Memoire Online - Analysis of microfinance performance and development of informal institutions in Cameroon

Analysis of microfinances' performance and development of informal institutions in Cameroon

ANALYSIS OF MICROFINANCES' PERFORMANCE AND
DEVELOPMENT OF INFORMAL INSTITUTIONS IN
CAMEROON

A dissertation submitted in partial fulfillment of the requirements in Masters
of Finance and Control at the Amity Center for E-learning Amity University,

Analysis of microfinances' performance and development of informal institutions in Cameroon

ABSTRACT

Historically, microfinance has been successful in reaching the population excluded from the classical financial system. In the 90's, efforts have been concentrated towards the financial and institutional sustainability of the microfinance institutions (MFIs). Tools to evaluate financial performances have been developed, but the social performances were taken for granted.

This study is intended to investigate the relationship between social and financial performance of MFIs and factors that contribute to the development of informal sector in Cameroon; with a particular interest in the role that microfinance institution may be playing. In addition to gaining a more general understanding of the challenges facing developing informal institutions, the study will identify how the evaluation of microfinances' performance is contributing to overcome the mission drift or arbitrage between social and financial performance of microfinance institutions. This thesis is focused on three specific objectives:

The First is to analyse the influence of social performance on the financial performance, with the aim to study whether there is a good management or arbitration by MFIs. The second objective is to study the impact of the financial performance on the social performance, with the aim to find whether good financial performance enables the firm to allocate some margin to social issues or financially powerful companies are the worse in terms of social performance because of their leaders' greed, who do not share the margin. The last objective is to analyse the reciprocal influence of informal sector and microfinances' performance.

Key words: microfinance, social performance, financial performance, informal sector, Cameroon and mission drift

Analysis of microfinances'performance and development of informal institutions in Cameroon

This thesis would not have been realized without the valuable inputs of the Pan African e-Network Project, AMITY University Campus Uttar Pradesh India 201303 and our Focal Team of the National Virtual University. We will like to thank them largely on the knowledge they imparted in us. Gratitude is given to Professor Emmanuel TONYE, Professor Mama FOUPOUAGNIGNI and Mr TAKANG Nixon

We will also like to thank the MOANTAMB's and DJONG's families, for their love, encouragement and the support they gave to us to realize this work, their tolerance made us to understand that winners do not quit and quitters do not win. This is especially to my parents Mr MOANTAMB Nicolas and Mrs NTAMKEN Marie, my aunt Mrs AMBO'O Odette and his husband Mr DJONG Simplice.

We will also like to use this opportunity to thank all those who have contributed directly or indirectly to this thesis. Especially the classmates of Central Africa Virtual University of Cameroon, my friends: BILE'E Etoga Matrhe, NSOUNFON Donald, MVOGO Lucien, NZODIA Ines, ABENGMONI Emmanuel II and KIYEM Gisèle.

To crown it, our profound gratitude goes to God Almighty who gave us the enabling capacity both mentally and physically as well as the opportunity to be alive for the completion of this work.

Analysis of microfinances' performance and development of informal institutions in Cameroon

Analysis of microfinances'performance and development of informal institutions in Cameroon

Table5: A set of various assumptions on likely relationships between SP and FP 45

Analysis of microfinances' performance and development of informal institutions in Cameroon

The proclamation of 2005 as International Year of Microcredit by the United Nations has certainly contributed to make this tool even more popular launched at the end of 1970. Since then, microfinance has developed to enable excluded people to access banking services to financial services. Within a few decades, seeing the results qualitatively and quantitatively promising, microfinance has taken center stage in international cooperation. Non-Governmental Organizations (NGOs), associations, mutual societies, credit unions, private companies have sprung up around the world and are currently serving over 90 million people worldwide.

The Gramenn Bank and Muhamed Yunus had the Nobel Prize in 2006. They have enabled the poor population of Bangladesh which is up to six millions persons, with 96% of women to have access microcredit. The microcredit belongs to the range of varied products offered by microfinance institutions (MFIs). Microfinance means the finance of small size. She represents a financial intermediation in favour of poor people who have low income and are generally marginalized by classical banking system. That is why, most African countries have developed in their PRSP (Poverty Reduction Strategy Paper) some actions concerning microfinance, with the aim to improving financial services offered, in particular credit to poor people and contribute in stimulating economic growth. However, these MFIs sometime face social mission (social performance, which consist in touching a large number of those who are excluded to the classical banking system) and financial viability or financial performance, which means that cost of supply service must be taken into consideration (Doligez , Lapenu, 2006).

In fact, the real contribution of services offered to microfinance institutions with the aim of reaching social objectives such as the fight against poverty, the local development or the reduction of inequalities, still at the center of various debates (Hulme & Mosley, 1996; Morduch, 2000; Pitt & Khanker, 1999). Generally, in developing countries and particularly in Cameroon the fight against poverty can be effective through the financing of micro and small businesses. The creation of Small and Medium Size Enterprises generates employment but these enterprises are short live and consequently cause those who gained job positions to lose them and even go poorer than they were. It should be noted that microfinance is not a panacea but it is a main tool that fosters development in developing countries. It is known worldwide that the poor cannot borrow from banks. The latter does not lend to them because they do not have what is required to be granted a loan or to be provided with bank services. The lack of financial power is a contributing factor to most of the societal problems. These problems emanate from poverty and it

Analysis of microfinances' performance and development of informal institutions in Cameroon

is known that with poverty one is bound to suffer so many consequences ranging from lack of good health care system, education, nutrition, Microfinance has proved this bank concept to be wrong. They target the poor who are considered risky but the repayment rate turns to be positive as compared to the regular commercial banks (Zeller and Sharma, 1998).

Researchers regard microfinance from different dimensions. Microfinance gives people new opportunities by helping them to get and secure finances so as to equalize the chances and make them responsible of their own future. It broadens the horizons and thus plays both economic and social roles by improving the living conditions of the people (Microfinance Radio Netherlands, 2010). These improvements are to alleviate poverty, and according to this project, it will be seen from the point of the development of informal institutions. The accomplishment of 2035 Cameroon emergence to alleviate poverty at this date is far-fetched despite the enormous works that microfinance institutions are doing to contribute in this domain. The main challenge faced by the poor is to gain financial power to enable them boost their income generating activities (Yunus, 2003).

I.1- Background of the study

Since independence, the government of Cameroon has embarked on several attempts aimed at promoting agricultural development in the country. In the first few years after independence in 1961; the government embarked on the policy of «Green Revolution», which aimed at encouraging the development of agriculture in the country (Simarski, 1992). Other efforts included the setting up of agencies like the National Fund for Rural Development (FONADER) and other rural agricultural extension programs. In spite of all these attempts, much is still needed to boost this sector, which is considered very vital in the economic life wire of the state. A recent development in this sector has been the increase involvement of NGOs and the microfinance institutions in the process of enhancing the development of informal sector.

Moreover, recent years have seen a growing push for transparency in microfinance. An important aspect of this trend has been the increasing use of financial and institutional indicators to measure the performance of microfinance institutions.

Historically, microfinance has been successful in reaching the population excluded from the classical financial system. In the 90?s, efforts have been concentrated towards financial and institutional sustainability of the microfinance institutions. Tools to evaluate financial performances have been developed, but the social performances were taken for granted.

Analysis of microfinances' performance and development of informal institutions in Cameroon

However, nowadays, donors and social investors ask the MFIs to justify the fundings: Who are the clients targeted? How can we combine social and financial objectives? How do we avoid mission drift? Some MFIs themselves have the intuition that reinforcing social performances can lead, on the mid run, to strengthen financial sustainability. Some initiatives have flourished, trying to identify few indicators that could be used to assess the social process followed by the MFIs.

In Cameroon, studies conducted on MFIs efficiency are rare. Monkam et al (2001), shown through the financial ratios that, IMFs are viable even the cost of money is expensive. However, Monkam?s study is focus on financial aspect to the detriment of social objectives. Likewise, Djeuda & Heidhues (2005) have done the growth stimulations of Cameroonian Mutual Growth by using Cobb - Douglas production function in the cost behaviour analysis. But their study is just based on structure growth, without seeking to know if credit grant toward the poor is effective. Therefore, we are based on this lack of research on social performance on MFIs to structure our argumentation. It is important to look at it because even though the government promotes informal sector through different institutions, microfinance institutions are not leaving any stone unturned to make sure that the acute poverty striking the poor population is redressed.

I.2- Problem statement

The microfinance sector in Cameroon is quickly expanding, and institutions have increased their activities. In fact, the microfinance sector has a customer base of about 1.2 million clients (2012 Cameroon financial law: Report of the Economic, Social and Financial Situation and Prospect). This sector has been successful in reaching the population excluded from the classical financial system. In the last decade, efforts have been concentrated towards financial and institutional sustainability of the microfinance institutions. The objective of these MFIs is to reach the best possible performance, which can be achieved when people combine two requirements, namely: social performance (through the reduction of poverty) and financial performance (in ensuring sustained profitability). However, these two requirements raise a debate between two opposing schools of thought:

? The «welfarists» argue that, the social requirement of targeting the poorest and improvement of living conditions;

Analysis of microfinances' performance and development of informal institutions in Cameroon

? «Institutionalists» defend the requirement of economic profitability and viability of institutions.

MFIs of Cameroon provide a clear illustration of this discussion and analysis of their activities that can answer the questions: Is there a trade-off between the two types of performance namely social and financial performance? In other words, does the pursuit of social objectives enable MFIs eventually to expand their financial performance?

This study is intended to investigate the relationship between social and financial performance of MFIs and factors that contribute to the development of informal sector, with a particular interest in the role that microfinance institution may be playing. In addition to gaining a more general understanding of the challenges facing developing informal institutions, the study will identify how the evaluation of microfinances? performance is contributing to the development of small and medium size businesses and how we can overcome the arbitrage between social and financial performance of microfinance institutions.

Analysis of microfinances' performance and development of informal institutions in Cameroon

This study is focused on the assessment of microfinace performance and how microfinance may contribute to improve or to boost the development of the non-formal institutions. The specific objectives in this study are as follows:

+ To give an overall view of microfinance sector and informal institutions in Cameroon and especially in Yaoundé (creation, typology, regulation, etc.);

+ To set up a research methodology: which is based on research question, which will try to

overcome the arbitrage or trade-off between social and financial performance of MFIs; + To set up the correlation between microfinance and development of informal sector;

+ The last but not the least objective will be to find out if the pursuit of social objectives

I.5- Research outline

In this chapter, we are going to provide some of the concepts of microfinance and the role they

play in the development of informal institutions. And also the critical review of the existing

This chapter will take into account the concept of microfinance, the concept of informal sector,

theoretical links between MFIs and development of informal sector, the microfinance schism and

In this chapter, we will explain the relationship between social and financial performance, the

selection of variables and indicators, the hypothesis and research models and regression

The main topics here are: data collection, the dataset,, preliminary data analysis and regression

Analysis of microfinances' performance and development of informal institutions in Cameroon

Throughout the world, poor people are excluded from formal financial systems. Exclusion ranges from partial exclusion in developed countries to full or nearly full exclusion in lesser developed countries (LDCs). Absent access to formal financial services, the poor have developed a wide variety of informal, community-based financial arrangements to meet their financial needs.1 In addition, over the last two decades, an increasing number of formal sector organizations (non-government, government, and private) have been created for the purpose of meeting those same needs. Microfinance is the term that has come to refer generally to such informal and formal arrangements offering financial services to the poor. The purpose of this chapter therefore is to give a comprehensive of the existing literature concerning the following points: Welfarists and Institutionalists approaches, the Self-Sufficiency and Sustainability of MFIs, Impact of Microfinance Institutions and the literature review on the social performance of MFIs.

II.1- Welfarists and Institutionalists approaches

Microfinance is a means to fight against poverty in developing countries, through the financing of income-generating activities for poor households. However, the best way to help the poor gain access to financial services welfarists opposes the approach to that of institutionalists. Although they share the goal of poverty reduction, these two approaches put microfinance in the Crossroads.

The welfarists are based on the theory of social responsibility vis-à-vis the customer to meet its expectations (Carroll, 1979; Servet, 2007). This school of thought evaluates the performance of MFIs in terms of the customer through the social (outreach) and impact analysis (impact assessment): it targets the poor whose incomes are 50% lower the poverty line ($ 1 per day) and aims to improve their living conditions. It is composed mainly of supportive institutions NGOs or cooperatives that see microfinance as a key means to reduce poverty of the poorest. Despite its emphasis on the rational management of resources and does not exclude that MFIs can conduct a profitable business after a period of 5 to 12 years, this school of thought advocates an offer financial services at rates interest and a relatively low reliance on subsidies.

The institutionalists rely more on contract theory, which considers that incomplete contracts can lead to opportunistic behavior of applicants for credit (and Guinanne Ghatak,

Analysis of microfinances' performance and development of informal institutions in Cameroon

1999). The institutionalists evaluate the performance in terms of the institution by targeting a clientele of poor households and to the financial sustainability of MFIs. They designed a set of "best practices" (Appendix 1) bank-bank to increase the effectiveness of management systems (finance and accounting, marketing, service delivery, etc), whose adoption is a step essential to achieving financial self-sufficiency in industrial scale and access to financial markets. They consider financial independence as a criterion that best fulfills the social mission. They are essentially financial institutions: either specialized microfinance institutions regulated (NGOs, NBFIs and microcredit associations) that falls clearly within the realm of profitability or village banks and some commercial banks that are more traditional recently involved in microfinance.

The respective approaches of welfarists and institutionalists have the subject of a number of criticisms. The first approach faces the problem of viability and sustainability induced by subsidies, low reimbursement rates and rising operating costs, the second approach a customer micro entrepreneurs very close to the poverty line ($ 2 per day) which are applied in interest rates high enough to ensure the financial autonomy of MFIs. This "microfinance schism" (Morduch, 1998) refers to the tradeoff between targeting the poor and profitability of MFIs.

II.2- The Self-Sufficiency and Sustainability of MFIs

Unlike formal sector financial institutions, the large majority of MFIs are not "sustainable," where sustainability is equated in microfinance literature and parlance with financial self-sufficiency¹. Instead, most MFIs are able to operate without covering their costs due to subsidies and gifts from governments and other donors. Notwithstanding, the microfinance industry is dominated by an institutionist paradigm (Morduch (2000), Woller et al. (1999a)) asserting that an MFI should be able to cover its operating and financing costs with program revenues. The conceptual foundations of the institutionist paradigm stem to a large degree from the work of researchers at the Ohio State University?s Rural Finance Program. Their analysis of the failed rural credit agencies established by several LDC governments during the 1960s and 1970s diagnosed the primary cause of failure to be the «lack of institutional viability» (Gonzalez-Vega (1994)). This diagnoses led logically to two principal conclusions: (1) institutional sustainability was key to successful provision of financial services to the poor and

¹Morduch (2000) reports a rough estimate that only 1 percent of MFIs are currently financially self-sustainable and that no more than 5 percent ever would be.

Analysis of microfinances' performance and development of informal institutions in Cameroon

(2) financial self-sufficiency was a necessary condition for institutional sustainability². The institutionist argument is consistent with Hollis and Sweetman (1998a) who discuss six historical cases in an attempt to identify the institutional designs that facilitated success and sustainability for 19th century loan funds in the UK, Germany, and Italy. The authors conclude that subsidized loan funds were more fragile and lost focus more quickly than those that obtained funds from depositors.

In contrast, Welfarists take odds with institutionists over the issue of sustainability. Welfarists argue that MFIs can achieve sustainability without achieving financial self-sufficiency (Morduch (2000), Woller et al. (1999a)). They argue that donations serve as a form of equity and as such, the donors can be viewed as social investors. Unlike private investors who purchase equity in a publicly traded firm, social investors do not expect to earn monetary returns. Instead, these donor-investors realize a social, or intrinsic, return. Social investors can be compared to equity investors who invest in socially responsible funds, even if the expected risk-adjusted return of the socially responsible fund is below that of an index fund. These socially responsible fund investors are willing to accept a lower expected financial return because they also receive the intrinsic return of not investing in firms that they find offensive. Microfinance social investors take this notion to the limit, generally earning zero financial returns and relying totally upon intrinsic returns.

Welfarists tend to emphasize poverty alleviation, place relatively greater weight on depth of outreach relative to breath of outreach, and gauge institutional success more so according to social metrics³. This is not to say that neither breadth of outreach nor financial metrics matter. Welfarists feel these issues are important, but they are less willing than institutionists to sacrifice depth of outreach to achieve them. Welfarists envision an industry characterized by a plurality of institutional types (including both profit-seeking and social-mission entities) targeting different markets, with different combinations of market and non-market funding, and with different levels of commitment to social versus financial return.

