Microfinance, Entrepreneurship and Rural Development: Empirical Evidence from Makueni District, Kenya. By: Joy M. Kiiru Centre For Development Research (ZEF) Bonn University Walter Flex Str. 3, D 53113 Bonn Germany, email
[email protected]
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Abstract Although microfinance has elicited different reactions from different stakeholders, there seem to be a general agreement that it is useful in reducing poverty. However the context in which microfinance is of help to rural poor households is not well researched. This study is an attempt to contribute in to the debate on what works and what does not work for microfinance and poverty reduction. Our main objective is to find out under what circumstances microfinance creates jobs, and increases wage employment and higher incomes in the rural areas. We use a rich panel data set collected from the south western part of Makueni district with three observations within eighteen months to study the welfare effects of microfinance on the rural households and the patterns of entry, exit, and growth of micro enterprises, and to compare these with the mainstream theoretical and empirical work on rural development through entrepreneurship. Key words: entrepreneurship, microfinance, poverty reduction. 1. Introduction About 65% of Kenyans live in the rural areas deriving their livelihoods mainly from agriculture. However over the years the subsistence agriculture sector has continued to suffer declining productivity. The effect of this decline has been lost incomes, food insecurity and widespread poverty. The declining agricultural production for small scale farmers has to a large extent been caused by erratic rainfall since most of the subsistence agricultural productivity in Kenya is rain fed. However, on the other hand even when the rural areas receive a reasonable amount of rainfall peasant farmers who form majority of farmers still have to content with low yields and food insecurity due to lack of proper or non utilization of farm inputs to enhance productivity and also lack of proper storage and preservation of farm produce. Low agricultural production has serious implication on welfare not only in terms of food insecurity but also in terms of lost incomes thereby leading to inability to afford social services like quality health care and education. These problems coupled with a lack of integration of the rural and urban economies have contributed to the increase in poverty among the rural poor that mainly depend on agriculture. Many public policies in the recent times have been focused towards poverty reduction, finding ways to improve household productivity and thereby incomes. Since the 1960s and 1970s, there have been policies on the role of microfinance in the rural development process. These policies focused on the provision of agricultural credit as a necessary support to the introduction of new, more productive agricultural technologies that would ensure that farmers improve their incomes and feed the nation (Moll 2005). Later this approach broadened to include individuals involved in both small and micro- enterprises like handcrafts and home based business.
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1.1. Rural Poverty and the Microfinance Promise
Low labour productivity
Low incomes
Low household demand for goods and services Figure 1: the poor are held up in a vicious cycle of poverty: Poor households are held up in a vicious cycle of poverty, where labor, their best resource is “locked up as unproductive” due to different constraints including a liquidity constraint. For example a poor household may have family members who are willing to work in the family garden to grow crops. However if they can not afford improved crop varieties and farm inputs then the returns to their labour are not enough to ensure a good standard of living. Many governments and donor communities believe that the liquidity constraint is the most important constraint impeding poor households and that if it is addressed it will be possible for households to escape poverty. Economists argue that to break the vicious cycle of poverty, there needs to be an outside force that will intervene at some point of the cycle to improve demand for goods and services. This could be done by for example injecting some liquidity, thereby unlocking the productivity of household labour. Microfinance promises not only to break the vicious chain of poverty but also it promises to initiate a whole new cycle of virtuous spirals of self enforcing economic empowerment that lead to increased household well-being. Figure two is illustrates the microfinance promise.
