no increase after microfinance. Therefore the unobserved variable Y in case of binary logistic regression is: 1 if Y 40 y¼ ð3Þ 0 if Y p0 The independent variable for the three hypotheses is the amount of microfinance loan with three categories. All have the control variables of age, education, number of children of the women entrepreneurs, family system and household head. The two additional control variables “number of years of business experience” and “newly established or old enterprise with the use of microfinance facility” are included in the dependent variable “increase in income” due to enterprise development factors. The variable of “control on decision to spend money on family health” by women entrepreneurs is included in the dependent variable of family health. Analysis and discussion Hypothesis testing Table I lists the dependent and independent variables and their respective statistics. To check whether the predictors are not highly correlated, the multicollinearity test was run between the independent variables. The values of tolerance not less than 0.1
Variables
%
Age of women (in years) 18-39 66 40-more than 40 33 Education of women No education 53 School education 40 College/university/profession education 7 Number of children No children 14 1-4 children 50 5 and more 36 Family system Nuclear 58 Joint 42 Household head Women 26 Husband 44 Both/any other 30 Business experience of women Less than 1-2 years 23 3-5 years 28 6-10 and more years 49 Enterprise developed by women Existing enterprise 84 Newly established enterprise 16 Control on decision relating to spend money on family health and nutrition after microfinance No 46 Yes 53 Amount of microfinance loan (amount in Rupees) 5,000-15,000 – low 48 15,001-25,000 – medium 34 25,001-35,000 and more – high 18 Increase in income after microfinance (0,1) (24, 76) Increase in children’s education after microfinance (0,1) (45, 55) Increase in family health and nutrition after microfinance (0,1) (33, 66)
and VIF not greater than ten show that there was no issue of collinearity between the predictors. Increase in income after microfinance. In the preliminary analysis, the w2 test for independence explores the relationship between dependent variable “increases in income” with the independent variable “amount of microfinance”. The result of Pearson w2 ¼ 12.62[2] test is significant, which indicates that there is a relationship between levels of loans and increase in income. To check whether the results will be the same with the control variables in the model, we run a binary logistic regression. The model contained eight independent variables: amount of loan, age, education, number of children, household head, family system, business experience of women and enterprise developed by women. The model, containing all predictors, is statistically significant w2 (8, n ¼ 114) ¼ 28.92, po0.01, indicating that it is capable of distinguishing between women with and without increase in income after microfinance. The model explained between 22.4 per cent (Cox & Snell R2) and,
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Table I. Dependent and independent variables statistics
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34.4 per cent (Nagelkerke R2) of the increase in income, and correctly classified in 79.8 per cent of cases. Table II indicates that only two independent variables, age and amount of loan, made a statistically significant contribution in the model. The amount of loan predictor shows that women entrepreneurs taking medium loan amounts of Rs.15,001-25,000 (£104.60-£174.40)[3] are four times (odd ratio of 4.703) more likely to report an increase in the income of household than those who secured lower loans ranging between Rs.5,000 and 15,000 (£34.90-£104.60. However, women taking loans of higher amounts of Rs.25,001-35,000 (£174.40-£244.10) show insignificant improvement in their position. The likelihood of women entrepreneurs having higher income after securing microfinance, increases with the amount of loans greater than Rs.25,000 (£174.40). The odd ratio of 0.22 for age is less than 1, indicating that women aged 40 years and above, are 0.22 times less likely to report increase in income as compared to women aged between 18 and 39 years, controlling for all the factors in the model (see Pallant, 2007, pp. 177-178).