Morduch (2000) refers to the debate between institutionists and Welfarists as the «microfinance schism.» Driving the schism are competing perceptions of the implications for financial self-sufficiency on depth of outreach. General consensus holds that there exists a tradeoff between

² Additionally, Bennett and Cuevas (1996) argue for the need of building sustainable financial systems for the poor from three perspectives: a) financial sector development, b) enterprise formation and growth, and c) poverty reduction.

³ Depth of outreach here refers to servicing the very poorest of clients, whereas breadth refers to servicing large numbers of clients, even if they are only marginally poor or non-poor.

Analysis of microfinances' performance and development of informal institutions in Cameroon

financial self-sufficiency and depth of outreach (e.g., von Pischke (1996)). But masked by this consensus is much disagreement about the nature, extent, and implications of this tradeoff. Nonetheless, what little evidence exists suggests that those MFIs that have achieved true financial self-sufficiency have also tended to loan to borrowers who were either slightly above or slightly below the poverty line in their respective countries (Navajas et al., (2000)).

These MFIs are able to capture economies of scale by extending larger loans to the marginally poor or non-poor. Although still an open question, this limited evidence leads many to conclude that if financial self-sufficiency is desired, then the very poor will not be reached by MFI services. That is, the MFI will not be able to achieve enough depth to reach those who need credit the most desperately.

An important area of financial research that has yet to be rigorously explored but which has significant potential to inform the debate mentioned above is the feasibility of introducing microfinance into the world capital markets. With the high repayment rates of many MFIs (e.g., upper 90% in many cases), there exists the potential to tap MFIs into world capital markets through instruments such as commercial banks loans, commercial paper, bond financing, equity financing, or through the bundling and securitization of MFI loans. Determining avenues to permit investment in MFIs via capital markets is an area of research that seems tailored to the tools and theory of finance academics.

In practice, there are currently several ongoing attempts to tap capital market investors for MFI funding. The ACCION Gateway Fund makes equity, quasi-equity, and debt investments in MFIs with a proven track record of financial sustainability. The AfriCap Microfinance Fund makes equity investments in African-based MFIs, as well as financing technical assistance for said MFIs. Blue Orchard Finance promotes private investments in microfinance by identification and analysis of MFIs and investment monitoring and reporting of its funds. Using a venture capital approach, ProFund International is an investment fund that attempts to earn a competitive return for its shareholders while facilitating MFI growth. Finally, the Community Reinvestment Fund provides a secondary market for microfinance loans by securitizing the microloans and collateralizing bonds that are sold to private investors⁴. If capital markets can be tapped to give MFIs the needed funds to be self-sufficient, and if investors can earn returns commensurate with the risk borne, the vision of a poverty-alleviation mechanism that pays for itself (both implicit and explicit costs) may be realized in greater proportions. Issues surrounding MFI sustainability

Analysis of microfinances' performance and development of informal institutions in Cameroon

+and self-sufficiency, and the implications/tradeoffs implied therein seem well-suited for finance researchers. Few rigorous studies have been conducted in a financial institutions framework to develop and test theory pertaining to MFI self-sufficiency.

Some evidence does exist however, that MFIs have historically been very resilient and sustainable. Hollis and Sweetman (2001) discuss the microloan funds in 18th and 19^th century Ireland. They report that Irish loan funds thrived for over 100 years due to their ability to change rapidly to external conditions, at one point providing financial services for 20% of Ireland's population. It took a combination of formal bank lobbying that resulted in anti-MFI legislation and the Irish potato famine to cause the demise of these early loan funds. Patten et al. (2001) provide a more recent historical example of the resilience of MFIs and their clientele.

They compare the performance of the Indonesian MFI Bank Rakyat Indonesia (BRI) to formal Indonesian banks during the East Asian financial crisis. They find that BRI performed superior to the formal banking sector when comparing both loan repayment rates and savings rates of members. Having discussed MFI self-sufficiency and sustainability, we now turn our attention to the products and services offered within the current microfinance framework.

II.3- Impact of Microfinance Institutions

In this section, we will discuss the impact of microfinance as measured by their impact on clients, their enterprises, households, and the communities in which they live. As a general rule, MFIs work toward a double bottom-line (financial and social) unlike the typical formal financial institution which works solely toward a financial bottom-line. Measuring financial returns is relatively straight-forward. Microfinance has borrowed liberally from the financial accounting and performance standards in the formal financial sector. Concepts such as return on equity, return on assets, portfolio-at-risk, and so forth are increasingly becoming the lingua franca of the microfinance industry⁵. Measuring social return, however, is anything but straightforward. In practice, the specific impacts of microfinance are hard to pin down and harder still to measure. Impact assessments require adoption of research methodologies capable of isolating specific effects out of a complicated web of causal and mediating factors and high decibels of random

⁵ Use of standard accounting measures of institutional performance in microfinance frequently requires adjustment to reflect financial subsidies (e.g., cash donations, in-kind donations, or other types of below-market financing) received by MFIs. Thus the common use of the concept «Financial Self-Sufficiency», which adjusts institutional profitability for the imputed market cost of subsidized financing, in lieu of profitability.

Analysis of microfinances' performance and development of informal institutions in Cameroon

environmental noise, as well as attaching specific units of measurement to tangible and intangible impacts that may or may not lend themselves to precise definition or measurement.

II.4- Literature review on the social performance of microfinance institutions

In the social performance standards report a distinction is made between the achievement of social goals by MFIs and the poverty measurement amongst microfinance clients. Also, Zeller, Lapenu & Greely (2003) argued that social performance measurement is not the same as social impact measurement. Social impact measurement should be concerned with the poverty outreach, and the changes in welfare and quality of life of microfinance clients, whereas social performance measurement is associated with the outreach measurement of microfinance programs.

II.4.1- Impact studies on microfinance

Although the number of empiric studies on the impact of microfinance from large samples of microfinance clients is growing, «measuring the impact of financial services has become one of the most controversial issues facing the microfinance industry». (Meyer, 2006, p. 225) Armendáriz & Morduch (2005) and Meyer (2006, p. 226) found several «issues of study design, data collection and statistical analysis», making impact measurement and analysis troublesome. First, appropriate poverty proxies have to measure the initial levels and the change in the poverty levels of microfinance clients and non- clients. Second, an important issue in providing empirical evidence on the benefits of microfinance is clarifying the causal role of microfinance. Accordingly, identifying reliable treatment and control groups is crucial. In more detail, while measuring the impact of microfinance programs one should (1) account for the displacement of economic activity undertaken by non-clients, (2) one should consider current and past clients by identifying previously successful and inactive microfinance graduates?, and (3) one should deal with attrition by accounting for household drop outs. (Armendáriz & Morduch, 2005) Third, Meyer (2006) considers two important forms of selection biases. The selection of microfinance clients participating in microfinance programs is likely biased. Random selection is unlikely since new microfinance clients may be: (1) more entrepreneurial, (2) willing to take risk or (3) may have more carefully been selected by loan officers. Also, the programs placement is likely to be biased, since MFIs may choose to locate their activities in areas with better infrastructure and communication facilities.

Analysis of microfinances' performance and development of informal institutions in Cameroon

II.4.2- Studies on the social performance of microfinance institutions

In 2006, Zeller & Johannsen examined the breadth and depth of outreach of microfinance in Bangladesh and Peru. The authors (2006, p. 29) find «that member based organizations, namely cooperatives in Peru and NGO-MFIs based on solidarity group lending in Bangladesh, perform best with respect to depth of poverty outreach». The authors find that a long-term relationship between the financial service provider and the client enhances the institutions financial sustainability and the programs social impact. Also, poorer populations seem to demand microcredit services rather than saving services. The authors (2006, p. 31) concluded that «MFIs that expand in rural areas, that actively target women, and that use poverty targeting indicators to screen out wealthier applicants are likely to have a higher poverty outreach». In 2007, Mersland & Strom (2007) found that the type of ownership of MFIs does not significantly influence their social performance. The authors (2008, p. 4) use Schreiner?s (2002) framework, but reject the hypothesis that greater depth in NGOs is a trade-off against lower breadth, length and scope of their activities. «NGOs are not more socially orientated that SHFs [shareholder-owned MFIs], nor are SHFs more profit orientated than NGOs», according to Mersland & Strøm (2007, p. 5). On the contrary, Gutiérrez-Nieto, Serrano-Cinca & Mar Molinero (2009) found that NGOs show the highest level of social efficiency, with the number of active women borrowers reached as their output. More recently, Lensink & Mersland (2009) explored the concept of microfinance plus?. The authors distinguish between MFIs that specialize in their financial service activities, and MFIs that provide additional non-financial service⁶.

The authors find that microfinance plus providers are: (1) NGOs, (2) unregulated by banking authorities, and (3) mainly providing microfinance services through village banking methodologies. Being part of an international microfinance network does not seem to influence whether a MFI provides plus services. Also, the authors find that microfinance plus providers reach out to poorer microfinance clients and reach out to a higher percentage of women borrowers.

The number of clients reached by the MFIs grew significantly over the period 2005-2007. The median number of active borrowers is highest in Asia. Outreach to microfinance clients grew in 2007, but at a slower pace than in previous years. Microfinance banks perform exceptionally well in terms of number of active borrowers reached. Second, MFIs in Asia seem to concentrate on solely serving women microfinance clients. MFIs in the African, Latin

⁶For example, MFIs may provide literacy training, health services, or business training to their microfinance clients.

Analysis of microfinances' performance and development of informal institutions in Cameroon

American and the Caribbean, and the Middle Eastern and North African region predominantly serve women borrowers. Less than 50 percent of the microfinance clients in the Eastern European and Asian region are women. Alternatively, NGOs and rural banks perform best in reaching out to women micro-entrepreneurs. Third, the cost per borrower ratios is calculated by dividing the operating expense by the average number of microfinance clients over a period of a MFI. The expenses per client are lowest for NGOs and rural banks, while microfinance banks face significantly higher operating expenses. Despite their aver-age number of borrowers reached, microfinance banks do not seem to benefit from economies of scale. Alternatively, the costs per borrower ratios are highest in the Eastern European and Central Asian region, and lowest in the Asian region. Fourth, the average loans balance per borrower /the GNI per capita is highest in Eastern Europe and Central Asia. Unexpectedly, the correction for GNI per capita allows for a relatively high average loan size in Africa. The average loan balance per borrower / GNI per capita is unambiguously lowest for NGOs. Banks report average loan sizes over five times as high as the average loan sizes reported by NGOs. Credit unions and NBFIs report average loan sizes in-between those reported by NGOs and microfinance banks. (MIX, 2008, 2009d)

II.4.3- Clients targeting

There are two primary issues in client targeting: first, gender targeting (lending to women versus lending to men) and second, poverty targeting (lending to the very poor and poor versus lending to the marginally poor and non-poor).

Many MFIs target primarily, or exclusively, women. This practice is based on the common belief that women invest the loans in productive activities or in improving family welfare more often than men, who are assumed to consume rather than invest loan funds. Pitt and Khandker (1998) use empirical data from Bangladesh over the period of 1991-1992 to test the hypothesis that women use borrowed funds more efficiently than men. They use household expenditures, nonland assets held by women, male and female labor supply, and boys' and girls' schooling as measurement outcomes. The authors find that although the availability of microfinance positively impacts all six areas in the aggregate, all areas are significantly affected when women borrow, but only one of the six is significantly affected when men borrow. When women borrow, but only one of the six is significantly affected when men borrow.

Analysis of microfinances' performance and development of informal institutions in Cameroon

Examining a related question, Kevane and Wydick (2001) use a sample of 342 MFI participants in Guatemala to analyze the assertion that male borrowers produce more economic growth than women and those women facilitate more poverty alleviation. They find no significant differences between men and women in generating business sales and a small advantage of employment generation by men relative to women. They attribute the difference between men and women to the role of women in childbearing.

Underlying the emphasis on lending to women is the widespread belief that access to financial services empowers women, both financially and socially⁷.Testing this belief, Amin et al. (1998) use qualitative and quantitative evidence in Bangladesh to show that membership in microfinance programs among other factors is positively related to women's empowerment. In contrast, Ehlers and Main (1998) analyze microenterprise development programs for poor US women and argue that the microfinance assistance is more detrimental and problematic than advocates believe.

As mentioned earlier, one of the most significant and controversial debates in microfinance is whether and to what extent there exists a trade-off between financial self-sufficiency and depth of outreach. Integral to this debate is whether to achieve self-sufficiency MFIs must target marginally-poor or non-poor clientele so as to capture economies of scale and cover costs⁸.

The last three articles in this section address who participates, and who does not participate, in microfinance programs and whether micro entrepreneurs are subject to credit rationing. Evans (1999) conducts an empirical examination of microfinance clients in Bangladesh. He reports that only 25% of eligible households participate and that rates of

Participation is higher among the poorer. Multivariate analysis indicates that lack of female education, small household size, and landlessness are risk factors for nonparticipation. Baydas et al. (1994a, 1994b) analyze credit rationing in Ecuador by MFIs. In one study (1994a), they construct and estimate a supply and demand model to analyze factors MFIs use to ration credit and find that micro entrepreneurs with less profitable enterprises and less education have

⁷Women's empowerment is a critical issue in the developing world context in which women routinely live at the margins of society being denied basic human rights, individual dignity, economic and educational opportunities, and social/political voice by male-dominated social norms both within society at large and within their own households.

⁸The issue of targeting has taken on more importance, as the U.S. Congress recently amended the Microenterprise for Self-Reliance Act to ensure that at least fifty percent of all the microenterprise resources it grants shall be targeted to the very poor. The very poor are defined either as those living in the bottom fifty percent below the «official» national poverty line or those living on the equivalent of less than $1 per day adjusted for purchasing power parities.

Analysis of microfinances' performance and development of informal institutions in Cameroon

smaller. Demand for microcredit. In another study (1994b), they test for evidence of discrimination against women micro entrepreneurs by formal sector lenders in Ecuador. They find that men and women have equally small probabilities of being quantity rationed for loans and conclude that gender discrimination is not widely practiced in Ecuador.

Conclusion

The purpose of this chapter has been to give a comprehensive review of the existing literature to the discipline of microfinance and microfinance institutions. We have discussed the issues of MFI Welfarists and Institutionalists approaches, The Self-Sufficiency and Sustainability of MFIs, client targeting, and impact assessment in a summary literature review.

Analysis of microfinances' performance and development of informal institutions in Cameroon

This chapter focuses on some of the concepts of microfinance and the role they play in the development of informal institutions. The concepts chosen are those that are in relation with the area of this thesis. The chapter opens with an overview of microfinance. This shows the various products and services that MFIs have and explains how importance they are to the development of non-formal sector. The next center of attention is the concept of informal sector. This gives an idea of informal sector in Cameroon. The following concern is to investigate the theoretical links between microfinance and the development of the informal sector. Further, we will explain the microfinance schism i.e. the relationship between social performance and financial performance.

The term micro-credit? was first coined in the 1970s to indicate the provision of loans to the poor to establish income-generating projects, while the term microfinance? has come to be used since the late 1990s to indicate the so-called second revolution in credit theory and policy that are customer-centered rather than product-centered (Elahi and Rahman 2006:477). But the terms micro-credit? and microfinance? tend to be used interchangeably to indicate the range of financial services offered specifically to poor, low-income households and micro-enterprises (CGAP website 2010; Brau and Woller 2004:3). Microfinance principally encompasses micro-credit, micro-savings, and micro-insurance and money transfers for the poor⁹. Microcredit, which is part of microfinance, is the practice of delivering small, collateral-free loans to usually unsalaried borrowers or members of cooperatives who otherwise cannot get access to credit (CGAP website 2010; Hossain 2002:79). And while non-financial services such as education, vocational training and technical assistance might be crucial to improve the impact of microfinance services, they are not the focus of this review. Like anyone else, poor people need an array of financial services to help them deal with a range of short to long term consumption needs and the ups and downs of income and expenses, to make use of opportunities, and to cope with vulnerabilities and emergencies. The needs of the poor for financial services have been

⁹Of late, housing finance for the poor, micro-leasing, micro franchising and other financial services for the poor have been added to the broad grouping of microfinances.

Analysis of microfinances' performance and development of informal institutions in Cameroon

categorized into three groups, namely life-cycle needs that can be anticipated (like marriage, burial and education), unanticipated emergencies (like sickness, loss of employment, death of a breadwinner, floods), and opportunities (like investing in a new business or buying land) (Matin et al. 1999:7-8)¹⁰.