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Unlocking household labour that had been locked up due to liquidity constraints
Microfinance Repayment
High productivity
High incomes
High household demand for goods and services
Improved nutrition
Better health care
Better education
Escape from poverty Figure 2: Microfinance promise Such is the model that has promoted the microfinance institution and given it the “polite and respectable” image it currently enjoys. There are several assumptions that go with this model, first it is assumed that all poor people can become micro-entrepreneurs if only they were given a chance through credit; and even if this assumption were to be granted, the model further assumes that there is a vibrant market for goods and services and that it is possible for micro-entrepreneurs to get linked up to markets for their products: otherwise how else is microfinance supposed to improve incomes if there was no demand for goods and services, Lastly some proponents of the model also assume that the fact that the poor can repay at market interest rates or slightly above market rates it is a good indication that they are improving
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their financial status and therefore it is a sign of good impact of microfinance; the irony being that even before the microfinance revolution many governments and non governmental organisations believed that informal money lenders were exploiting the poor and that is why it was justified to bring to the poor a cheaper alternative; yet the poor were still paying for the money lender services!! On the other hand great stories on the benefits of microfinance have been told from around the globe and have gone a long way to turn microfinance from a few scattered programs in to a global movement. Consider the ever repeated stories of women and their families living at the verge of poverty and desperation, then eventually the lives of the household members take a turn for the better once these women are given the opportunity to access credit. These women usually do not get in to very sophisticated enterprises but rather they may buy some yarn and other sawing supplies, or start any other such humble business venture, and they are already off in to a route course that will see their households lifted out of poverty and can afford better nutrition, health and education for their children. Great anecdotes like these ones should not be substitutes for careful statistical investigations; we need to have statistical information if indeed the success story generally applies to most of the microfinance clients. What is important is to understand that these great stories are generally meant to illustrate the potential of microfinance while statistical investigations and analysis are meant to show typical impacts across the board. Regarding the argument that microfinance enables households to start income generating enterprises, development economists argue that if every informal self employment is to be defined as entrepreneurship then lots of such entrepreneurship in a country does not necessarily mean economic growth or the reduction of poverty (Acs 2006). Acs continues to say that, “If by entrepreneurship, one allows inclusion of any type of informal self-employment, then high levels of such entrepreneurships may actually mean either that there are substantial bureaucratic barriers to formally creating a new business, or simply that the economy is creating too few conventional wage-earning job opportunities. Under these circumstances, we might reasonably hypothesize that high level of sole- proprietorship informal entrepreneurship would correlate with slow economic growth and lagging development (Acs 2006). Logically, it can not be expected that microfinance is a “magic bullet” against poverty. In some contexts just like research has demonstrated microfinance could work well for the poor Khandker (2005), Morduch (1999) and in other contexts it may not work the same way Kiiru and Mburu (2006), Kiriti (2006). Once researchers and policy makers agree that microfinance can not be a panacea against poverty then research would concentrate more on what works and the context in which it works. It is within this background that this paper becomes of importance. Our main objective is to find out under what circumstances microfinance creates jobs, and increases wage employment and higher incomes in the rural areas. We have two main research questions, the first research question is: What are the individual household characteristics in the rural areas and which of these household characteristics are important determinants in the participation in joint liability microfinance borrowing groups. The second objective is to find out the effect of these loans on the livelihood assets of households. We use a rich cross-sectional data set collected from the south western part of Makueni district in
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Kenya to study the households’ access to microfinance credit and how this affects their livelihoods. The analysis is based on the mainstream theoretical work on rural development through entrepreneurship. The results are interesting, the econometric model show that demand for joint liability microfinance loans decrease with household socioeconomic status in the sense that wealthier households are unlikely to join joint liability microfinance programs. We also find that the possibility of good welfare outcome after a microfinance intervention is also influenced by the pre-existing wealth of participating households. In other words there are three important points we are making from these results; the first is that microfinance is only an option for the relatively poor of the society, second even among the participating poor there are the better “off poor” or the active poor who are likely to get positive impact from microfinance and thirdly the vulnerable poor have a greater risk to slide backwards in the course of stringent loan repayment procedure. Yet these results are not far fetched, theory as well as recent empirical work confirms that indeed microfinance is an option for the relatively poor in society (Roodman 2006,). The richer in society would rather opt for individual loans which are cheaper in terms of both interest rate and also do not have the kind of opportunity costs that go with joint liability loans. In line with these findings other researchers have written that the vulnerable poor are too poor to benefit from market oriented approaches and as such some have even recommended social safety nets as well as basic charity as a poverty intervention for the vulnerable poor (Morduch, 2000, Amin et al 2003). We discovered that there are two kinds of entrepreneurship in the rural areas, the first is an “opportunity” driven entrepreneurship1 and the second is a “necessity or survival” driven entrepreneurship. Opportunity driven entrepreneurship means that the household starts a business enterprise in order to exploit a good business opportunity as opposed to necessity or survival entrepreneurship where the household would start a business for basic household economic survival. Households involved in necessity entrepreneurship tend to be of lower socioeconomic status, are looking for basic household survival in terms of meeting basic needs like food and medication, these households are likely to deplete their livelihood assets in loan repayments and are more likely to become worse off in the process of borrowing and repayment in a market oriented microfinance intervention. The results also show that loan repayment rate by the joint liability borrowers is well above 97%, however about 15% of the households studied end up depleting their livelihood assets and therefore become worse off in the course of loan repayments. Another 8% of the households experience no significant welfare effects on accessing microfinance. Given the results of this study we could draw two important policy implications. The first echoes Kiiru and Mburu 2006, where they argue that microfinance can not improve welfare unless there is effective demand for goods and services, which ensures that the products of micro-entrepreneurs are consumed. Theoretically speaking the presence of a market for goods and services is one of the push factors of a rural economy from stage one to the next stage. There is therefore need for targeted policy measures to increase consumption of goods and services in the rural areas. 1
Opportunity driven entrepreneurship means that household get in to entrepreneurship in order to exploit a business opportunity as opposed to necessity entrepreneurship where households get in to entrepreneurship for the sake of household survival since no other opportunity is forth coming.