Increase in income after microfinance
Table II. Logistic regression estimation of increase in income of the family
Coef. B
SE
Constant 1.937 1.676 Amount of loan 5,000-15,000 – 15,001-25,000 1.548* 0.685 25,001-35,000 and more 20.937 8,558.061 Age 18-39 years – More than 40 1.479* 0.717 Education No education – School education 0.215 0.596 College/university education 0.856 1.222 Children No children – 1-4 children 0.766 1.215 5 and more 0.368 1.326 Household head Women – Husband 1.249 0.772 Both/any other 0.093 0.884 Family system Nuclear – Joint 0.106 0.574 Business experience of women Less than 1-2 years – 3-5 years 0.130 0.708 6-10 and more years 0.705 0.686 Enterprise developed by women Existing enterprise – Newly established enterprise 0.274 0.719
Sig. p
Odds ratio Exp B
0.248
6.935
0.024 0.998
4.703
1.227 0.000
18.022
0.039
0.228
0.056
0.928
0.876 0.614
0.807 0.425
0.251 0.039
2.595 4.660
0.397 0.077
0.465 0.692
0.043 0.051
5.033 9.317
0.105 0.916
0.287 0.911
0.063 0.161
1.301 5.149
0.854
1.112
0.361
3.426
0.854 0.304
1.139 2.024
0.284 0.528
4.565 7.768
0.703
1.315
0.321
5.384
2
95% CI for odds ratio (B) Lower Upper
Notes: –, Reference category; number of obs. ¼ 114; R ¼ 0.93 (Hosmer and Lemeshow), 0.22 (Cox and Snell), 0.34 (Nagelkerke); model w2 ¼ 28.92, po0.01. *po0.05
Increase in children’s education, after microfinance. The w2 test for independence explores the relationship between two dependent variable “increases in children’s education” with independent variable “amount of microfinance”. The result of w2 ¼ 8.430[4] test is significant, which indicates that there is a relationship between loan amount and increase in children’s education, after securing microfinance. To check whether the results will be same with the control variables in the model, we run a binary logistic regression. The model contained six independent variables: amount of loan, age, education, number of children, household head and family system. The model containing all predictors is statistically significant w2(6, n ¼ 117) ¼ 28.70, po0.01, indicating that it is able to distinguish between women entrepreneurs with or without the increase in children’s education, after obtaining microfinance. The model explained between 21.8 per cent (Cox and Snell R2) and 29.1 per cent (Nagelkerke R2) of the variance in the increase in children’s education and correctly classified 69.2 per cent of cases. Table III shows that four independent variables, including number of children, household head, family system and amount of loan made a statistically significant contribution to the model. The loan predictor indicates that women entrepreneurs taking medium-sized loans are four times (odd ratio of 4.412, po0.01) and those recurring higher loans, five times (odd ratio 5.050, po0.05) more likely to report an increase in their children’s education than those who are taking lower loans. Women entrepreneurs who live with their families in “joint systems” are three times (odd ratio of 2.994, po0.05)
Increase in children’s education after microfinance Coef. B Constant Amount of loan 5,000-15,000 15,001-25,000 25,001-35,000 and more Age 18-39 years More than 40 Education No education School education College/University education Children No children 1-4 children 5 and more Household head Women Husband Both/any other Family system Nuclear Joint
SE
Sig. p
Odds ratio Exp B
1.143
0.001
0.025
– 1.484** 0.525 1.619* 0.675
0.005 0.016
4.412 5.050
1.577 1.344
12.340 18.973
3.696
241
95% CI for odd ratio (B) Lower Upper
– 0.123
0.533
0.818
0.885
0.311
2.515
– 0.437 0.383
0.516 1.066
0.397 0.719
1.548 1.466
0.563 0.182
4.255 11.847
– 1.912* 1.766
0.844 0.916
0.023 0.054
6.770 5.848
1.296 0.971
35.377 35.215
– 1.481** 0.558 0.788 0.624
0.008 0.207
4.397 2.200
1.474 0.647
13.118 7.479
– 1.096** 0.473
0.020
2.994
1.185
7.563
2
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Notes: –, Reference category. number of obs. ¼ 117; R ¼ 0.78 (Hosmer and Lemeshow), 0.22 (Cox and Snell), 0.29 (Nagelkerke). Model w2 ¼ 28.70, po0.01. *po0.05; **po0.01
Table III. Logistic regression estimation of increase in children’s education