The spectrum of financial services available to meet these needs includes investment (savings), lending (credit services), insurance (risk management) and money transfers. But the poor?s access to formal financial services is limited, and the services available do not acknowledge the diverse requirements of the poor (Matin et al. 1999:3). Instead poor people tend to juggle financial relationships with various financial institutions (and with friends and family) to have the flexibility and reliability they need (Collins and Morduch 2010:23). They depend on various types of formal and informal community funding, credit unions, moneylenders, cooperatives, self-help groups and associations (like accumulating savings and credit associations, rotating savings and credit associations, burial societies), and financial NGOs. And with commercial financial institutions considering ways in which to provide financial services to the poor in a profitable manner, microfinance services are now provided by a whole spectrum of role players. To categorize the various financial institutions, Matin et al. (1999:5) created a three-by-three matrix, with one axis comprising the financial service components (savings, credit and insurance) and the other axis the providers (informal, formal, and semi-formal providers). Rutherford (1996) based his categorization on the type of service as well as whether it is owned and managed by the users themselves or other providers, while Staschen?s typology (1999:7-8) is based on the source of funds. The reality then is a mix of financial services accessed by poor people from a variety of service providers, depending on local knowledge, history, context and need (Matin et al. 1999:9).

III.1.2- Overview of microfinance in Cameroon

In Cameroon, studies on the efficiency of microfinance institutions in poverty reduction are relatively scarce. Monkam et al (2001) show, through financial ratios that MFIs are sustainable even if the cost of money remains expensive. However, this study emphasizes the financial aspect at the expense of the original objectives of MFIs that are consistent with the accessibility of financial services to poor and their role in the fight against poverty as formulated in the PRSP.

¹⁰Matin et al. (1999:6) refer to the role of financial services in meeting these needs as a protective role (to help cope with risks) and a promotional role (to provide a return).

Analysis of microfinances' performance and development of informal institutions in Cameroon

Similarly, Djeuda & Heidhues (2005) are simulations of growth M (Community Growth Mutual Funds) using a Cobb - Douglas model in the analysis of cost behaviour. But the study is only interested in the growth of the structure while the question of whether the granting of credit to the poor is effective. However despite this lack of research focused specifically on the effectiveness of MFIs, there are studies that propose a descriptive inventory of the supply by MFIs. This inventory shows that the supply by MFIs in Cameroon relates generally to savings, credit, and remittances. This offer is provided by three categories of MFIs described by Creusot (2006):

? The first category consists of MFIs who deal only with their members. These are cooperatives, associations;

? The second comprises MFIs that provide financial services to third parties. They have the status of limited company;

? The third is composed of MFIs that offer credit and are not allowed to mobilize savings. Moreover, with the deposits amounting to 300 billion and outstanding loans standing at 200 billion at the end of December 2010, the microfinace sector has a customer base of about 1.2 million clients. In 30 June 2011, out of 480 approved MFI, close to fifty were under liquidation, suspension of activities, adjustment and/or temporary administration. In a bid to strengthen financial reporting, COBAC accelerated the putting in place of the «Microfinance Activity Evaluation and Supervision System» (SESAME)

whose accounting component entered into force in June 2010. The microfinance sector employs about 6000 workers of which 732 senior staff and has six principal approved networks namely: CAMCCUL (about 177 MFI), CVECA(41), CMEC(27) and M. Another network, MUCADEC is being approved.

There are 386 MFI under category I, 43 under category 2 and 4 under category 3. Category 2 MFI occupied the leading position in terms of geographic coverage and market share. They accounted for more than half of deposits and loans.

Analysis of microfinances' performance and development of informal institutions in Cameroon

At the end of 2010, about twenty MFIs had a volume of deposits above one million, half of which are under category 2. Regarding network MFI, CAMCCUL collected deposits of more than 85.4 billion. As concern independent MFI, Crédit Communautaire d'Afrique collected 66.5 billion. Loans were mainly short-term (63%) and medium-term (34%). The bulk of loans where granted for trade (39%) and consumption (27%). In terms of market share, with close to 57.3 billion, CAMCCUL accounted for more than one-quarter of loans.

Interest rate remained quite high despite stiff competition in the sector. Debit rate were between 4% and 30% per year for an average intermediation margin of 17%. Interest rates in the microfinance sector ranged from 6% to 33% for interest expenses and from 1% to 10% for interest income. Regarding prudential ratio, out of a sample of 50 MFI, half of them complied with the liquidity, risk coverage and fixed assets coverage ratios. Only some ten MFI had sufficient own funds.

Analysis of microfinances' performance and development of informal institutions in Cameroon

Liabilities	Amounts (million fcfa)		Assets	Amounts (million fcfa)
Capital	42	283	Fixed assets	44	802
Shares	38	902	Loans	221	378
Fixed deposits	373	872	Others	39	397
Others	35	870	Cash	152	786
Cash	6	338
Total	458	363	Total	458	363

The total aggregated balance sheet of MFIs in Cameroon at the end of December 2010 is established at FCFA 458,363 billion. It represents 15.7% of total assets of commercial banks in the same date. 80% of the main activities of microfinance sector are covered by MFIs of first category. The most important structures are CAMCCUL network and Crédit Communautaire d'Afrique (CCA), with respectively 70,081 and 119,211 billion of total assets at the end of 2010.

The financial intermediation operations are important in the balance sheet structure and reinforce the activities of this sector. Deposits collected, represent an amount of FCFA 373,872 billion and correspond to 81.5% of the total aggregated balance sheet. They represent 15.5% of total deposits collected by commercial banks in Cameroon. They are largely from CAMCCUL network (95.85 billion), CCA (65,656 billion) and COMECI (17,575 billion). However, the cash outstanding loans are estimated at FCFA 223,563 billion, or 49% of consolidated total assets. Based on the level of lending by commercial banks, they represent approximately 15.7%.

Net cash microfinance is lending of FCFA 146,448 billion on 31st December 2010. It is usually held in the form of cash in hand, deposits held at call with local correspondents and, accessorily, in the form of investments in certificates of deposit or government bonds. Thus, it highlights the problem of the management of cash surplus in Cameroon MFIs.

Analysis of microfinances' performance and development of informal institutions in Cameroon

Table3: evolution of microfinance activities in Cameroon from 2002 to 2010.

Years	Issued capit*	Fixed deposit*	Gross loan*	Number of MFI	Member/clients /number	Countrs number	1st cat MFI	2^nd cat MFI	3rd cat MFI
2002	6781	66727	44748	601	331006	695	587	14	0
2003	9501	55769	56077	301	462585	749	582	19	0
2004	13666	98743	65402	567	541980	756	532	35	0
2005	16974	116840	70795	453	460706	879	404	35	0
2006	19887	162427	104173	453	849030	1052	418	35	0
2007	25323	194830	117233	460	962627	1111	420	38	2
2008	22.23	258220	138523	470	1073621	983	420	38	2
2010	42.283	373872	221378	490	/	/	442	44	4

III.1.3- Evolution of equities

The financial structure of MFIs has strengthened. Indeed, the equity of the sector rose to about 35%, from 27,511 in 2008 to 42,283 billion at the end of 2010. It should be noted that the capital structure displayed by the sector (27,511 billion) represent 19.8% of those commercial banks in Cameroon at the same date.

The importance of first category of MFIS is not negligible. CAMCCUL network is the largest settlement funded with shares subscribed and paid that amount to 7571 billion. It is followed by CCA and ADVANS Cameroon, which belongs to the second category, which have subscribed and paid up capital respectively of 3 billion and 2500 billion. Some MFIs of second category are in the process of important recapitalization, thus it is noted that the CCA in early 2010 increased its capital to 5 billion FCFA, COMECI launched a program of action to go to 3 billion FCFA, First Trust follows the same trend with new entrants in the capital.

Since 2005, commercial banks are increasingly interested in this sector developed by the MFI, and thus BICEC entered the capital of ACEP, SGBC created in 2006 with other partners (Horus Finance) ADVANS. Eco Bank has partnered with ACCION International to launch in early 2010 EB-ACCION Microfinance Cameroon (EAMF). Apart from these initiatives, we must add those already underway for over a decade. This is first Afriland First Bank, which in 1992 embarked on the promotion of M and MUFFA, BICEC with CVECA (focus on refinancing) in the middle 1990s and the Union Bank of Cameroon (UBC) and the CAMCCUL network since 1999,

Analysis of microfinances' performance and development of informal institutions in Cameroon

collaboration will be strengthened with the entry of OCEANIC BANK International shareholding in UBC. Just because these institutions are good customers for them, profitable and safe, because their risk is spread over thousands of small loans. In addition, commercial banks in microfinance are an extension of their business into new markets. Microfinance, which attracts private capital to those who need it most, opens unprecedented opportunities.

Several private investors have entered in Cameroon include: BLUE FIANANCE into CADECI MFI in first category, ECP (first Trust), AFRICAP or MAURITUS MECENE (The Regional), CORDAID (CECAW) and RABOBANK (CECAW and MUCEPI).

III.1.4- Profitability of microfinance sector

Mainly due to the poor quality of loan portfolios, the profitability of Cameroon MFI is generally low and highly dependent, for structures that are profitable, grants and funding received from the Government (HIPC and other projects) and / or external donor funding. Thus, despite the above noted performance, the financial situation of the microfinance sector in Cameroon is generally troublesome. In general, it appears that independent MFI, including first category are characterized by fragile financial situations. Only MFI in a network and those benefiting from the technical assistance of a regular partner (ADAF case for M), have an acceptable financial situation.

Microfinance institutions in difficulties include: FIFFA, CICA, EDPS, CPAC, CAMAC. The situation is also worrying for authorized networks. Of the six networks, two, despite some shortcomings, financial situation acceptable (CAMCCUL and A3C), both have a marginal activity (CMEC CMEC West and North), one has not yet reached financial independence (ECSC CVECA North) and is out of business since 2008.Two microfinance institutions COFINEST SA and FCIC, respectively, were placed in liquidation (after nearly three years of provisional administration) and under provisional administration by COBAC.

Despite this situation as a leader in the sub-region of Central Africa, the microfinance sector and in this case the supply of microfinance services has serious shortcomings. For industrial actors, these failures are generic. First, MFIs in Cameroon are characterized by unequal distribution of the national territory. One can also observe their high concentration in the central, Littoral and West regions. MFIs independent grant a preference to install their seats in urban areas specifically Yaoundé, Douala and Bafoussam, while networks are much more rural.

Analysis of microfinances' performance and development of informal institutions in Cameroon

Moreover, the deposits are concentrated among a small number of MFIs (networks in this case). Then, the expansion of savings is remarkable but it is accompanied by a low coefficient of transformation of these credit resources, covering imperfectly financing needs in the short, medium and long term customer. Access to external financing is very limited due to lack of suitable guaranteed mechanisms. Finally, intermediation between Bank and MFI is low as well as dialogue between different stakeholders.

Also, the state has, for the moment, a very insufficient role in promoting the sector and service offerings in particular, regardless of the definition of a national strategy for development of the microfinance sector in the PRSP and the establishment of a sub-department in charge of microfinance in the Ministry of Finance.

The original use of the term informal sector' is attributed to the economic development model put forward by W. Arthur Lewis, used to describe employment or livelihood generation primarily within the developing world. It was used to describe a type of employment that was viewed as falling outside of the modern industrial sector. An alternative definition uses job security as the measure of formality, defining participants in the informal economy as those 'who do not have employment security, work security and social security.» While both of these definitions imply a lack of choice or agency in involvement with the informal economy, participation may also be driven by a wish to avoid regulation or taxation. This may manifest as unreported employment, hidden from the state for tax, social security or labour law purposes, but legal in all other aspects.

The term is also useful in describing and accounting for forms of shelter or living arrangements that are similarly unlawful, unregulated, or not afforded protection of the state. Informal economy' is increasingly replacing informal sector' as the preferred descriptor for this activity.

Informality, both in housing and livelihood generation has often been seen as a social ill, and described either in terms of what participant's lack, or wish to avoid. A countervailing view, put forward by prominent Dutch sociologist Saskia Sassen is that the modern or new informal' sector is the product and driver of advanced capitalism and the site of the most entrepreneurial aspects of the urban economy, led by creative professionals such as artists, architects, designers

Analysis of microfinances' performance and development of informal institutions in Cameroon

and software developers. While this manifestation of the informal sector remains largely a feature of developed countries, increasingly systems are emerging to facilitate similarly qualified people in developing countries to participate.

III.2.2- Informal sector in Cameroon

The informal sector in Cameroon is expanding rapidly: it contributes 39% to total employment. Without any doubt it has increased further since; some even estimate that 85% of all those employed outside agriculture are now working in the IS. While formal sector jobs have gone predominantly (82%) to men, women work almost exclusively (95%) in the IS.

In Contrary to other countries where information on the informal sector is hard to come by and often outdated, recent information is available albeit referring only to informal employment in Yaoundé (see Fluitman and Momo 2001). The survey provides interesting information on urban IS enterprises in Cameroon in 12 selected trades32/ (including informal internet cyber). It particularly studied the education and training background of the IS producers interviewed.

The results of the survey indicate that the non-formal institutions are still the resort of people who migrate from the rural areas: over three-quarter of the entrepreneurs were not born in Yaoundé and almost half of them grew up in farmers' homes. Interestingly, the younger IS producers surveyed are not only more likely to be born in Yaoundé but also in families of wage workers. The owners of IS enterprises, who in earlier studies were found to be surpassed in education by their TAps and workers, to have reached a higher educational level than those that work under them. Income in the surveyed trades was low, with the net profit of owners of leather workshops estimated to only US $43 per month. It was somewhat higher for women's dressmakers, cyber cafes and restaurants, and highest in garages (mean US $177, but half of them less than US $88).

III.3- Theoretical links between MFIs and informal sector development

Accessing credit is considered to be an important factor in increasing the development of SMEs. It is thought that credit augment income levels, increases employment and thereby alleviate poverty. It is believed that access to credit enables poor people to overcome their liquidity constraints and undertake some investments such as the improvement of farm technology inputs thereby leading to an increase in agricultural production (Hiedhues, 1995).

Analysis of microfinances' performance and development of informal institutions in Cameroon

The main objective of microcredit according to Navajas et al, (2000) is to improve the welfare of the poor as a result of better access to small loans that are not offered by the formal financial institutions.

Diagne and Zeller (2001) argue that insufficient access to credit by the poor just below or just above the poverty line may have negative consequences for SMEs and overall welfare. Access to credit further increases SME?s risk-bearing abilities; improve risk-copying strategies and enables consumption smoothing overtime. With these arguments, microfinance is assumed to improve the welfare of the poor.

It is argued that MFIs that are financially sustainable with high outreach have a greater livelihood and also have a positive impact on SME development because they guarantee sustainable access to credit by the poor (Rhyne and Otero, 1992).

Buckley (1997) argue that, the indicators of success of microcredit programs namely high repayment rate, outreach and financial sustainability does not take into consideration what impact it has on micro enterprise operations and only focusing on «microfinance evangelism». Carrying out research in three countries; Kenya, Malawi and Ghana, Buckle (1997) came to the conclusion that there was little evidence to suggest that any significant and sustained impact of microfinance services on clients in terms of SME development, increased income flows or level of employment. The focus in this augment is that improvement to access to microfinance and market for the poor people was not sufficient unless the change or improvement is accompanied by changes in technology and or technique.

Zeller and Sharma (1998) argue that microfinance can aid in the improvement or establishment of family enterprise, potentially making the difference between alleviating poverty and economically secure life. On the other hand, Burger (1989) indicates that microfinance tends to stabilise rather than increase income and tends to preserve rather than to create jobs.

Facts by Coleman (1999) suggest that the village bank credit did not have any significant and physical asset accumulation. The women ended up in a vicious cycle of debt as they use the money from the village banks for consumption purposes and were forced to borrow from money lenders at high interest rate to repay the village bank loans so as to qualify for more loans. The main observation from this study was that credit was not an effective tool to help the poor out of poverty or enhance their economic condition. It also concluded that the poor are too poor because of some other hindering factors such as lack of access to markets, price stocks, unequal

Analysis of microfinances' performance and development of informal institutions in Cameroon

land distribution but not lack of access to credit. This view was also shared by Adams and Von Pischke (1992).

A study of thirteen MFIs in seven countries carried out by (Mosley and Hulme (1998) concludes that household income tends to increase at a decreasing rate as the income and asset position of the debtors is improve. Diagne and Zeller (2001) in their study in Malawi suggest that microfinance do not have any significant effect in household income meaning no effect on SME development. Investing in SME activities will have no effect in raising household income because the infrastructure and market is not developed.

Some studies have also argued that using gender empowerment as an impact indicator; microcredit has a negative impact (Goetz and Gupta, 1994; Ackerly, 1995; Montgomery et al, 1996). Using a «managerial control» index as an indicator of women empowerment, it came to conclusion that the majority of women did not have control over loans taken by them when married. Meanwhile, it was the women who were the main target of the credit program. The management of the loans was made by the men hence not making the development objective of lending to the women to be met (Goetz and Gupta, 1994). Evidence from an accounting knowledge as an indicator of women empowerment concluded that women are marginalized when it comes to access to credit (Ackerly, 1995).