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Secondly; the microfinance institutions involved in the study area “officially” lend to boost business enterprises by the poor in the rural areas. Surprisingly, they have no proper control to ensure that this indeed is the reality. This is the case given the fact that just like any other such microfinance institution, they have shifted some two classic banking obligations to their clients, namely: it is the clients who decide who is credit worthy and it is still the same clients who are responsible for debt collection. The issue becomes problematic when borrowing groups use the “ability to repay” criteria based on household assets and peer contracts to recruit members in to the borrowing groups. As long as there continues to be a disjoint between the objectives of the microfinance institution and the operations of the borrowing groups many poor households will continue to loose basic livelihood assets in the process of loan repayments through peer repossessions or undue peer pressure. In conclusion, there are no strong indications that microfinance is leading towards the path of rural development through entrepreneurship as expected. Households are trapped in to micro-sole proprietorships as they continually get involved in survival entrepreneurship. There is a glaring absence of markets for diversified goods and services and therefore in a bid to meet strict debt regulations, rural microfinance participants compete in over supplied and fast moving products but with marginal returns, thereby exerting a downward pressure on product prices and therefore profitability, and the overall ability to raise household incomes. If household incomes continue to be low coupled with bad inter-rural infrastructure then the overall rural economic system can not be propelled to the next stage where we expect increased (paid) job opportunities in relatively larger enterprises, and less micro-sole proprietorships due to diminishing returns in management. The rest of this paper proceeds as follows, section two is the theoretical framework, followed by the economic model and then econometric models; Section three is the results and discussion while in section four we put down some concluding remarks.
2.0 Theoretical Model: Rural Entrepreneurship and Development Let us begin the theoretical modeling of the rural economy by asking a straight forward question: Is informal micro entrepreneurship in the rural areas good for the economic development of the poor?2 This question may not necessarily have an obvious simple answer like yes or no. Many would like to argue that as long as micro entrepreneurs create new businesses and new businesses in turn create jobs and intensify competition, and may even increase productivity through technological change, then high numbers of informal micro enterprises in the rural areas will thus translate directly into high levels of economic well being. However, the reality about persistent high levels of informal sole proprietorship in the rural areas and what it means in terms of economic well being could be much more complicated; at least in theory. Just as development economists distinguish three major stages of economic development we could as well distinguish three major stages in transforming rural households and 2
In modeling this rural economy I was greatly inspired by the works of ACS (2006) where he models entrepreneurship and economic growth. For a complete reference refer to the reference section.