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more likely to report an increase in children’s education than those who are living in “nuclear” families. Interestingly, if the household head is the husband, then it is (odd ratio of 1.474, po0.01) more likely that there will be an increase in children’s education than if the household head was a woman. The likelihood of an increase in children’s education is significant at po0.05 when there are between one and four children (odd ratio 1.296). However, with the increase in the number of children to five or above, there is no significant increase in the rise in education, after securing microfinance. Increase in family health after microfinance. The w2 test for independence between “increases in family health” with independent variable “amount of microfinance” was also calculated. The result of w2 ¼ 0.971 test is insignificant, which indicates that there is no relationship between loan amounts and the increase in family health. To check whether the results will be the same with the control variables in the model, we run a binary logistic regression. The model comprised seven independent variables (amount of loan, age, education, number of children, household head, family system and control on decision to spend money on family health). The model is statistically significant w2(7, n ¼ 117) ¼ 20.14, po0.05, indicating that it is able to distinguish between women entrepreneurs with and without the increase in family health. The model explained between 15.8 per cent (Cox and Snell R2) and 22.2 per cent (Nagelkerke R2) of the variance in the increase in family health, and correctly classified 75.2 per cent of cases. Table IV shows that two independent variables, “number of children” and “control on decision to spend money on family health” by woman entrepreneurs, after securing microfinance, made a statistically significant contribution to the model. The main independent variable, “amount of microfinance loan”, is insignificant and hence confirms the result of the w2 test of independence. The number of children predictor indicates that women having between one and four children are nine times (odd ratio of 9.316, po0.01) and women having five or more children 14 times (odd ratio 14.027, po0.01) more likely to report an increase in family health than those who have no children, controlling for all other factors in the model. Similarly, women entrepreneurs’ control over family health expenditures predictor, after obtaining microfinance, was three times (odd ratio 3.684, po0.01) more significant than in the case of those who had no control over it. Semi structured interviews analysis Microfinance and reduction in poverty. The ten women involved in the semi structured interviews lived below the poverty line (£1.25 per day) before securing microfinance and experienced extreme poverty. In seven of these interviews, women fell into the category of “core poor” (i.e. significantly below the poverty line). After obtaining loans from MIs and investing in their enterprises, these women entrepreneurs’ income, expenditure, health and education, have improved. The results validate the quantitative outcomes reported in the previous section of this paper. Food, health and the education of children represent a major proportion of household expenses. The microfinance loan amount used in income generating activity yields returns that are mostly used, by these women entrepreneurs, to buy food and nutrition as well as improve the health of their families and their children’s education. In addition, a proportion of returns are saved for future expenses relating to their children’s marriages. Saving for their daughters’ marriage gives these women a feeling of satisfaction and provides security marriage party expenses and dowries. These women entrepreneurs also pointed out that the loan instalments are easy to repay. This is how they succeeded not only to repay their loans,
Increase in family health after microfinance Constant Amount of loan 5,000-15,000 15,001-25,000 25,001-35,000 and more Age 18-39 years More than 40 Education No education School education College/university education Children No children 1-4 children 5 and more Household head Women Husband Both/any other Family system Nuclear Joint Control on decision by woman No Yes
Coef. B
SE
Sig. p
Odds ratio Exp B
2.063
1.144
0.071
0.127
– 0.346 0.282
0.534 0.671
0.517 0.679
1.413 0.758
0.496 0.203
4.023 2.823
0.009
0.583
0.987
1.009
0.322
3.165
0.215 0.856
0.596 1.222
0.876 0.614
0.807 0.425
0.251 0.039
2.595 4.660
0.840 0.961
0.008 0.006
9.316 14.027
1.797 2.133
48.292 92.226
0.595 0.677
0.587 0.677
0.724 1.326
0.226 0.352
2.324 4.997
0.561
3.670
1.411
9.620
– 2.232** 2.641** – –0.323 0.282
– 0.361 0.479 0.451 1.435 on family health after microfinance – 1.304** 0.490 0.008 3.684
95% CI for odd ratio (B) Lower Upper
2
Notes: –, Reference category. number of obs. ¼ 117. R ¼ 0.47 (Hosmerand Lemeshow), 0.16 (Cox and Snell), 0.22 (Nagelkerke). Model w2 ¼ 20.14, po0.05. **po0.01
but also to cover expenditure on the health and education of their families. According to interviewee 10: It is difficult to repay a loan, as whole, but this loan is easy to pay back, due to the small instalments involved [y].