III.4- Microfinance schism

According to the 1997 World Microcredit Summit, the poorest are those who belong to the lower half of the group of people who live beneath the 1$ a day per capita poverty threshold. The best manner to help the poor accessing financial services causes debates between Welfarists and Institutionalists. Although they share the objective of poverty alleviation, these two approaches place the microfinance at crossroads (Table 3). The former emphasizes impact on the borrower as the core mission of MFIs whereas the latter aims at integrating microfinance in the financial markets (Cornée, 2007). The "schism of microfinance» (Morduch, 1998) stands as a trade-off between targeting the poor and ensuring the profitability of MFIs.

III.4.1- The welfarists' approach

Using the denomination coined by Woller et al. (1999), welfarists are identified as a school of measurement of the poverty, according to which, "an individual is regarded as poor when he (or she) is beneath a given threshold to be well off in terms of economic standards.

Analysis of microfinances' performance and development of informal institutions in Cameroon

This school aims at the very poor who are generally riskier and less accessible (rural population, people living in remote areas). It is primarily made up of NGOS or co-operatives, which regard microfinance as a major tool for reducing the poverty of poorest (Hamed, 2004). As it promotes a strategy for improvement of the wellbeing of the poor populations (Mayoux, 1998), it seeks to measure the impact of micro credit on the living conditions of the targeted populations, i.e. the change in terms of wellbeing and quality of life of the recipients. Welfarists concentrate on the level of poverty of the customers and emphasize the fast improvement of their living conditions, even with a broad recourse to subsidies. Although they insist on rational resources management and do not abstain from having a profitable activity, they do not without the need and the advantages that subsidies bring to MFIs, even on the long run (Olszyna-Marzys, 2006).

This approach, which is depends on subsidies, has generated refunding rates below 50% as well as very high operation costs leading to the failure and the disappearance of some MFIs: Such was the case for the NGO Corposol in Colombia, Caisses Populaires in South central Cameroon, Projet de Promotion du Petit Crédit Rural (PPPCR) in Burkina Faso and Crédit Mutuel in Guinea (Woolcock, 1999; Labie, 2002). MFIs face the issue of sustainability, the lack of which blocks their development and their capacity to contribute to the wellbeing of the people that they support. Thus, the welfarists? approach has been subject to many criticisms as regards costs and methodological problems (De Briey, 2005). A revival of financial thought took place in order to study the conditions of successful MFIs. The concern expressed by economists and experts for the effectiveness of MFIs in the struggle against poverty led to apprehend effectiveness more and more in financial and accounting terms.

III.4.2- The institutionalists' approach

Supported by international organizations such as the World Bank and the United Nations, the institutionalists? approach (Woller et al., 1999) considers that the one best way to reach the large majority of the poor without access to financial services is to integrate microfinance in the formal financial system. It seeks to encapsulate MFIs within the logic of the "money market", while insisting on the will of the installation of perennial microfinance systems as well as on mass distribution of credit (De Briey, 2005). Each MFI should aim at financial sustainability by maximizing its effectiveness and its productivity, in order to reach financial autonomy.

Analysis of microfinances' performance and development of informal institutions in Cameroon

This emphasis on self-sufficiency started from awareness that funds are scarce. Institutionalists believe in the need for a large scale intervention, which requires financial resources beyond the amount the national or international backers (donors and investors) can provide. They fear the backers? fickleness, because a MFI searching for sustainability that becomes structurally dependent on subsidies, would likely be a program without a future. The only means of obtaining the necessary financial resources is to resort to private sources (savings, commercial debts, own capital stocks and capital risk). Institutionalists designed a set of best practices, which aim at enhancing efficiency as regards management systems, finance and accountancy, marketing, services delivery, etc. The adoption of such practices is an essential stage to reach large scale financial self-sufficiency, to access the money market, and to reach the maximum of poor customers: This win-win approach contends that: "Institutions following best practices are also those which succeed better in fighting poverty" (Morduch, 2000).

Institutionalists emphasize the performance evaluation from the standpoint of the institution rather than from that of the customers: They consider financial autonomy as a criterion which fulfills their social mission as well as possible (Cornée, 2007). They cover two main trends. On the one hand, the upgrading process of some MFIs (such as regulated NGOs in the countries which regulate microfinance specialized agencies), gives birth to regulated financial institutions, which clearly fit in a logic of profitability (De Briey, 2005). On the other hand, the more recent downgrading process of village co-operatives and some commercial banks searching for new market niches and convinced by the potentialities of micro credit, led establishments that have an easier access to funds and better marketing tools, such as Rakyat Bank of Indonesia and BancoSol in Bolivia, to enter the microfinance sector: Thus, they can directly grant credit to micro-entrepreneurs or take participations in MFIs.

The institutionalists? approach faces also some criticisms. Concerning the targeted population, its core customers are micro-entrepreneurs very close to the poverty line, geographically, concentrated, with high-output activities and short production cycle. It requires rather high interest rates from customers in order to ensure financial autonomy within a period of five up to twelve years. However, the goal of financial and institutional viability remains out of reach for most MFIs (De Briey, 2005).

Analysis of microfinances' performance and development of informal institutions in Cameroon

	Welfarists	Institutionalists
Approach	Performance evaluation from the standpoint of customers: - Social outreach - Impact assessment	Performance evaluation from the standpoint of the institution: - Broadness of the MFI - Sustainability of the MFI.
Targeted customers	Very poor ($1/day)	Micro-entrepreneurs close to the poverty line ($2/day)
Type of institutions	Social bonds	Commercial contracts
Methodology	Resort to subsidies	Financial self-reliance
Criticisms	- Sustainability issue - High operation costs - Various impact measurement methods - Failures (refunding rate < 50%)	- Customers selection bias (MFIs do not reach the very poor) - High interest rates - Long term self-reliance strategy
Common goal	Poverty alleviation

III.5- Social performance

Struggling against poverty is the mission of microfinance. The analysis of the outcomes

of this mission enables to evaluate the social performances of MFIs according to two complementary steps: An evaluation based on the institution according to its outreach and an evaluation based on its customers according to impact assessment.

III.5.1- Outreach

MFIs make efforts in order to serve those who are constantly excluded from official

financial systems: Their operation rests on the social bonds and the proximity with the recipients while moving into the rural zones, by contacting them and in their offering training sessions. They are based on group work and meet the needs of the populations by supplying small amount loans and regular refunding. The goal, which aims at extending microfinance services to the populations that are not served by official financial institutions, defines outreach (Lafourcade et al., 2005). However, MFIs must determine which group-target they must satisfy.

Analysis of microfinances' performance and development of informal institutions in Cameroon

Poverty, by its multidimensional nature, covers various aspects of the households? economic and social status. To capture these dimensions requires at the same time quantitative and qualitative indicators. Poverty is quantitatively defined as being a given daily (or yearly) income, for people without provision of a stock. It is also qualitative as it takes into account their living conditions (Lelart, 2006). It can integrate data such as the needs for food and clothing, housing availability, level of educational, health care, women empowerment, level of integration within the social background, etc. In this respect, extending accessibility to financial services for these poor seems the major goal of MFIs: Thus it raises the question if they do manage to reach the poorest (Van Bastelaer and Zeller, 2006).

Some indicators, used as proxies, enable the measurement of outreach: The extent or scale of outreach corresponds to the numbers of customers, total outstanding portfolio and volumes of services such as total savings in deposit (Lafourcade et al., 2005); the depth of outreach corresponds to the social and economic characteristics of the customers served by MFIs, i.e. the level of poverty of these customers as regards very low income and rural populations, women and/or unemployed. Schreiner (2002) worked out outreach indicators according to six dimensions, each one of which can also correspond to a component of social value: Worth of outreach measures the wealth of customers, cost of outreach measures transaction costs, scope of outreach measures the number of customers that are served, length of outreach measures the time delivery for requested services, depth of outreach measures the accuracy of targeting and breadth of outreach measures the number of services that are provided.

Studies of outreach devoted to the analysis of the characteristics of MFIs customers show that some institutions tend to be exclusive and are not accessible to all categories of population. Although customers are not necessarily among poorest (Lelart, 2006), according to their characteristics they belong to poor or vulnerable population such as individuals practicing survival productive activities, who do not access the banks and who are mainly female customers (Soulama, 2005). This latter characteristic is particularly significant in several programs such as Bancosol in Bolivia (74% women), BRAC (75%) and Grameen Bank (95%) in Bangladesh, as well as in East and Central Africa (Kenya, Malawi, Cameroon, etc.). Outreach varies according to the type of MFIs and across areas (Lafourcade et al., 2005), but the coverage rate of poor remains weak.

Analysis of microfinances' performance and development of informal institutions in Cameroon

III.5.2- Impact assessment

Social performances can be evaluated though the analysis of impact on the customers, i.e. answering the following question: "What is the payoff of a dollar lent in terms of additional income for the recipient?" (Lapenu et al., 2004). The impact consists in understanding how financial services affect the existence of poor; it represents the changes on customers that are ascribable to the action taken by the MFI. These changes constitute the social output of an investment provided by lenders (or donors) that are backing MFIs; the latter need to know if the financial support they bring to MFIs achieved well the goal that they set: Thus, they are concerned with the outcomes estimates (Lelart, 2006).

It seems natural to measure the impact of micro-credit, but some recognized microfinance experts are sceptical and decide against a thorough evaluation of impact on the following grounds: Impact studies are expensive, especially if they are regularly repeated; most impact analyses do not respect rigorous criteria in cases of changes observed in the customers? life that do not directly depend on MFIs but rather on other factors. The measurement of impact raises methodological problems: The calculation of income (or expenditure) must be adjusted according to Purchasing Power Parity and loan size is not an accurate indicator of poverty (Van Bastelaer and Zeller, 2006). However, in spite of these shortcomings, investigations prove to be necessary and must be multiplied in order to compare their results. Most used criteria to evaluate the impact of MFIs on recipient populations are the improvement of incomes and consumption, the start-up of very small businesses and generally speaking the improvement of living conditions.

III.5.2.1- Impact on income

Real impact of MFIs on the income of poor has been reviewed as regards various experiments in South Asia, Africa and Latin America (Montalieu, 2002). The first impact studies carried out by Hulme and Mosley (1996) relate to 13 MFIs located in seven countries (Indonesia, Kenya, Bolivia, Malawi, Bangladesh, India and Sri Lanka), which were operating between 1989 and 1993. They show that the granting of credit had a positive impact on the income of poor borrowers; impact was all the more important if MFIs just drive their action towards borrowers standing above the poverty line who request risky loans intended to invest in technologies and to continue activities which are more likely to increase income flows (CGAP, 1997). By contrast,

Analysis of microfinances' performance and development of informal institutions in Cameroon

very poor borrowers seek to ensure their subsistence thanks to weak amount loans and do not invest in an economic activity, accumulate capital or hire workforce (Hulme and Mosley, 1996).

Other impact studies corroborate the assumption of a positive effect of microfinance on the borrowers? income: In Guinea, Nicaragua and Benin, as regards three credit systems monitored by IRAM (Doligez, 2005) as well as in Burkina Faso, whereby comparative analysis of the situation of recipients vs. non recipients showed that recipient women could carry out multiple productive activities and diversify their sources of income, while improving and stabilizing the average income drawn from their activity (Soulama, 2005).

III.5.2.2- Impact on consumption

Micro-credit involves an increase in income which is intended for the improvement of daily consumption; it enables to ensure food and clothing, to build or acquire a housing, to buy animals or durable consumer goods etc. Customers can also borrow to carry out investments in human terms, such as healthcare and education or to pass from a crisis to another.

III.5.2.3- Impact on start-up businesses

Microcredit allows the borrower to start up a small business, which initiates activities generating incomes. Although some micro-entrepreneurs can start their activity thanks to their personal savings (supplemented by gifts and loans from their relatives), they face a financing problem once they have launched their activity, because they are unable to obtain a credit from a bank. Microcredit has a positive impact on the income of these small start-up businesses: Variables which determine and contribute for this positive outcome are job creation, profit and sales turnover, accumulation of assets and output (Hamed, 2004). Household customers often create jobs for other households and job opportunities are thus offered to poor.

Various studies highlight the positive impact of micro-credit on income, consumption and the activity of small businesses (Pitt and Khandker, 1998; Pitt et al., 2003), while other studies emphasize some negative impacts (Adams and Von Pischke, 1992; Rahman, 1999). Afar these two positions, various impact studies present mitigated outcomes: They question the efficiency of microfinance in the struggle against great poverty or dispute the reliability of most currently used methods of evaluation (Hulme and Mosley, 1996; Morduch, 1998).

Social performances cannot be limited to the targeting of poor and to impact analysis, but must relate more largely to the way in which MFIs continues its social mission. The model of

Analysis of microfinances' performance and development of informal institutions in Cameroon

social performance evaluation (Social Indicator Performance, SPI) developed by CERISE¹¹enlarges the framework of social performance, which encompasses four major dimensions: Targeting the poor and excluded population, adjustment of services to the targeted customers, improvement of the customers? social and political capital and MFIs social responsibility with respect to their customers, staff and environment (Lapenu et al., 2004). Other models have already been designed such Balanced Scorecard and Global Reporting Initiative, which take into account the stakeholders of MFIs, standing as any individual or group of individuals who can affect or be affected by the achievement of the goals of the enterprise or institution (Cornée, 2007).

III.6- Financial performance

In order to expand microfinance, financial performance has been emphasized. As regards

evaluation of this performance, a large set of indicators have been in use, most of which became standard. Although there is no consensus on their definitions and their calculation methods, indicators were institutionalized in the sense that they correspond to durable rules which are compiled by the microfinance community. Among several dimensions, various ratios of profitability provide the most important measurement of financial performance.

III.6.1- Determinants of a profitable institution

Generally speaking, for an institution to be profitable over one period, its resources

should at least cover its expenditure. Profitability may be reached according to two pathways: One is to reduce expenditure, more precisely the transaction costs; the other consists in enlarging output by increasing the interest rate on credits.

III.6.1.1- Reducing transaction costs

A transaction will take place through a process of identification, meeting and negotiation

between the partners that are concerned (Howitt, 1985). Thus it generates costs, which should be specified according to their nature and origin (Diamond, 1987).

Poor population is a very risky population related to high transaction costs. Being given that MFIs cannot elucidate all information on their customers, they try to minimize their default

¹¹Comité d'Echanges, de Réflexion et d'Information sur les Systèmes d'Epargne.

Analysis of microfinances' performance and development of informal institutions in Cameroon

risk. On the one hand, they adopt innovating strategies such as close collection of refunding, constitution of interdependent groups, literacy programs, management training of the customers and monitoring: All these elements generate high operation costs. In addition,

MFIs grant weak amount loans because they do not distinguish good from bad customers, especially as regards start-up businesses. To these costs of failure are added then administrative costs. Most typical and serious errors often concern recruitment and staff management policy: Some MFIs increase progressively the number of agents with the increase of customers and the opening of local agencies, without evaluating beforehand short and medium term profitability of their operations (Lelart, 2006). The reduction of transaction costs is one of the surest and effective means enabling to build self-reliant, viable and efficient institutions. To cut costs to the minimum, especially ex-ante costs, the technique of proximity is generally used by the lenders and very often, the literature is restricted to defend this recourse.

Reaching poor customers who never had recourse to formal banking services requires more interaction with the customers and more time from the staff of the financial institution, which implies additional costs. Costs of time use constitute the transaction costs for the MFI. They are ex-ante, as regards costs of research of the funds to be lent, information retrieval on the borrower, negotiation on the terms of contract, evaluation of the borrowers and the project, design and registration of contracts, costs of personnel, expenses for training both the staff and the customers, transportation and communication in order to meet poor population; these primary transaction costs are mostly of legal nature. In addition, costs are ex-post, as regards the operation of contracts, costs of administration, monitoring and control of the execution of agreements, in order to take care of the contractual clauses, provisions, depreciation as well as the costs of missed opportunities because of the agreements such as adjustment costs to correct initial agreement or to establish another better agreement. These various non-financial costs are transaction costs supported by the MFI and may be gathered in three large headings. (Box 1).

OE = Operating Expenses (expenses for personnel + other administrative expenses + other operating expenses)

Analysis of microfinances' performance and development of informal institutions in Cameroon

III.6.1.2- Carrying out a financial margin

MFIs need to be financially autonomous in order to ensure financial intermediation. That

can be reached by carrying out a financial margin (Box 2), i.e. a sufficient positive differential between the rate paid by MFIs to access funds and the rate earned on loans, so as to cover both direct and indirect costs related to the activity (Labie, 1996).