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rural economies from poverty stricken to wealthier households. In the first stage, the households engage in subsistence farming, spending most of their expenditures on food; Sachs, (2004) writes that “farm households in the rural sector live pretty much in economic isolation. There are no roads within the villages, and there is no electricity. Households are mainly subsistence farmers consuming most of what they produce and commercial activity in the village is very low”. This stage is characterized by disease, hunger and general poverty. When microfinance becomes an option at this stage, each household chooses whether or not to accept microfinance depending on utility preferences. They accept microfinance if the utility of accepting microfinance exceeds the utility of not accepting. Depending on household characteristics and socioeconomic status of the household there are two main reasons why entrepreneurship becomes attractive to households in poor rural areas, the first reason has to do with the possibility to exploit a business opportunity given microfinance as a source of capital (opportunity–driven- entrepreneurship or financing), while the other reason has to do with raising fast finances for household survival (survival- driven- financing). If households involved in “survival- driven- financing” ever invest the loan money, the investments are usually in over-exploited business ventures with marginal but fast returns (Kiiru and Mburu, 2006). Research has shown that whether a household gets in to either survival or opportunity driven financing it mainly depends on the socioeconomic status of the household and\or entrepreneurship capability. However theoretically microfinance is likely to thrive in the first stage of economic development mainly because households are willing to comply with the credit conditions due to lack of alternatives. Regardless of whether the household is involved in either survival or opportunity- drivenentrepreneurship real income improvements will be realized depending on whether the following preconditions are met. First there must be some entrepreneurship capability within the household, second there must be at least some reasonable infrastructure facilitating easy inter-village and inter shopping-centre movements in order to improve local market for goods and services. These two are the greatest push factors from first to second stage of rural development through entrepreneurship. These push factors need to be reinforced by conscious policy actions to improve the demand for goods and services among the vulnerable poor who can not directly benefit from market oriented intervention policies. In the second stage, we rationally expect enterprise growth from informal micro- sole proprietorships to small and medium scale enterprises in line with income maximization principle. Theoretically this stage should be marked by decreasing rates of household micro sole-proprietorships. There are reasons to expect that entrepreneurial activity in terms of number of enterprises should decrease as rural economies pick up. To understand how this happens let us assume that individuals have different endowments of managerial ability, then as the rural economy becomes wealthier, the average enterprise size should increase as better managers run enterprises (Acs 2006). Average enterprise size is an increasing function of the wealth of the rural economy if capital and labor substitute. When capital and labor are substitutes, an increase in the capital stock increases the returns from working and decreases the returns from managing. In other words, marginal managers find they can earn more money while being employed by somebody else (Acs 2006). The overall expectations is that as the
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rural economy becomes more developed with lower absolute poverty incidences we should find fewer people pursuing informal micro sole proprietorship. There is also another explanation as to why we expect the quantity of household sole proprietorships to decrease with rural economic development. Households that get involved in informal sole-proprietorship because of lack of a better income alternative may find that on easing the liquidity constraint through microfinance and realizing improvements in income, it is possible to achieve more utility from agricultural activity as they can now afford farm inputs. Households will only shift from entrepreneurship fully to agriculture (and or) wage employment as long as returns from agriculture (and or) wage employment are more compared to returns from entrepreneurship; a scenario that is determined by access to capital, household managerial and entrepreneurial capability as well as a market for the goods and services produced. Decreasing micro - sole proprietorships and increasing wage employment coupled with a rise in agricultural productivity and better infrastructure should lead the rural economy to the third stage. In the third stage we expect that the increasing wealth for the rural households, as well as the overall wealth of rural economy will lead to the integration of the rural economy with the urban economy as well as the subsequent alleviation of poverty. 2. The Econometric Model: Household Selection in to Microfinance Joint liability Borrowing groups Each household chooses whether to join the groups and what business to invest in based on preference and prevailing household income conditions. Households take loans when utility of taking the loans exceeds utility without the loans. To model household decision and final selection in to the joint liability borrowing groups, we propose to use the Heckman model in order to eliminate any bias due to self selection in to the borrowing groups. In the selection equation, the likelihood of joining a borrowing group and the subsequent entrepreneurship decisions depends on the same set of regressors plus variables that describe individual household characteristics. An individual household would like to start or boost already existing businesses using microfinance loans in order to maximize utility, which depends on household consumption (C) and whether household would be selected in to a joint liability group,
U = U (C , h( X , Z , φ )..........................................................................................1 C is a continuous variable, The function h(.) reflects household preferences for loans through joint liability borrowing, and depends on observables, X and Z , and unobservables φ . Each household involved in loan programme has three types of attributes, first, there is a vector X of characteristics, such as education, and household size that are observable to the researcher. There are also two types of unobservable characteristics. µ L represents entrepreneurial capacity, the ability to take risks, or managerial capacity and the other standard unobservable that favorably impact business returns. µ H represents characteristics such as honesty and other business ethics that are more closely associated with business productivity.