Other, tangential aspects have also emerged from these interviews. For example, an increase in immovable property, such as a house, proved less positive than the increase in income or expenditures. The political participation of these women entrepreneurs has also increased, accordingly. Business engagement requires National Identity Cards (NICs) in Pakistan. Women in poor segments of the population do not generally feel the need to have a NIC. When they take a loan from a MI, they are required to have a NIC, which represents an unintended benefit, inclusive of assistance to complete forms and lodge the necessary application. Being on the voter register brings greater interaction with political parties, which gives women entrepreneurs greater awareness and also improves their social networking and flow of relevant information. The interview results highlighted that all the respondents were in the Phase 1 of failure before obtaining microfinance and graduated to Phase 2 after taking the loan, which suggested an incremental improvement in their position. The analysis of
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Table IV. Logistic regression estimation of increase in family health
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interview data showed that two out of ten women entrepreneurs further progressed to Phase 3, a change brought about by an increase in all six factors, leading to poverty reduction and commensurable increase in income, expenditures, assets, health, children’s education and political participation. According to interviewee 5: I could have not got such prosperity, so soon, without this [microfinance] loan [y].
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Microfinance and entrepreneurship. In the interview sample, these women entrepreneurs were educated, at most, up to GCSE level and had families in the range of two to 12 persons, including children. With large families and few resources, they managed to establish an enterprise or invested in an already established business by accessing a microfinance loan, either as a sole proprietor or as partners with their husbands. As interviewee five explained: As a group leader, I got instalments of loan on time from each group member, because all the members were doing business because of taking the loan [y].
These micro enterprises had either retail outlets, sale of clothes, electronic items, blankets and food items or very limited levels of production by manufacturing carpets, wooden decoration pieces, car mats and hosiery. A few of these women entrepreneurs were involved in livestock and services businesses, or stitching and sewing cloths. Their business-related experience ranged from one to more than ten years and all were members of MIs for six months to six years. Two of the three MIs in the sample provided training facilities to their clients. The entrepreneurial training offered by one NGO-based MI included two courses in Business Orientation covering market assessment and dealing with customers as well as Cash Flow Development relating to accounting and finance processes and regulations. They were also given the opportunity to attend international exhibitions, in order to make contacts and sell their goods. Another MI offered training programmes in basic financial literacy and systemised financial education. Unfortunately, there were no training programmes on offer from the third MI under investigation, and therefore no help or support in developing the entrepreneurship abilities of their clients. All the MIs in the study were providing product knowledge and prospects of different types of business to their clients. The advice received from MI staff and peers of women borrowers were helpful in starting or expanding their businesses, as stated by interviewee 1: I, as a member of this Microfinance Institution, thought not only to expand the business but also of starting a new business, such as putting stickers on bottles and selling them [y].
Most of these women entrepreneurs had benefited from peer mentoring because they had to attend monthly meetings in order to qualify for a microfinance loan. In these monthly meetings, they discussed the problems of every group member, regarding both business and household. They gave and received advice as well as supported one another on various matters. According to interviewee 2: When I took money as loan, I could not talk to people as I am talking to you today. Because of meeting with different people in group meeting, my mind changed and I got courage, while listening to others, to find new ways of business and financial management [y].