Financial Assets: assets ensuring financial returns (investments, gross value of loan portfolio, etc.)

III.6.2- Perennial MFIs

Perennial MFIs can be envisioned from two angles: Life cycle and dependence upon subsidies.

III.6.2.1- Life cycle

The life cycle of a (successful) MFI represents an ideal way to reach financial balance and thereafter become perennial (Otero and Drake, 1993): It corresponds to the transformation of a supportive institution towards a thorough financial intermediation institution, according to a three phases process (Box 3).

The first phase of "demonstration" defines an operating mode adopted by the supportive institution, which enables it to lend to poor according to its environment and its constraints, and that it will progressively refine with its experiment. The phase of "second generation" must lead the institution, which has now reached a certain maturity, to consolidate its operating mode in order to tend towards relative autonomy. The last phase is that of the "operational development related to expansion", within which the transformation into a true bank dedicated to poor can be considered, especially in many countries where regulations prohibit NGOs to collect savings (Cornée, 2007): The institution aims at gradually providing the function and the status of a financial intermediary. Seven variables should evolve during these three phases: Administrative duty, customers, financing sources, methodology for the provision of financial services, financial management, autonomy and staff training (Counts et al., 2006).

Analysis of microfinances'performance and development of informal institutions in Cameroon

Perennial MFIs can be envisioned from another angle: Regarding access to financial Autonomy as a decreasing function of subsidies necessary to the operation of the MFI programs (Otero and Rhyne, 1994, in Labie, 1996), according to a process that encompasses four levels (Box 4).

			Dependence upon subsidies Time

Large subsidies Necessay ubsidies Doing without subsdies Financing through savings

Are below operation costs; subsidies are the resources covering these costs and feed the

Loan funds decrease due to inflation and non-refunding from customers (Hamed, 2004). The institutions of the second level carry out interests that cover the cost of funds and part of administrative expenses; subsidies remain necessary to finance some operating elements and institutions borrow below the market rate. The institutions that reach the third level are those which for most of subsidies are eliminated; nevertheless they cannot do without some subsidies, although this stage is necessary to reach a volume of operation on a large scale.

The passage of the third level to the fourth level whereby MFIs become a true intermediate pole requires time; this last level is reached when the program is entirely financed thanks to the customers? savings and funds raised through market rates from official financial institutions (Labie, 1996). However, very few programs have reached this level, although it is regarded as an essential condition for perennial MFIs; most cases, which are generally at the third level, are those one regards as successful, e.g. Grameen Bank.

With respect to the two solutions at hand, reducing transaction costs or increasing the interest rate, few MFIs manage today to reach balance at their starting point. In general, reducing transaction costs proves to be difficult; indeed, it is necessary to increase the interest rate,

Analysis of microfinances' performance and development of informal institutions in Cameroon

although this solution is far from being the best strategy. The recourse to subsidies proves to be necessary when MFIs begin their activity and carrying out a financial margin is the key element of any long-term strategy.

III.7- The mission drift of MFI: The institutionalists and the welfarists III.7.1- The concept of mission drift

At the heart of the debate, the question arises whether a trade-off between the financial sustainability and efficiency and the outreach to the poorest microfinance clients by MFIs exists. The occurrence of a trade-off between the financial and social performance of MFIs is captured by the concept of mission drift.

Armendáriz & Szafarz (2009, p. 2) defined mission drift as «a phenomenon whereby an MFI increases its average loan size by reaching out wealthier clients neither for progressive lending nor for cross-subsidization reasons». In other words, an increase in average loan sizes may result from progressive lending, whereby microfinance clients reach out to higher credit ceiling based on their performance and demand. Also, average loan sizes may be higher resulting from cross-subsidization. Cross-subsidization means that a MFI reaches out to the wealthier unbanked, using larger average loan sizes, in order to finance a larger pool of the poorest unbanked, using small average loan sizes. Instead, the authors argue that mission drift occurs because MFIs find it more profitable to reach out to wealthier clients while crowding out poorer clients. In addition, the authors add that mission drift can only occur when MFIs announced mission is not aligned with the MFIs maximization objective.

Cull et al., (2007, p. 23) underlined that mission drift occurs when MFI show «a shift in the composition of new clients, or a reorientation from poorer to wealthier clients among existing clients».

Mersland & Strøm (2009, p. 3) reported that «if mission drift occurs, the MFIs outreach to poor customers, its depth of outreach (Schreiner, 2002), is weakened». In practice, the average loan size is the most common used proxy for measuring the depth of outreach¹². Alternatively, the authors argue that increasing the depth of outreach implies increasing the outreach to women clients. Also, the authors argue that switching from the group-based lending methodology to the individual lending methodology can be an indication for the occurrence of mission drift.

¹² Schreiner (2002), Cull, Demirguç-Kunt & Morduch (2007), and Mersland & Strøm (2009).

Analysis of microfinances' performance and development of informal institutions in Cameroon

III.7.2- The debate between the institutionalists and welfarists

The growing emphasis on the financial sustainability and efficiency of MFIs is believed to reduce the scope for the social objectives and outreach to microfinance clients. Consequently, a debate on the assessment of the performance of MFIs has emerged between the institutionalists and welfarists¹³.

In 2009, Gutiérrez-Nieto et al. claimed that the institutionalists appear to have the upper hand in the debate. In general, «each position differs in their views: (1) on how microfinance services should be delivered (NGO versus commercial banks), (2) on the technology that should be used (a minimalist approach versus an integrated service approach), and (3) on how their performance should be assessed» (Olivares Polanco, 2004, p. 3).

Institutionalists believe that the performance of a MFI should be assessed in terms of the institution's success in reaching a financially self-sustainable position. According to Rhyne (1998, p. 7), «the sustainability group argues that any future which continues dependence on donor and governments is a future in which few microfinance clients will be reached». According to Hermes et al. (2007), the commercialization of MFIs is believed to ensure the growing amount of commercial funding, ensuring and enhancing the future outreach to new microfinance clients around the world. Also, Rhyne (1998) and Olivares-Polanco (2004) reported that the institutionalists' approach combines financial sustainability with (breath of) outreach objectives. Institutionalists aim to provide access to financial services to the full spectrum of low-income people living around the world. Nonetheless, Schreiner (2002) recognized that the self-sufficiency approach is believed to target less poor clients.

Welfarists believe that the performance of a MFI should be assessed by determining whether the institution is successful in reaching its poverty alleviating objectives. Olivares-Polanco (2004) stressed that a key advantage of the welfarists' approach is the opportunity to gain a direct insight in the poverty alleviating potential of microfinance. Olivares-Polanco (2004, p. 6) reported that «the methods used by the welfarists assesses the impact of the programme on their clients, by measuring changes in dependent variables such as the level of income, the level of production, sales, assets or the general wellbeing of the clients». According to Schreiner (2002), the welfarists ?approach is expected to target the very poor clients, compared to the less poor clients targeted by the institutionalists» approach.

¹³Yaron (1994), Morduch (2000), Schreiner (2002), Olivares-Polanco (2004), Hermes, Lensink & Meesters (2007), and Gutiérrez-Nieto, Serrano-Cinca & Mar Molinero (2009).

Analysis of microfinances' performance and development of informal institutions in Cameroon

Alternatively, some are advocating the win-win proposition of microfinance. For example, Yaron (1994) proposed a framework combining the assessment of the financial self-sufficiency and outreach of MFIs. One the one hand, the author argues that state support and donations are a fundamental source of resources for newly established MFIs initially facing a negative cash flow. On the other hand, the author argues that the mobilization of savings is fundamental in the support of the expansion of more mature MFIs, allowing for less government support and donations. Also, «one key to success appears to be the introduction of a social mechanism that lowers transaction costs, while supplying effective peer pressure for screening loan applications and collecting loans», according to Yaron (1994, p. 68).

In addition, Morduch (2000, p. 617) states that for the win-win proposition «a key tenet is that poor households demand access to credit, not cheap credit». The author identifies a number of assumptions underlying the win-win proposition. First, raising the costs of financial services will not negatively affect the demand of microfinance. Second, financially sustainable MFIs can achieve a greater scale and outreach than subsidized MFIs. Third, subsidies reduce the scope for savings mobilization. Fourth, financial sustainability is critical for the access of MFIs to commercial financial markets. Fifth, «microfinance has been and should continue to be a movement with minimal governmental involvement» (Morduch, 2000, p. 624).

Analysis of microfinances' performance and development of informal institutions in Cameroon

After the appearance of theoretical perspectives, this chapter will enable us in turn to define the indicators and variables necessary for our analysis. Thereafter, we will proceed with the analysis of the research hypotheses and the model associated with this assumption

IV.1- Relationship between social and financial performance

IV.1.1- A tentative typology of the firms' performances

The examination of the outcomes of the research on enterprises in terms of financial

performance (FP) and social performance (SP) enables to assess various assumptions by considering two dimensions, which designs a tentative typology: The sign of relationship and causality between these two performances (O' Bannon and Preston, 1997).

Table5- A set of various assumptions on likely relationships between SP and FP

The various assumptions on the likely relationships between SP and FP can indicate a positive, negative or neutral link. If the existence of such relationship is proven, it should be known if SP influences FP, or conversely. One can also wonder whether these phenomena interact. Provided that attention paid to SP improves relationships between the company stakeholders, assumption 1 relates to the fact that good management practices are strongly correlated with good SP and have consequences on FP: An additional cost in well managed SP is then the landmark of good management and leads thereafter to an improvement of FP.

In the contrary, assumption 2 describes the case whereby any socially responsible initiative moves away the leaders from their objective for profit maximization, i.e. a higher level of SP drives a fall in FP: Thus, it brings in the concept of trade-off. According to assumption 3,

Analysis of microfinances' performance and development of informal institutions in Cameroon

good FP enables the firm to allocate some margin to social issues. Thus, an allowance resulting from good economic figures brings in an improvement of SP.

However, assumption 4 considers the possibility that financially powerful companies are the worse in terms of SP because of their leaders? greed, who do not share the margin. Assumptions 5 and 6 design interactions between SP and FP. According to assumption 5, which gathers assumptions 1 and 3, better FP results in an improvement in SP and better SP leads to an improvement in FP: Such a simultaneous and interactive relationship is a vicious circle whereby financial and social values are created (Waddock and Graves, 1997).

Conversely, assumption 6 deals with the vicious circle of disrupting both financial and social values: SP is reduced by a fall in FP, which in turn degrades SP. This is an example of what may occur when the leaders wish to instantly change their strategy of wealth distribution in order to comply with evolving management methods or requirements from financial markets, as well as economic constraints (D' Arcimoles and Trébucq, 2003).

No relationship, whether positive or negative, will occur between SP and FP in case of the rejection of assumptions 1 to 6: This neutral relationship corresponds to assumption 7

(Mc Williams and Siegel, 2001). An additional assumption has been added i.e. assumption 8 in order to take care of more complex links between SP and FP, which may result from measurement problems.

IV.1.2- The problem statement

The research aims to find empirical evidence on microfinance schism (arbitrage between social and financial performance). As we have stated earlier, the objective of MFIs is to reach the best possible performance, which can be achieved when people combine two requirements, namely: social performance (through the reduction of poverty) and financial performance (in ensuring sustained profitability). However, these two requirements raise a debate between two opposing schools of thought: the welfarists and institutionalists approaches

MFIs of Cameroon provide a clear illustration of this discussion and analysis of their activities can answer the question: is there a trade-off between the two types of performance? In other words, does the pursuit of social objectives enable microfinances to eventually expand their financial performance? At the same time, how does microfinances' performance affect the development of informal sector?

Analysis of microfinances' performance and development of informal institutions in Cameroon

Following the problem statement, the research requires a selection of variables and indicators to study the financial performance and social performance of MFIs. In addition, a selection of variables and indicators for the non-formal sector of MFIs is required.

The selection is made based upon the previously discussed information and literature, and the existing knowledge and experience of the rating agencies MicroRate and Inter-American Development Bank Sustainable Development Department Micro, Small and Medium Enterprise Division.

IV.2- Selection of variables and indicators

IV.2.1- Selection of the financial performance indicators

The key indicators of financial performance are mainly measured by return on assets, return on capital and operational self-sufficiency. The selection of the financial performance indicators corresponds to the selection of indicators considered by the rating agency MicroRate in its investment decision-making process.

? Operational self-sufficiency (OSS): Essentially, the ratio measures how well a MFI is able to cover the institution's total costs of operating. Morgan Stanley (2007) and Fitch (2008) implicitly included the OSS ratio in their rating methodologies to assess the financial sustainability of MFIs. Fitch (2008, p. 10) analysed the OSS ratio «to assess the adequacy of an MFI's cost and revenue structure»;

? Return on equity: ROE is calculated by dividing net income (after taxes and excluding any grants or donations) by period average equity. Return on equity indicates the profitability of the institution. This ratio is particularly relevant for a private for-profit entity with real flesh-and-blood owners. For them, ROE is a measure of paramount importance since it measures the return on their investment in the institution. However, given that many MFIs are not-for-profit-organizations, the ROE indicator is most often used as a proxy for commercial viability.

A single year's ROE can at times misrepresent the institution's «true» profitability. Extraordinary income or losses, for example in the form of asset sales, can have a significant impact on the bottom line. In other circumstances the institution may

Analysis of microfinances' performance and development of informal institutions in Cameroon

temporarily record higher net income figures. Another issue to consider is taxes. Incorporated and supervised MFIs generally pay taxes, while not-for-profit, non-supervised MFIs do not; reporting and other requirements of bank regulators also add to the costs of supervised institutions.

Finally, there are still very significant differences in portfolio yield among MFIs, as is to be expected in a young industry. In Bolivia, where competition among urban MFIs has become fierce, portfolio yields have dropped to under 30%, whereas in other less competitive markets portfolio yields can be more than twice as high. Where yields are low, MFIs are forced to be highly efficient and to maintain high portfolio quality to remain profitable, whereas high yields often lead to high returns despite a multitude of weaknesses.

? Return on assets: ROA is calculated by dividing net income (after taxes and excluding any grants or donations) by period average assets. Return on assets is an overall measure of profitability that reflects both the profit margin and the efficiency of the institution. Simply put, it measures how well the institution uses all its assets. The ratio functions as an indicator of financial performance in the research by Olivares-Polanco (2004) and Cull et al. (2007). Morgan Stanley (2008, p. 126) reported that, «return on average assets takes into account taxes and other source of revenues, including income earned on cash in the bank, thereby providing a more complete measure of profitability».

Return on assets is a fairly straightforward measure. However, as in the case of ROE, a correct assessment of ROA depends on the analysis of the components that determine net income, primarily portfolio yield, cost of funds and operational efficiency. In what seems like a paradox, NGOs generally achieve a higher Return on Assets than licensed and supervised MFIs. This state of affairs is explained by the fact that microfinance NGOs, with low Debt/Equity Ratios and limited possibilities to fund themselves in financial and capital markets, need to rely heavily on retained earnings to fund future growth.

Analysis of microfinances' performance and development of informal institutions in Cameroon

IV.2.2- Selection of the social performance indicators

Today, data availability predominantly allows for the measurement and assessment of the outreach to microfinance clients for a large sample of MFIs. However the access to data in our environment is sometimes difficult. In fact, on one hand, we have used a main indicator which serves to measure the social performance that is Average loan size. On the other hand, we have used some indicators which are consistent and are adaptable in our environment or sample, namely Engagement in Favor of Individual Related and Engagement in Favor of Global related.

? Average loan size: The average loan size measure is the most common used proxy for the depth of outreach to microfinance clients in the existing empirical research of the social performance of MFIs¹⁴.

S&P (2007) included the average loan size in their management and strategy assessment of a MFI. The agency stressed that the appropriateness of the measure of depth of outreach is depending on the institution's self-declared social objectives. In addition, the SPTF (2009) standard reports showed that the outreach depth is an important feature in the various measurement of performance and assessment tools used.

Olivares-Polanco (2004) found that the per capita GNP and the per capita GNP of the 20 percent poorest average loan size measures are highly correlated. However, Schreiner (2001) opposed the use of average per capita GNP for two reasons. First, the per capita GNP is typically higher than a country's median per capita GNP or compared to the poverty-line income. Secondly, per capita GNP is a flow from average income in a year, whereas the term the flow disbursed as a loan may be very different. Following the studies of Olivares-Polanco (2004) and Cull et al. (2007), the average loan size divided by per capita GDP is considered in this research.