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The first step is to solve for a households decision to join the borrowing groups, given its observables, unobservables, and the microfinance market. The second step is to estimate the coefficients of the independent variables that determine access to loans. Microfinance institutions impose a trade off between what the entrepreneur desires as entrepreneurial capital α and actual business capital requirements Q that is determined by the institution after evaluation. Individual households face a range of (Q, α) pairs, the fraction of Q and α, is negotiated prior to actual financing. The choice is summarized by the expression:
α = α (Q, X , µ L , µ H ,π )................................................................................................2 where π represents group conditions favorable to being accepted as a member of a microfinance joint liability borrowing group. α is increasing in X, π, and the µ’s. The household’s consumption is described by the expression: C M = α (Q, X , µ L , µ H ).g (Q, X , µ L , µ H ).....................................................................3
Where g (Q, X , µ L , µ H ) is business returns which depend on market conditions for the goods and services and household specific characteristics. Given household entrepreneurial capabilities and market conditions, the maximum consumption for a household is the solution of the problem:
MaxQ
CM = MaxQ
α (Q, X , µ M . , µ H , π ) g (Q, X , µ M . , µ H )....................4
The solution of this problem is, Q* = Q * ( X , µ E , µ H , π )...................................................................................5 The consumption of a household that is not a member of a joint liability borrowing group depends on its observables, X, and the two unobservable components: C S = f ( X , µ L , µ H )...........................................................................................6 They will join the joint liability borrowing groups if the utility from the loans outweighs the utility without the loans. i.e if: M = U (C M (Q*), h( Z , X , φ ).1) − U (C S ,0) > 0...........................................................7 Or the reduced form
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~ ~ M = M ( X , Z , π , µ L µ H , φ ) > 0…………………………………………………….8 The econometric model of whether a household joins a joint liability borrowing group is obtained by linearizing equations (5) and (8):
Q* = Xβ Q + πγ Q + ε Q ………………………………………………………….9a ~ M = Xβ M + πγ M + Zδ M …………………………………………………………..9b Where X, π, and Z are vectors of observables, and β M , γ M and δ M ( K ∈ (Q, M ) are the ~ respective vectors of coefficients. M > 0 ⇔ M = 1 and indicates that a household receives microfinance loans. The error terms in (9a) and (9b) can be expressed in terms of the unobservable µ L , µ H , and φ , and constants a,b, c, d and e:
ε Q = aµ L + bµ H ....................................................................................................10a ε M = cµ L + µ H + eφ ..................................................................................................10b The selection model is estimated under maximum likelihood, assuming that ε M and ε Q are distributed bivariate normal. When ε M and ε Q are distributed bivariate normal:
[
]
E [Q | M = 1] = β Q X Q + πγ Q + A ε Q M = 1
= β Q X Q + πγ Q + cov(ε Q , ε M )λ ( Xβ M + πγ M + Zδ M ) ………………………………..11 Where λ ( Xβ M + πγ M + Zδ M ) is the inverse mills ratio. Because Z is included in (9b) but not (9a), the model is identified (in addition to the identification through nonlinearity). The strength of the identification assumption is gauged from a test of the joint significance of the variables included in Z. The covariance between the error terms can be expressed as:
cov(ε Q , ε M ) = cov(aµ L + bµ L + dµ H + eφ ) = acδ µ2L + (ad + bc )δ µL , µH + bdδ µ2H + aeδ µL ,φ + beδ µH ,φ ................................12
When (12) is positive we have positive selection: On net, the unobservables associated with desire for credit are correlated with the unobservables affecting the propensity to attain credit from the microfinance institution. In this case, households that already have
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credit have more favorable unobservables than households that do not have credit. However, if, say, c is sufficiently negatively, or if the two µ’s are sufficiently negative correlated, then we have negative selection. Then, households that receive credit have less favorable unobservables than households that do not. A test for the presence of selection is a test of whether:
ρ (ε Q , ε M ) ≡ cov(ε Q , ε M ) / (δ εQ δ M ) ≠ 0...........................................................................13 While we cannot estimate the parameters, a, b, c, d and e individually, we can conjecture about the sign and relative magnitude of (12) (and therefore (13) in various cases. For instance, by assumption, µ L and µ H increase value in the credit market and φ measures preferences for credit. This implies that a, b and e > 0, respectively.