The results emerging from these interviews show that the women entrepreneurs in the subsample enjoyed significant enhancements in the quality of their life after accessing microfinance. This is evidenced from the fact that these women moved from Phase 1 to 2, because access to finance offered entrepreneurial opportunities, training, business networks, peer mentoring, product knowledge, budgeting and finance. This further
enabled two women to move into Phase 3 of success, where they experienced significant poverty reduction and greater opportunities to enhance their entrepreneurial skills in order to break out of the poverty cycle. Discussion A general finding that emerges from this research study is that access to finance is important for women entrepreneurs to release them from poverty and to help them realise their full potential. The results derived from quantitative analysis suggest that two out of three variables, namely income and education, are significant and have a high correlation with access to microfinance. A closer examination of the results suggest that an increase in the income of the family is positively correlated with the size of the microfinance loan, up to a point, but this relationship does not hold when the size of loan reaches a certain level. That may be the reason why women entrepreneurs generally avoid taking larger loans, which can make their financial situation in the household worse than before (see Agier and Szafarz, 2012). Thus, the relationship between increase in income and amount of loan has an inverted U-shape. Therefore H1 is not conclusive: this may be due to use of loans at higher level for other purposes, not related to the enterprise. These results have important implications for MI managers, donors and policy makers. The logistic regression results show that with the increase in amount of loan, there is a probability of increase in children’s education, therefore we accept H2 at po0.01 at medium level of loan amount and at po0.05 at high level of loan. This finding is in line with the positive outcome of microfinance on children school enrolment found by Chemin (2008). The results from interviews show the same increase in income, expenditure and in children’s education. H3 is rejected, as there is no probability of improvement in family health with an increase in the amount of microfinance loan. The reason may be that observed by Banjeree et al. (2010) who noted that women borrowers are generally not the primary decision makers on how to spend money in a household. Interestingly, however, the increase in family health was found to be positive in the interviews with women entrepreneurs. As Kim et al. (2007) indicated, microfinance initiatives can empower women and also result in some positive health outcomes. The in-depth interview results show positive outcomes relating to entrepreneurship attributes, except to budgeting and finance. The increase in product knowledge and peer mentoring helped to reduce information asymmetry relating to these women entrepreneurs’ target niche markets. Regular monthly meetings and repayments were found to build bonds, create a sense of belonging, facilitate learning of business practices and instil discipline amongst women entrepreneurs. MIs proved helpful in increasing the entrepreneurial potential and skills of their women clients, helping them progress and prosper in their enterprise. There is a need, however, for more and better training programmes for women entrepreneurs, to facilitate an increase in their financial and budgetary skills. This confirms findings by Karlan and Valdivia (2011) who argued that entrepreneurial training offered to microfinance borrowers tended to improve their skills and entrepreneurship knowledge. The results emerging from the ten interviews focused on factors affecting poverty and entrepreneurship, in relation to the level of the loan size availed to these women entrepreneurs. The positive results of each factor appertaining to women entrepreneurs are presented in the form of web diagram (Figure 2) against the three levels of microfinance loan that were used in the questionnaire. The qualitative analysis reported
Loan size and poverty reduction 245
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in Table IV, shows that microfinance loans have a positive impact on poverty reduction. Access to finance leads to an increase in income and business networks, especially when this is supported with peer mentoring for new members of MIs, who borrow in the range of Rs.5,000-15,000 (£34.90-£70.00). With the increase in the range of loans from Rs.15,001-25,000 (£104.60-£174.40) there is further reduction in poverty, by an increase in income, expenditures, health and children’s education, with improvements in budgeting and finance skills as well as training facilities. Furthermore, there is a positive correlation with the size of loan and political participation, which reflects on the right of women entrepreneurs to vote in election campaigns. The relation, however, did not hold if the microfinance loan exceeded Rs.25,000 (£174.40). There still is an improvement in income, expenditure, health, education, product knowledge and peer mentoring, but this is considerably lower as compared to smaller sizes of loan. The results of hypotheses testing exhibited similar results. We found that loans below