Engagement in favour of related Commitment is a prudential ratio used as an indicator of social performance. This ratio was defined in the survey conducted by the Ministry of Finance (MINFI) near the Microfinance Institutions. Indeed, the aforesaid investigation culminates in the setting-up of a report which follows by the assessment of Cameroon MFI, carried out within the framework of the implementation of the Microfinance Activity Evaluation and Supervision

¹⁴Olivares-Polanco, 2004; Hermes, Lensink & Meesters, 2007; Cull, Demirguç-Kunt & Morduch, 2007 & 2009; Gutiérrez-Nieto, Serrano-Cinca & Mar Molinero 2009, and Mersland & Strøm, 2009.

Analysis of microfinances' performance and development of informal institutions in Cameroon

System (SESAME). This implementation was carried out from March to September 2011. The prudential ratio indicates the degree of commitment of microfinace with its target population. It consists of two components, namely:

Within the framework of our analysis, these two components will be considered as social performance indicators. In order to provide further explanation we are going to illustrate a particular case of CCA.

Commitments: The Department of Credit is responsible for the liabilities of the institution. The procedure for granting credit is described in a document entitled "MANUAL CREDIT" which was updated in August 2010 by the audit unit. This manual assumes the responsibilities of all those involved in the process of granting credit. In addition, it describes the procedures for granting credit and the methodology for monitoring commitments and guarantees to collect. Accounts managers take delivery of each agency credit applications and carry out the assembly and analysis of credit records under the supervision of the agency. Counterfactual analysis of cases is made by the Regional Director before their transmission to the Regional Credit Committee opinion. Credit records which have received a favorable opinion are then transmitted to the Credit Committee Branch for a final decision on all competitions lower than or equal to 50 Million. Beyond this threshold, only the CEO is responsible for taking the decision to grant credit.

IV.2.3- Selection of developmental indicators for the informal sector

Within the framework of our research, indicators of informal sector development related to performance (social and financial) is illustrated by the number of deposits and the number of gross loans granted by microfinance institutions, all things being equal (Ceteris Paribus). Table 6 resulting from table 3 of section III.1.2 on the evolution of the activity of microfinance in Cameroun from 2002 to 2010 illustrates this situation clearly.

Analysis of microfinances' performance and development of informal institutions in Cameroon

The observation of the figure shows that deposits and gross loans change in the same direction, but the increase in gross loans is less proportional than bank deposits. In the first year, there was a slight increase in savings from the credit to this sector. In year 2, the amount of deposits is substantially equal to the credits, but with a slight decrease with respect to savings. Then the situation changes proportionally to year 5 where we observe that the volume of savings has significantly increased (in reference to the year 1), and this is due to the proliferation of small and medium enterprises which promotes the mobilization of a large volume of informal savings. Subsequently, the position of deposits and loans is growing exponentially until reaching in 2010 the respective amounts of 373,872 million and 221,378 million.

Analysis of microfinances' performance and development of informal institutions in Cameroon

IV.2.4- Selection of the control variables

For reasons of robustness, three control variables are used in the regression explaining the performance (both social and financial) of MFIs, namely: Total Asset, Coefficient of Activity and Hedge Loans by Available Resources.

Those indicators have been chosen with reference to the research environment. In fact, and in spite of scarcity of data, the control variables reflect perfectly and respectively the capital structure, a day to day activities and available resources of the MFIs environment

IV.3- The research hypothesis and research model

In this section, we are going to give guidelines about the formulation of research hypothesis.

Firstly, the research concentrates on the financial performance of MFIs. The general assumption under this hypothesis (H1) is that: social performance influences financial performance of MFIs. This hypothesis can be subdivided into two categories as follows:

? Positive link, H1a: «influence of social performance on financial performance implies a good management of MFI»;

? Negative link, H1b: «influence of social performance on financial performance implies arbitration». This hypothesis means that any socially responsible initiative moves away the leaders from their objective for profit maximization (this hypothesis lead to the occurrence of mission drift by MFIs)

Secondly the research focuses on hypothesis two (H2) which assumes that: «financial performance influences social performance». As we have undertaken in the first hypothesis, the second can also be subdivided into two categories such as positive and negative links

? Positive link, H2a: «good financial performance enables the firm to allocate some margin to social issues» this hypothesis implies the availability of fund by the microfinance institution. Thus, an allowance resulting from good economic figures brings in an improvement of SP

? Negative link, H2b: «financially powerful companies are the worse in terms of SP because of their leaders' greed, who do not share the margin»

Analysis of microfinances' performance and development of informal institutions in Cameroon

Apart from the above hypothesis, it is important to remember that our study takes into consideration not only social and financial aspects, but also the relationship between these aspects and development of informal institutions in Cameroon. Indeed we have included some variables in our research which are correlated to the development of the informal sector. The aforesaid variables are Fixed Deposit and Gross Loan.

Consequently, in a bid to reach one of our objectives (which is to show the relationship between microfinance performance and the development of non-formal institutions) we have stated another hypothesis as follows:

This hypothesis implies that more contact of MFIs with the poorest population (those who cannot access to the classical bank system) will contribute to improve the amount of fixed deposits and gross loan.

IV.4- Regression approach

It is important to underline that, our research focuses on the study of the link between

social and financial performance on one hand and MFIs performance and development of the informal sector on the other hand. In fact the repetitive verb in our dissertation is «to link». This verb implies that we are studying the correlation among the variables which characterizes each

Analysis of microfinances' performance and development of informal institutions in Cameroon

indicator. Therefore, the regression approach, based on the Ordinary Least Square (OLS) is used

To best describe our hypothesis, the research requires the following regression models

Notes: the mission drift regression is included in the social and financial regression (H1), which is the consequence of negative link of the influence of social performance on financial performance. The list of variables and indicators are given in the appendix

General multiple regression models are used to analyse the explanatory function of the control variables and independent variables. The selected financial and social performance indicators are first used as the dependent variables for testing hypothesis 1 and 2. Concerning hypothesis 3 and 4, the indicators of the development of the informal sector function as dependent variables, whereas social performance, financial performance and control variables are used as independent variables. It is important to notice that even the informal sector and control variables are considered as independent variables in the financial and social performance regression.

The next chapter provides an insight in the descriptive statistics of the variables and indicators presented in the dataset. Preliminary, the minimum and maximum values suggest a wide range for many of the variables. Hence, outliers may be a concern in the regression analyses. Woolridge (2003, p. 312) stated «OLS is susceptible of outlying observations because it minimizes the sum of squared residuals: large residuals (positive or negative) receive a lot of weight in the least squares minimization problem». Cull et al. (2007, p. 17) faced the same concern and applied a robust estimation technique. The authors found that «those results are similar to the base results, although there are a few minor differences». The next chapter also provides an insight in the correlation and coefficients of regression between the selected variables and indicators.

Analysis of microfinances' performance and development of informal institutions in Cameroon

IV.5- conclusion

A selection of variables and indicators used for the financial performance, social performance and informal institutions has been presented. For robustness, a selection of control variables has been added to the regression models. We have given the different hypotheses underlying this research. From the hypothesis one assumes that «social performance influences financial performance of MFIs» The next hypothesis assumes that: «financial performance influences social performance» The third hypothesis assumes that «financial performance influences the development of the informal sector» and the last hypothesis supposes that «social performance influences the development of informal sector»

In this research the OLS regression approach is used. The regression approach has been successful in previous studies. In line with the hypotheses, the research contains three general regression models: financial performance regression, social performance regression and informal sector regression.

Analysis of microfinances' performance and development of informal institutions in Cameroon

This chapter contains four sections. Section 1 provides an insight in the various sources and the process of data collection. In section 2, multiple sources have been combined in order to collect general information, financial and social performance data of 45 active MFIs in Yaoundé (Cameroon). In section 3, we will give preliminary data analysis and section 4 explains the different regressions analysis that we will perform in our research.

The dataset contains general information, financial performance data, social performance and non-formal institutions data from 45 MFIs of Yaoundé. All the observations are from the year 2010. Let us mention that the sample was drawn from the population of Cameroon MFIs which is about 488 microfinances. Table 7 shows the distribution of microfinances based on their categories

Analysis of microfinances' performance and development of informal institutions in Cameroon

Categories	Center region	East region	Littoral south region	and west	West region	Far region	North	North region	west	Total
First	45	13	32		52	79		221		442
Second	17	0	18		2	1		4		42
Third	0	0	2		0	2		0		4
Total	62	13	52		54	82		225*		488

Concerning the network we have CAMCCUL: 191, A3C: 34, UCCGN: 9, CMEC West: 19, CMEC North West: 9 and MUCADEC: 3

From the 488 approved MFIs in 31^st December 2010, there are 442 in the first category, 44 in the second category and 4 in the third category. This sector is predominated by MFIs of first category which represents 90.1% of total MFIs, follows by the structures of second category (9%). MFIs of third category that are essentially of old project are established in far North and West areas. Despite the fact that the proportion of MFIs of second category is low, they still control almost half the market especially in terms of fixed deposits and loans from clients. Another network received in 2011 is the agreement of monetary authority with three of its affiliated, they include the MUCADEC network.

V.3- Preliminary data analysis

In this section, we are going to talk about descriptive statistics and correlation analysis.

V.3.1- Descriptive statistics

The descriptive statistics for the variables and indicators used in the research are presented in table 8.

Analysis of microfinances' performance and development of informal institutions in Cameroon

	ROA	ROE	OSS	AL	CFIR	CFGR	TA	COA	HLRA	FD	GL
N	45	45	45	45	44	45	45	45	45	45	45
Mean	1.08	17.29	124.36	7.44	0.84	11.56	159667.00	108.22	30.75	17245.30	56514.30
Std dev	8.87	50.98	101.30	48.72	21.46	40.89	1055060.0 0	79.08	113.68	104153.0 0	372536.0 0
Coef. of var in%	824.00	294.79	81.45	654.87	2552.20	353.84	660.79	73.07	369.71	603.95	659.19
Min	-31.12	-130.77	-3.54	0	-85	-85	20	-50	-500	0	5
Max	35	227.27	434.3	327	62	218	7.08E+06	358.3	500	700000	2.50E+06
Range	66.12	358.04	437.84	327	147	303	7.08E+06	408.3	1000	700000	2.50E+06
Std. skew	-0.01	4.11	3.37	18.37	-4.36	8.95	18.37	3.49	-1.93	18.34	18.37
Std. kurt	10.76	10.94	1.91	61.61	12.62	21.80	61.62	2.50	22.97	61.47	61.62

This table shows the summary statistics of each of the selected data variables. It includes measures of central tendency, measures of variability, and measures of shape. Of particular interest here are the standardized skewness and standardized kurtosis, which can be used to determine whether the sample comes from a normal distribution. Values of these statistics outside the range of -2 to +2 indicate significant departures from normality, which would tend to invalidate many of the statistical procedures normally applied to this data. In this case, the following variables show standardized skewness values outside the expected range: ROE, OSS, AL, CFIR, CFGR, TA, COA, FD, GL

The following variables show standardized kurtosis values outside the expected range: ROA, ROE, AL, CFIR, CFGR, TA, COA, FD, GL

V.3.2- Correlation analysis

A correlation coefficient measures the linear relationship between two variables that does not depend on the unit of variables of measurement. Table 9 shows the correlation between the selected variables and indicators used in the research.

Firstly there is a low correlation among the financial performance variables (cross correlations), two coefficients are positive and relatively low whereas another is negative. Further we can observe the same trend between the FP variables and other indicators. This means

Analysis of microfinances' performance and development of informal institutions in Cameroon

that there is a relatively low link among the variables (sometimes this link is negative and sometimes it is positive).

Secondly, concerning social performance, the cross correlation among variable illustrates that the relationships exist among the variables and these links are relatively low, sometimes positive and sometimes negative. The general trend between the social performance indicators and another variable presents relatively low correlations (positive or negative). However we can observe some cases of perfect relationships between social performance and informal sector variables. Meaning that the knowledge of one variable gives us the value of other variables (example: Average Loan /GDP per capita and fixed deposits).The cross correlation between the informal sector variables is perfectly positive, meaning that there is a positive and linear relationship between the variables. However, it is important to notice that the correlations are significant at 0.01level (2 tailed) and 0.05 level (2 tailed).

	ROA		ROE	OSS	AL	CFIR	CFGR	TA	COA	HLAR	FD	GL
*Financial performance*
ROA	1
ROE	0.045		1
OSS	0.245		-0.077	1
*Social performance*
AL	-0.551**		0.132	-0.098	1
CFIR	0.040		0.172	0.063	-0.006	1
CFGR	0.027		0.207	0.054	-0.043	0.632**	1
*Controllable variables*
TA	-0.553**	0.132		-0.097	1.000	-0.006	-0.043	1
COA	-0.401**	-0.035		-0.356*	0.057	-0.113	-0.080	0.057	1
HLAR	0.045	0.002		-0.012	-0.041	0.037	0.023	-0.041	-0.140	1
*Informal sector*
FD	-0.553**	0.126		-0.083	1.000**	-0.005	-0.043	1.000**	0.054	-0.041	1
GL	-0.553**	0.132		-0.098	1.000**	-0.006	-0.043	1.000**	0.057	-0.041	1.000**	1

Analysis of microfinances' performance and development of informal institutions in Cameroon

**Correlation is significant at the 0.01 level (2-tailed); *Correlation is significant at the 0.05 level (2-tailed)

This table shows Pearson products of correlation moments between each pair of variables. These correlation coefficients range between -1 and +1 and measure the strength of the linear relationship between the variables.

V.4- Regression analysis

Introduced in section IV.3, three hypotheses are derived from the problem statement.

These hypotheses can be tested using three regression models: the (1) financial performance regression, (2) social performance regression, and (3) informal sector regression. This section provides the financial performance regression analysis, the social performance regression analysis, and the informal sector regression. It is important to underline that the data have been analyzed by the Statistical Package for Social Sciences (SPSS), Excel and Statgraphics software

V.4.1- Financial performance regression analysis

There are three financial performance regression based on the dependent variables,

MODEL1: FD, HLAR, COA, AL: ROA Model2: FD, HLAR, COA, AL, CFIR Model2: FD, HLAR, COA, AL CFGR

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	df1	df2	Sig. F Change
1	0.673*	0.453	0.399	6.878	0.4533	8.292	4	40	0.00
2	0.673**	0.453	0.383	6.966	0.00	0.00	1	39	0.993
3	0.674***	0.454	0.368	7.050	0.001	0.071	1	38	0.791

Analysis of microfinances' performance and development of informal institutions in Cameroon

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	1569.26501	4	392.316254	8.29235437	5.7212E-05
	Residual	1892.42397	40	47.3105992
	Total	3461.68898	44
2	Regression	1569.26831	5	313.853662	6.46806125	0.0001819
	Residual	1892.42067	39	48.523607
	Total	3461.68898	44
3	Regression	1572.8065	6	262.134417	5.27354558	0.00049015
	Residual	1888.88248	38	49.7074337
	Total	3461.68898	44

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
	B		Std. Error	Beta	t	Sig.
1	(Constant)	6.939	1.903		3.646	0.000
	AL	0.536	0.684	2.945	0.784	0.437
	COA	-0.043	0.013	-0.384	-3.238	0.002
	HLAR	-0.003	0.009	-0.033	-0.285	0.776
	FD	0.000	0.000	-3.477	-0.926	0.360
2	(Constant)	6.934	1.935		3.587	0.000
	AL	0.536	0.692	2.944	0.774	0.443
	COA	-0.043	0.013	-0.384	-3.184	0.002
	HLAR	-0.003	0.009	-0.0337	-0.281	0.779
	FD	0.000	0.000	-3.477	-0.915	0.366
	CFIR	0.000	0.05	0.000	-0.008	0.993
3	(Constant)	7.046	1.998		3.526	0.001
	AL	0.538	0.700	2.953	0.767	0.448
	COA	-0.043	0.014	-0.385	-3.151	0.003
	HLAR	-0.003	0.009	-0.034	-0.280	0.781
	FD	0.000	0.000	-3.487	-0.906	0.371
	CFIR	0.010	0.065	0.025	0.161	0.873
	CFGR	-0.009	0.034	-0.041	-0.267	0.791

Analysis of microfinances' performance and development of informal institutions in Cameroon

Interpretation: the p-value of F test is 0.000. This means that the overall model is statistically significant under ANOVA analysis. The R square of all models is less than 0.50. This supposes that there is a low relationship between independent variables and Return on Asset.

F test, model 1: observed value 8.292 is greater than empirical value F= 2.021. Then the regression equation is useful in the estimation of ROA.

Based on T test, we can also conclude that all variables used in the regression equation are useful to predict the return on asset.

F test, model 2: observed value 6.468 is greater than empirical value 0.0150. Then the regression equation is useful in the estimation of ROA. Consequently social performance variables influence ROA

F test, model 3: observed value 5.273; empirical value 0.0272. Here, we can also conclude that all variables used in the regression equation are useful to predict ROA.

As summary, social performance influence the Return on Asset. Therefore, this can confirm the hypothesis of good management by the MFI. It is important to underline that the significant level for all F test and T test is 0.05.