2.3 Welfare effects of Microfinance Sustainable livelihood approaches have focused on assets to measure poverty and vulnerability to poverty. Quantitative work has also found that access to assets is an important determinant of poverty and of the ability to cope with hardship. Our task here is to develop an analytical framework to determine when a household could be said to have become poorer based on ownership of assets. We define the model as follows; Let the vulnerability of household h , be vh , and the welfare measure be y which for this case it is approximated by access to assets. We define the vulnerability of household hi as vhi = f ( yhi , z , phi ) where z is a benchmark welfare indicator and p is the probability of falling below this bench mark. Z is a relative benchmarking which for all households it is less than the initial wealth index. Therefore vulnerability or decrease in welfare (Z i ) after a microfinance intervention can be defined as follows E ( Z i ) = Pi ( Z i ) = f (αX i ) Where Z i denotes vulnerability as a discrete variable, and X i denotes variables that can be hypothesized to affect vulnerability. By employing the model as specified above, the logit model can be applied to provide information about the determinants of welfare outcome (better or worse) after microfinance intervention for different households. The Logit model is usually specified as follows: e αX i E (Z i ) = P (Z i ) = 1 + e αX i Where α is the coefficient to be estimated and E (Z i ) = P(Z i ) = 1, if the individual becomes worse off after microfinance intervention 0 otherwise. Variables used in the model are shown in table 3.
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2.5 Rapid appraisal method for measuring relative poverty Ownership of and access to assets is very important socioeconomic indicator. In this particular study ownership of assets3 was particularly important for the household to become a member of a joint liability borrowing group. Assets were closely associated with intra group insurance activities in that group members were not willing to insure each others loans based on trust alone. Group members demanded to be shown what assets could be liquidated by the group incase of default. To be able to compile a legitimate4 list of assets which could be used for wealth ranking, we asked borrowers to write down all the assets that are available among members and that could be used to secure their loans. What we learned from this exercise is that the poor don’t have many assets and virtually every asset they had apart from land was eligible to act as collateral depending on its condition, “good or bad”. These assets included kitchenware, simple electronics, clothing, furniture, livestock among other household assets. During focus group discussions we asked the participants to rate the worth of every asset relative to another. The ranks given by members indicated the value attached to each asset and gave an indication of magnitude of the index assigned to the different assets in this study. It is true that these weights are very subjective, but the good thing about them is that they were informed by how the society attaches value to assets in terms of wellbeing of a household. A much more complete list of the assets used is given at the annex section of this paper. The other advantage about this kind of exercise is that in case a household has problems of repayment of their loans the same assets would be liquidated in most cases. On the other hand, if a household became better off, there is an incentive to invest in more assets since they could be used to guarantee larger loan amounts in the future. Barnes et al (1993), observes that there is a strong case that assets are particularly useful indicator of impact because their level does not fluctuate as greatly as other economic indicators and it is not simply based on annual estimates. Zeller and Meyer (2002), Argues that subjective measures of relative poverty or wellbeing are very important since to be poor is relative; it is therefore the relativity in poverty that is important to the policy maker. Apart from ownership of assets focus group discussions revealed that the general condition of a homestead is also a strong indication of the social economic status of that particular household. In light of this we included variables like walls, roofing and floor of main house to explain household socioeconomic status. Each was ranked differently depending on how the community viewed the worth of such construction materials. Finally by use of this rapid appraisal method we were able to construct a wealth index per household as a measure of household socioeconomic status. The index is a continuous variable.