Rs.25,000 (£174.40) significantly enhanced the well-being of women entrepreneurs. Above this amount, significant improvements were not observed, suggesting that there may be an optimal loan size that MIs should offer to women entrepreneurs. In this context, Mersland and Strom (2010) suggested that smaller average loan size by MIs were more cost effective, as the reduction helped reach poorer segments of the population. Conclusion This research study illuminates the relationship between microfinance and poverty reduction, with a specific focus on women entrepreneurs. The results of both quantitative and qualitative research suggest that microfinance can help reduce poverty amongst women entrepreneurs. It also facilitates an increase in the family income and children’s education of women entrepreneurs who secured a loan from MIs. Interestingly, family income and children’s education can vary considerably at different ranges of microfinance loans. Typically, microfinance loans up to Rs.25,000 (£174.40) result in a significant increase in income and business networks, especially when these are supported with peer mentoring for new members of MIs. Conversely, in the case of microfinance loans that exceed Rs.25,000 (£174.40), while there still is an improvement in income, expenditure, health, education, product knowledge and peer mentoring, this is considerably lower, as compared to smaller sized loans. The increase in family health and nutrition due to microfinance showed positive result in interviews. These results suggest that microfinance is becoming increasingly Political participation Better child education
Figure 2. Impact of increase in amount of microfinance on poverty reduction and entrepreneurship attributes
Training 40% 35% 30% 25% 20% 15% 10% 5% 0%
Business Networks
Peer Mentoring 5,000-15,000 15,001-25,000 Product knowledge
Better health
Increase in assethouse Increase in expenditures
Budgeting and finance Increase in income
25,001-35,000 and more
successful in reducing poverty and in developing entrepreneurial attributes amongst women entrepreneurs as well as increase the income of their households. There is evidence of a narrow focus, amongst MIs, which tend to support start-ups that have potential to become independent earners. Emergent results suggest that there is a case for supporting established enterprises or new start-ups of women in Phase II, to enable these women entrepreneurs to learn from their experience, network with others, draw upon training opportunities and mentor individuals in similar positions. Experienced women entrepreneurs exhibit a positive attitude towards microfinance initiatives. They are successful in increasing their income and thereby ensure that MIs have a positive impact on poverty reduction amongst women entrepreneurs in Pakistan and, potentially, in other developing countries. Notes 1. www.ophi.org.uk/wp-content/uploads/OPHI-MPI-Brief.pdf 2. n ¼ 120, p ¼ 0.002, Cramer V ¼ 0.324 (effect size medium ¼ 0.30). 3. Exchange rate from www.xe.com/ucc/dated on 22 February 2012. 4. n ¼ 120, p ¼ 0.015, Cramer V ¼ 0.265 (effect size small ¼ 0.01 and medium ¼ 0.30). References Agier, I. and Szafarz, A. (2012), “Microfinance and gender: is there a glass ceiling on loan size? World development”, available at: http://dx.doi.org/10.1016/j.worlddev.2012.06.016] (accessed 8 November 2012). Alkire, S. and Santos, M.E. (2010), Multidimensional Poverty Index, Oxford Poverty and Human Development Initiative (OPHI), Oxford, available at: www.ophi.org.uk/wp-content/ uploads/OPHI-MPI-Brief.pdf (accessed 19 November 2012). Banjeree, A., Duflo, E., Glennerster, R. and Kinnan, C. (2010), “The miracle of microfinance? Evidence from a randomized evaluation”, Working Paper No. 278, Bureau for Research and Economic Analysis of Development, MIT Department of Economics and Abdul Latif Jameel Poverty Action Lab, Cambridge, MA, 30 June, available at: http://ipl.econ.duke.edu/ bread/papers/working/278.pdf (accessed 8 November 2012). Brixiova, Z. (2010), “Unlocking productive entrepreneurship in Africa’s least developed countries”, African Development Review, Vol. 22 No. 3, pp. 440-451. Cagatay, N. (1998), “Gender and Poverty. Social development and poverty elimination division”, Working Paper Series No. 5, UNDP, New York, NY, available at: www.iknowpolitics.org/ files/Gender%20and%20Poverty.pdf (accessed 31 May 2009). Chemin, M. (2008), “The benefits and costs of microfinance: evidence from Bangladesh”, Journal of Development Studies, Vol. 44 No. 4, pp. 463-484. Chowdhury, M.J.A., Ghosh, D. and Wright, R.E. (2005), “The impact of micro-credit on poverty: evidence from Bangladesh”, Progress in Development Studies, Vol. 5 No. 4, pp. 298-309. Coleman, B.E. (1999), “The impact of group lending in Northeast Thailand”, Journal of Development Economics, Vol. 60 No. 1, pp. 105-141. Coleman, B.E. (2006), “Microfinance in Northeast Thailand: Who benefits and how much?”, World Development, Vol. 34 No. 9, pp. 1612-1638. Duong, P.B. and Izumida, Y. (2002), “Rural development finance in Vietnam: a micro econometric analysis of household surveys”, World Development, Vol. 30 No. 2, pp. 319-335. Economic Survey of Pakistan (2009-2010), “Pakistan economic survey 2009-10”, available at: www.finance.gov.pk/survey_0910.html (accessed 13 February 2011).
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