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	df1	df2	Sig. F Change
1	0.234*	0.05	-0.042	52.62214	0.055	0.564	4	39	0.690
2	0.290**	0.08	-0.036	52.46893	0.030	1.228	1	38	0.275
3	0.318***	0.101	-0.044	52.67756		0.700	1	37	0.408

Analysis of microfinances' performance and development of informal institutions in Cameroon

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	6252.9397	4	1563.23492	0.56453017	0.68979795
	Residual	107994.516	39	2769.09015
	Total	114247.455	43
2	Regression	9633.87489	5	1926.77498	0.69988475	0.62690603
	Residual	104613.581	38	2752.98896
	Total	114247.455	43
3	Regression	11575.2045	6	1929.20075	0.69522609	0.6549512
	Residual	102672.251	37	2774.9257
	Total	114247.455	43

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
Model	B		Std. Error	Beta
1	(Constant)	24.007	15.266		1.573	0.124
	AL	6.549	5.231	6.260	1.252	0.218
	COA	-0.033	0.116	-0.044	-0.280	0.781
	HLAR	-0.002	0.071	-0.006	-0.035	0.972
	FD	-0.003	0.002	-6.129	-1.226	0.228
2	(Constant)	22.314	15.298		1.459	0.153
	AL	6.602	5.216	6.311	1.266	0.213
	COA	-0.019	0.116	-0.025	-0.159	0.875
	HLAR	-0.004	0.070	-0.009	-0.060	0.953
	FD	-0.003	0.002	-6.180	-1.240	0.223
	CFIR	0.416	0.375	0.173	1.108	0.275
3	(Constant)	20.033	15.600		1.284	0.207
	AL	6.562	5.237	6.272	1.253	0.218
	COA	-0.019	0.117	-0.026	-0.165	0.870
	HLAR	-0.004	0.071	-0.009	-0.056	0.955
	FD	-0.003	0.002	-6.134	-1.226	0.228
	CFIR	0.160	0.485	0.067	0.330	0.743
	CFGR	0.210	0.251	0.168	0.836	0.408

The first model here is not statistically significant because its F value is lower than the significant level. The R square of all models is less than 0.50. This supposes that there is a low relationship between independent variables and Return on Equity.

Analysis of microfinances' performance and development of informal institutions in Cameroon

F test, model 1: observed value 0.564 is less than empirical value which is 0.690. Thus the regression equation is not useful to predict the ROE. Consequently social performance variables have no influence on ROE. We can conclude that this is the hypothesis of mission drift or arbitration.

F test, model 2: as we can observe in ANOVA table of ROE, the model is statistically significant. The R square of the model is less than 0.50. This implies that that there is a low relationship between independent variables and Return on Equity. Observed value 0.699 of F test is greater than the empirical value which is 0.408. We can conclude that all social variables used in the regression equation are useful to predict ROE.

F test, model 3: under ANOVA table of ROE the model is statistically significant. We found with the F test that observed value 0.695 is greater than empirical value 0.409. We can conclude that this model is useful to estimate ROE. Thus social performance variables used in this model influence the dependent variable ROE (assumption of good management practice)

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	df1	df2	Sig. F Change
1	0.552*	0.305	0.234	88.75586	0.30489	4.277	4	39	0.006
2	0.553**	0.305	0.214	89.88087	0.00054	0.030	1	38	0.864
3	0.553***	0.306	0.193	91.07649	0.00017	0.009	1	37	0.926

Analysis of microfinances' performance and development of informal institutions in Cameroon

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	134756.714	4	33689.1786	4.27657748	0.00577733
	Residual	307226.508	39	7877.60277
	Total	441983.222	43
2	Regression	134997.562	5	26999.5125	3.34211531	0.01341161
	Residual	306985.66	38	8078.57
	Total	441983.222	43
3	Regression	135070.9	6	22511.8167	2.71392564	0.0275939
	Residual	306912.322	37	8294.92762
	Total	441983.222	43

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
	B		Std. Error	Beta
1	(Constant)	156.438	25.749		6.075	0.000
	AL	-28.635	8.823	-13.916	-3.246	0.002
	COA	-0.445	0.196	-0.307	-2.270	0.029
	HLAR	-0.045	0.119	-0.050	-0.374	0.710
	FD	0.013	0.004	13.843	3.229	0.003
2	(Constant)	155.986	26.207		5.952	0.000
	AL	-28.621	8.935	-13.910	-3.203	0.003
	COA	-0.441	0.200	-0.305	-2.210	0.033
	HLAR	-0.045	0.121	-0.051	-0.373	0.711
	FD	0.013	0.004	13.836	3.187	0.003
	CFIR	0.111	0.643	0.024	0.173	0.864
3	(Constant)	155.543	26.971		5.767	0.000
	AL	-28.629	9.054	-13.913	-3.162	0.003
	COA	-0.441	0.202	-0.305	-2.182	0.036
	HLAR	-0.045	0.122	-0.051	-0.368	0.715
	FD	0.013	0.004	13.840	3.146	0.003
	CFIR	0.061	0.839	0.013	0.073	0.942
	CFGR	0.041	0.434	0.017	0.094	0.926

In the OSS regression, all the models are statistically significant, because their respective F values (4.276, 3.342, and 2.713) are greater than their respective significant level (0.005, 0.013 and

Analysis of microfinances' performance and development of informal institutions in Cameroon

0.027). The R square of all the models is less than 0.5; this supposes that there is a low relationship between independent variables and Operational Self Sufficiency.

F test, mode l: observed value 4.277 is greater than empirical value 0.005. Therefore social performance variables used in this model is useful to estimate OSS

F test, mode 2: observed value 3.342 is greater than empirical value 0.075. The model is useful to estimate the Operational Self Sufficiency. Thus all social variables used influence OSS

F test, mode 3: observed value 2.71 is greater than empirical value 0.108 we can conclude that this model is useful to estimate OSS. Thus social performance variables used in this model influence the dependent variable OSS (assumption of good management practice).

V.4.2- Social performance regression analysis

There are three social performance regressions based on the dependent variables, namely: AL/GDP, CFIR, CFGR

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	df1	df2	Sig. F Change
1	1.000*	1.000	1.000	0.23107	1.0000	391223.8187	5	39	0.000
2	1.000**	1.000	1.000	0.23386	0.0000	0.0739	1	38	0.787
3	1.000***	1.000	1.000	0.23050	0.0000	2.1161	1	37	0.154

**Predictors: (Constant), FD, HLAR, COA, ROA, TA, ROE ***Predictors: (Constant), FD, HLAR, COA, ROA, TA, ROE, OSS

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	104442.66	5.00	20888.53	391223.82	0.00
	Residual	2.08	39.00	0.05
	Total	104444.75	44.00
2	Regression	104442.67	6.00	17407.11	318278.41	0.00
	Residual	2.08	38.00	0.05
	Total	104444.75	44.00

Analysis of microfinances' performance and development of informal institutions in Cameroon

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
1	B		Std. Error	Beta
	(Constant)	-0.0200	0.0737		-0.2707	0.7881
	ROA	0.0167	0.0053	0.0030	3.1660	0.0030
	TA	0.0000	0.0000	1.0166	42.7652	0.0000
	COA	0.0005	0.0005	0.0009	1.0850	0.2846
	HLAR	0.0003	0.0003	0.0006	0.8513	0.3998
	FD	0.0000	0.0000	-0.0149	-0.6274	0.5341
2	(Constant)	-0.0163	0.0758		-0.2151	0.8309
	ROA	0.0169	0.0054	0.0031	3.1375	0.0033
	TA	0.0000	0.0000	1.0178	41.5274	0.0000
	COA	0.0005	0.0005	0.0009	1.0727	0.2902
	HLAR	0.0003	0.0003	0.0006	0.8418	0.4052
	FD	0.0000	0.0000	-0.0162	-0.6594	0.5136
	ROE	-0.0002	0.0007	-0.0002	-0.2719	0.7872
3	(Constant)	0.0691	0.0950		0.7272	0.4717
	ROA	0.0179	0.0054	0.0033	3.3490	0.0019
	TA	0.0000	0.0000	1.0005	37.1174	0.0000
	COA	0.0003	0.0005	0.0005	0.6499	0.5198
	HLAR	0.0002	0.0003	0.0006	0.7627	0.4505
	FD	0.0000	0.0000	0.0012	0.0459	0.9636
	ROE	-0.0002	0.0007	-0.0002	-0.3018	0.7645
	OSS	-0.0006	0.0004	-0.0013	-1.4547	0.1542

The p-value of F test is 0.000. This means that the overall model is statistically significant under ANOVA analysis. The R-squared of all the models is 1.000 meaning that perfectly 100% of the variability of AL is accounted for by the variables in the model. The coefficients for each of the variables indicates the value of change that one could expect in AL given a one-unit change in the value of that variable, given that all other variables in the model are held constant.

F test: we can observe that all the 3 models have a very higher value of F test. This is very significant: therefore we can conclude that financial performance indicator is useful to estimate the dependent variable Average Loan/GDP. In fact, there is positive link between AL and

Analysis of microfinances' performance and development of informal institutions in Cameroon

financial performance variables ceteris paribus. This implies the availability of fund by the microfinance institution. Thus, an allowance resulting from good economic figures brings in an improvement of SP (H2a)

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	df1	df2	Sig. F Change
1	0.117*	0.014	-0.116	22.67354	0.0137	0.1052	5	38	0.990
2	0.212**	0.045	-0.110	22.61250	0.0311	1.2054	1	37	0.279
3	0.213***	0.046	-0.140	22.91574	0.0007	0.0272	1	36	0.870

**Predictors: (Constant), FD, HLAR, COA, ROA, TA, ROE ***Predictors: (Constant), FD, HLAR, COA, ROA, TA, ROE, OSS

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	270.494806	5	54.0989612	0.10523262	0.99047007
	Residual	19535.3916	38	514.089252
	Total	19805.8864	43
2	Regression	886.860095	6	147.810016	0.28907252	0.93839558
	Residual	18919.0263	37	511.325034
	Total	19805.8864	43
3	Regression	901.168592	7	128.73837	0.24515475	0.97053821
	Residual	18904.7178	36	525.131049
	Total	19805.8864	43

Analysis of microfinances' performance and development of informal institutions in Cameroon

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
Model		B	Std. Error	Beta
1	(Constant)	3.731	7.309		0.510	0.613
	ROA	0.047	0.539	0.018	0.086	0.932
	TA	0.000	0.000	-0.495	-0.092	0.927
	COA	-0.032	0.053	-0.105	-0.612	0.544
	HLAR	0.004	0.030	0.022	0.137	0.892
	FD	0.000	0.001	0.509	0.095	0.925
2	(Constant)	2.281	7.408		0.308	0.760
	ROA	-0.029	0.542	-0.011	-0.054	0.957
	TA	0.000	0.000	-1.631	-0.300	0.766
	COA	-0.032	0.052	-0.104	-0.608	0.547
	HLAR	0.004	0.030	0.022	0.135	0.893
	FD	0.000	0.001	1.604	0.295	0.770
	ROE	0.076	0.069	0.183	1.098	0.279
3	(Constant)	1.297	9.584		0.135	0.893
	ROA	-0.043	0.556	-0.017	-0.078	0.939
	TA	0.000	0.000	-1.176	-0.191	0.850
	COA	-0.029	0.055	-0.095	-0.527	0.601
	HLAR	0.004	0.031	0.024	0.144	0.886
	FD	0.000	0.001	1.148	0.186	0.854
	ROE	0.076	0.070	0.183	1.086	0.285
	OSS	0.007	0.041	0.032	0.165	0.870

The entire models have the p-value of F test higher than their F value. Thus model 1, 2 and 3 of this regression is not statistically significant. For example, under model 2 the significance level is 0.938 which is greater than F value 0.289.

Under T test, model 1 gives the following results: T (0.05; 38) is 2.024. When we compare it with the T Student of first regression coefficient model we observed that it is greater than all T test regression coefficients. Therefore, we could conclude that all independent variables used in this model cannot serve to estimate the dependent variable CFIR. Thus financial performance variables of that model do not influence the Commitment in Favour of Individual Related. This reflects to H2b: «financially powerful companies are the worse in terms of SP because of their leaders' greed, who do not share the margin»

Analysis of microfinances' performance and development of informal institutions in Cameroon

We can notice that this model is similar to the last two models and therefore have the same conclusion.

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	df1	df2	Sig. F Change
1	0.096	0.009	-0.118	43.22994	0.0092	0.0722	5	39	0.996
2	0.241	0.058	-0.091	42.69970	0.0489	1.9746	1	38	0.168
3	0.244	0.059	-0.118	43.24205	0.0013	0.0528	1	37	0.820

**Predictors: (Constant), FD, HLAR, COA, ROA, TA, ROE ***Predictors: (Constant), FD, HLAR, COA, ROA, TA, ROE, OSS

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	674.8437379	5	134.968748	0.07222109	0.99603927
	Residual	72884.26737	39	1868.82737
	Total	73559.11111	44
2	Regression	4275.056303	6	712.509384	0.3907877	0.88031162
	Residual	69284.05481	38	1823.2646
	Total	73559.11111	44
3	Regression	4373.752018	7	624.821717	0.33415167	0.93316901
	Residual	69185.35909	37	1869.87457
	Total	73559.11111	44

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
1		B	Std. Error	Beta
	(Constant)	17.364	13.792		1.259	0.216
	ROA	-0.210	0.987	-0.046	-0.213	0.833
	TA	0.000	0.000	0.034	0.006	0.995
	COA	-0.048	0.094	-0.094	-0.517	0.608

Analysis of microfinances' performance and development of informal institutions in Cameroon

	HLAR	0.003	0.058	0.010	0.060	0.953
	FD	0.000	0.002	-0.097	-0.018	0.986
2	(Constant)	13.919	13.841		1.006	0.321
	ROA	-0.385	0.983	-0.083	-0.391	0.698
	TA	0.000	0.000	-1.398	-0.262	0.795
	COA	-0.049	0.093	-0.094	-0.527	0.601
	HLAR	0.003	0.057	0.009	0.057	0.955
	FD	0.001	0.002	1.285	0.241	0.811
	ROE	0.184	0.131	0.229	1.405	0.168
3	(Constant)	11.388	17.827		0.639	0.527
	ROA	-0.415	1.005	-0.090	-0.413	0.682
	TA	0.000	0.000	-0.784	-0.130	0.897
	COA	-0.043	0.097	-0.083	-0.438	0.664
	HLAR	0.004	0.058	0.011	0.070	0.944
	FD	0.000	0.002	0.671	0.111	0.912
	ROE	0.185	0.133	0.230	1.391	0.172
	OSS	0.018	0.078	0.044	0.230	0.820

Under ANOVA of CFGR we can say that all the models are not statistically significant because the p-value of F test is higher than their F value (example of model 1: 0.996 is greater than 0.072). We can notice that most of the regression coefficients under this model are not significant.

The T test of the first model gives the following results: T(0.05; 39) is 2.022. When we compare it to the T Student of first regression coefficient model we observed that it is greater than all the T test regression coefficients. We can conclude by rejecting the entire hypotheses reflected by this model. This means that the hypothesis under which financial performance variables influence the commitment in favour of global related is false ceteris paribus.

The first model can be generalized to the next two models, because all T tests of those models are less than the empirical T tests.

V.4.3- Informal sector regression

There are three main models in this regression based on dependent variables: Fixed Deposits and Gross Loans.

Analysis of microfinances' performance and development of informal institutions in Cameroon

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	df1	df2	Sig. F Change
1	1.000*	0.999	0.999	3281.6557	0.999	11070.171	4	40	0.00
2	1.000**	0.999	0.999	3266.46464	0.000	1.373	1	39	0.248
3	1.000***	0.999	0.999	2965.52991	0.000	9.317	1	38	0.004

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	4.7687E+11	4	1.1922E+11	11070.1712	0.000
	Residual	430770564	40	10769264.1
	Total	4.773E+11	44
2	Regression	4.7689E+11	5	9.5377E+10	8938.976	0.000
	Residual	416121857	39	10669791.2
	Total	4.773E+11	44
3	Regression	4.7697E+11	6	7.9494E+10	9039.25088	0.000
	Residual	334185971	38	8794367.67
	Total	4.773E+11	44

Table23: FD regression coefficients when FP influences the informal sector

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
1		B	Std. Error	Beta
	(Constant)	2125.559	991.552		2.144	0.038
	ROA	-34.424	74.764	-0.003	-0.460	0.648
	TA	0.099	0.001	0.998	170.777	0.000
	COA	-5.102	7.066	-0.004	-0.722	0.474
	HLAR	-0.754	4.401	-0.001	-0.171	0.865
2	(Constant)	2269.238	994.550		2.282	0.028
	ROA	-22.316	75.131	-0.002	-0.297	0.768

Analysis of microfinances' performance and development of informal institutions in Cameroon

	TA	0.099	0.001	0.999	168.725	0.000
	COA	-4.907	7.035	-0.004	-0.698	0.490
	HLAR	-0.715	4.381	-0.001	-0.163	0.871
	ROE	-11.537	9.847	-0.006	-1.172	0.248
3	(Constant)	-243.712	1221.911		-0.199	0.843
	ROA	-43.098	68.549	-0.004	-0.629	0.533
	TA	0.099	0.001	0.999	185.848	0.000
	COA	1.047	6.678	0.001	0.157	0.876
	HLAR	0.098	3.986	0.000	0.025	0.980
	ROE	-8.821	8.984	-0.004	-0.982	0.332
	OSS	14.625	4.791	0.014	3.052	0.004

ANOVA of FD regression, we can say that all the models are statistically significant because the p-value of F test is zero. The R-squared of the entire models is 0.998, meaning that approximately 99.9% of the variability of FD is accounted for by the variables in the model. In this case, the adjusted R-squared also indicates that about 99.9% of the variability of FD is accounted for by the models; even after taking into account the number of predictable variables in the models.