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The wealth index compiled in this study is only relevant to the study area and therefore the same relative poverty measure can not be used for another study. 4 The list of assets that is relevant in the study context
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2.4 Data The analysis uses a primary panel of data with two observations within a period of 18 months. 400 households were interviewed, 50% of the respondents were participating in joint liability microfinance programs while the rest were not. Data collection was by use of formal questionnaires, participant observation and focus group discussions. Table 1: Summary of variables used in the regression model
Variable Age of head of household Gender of household head of household Household assets (pre existing) Level of education of head of household House hold size
Abbreviation agehead sexhead
Definition In years Dummy variable, 1= male, 0 other wise
wealth
Business size (pre existing) Other source of credit
size othercredit
Average Calculated index (the bigger the index the wealthier the household) Number of years spent in formal schooling of head of household Number of people who live together and eat from the same kitchen in a particular household Business worth in Kenya shillings If household has any other source of credit other than microfinance
edu sizehsel
Table 2: Variables used in the selection model
Variable
Abbreviation fod
Own food Age of head of household Gender of household head of household Household assets (pre existing) Level of education of head of household House hold size Business size existing) Fulltime or part entrepreneurship
agehead sexhead wealth edu sizehsel
(pre- size time fulltime
Definition How long in months home grown food lasts in the previous 3 growing seasons In years Dummy variable, 1= male, 0 other wise Average Calculated index (the bigger the index the wealthier the household) Number of years spent in formal schooling of head of household Number of people who live together and eat from the same kitchen in a particular household Business worth in Kenya shillings Whether household is involved in part time or fulltime entrepreneurship
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Table 3: Variables used in the Logit model
Variable Own food
Abbreviation Definition fod How long in months home grown food lasts in the previous 3 growing seasons. Age of head of household agehead In years Gender of household sexhead Dummy variable, 1= male, 0 other wise head of household Household assets (pre wealth Average Calculated index (the bigger the index the existing) wealthier the household) Level of education of edu Number of years spent in formal schooling of head head of household of household House hold size hhsize Number of people who live together and eat from the same kitchen in a particular household KADET kadetdum 1 if household receives loan from Kadet, 0 otherwise KWF kwftdum 1 if household receives loan from KWFT, 0 otherwise KREP krepdum 1 if household receives loan from KREP, 0 otherwise
3. Results and Discussion
3.1 Descriptive Many microfinance institutions prefer lending mostly to women, while some institutions like Kenya women Finance Trust (KWFT) lend exclusively to women. The main reason being that, not only are women better payers, but also empirical evidence has shown that women’s income have a great impact on overall household welfare, in terms of nutrition and education for girls (World Bank 2001). Little wonder that in this study 75% of the random sample of all the borrowers was female while 25% was male. The following is a table showing descriptive statistics of the size of household, age of household head, and years of formal education for the whole sample, Table 4: Descriptive statistics
Size of household Age of head of household Numbers of years of formal education
Minimum Maximum 1.00 13.00 19.00 75.00 .00
16.00
Mean 4.30 34.81
Std. Deviation 1.89901 8.85407
10.02
2.95557
Source: field data Thirty five percent of the total population sample of households was female headed, while 40% of the sample for households involved with microfinance was female headed. About 73% of all the respondents said that business was their main occupation, while the rest were civil servants, i.e teachers (7%), casual laborers (8%) and peasant farmers (12%). This result seems to be against the expectations of a typical rural setting, where
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the majority of households are expected to be relying on farming as their main occupation. How ever this could be explained by the fact that prior to the study the eastern province of Kenya and other arid and semiarid regions had suffered a prolonged drought for about 5 years. Many peasant farmers had therefore looked for other opportunities like entrepreneurship to earn a living. Of all the enterprises studied, 85% were located within rural shopping centers while the rest were local canteens and tea kiosks. About 58% of the entrepreneurs operated small retail shops and tailoring shops while the rest were involved in micro entrepreneurship activities like food vending 11%, and vegetable / grocery stands (30%). We identified three main microfinance institutions serving the area, these were Kenya Women Finance Trust (KWFT) with about 60% of all borrowers, K-rep with about 20% and Kenya Agency to Development of Enterprise and Technology (KADET) served 20% of all borrowers. All the institutions used the group lending approach to avail credit to their clients. Many researchers view the group borrowing approach as pro poor since it overcomes the challenge of lack of collateral by the poor, thereby encouraging the poor to access credit. At the same time group lending approach assures high loan repayment rates for the lending institutions. However this study asserts that this approach does not necessarily mean that the poor access microfinance without any form of collateral. The difference between securing loans by means of peer guarantee and a formal financial institution is only in the type of collateral and how recovery of unpaid debts is carried out. Whereas the formal financial institutions will insist on formal collateral like title deeds, logbooks etc, the group lending approach mostly relies on peer pressure from borrowers to recover debts.