The coefficients for each of the variables indicates the amount of change one could expect in FD given a one-unit change in the value of that variable, given that all other variables in the models are held constant.

The T test in the first model: T(0.05;40) is 2.021. This statistic proves in the case of TA regression coefficient that independents variables (financial performance variable) influence deposit by clients of small and medium size enterprises, ceteris paribus. But other regression coefficients are not significant because their T values are less than empirical value.

When we look at models 2 and 3, we can draw the same conclusion. Thus MFIs must concentrate their effort to improve their total assets, which results in the valorization of FD amount by the clients. This situation corresponds to H3.

Analysis of microfinances' performance and development of informal institutions in Cameroon

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	d f 1	df2	Sig. F Change
1	1.000*	1.000	1.0000	1232.30476	1.000	1005282.31	4	40	0.000
2	1.000**	1.000	1.0000	1247.30904	0.000	0.04344216	1	39	0.836
3	1.000***	1.000	1.0000	1195.53135	0.000	4.45128185	1	38	0.0421

Table24: FD regression coefficients when SP influences the informal sector

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
1		B	Std. Error	Beta
	(Constant)	520.664	372.341		1.398	0.170
	ROA	-57.588	28.075	-0.001	-2.051	0.047
	TA	0.353	0.000	0.999	1628.568	0.000
	COA	-2.614	2.653	-0.001	-0.985	0.331
	HLAR	0.063	1.653	0.000	0.038	0.970
2	(Constant)	510.904	379.772		1.345	0.186
	ROA	-58.411	28.689	-0.001	-2.036	0.049
	TA	0.353	0.000	0.999	1580.185	0.000
	COA	-2.627	2.686	-0.001	-0.978	0.334
	HLAR	0.060	1.673	0.000	0.036	0.971
	ROE	0.784	3.760	0.000	0.208	0.836
3	(Constant)	1211.150	492.604		2.459	0.019
	ROA	-52.620	27.635	-0.001	-1.904	0.064
	TA	0.353	0.000	0.999	1648.621	0.000
	COA	-4.286	2.692	-0.001	-1.592	0.120
	HLAR	-0.166	1.607	0.000	-0.103	0.918
	ROE	0.027	3.622	0.000	0.007	0.994
	OSS	-4.075	1.932	-0.001	-2.110	0.042

Analysis of microfinances' performance and development of informal institutions in Cameroon

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	df1	df2	Sig. F Change
1	1.000*	1.000	1.000	1906.119	1.000	559918.371	3	40	0.000
2	1.000**	1.000	1.000	1929.461	0.000	0.038	1	39	0.846
3	1.000***	1.000	1.000	1954.172	0.000	0.020	1	38	0.889

Table25: GL regression coefficients when FP influences the informal sector

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
Model		B	Std. Error	Beta
1	(Constant)	-400.556	532.146		-0.753	0.456
	AL	7646.003	5.920	1.000	1291.493	0.000
	COA	0.685	4.199	0.000	0.163	0.871
	HLAR	-1.569	2.555	0.000	-0.614	0.543
2	(Constant)	-389.330	541.730		-0.719	0.477
	AL	7646.007	5.993	1.000	1275.861	0.000
	COA	0.594	4.276	0.000	0.139	0.890
	HLAR	-1.558	2.587	0.000	-0.602	0.551
	CFIR	-2.692	13.802	0.000	-0.195	0.846
3	(Constant)	-375.289	557.619		-0.673	0.505
	AL	7645.962	6.078	1.000	1257.968	0.000
	COA	0.599	4.331	0.000	0.138	0.891
	HLAR	-1.559	2.621	0.000	-0.595	0.555
	CFIR	-1.092	17.999	0.000	-0.061	0.952
	CFGR	-1.314	9.315	0.000	-0.141	0.889

In this case, we have a similar result as the above conclusion: empirical value of T test is higher than T test of observed value in the entire models, except the case of Average Loan/ GDP. Indeed in the entire models, the T value of AL/GDP is greater than one of the empirical value (t (0.05; 40)). We can conclude that only AL/GDP is significant. Therefore, social performance

Analysis of microfinances' performance and development of informal institutions in Cameroon

through the AL/GDP influences the Gross Loan and consequently the development of informal sector.

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	df1	df2	Sig. F Change
1	1.000	1.000	1.000	1906.11900	1.000	559918.371	3	40	0.000
2	1.000	1.000	1.000	1929.46125	0.000	0.038	1	39	0.846
3	1.000	1.000	1.000	1954.17216	0.000	0.020	1	38	0.889

* Predictors: (Constant), HLAR, AL, and COA; **Predictors: (Constant), HLAR, AL, COA, and CFIR ***Predictors: (Constant), HLAR, AL, COA, CFIR, CFGR

Table26: GL regression coefficients when SF influences the informal sector

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
Model		B	Std. Error	Beta
1	(Constant)	-400.556	532.146		-0.753	0.456
	AL	7646.003	5.920	1.000	1291.493	0.000
	COA	0.685	4.199	0.000	0.163	0.871
	HLAR	-1.569	2.555	0.000	-0.614	0.543
2	(Constant)	-389.330	541.730		-0.719	0.477
	AL	7646.007	5.993	1.000	1275.861	0.000
	COA	0.594	4.276	0.000	0.139	0.890
	HLAR	-1.558	2.587	0.000	-0.602	0.551
	CFIR	-2.692	13.802	0.000	-0.195	0.846
3	(Constant)	-375.289	557.619		-0.673	0.505
	AL	7645.962	6.078	1.000	1257.968	0.000
	COA	0.599	4.331	0.000	0.138	0.891
	HLAR	-1.559	2.621	0.000	-0.595	0.555
	CFIR	-1.092	17.999	0.000	-0.061	0.952
	CFGR	-1.314	9.315	0.000	-0.141	0.889

Analysis of microfinances' performance and development of informal institutions in Cameroon

At the end of this chapter we will be able to conversant firstly with the conclusion of the results of our research. Secondly, to give the difficulties faced during the research. Lastly, to make recommendations for further researches in the same field of study.

VI.1- Conclusion

This research aims to find empirical evidence on a trade-off between the two types of performance namely social and financial performance. In other words, the research aims to verify or to analyse if the pursuit of social objectives enables MFIs to eventually expand their financial performance. At the same time, to analyse the development of Cameroon informal sector in relation to the mission drift of MFIs. Indeed, the problem indicates: Is there a trade-off between the social and financial performance? In other words, does the pursuit of social objectives enable MFIs to eventually expand their financial performance?

Based on the empirical evidence of the relationship between social and financial performance of MFIs, and more specifically to a typology of firms? performances, we have underlined some pertinent hypotheses to analyse. Indeed, we have assumed the influence of social performance on financial performance, the feedback relationship and the influence of social and financial performance on the development of informal institutions. The following lines give us more information on the hypotheses results.

Firstly, the research concentrates on the financial performance of MFIs. The general assumption under this hypothesis (H1) is that: social performance influences financial performance of MFIs.

? Positive link, H1a: «influence of social performance on financial performance implies a good management of MFI»;

This hypothesis has been tested in financial performance regression. As a result, there found that the overall models used to estimate the dependent variable ROA were statistically significant. In fact the observed value of F test was greater in each model than the empirical value. As summary, social performance variables influence the Return on Asset ceteris paribus. Therefore, this can confirm the positive link of good management by the MFIs. In the same idea, when ROE stands as a dependent variable in another financial regression, we reach to the same conclusion (in sub models 2 and 3). For example, under ANOVA table of ROE in the model 3,

Analysis of microfinances' performance and development of informal institutions in Cameroon

this model is statistically significant. We found with the F test that observed value 0.695 is greater than empirical value 0.409. We can conclude that this model is useful to estimate ROE. Thus social performance variables used in this model influence the dependent variable ROE, ceteris paribus (assumption of good management practice). It is important to note that the same conclusion can be drawn when Operational Self Sufficiency stands as a dependent variable

? Negative link, H1b: «influence of social performance on financial performance implies arbitration»

This hypothesis is so particular because the mission drift has been found only in one case. In fact taken as a dependent variable in sub model 1 in the financial regression analysis, social performance variables have no influence on the Return on Equity. This implies that the regression equation was not useful to estimate the ROE, because the observed value of F test was less than the empirical value.

Secondly the research focuses on hypothesis two (H2) which assumes that: «financial performance influences social performance»

? Positive link, H2a: «good financial performance enables the firm to allocate some margin to social issues»

This hypothesis has been tested in social performance regression. In fact, under the model where Average Loans/GDP is considered as an independent variable, they found that financial performance variables are useful to estimate the AL/GDP. Therefore, we can observe that all the entire sub models have a very high value of F test, and this is very significant. Indeed the results show that there is a positive link between AL and financial performance variables ceteris paribus. This implies the availability of fund by the Microfinance Institutions.

? Negative link, H2b: «financially powerful companies are the worse in terms of SP because of their leaders' greed, who do not share the margin»

This hypothesis can be verified through the social performance regression when the Commitment in Favour of Individual Related is considered as an independent variable. In fact all the entire models used here enable to prove that financial performance variables do not influence the CFIR and justify the fact that financially powerful companies are the worse in terms of SP because of their leaders? greed, who do not share the margin.

As we have mentioned earlier in our research another task was to prove the relationship between the microfinances? performance and the development of the informal sector in Cameroon. Thus we have stated two other hypotheses: 113 and 114

Analysis of microfinances' performance and development of informal institutions in Cameroon

The regression applied here was the social performance regression. The Gross Loan was set as the dependent variable. In that case, we have similar results as the above conclusion. Therefore, social performance through the AL/GDP influences the Gross Loan and consequently the development of informal sector.

VI.2- Limitations and recommendations

The occurrence of mission drift involves both the financial and social performance of

MFIs. Consequently, this research required a comprehensive analysis of the performance of MFIs. Choices have been made, leading to limitations and recommendations.

First of all, we have faced several problems at the level of data collection. Indeed social and financial data concerning Cameroon?s microfinance institution are very limited. However the existing data are difficult to access and sometimes there are not available and classified as confidential. In addition, the lack of data over several periods, making it impossible timing analysis that would allow us to better appreciate the impact of financial performance on the degree of social significance and vice versa.

Regarding the analysis method we used, we could also assess the financial performance of MFIs using DEA (Data Enveloping Analysis) as suggested by D'ARCIMOLES and TRÉBUCQ at the end of their article. Moreover Cull, Kunt and Morduch (2007) in their analysis of the trade-off between profitability and serving the poorest, their disaggregated variables depending on the type of loan used (lending type), ie according to whether individual loans and group loans. It would be interesting to add this variable, but we do not have the necessary data. Another control variable that was also very relevant is the interest rate on loans.

However, we noticed that Cameroonian MFIs do not use the research and development variable as observed in other countries. The lack of this variable also reduces the efficiency of assessment of MFIs. The lack of data concerning the number of women borrowers does not also

Analysis of microfinances' performance and development of informal institutions in Cameroon

enable a better analysis and understanding the deep of outreach of the poorest population, also called the social performance indicator. Sometimes, we face another problem which is non-availability of the information in microfinances? websites and even on the National Institute of Statistics website, Ministry of Finance, Ministry of Economics and other financial related institutions such as banks and libraries.

The most significant difficulty was the assessment of the impact of MFIs on the development of the informal sector. This is because data about Cameroonian informal sector are very scarce and sometimes inaccessible. Our task was therefore difficult but finding solutions to this problem came out to be interesting. Indeed we made use of the fixed deposits and gross loans in favour of clients and we used these data as informal sector indicators.

Moreover the relevance of this study is the lack of related research in the same field of study in our country. Therefore, for further researches, this thesis could be used to improve the assessment of microfinance activities in Cameroon.

Analysis of microfinances' performance and development of informal institutions in Cameroon

Allouche, José et Laroche, Patrice. 2005. "A Meta-analytical Investigation of the Link between Corporate Social and Financial Performance?" Revue de Gestion des Ressources Humaines, Juill-août-sept, pp.18-41.

CGAP (2003) «Microfinance Consensus Guidelines» Retrieved 25 June 2009, from the world wide web:

CGAP (2006) «Access for All: Building Inclusive Financial Systems». Retrieved 2 June 2009, from the world wide web:

Cull R., Demirguc-Kunt A., Morduch J. (2006): «Financial performance and outreach: a global analysis of leading microbanks», Policy Research Working Paper Series 3827, The World Bank.

Cull, R., Demirguç-Kunt, A. & Morduch, J. (2007) «Financial performance and outreach: a global analysis of leading microbanks». In Economic Journal, Royal Economic Society, volume 117(517), pp. F107-F133, 02.

D'Arcimoles C.-H., Trébucq S. (2004) : «Étude de l'influence de la performance sociétale sur la performance financière et le risque des sociétés françaises cotées (1995-2002)» La Semaine Sociale, 1186, octobre, pp 108-117.

Griffin J.J., Mahon J.F. (1997), «The Corporate Social Performance and Corporate Financial Performance Debate - Twenty-Five Years of Incomparable Research », Business & Society, vol 36, n°1, march, p. 5-31.

Hishigsuren, G. (2007) «Evaluating Mission Drift in Microfinance: Lessons for Programs with Social Mission». In Evaluation Review, volume 31, number 3.

Morduch J. (2000); «The microfinance schism» World Development, 28 (4), pp 617-629.

Navajas S. Schreiner M., Meyer R.C., Gonzalez-Vega C., Rodriguez-Meza J. (2000): «Microcredit and the Poorest of the Poor: Theory and Evidence from Bolivia», World Development, 28 (2), pp 333-346.

Preston L.E., O'Bannon D.P.(1997), « The Corporate Social-Financial Performance

Analysis of microfinances' performance and development of informal institutions in Cameroon

Relationship - A Typology and Analysis» Business & Society, vol 36, n°4, December, p. 419-429.

Ullman A. (1985), «Data in Search of a Theory : A Critical Examination of the Relationship Among Social Performance, Social Disclosure, and Economic Performance», Academy of Management Review, vol 10, p. 540-577.

Waddock S.A., Graves S. B. (1997); «The corporate Social performance-Financial performance Link», Academy of management Review, 10 (4), pp 303-319.

Analysis of microfinances' performance and development of informal institutions in Cameroon

VARIABLES	SHORTENED FORM	Unit
Return on Asset	ROA	%
Return on Equity	ROE	%
Operational Self Sufficiency	OSS	%
Average Loan Size per GDP	AL/GDP	%
Commitment in Favour of Indivual Related	CFIR	%
Commitment in Favour of Global Related	CFGR	%
Total Asset	TA	FCFA
Coefficient of Activity	COA	%
Hedge Loan by Available Resources	HLAR	%
Fixed Deposits	FD	FCFA
Gross Loan	GL	FCFA

CCA	Crédit Communautaire d'Afrique
CERISE	Comité d'échange et de Reflexion sur les systèmes d'Epargne
CGAP	Consultative Group to Assist the Poorest
COBAC	Commission Bancaire d'Afrique Centrale
FCFA	Franc de la Communautaire Financière Africaine
FP	Financial Performance
IRAM	Institut de Recherche et d'Application des Méthodes de Développement
IS	Informal Sector
MINFI	Ministry of Finance
NGOs	Non Governmental Organisation
PRSP	Poverty Reduction Strategy Paper
S&P	Standard and Poors
SESAME	Microfinance Activity Evaluation and Supervision System
SP	Social Performance
SPTF	Social Performance Task Force
TAP	Traditional Apprentice
USD	US Dallar
MIX	Microfinance Information eXchange