3.1.2 Operational Structure of the Joint Liability Borrowing Participant observation as well as focus group discussions revealed that, amongst all solidarity (borrowing) groups there exists a rigorous administrative structure to ensure that every loan is repaid on time. For example, In order to minimize the risk of non repayment by some poorer borrowers, solidarity groups advise their weaker members to start submitting their loan installments to the group’s treasurer on a weekly basis. This is besides the forced monthly savings by the microfinance institution. Neither the group nor the individual can access the forced savings at will, but it can be used as security for future laons and can only be paid back if the individual borrower is dropping out and has been cleared by all members of the group. The forced saving is not only a security for loans borrowed by an individual but can also be ceased by the microfiance instituion if any other member (s) of the group defaults on their loan repayment. Another requirement for all group members is that they must join a merry go round. Contributing funds every other month to one of the members. Incase the recipient of a merry go round fund has outstaqnding balances with the group, the money is not given to them directly but its used to settle the debts. Other fiancial burdens incluse registration fees (both in the group and microfiance insituttion) and loan insurance fee (only in case of death of the client). Focus group discussions revealed that the fiancial burdens on members of a borrowing group are so overwhelming such that members have oftenly found themselves in viciuos debt circles thus compounding the problem. By the 18th month 33% of initial microfiance
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particpartnts had dropped out citing repayment problems while surprisingly another 10% of non participants had already joined the borrowing groups. Some of the biggest challenges facing rural entrepreneurship are low incomes leading to low demand for goods and services, and therefore limited markets. There is also the challenge of competing basic needs like health care, food, and education for children. Micro entrepreneurs often have the dilemma of investing given the risks, or meeting the basic needs with the loan money. This means that loan money will be used for different purposes; focus group discussions revealed that whereas the official reason stated for acquiring loans is business oriented, usually to boost or start one, in reality borrowers used the money for various reasons Table 5: Loan uses
% of borrowers
% of loan money used for domestic purposes 100 75 25 < 25 ~0
1 5 37 20 37
The other loan uses includes basic household necessities, like school stationery for children, health care, food and at times school fees. It is not necessarily bad that households would borrow to smooth consumption, however savings would offer more viable alternative since it equips poor households to manage income volatility without the stress of debt. Respondents shared their experiences on loan repayment with the following result, Table 6: Loan Repayment
Method of Loan repayment Duress Property confiscation by peers Sale of pre-existing property Incur other debts Business Proceeds Source: Field data
% of poor borrowers affected 60 4 17 2 17
Payment by duress in this context means repayment merely due to excessive peer pressure, and not because the borrowers´ financial position allows for voluntary repayment. Domestic animals, house furniture, and electronic goods and sometimes clothing were some of the major assets sold or confiscated to repay the loans. Table 6: Utilization of labor by rural micro- enterprises
Enterprises by Enterprises by Non Microfinance participants Participants 19% of 33%
Utilization unpaid labor Labor from own 17% children 25% Paid labour
9% 39%
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Further research is however needed to establish whether or not this glaring disparity in labor utilization is indeed an extra attempt for microfinance recipients to lower costs of doing their businesses. If this were the case then in reality it would mean that there is a shift in costs that should not be taken for granted.
3.3 Regression Results 3.3.1 Heckman Model Table 7 is a summary of the results of both the regression and the selection model. The coefficient for pre existing business size, household wealth, and level of education of head of household are all significant in the regression model. We find that the demand for microfinance loans decrease with household socioeconomic status in the sense that wealthier households are unlikely to join joint liability microfinance programs. This could be due to the fact that wealthier households would rather avoid the demanding and time consuming schedules associated with joint liability borrowing programs. Similarly extra years of formal education reduce the demand for the joint liability loans. Also for households that are entrepreneurs, pre-existing business size is positively related to the demand of joint liability loans. This could be explained by the fact that the bigger the business the more the demands on capital and therefore rural entrepreneurs who do not yet qualify for formal bank loans might find microfinance a more appealing source of capital. In the selection model, household size is positively related to the possibility of selecting in the joint liability borrowing groups. This could be explained by the fact that larger households in the rural areas tend to be more vulnerable and as such microfinance could offer some much needed consumption smoothing resource. Pre-existing business size, is also positively related to the possibility of joining a joint liability borrowing group. Also entrepreneurs involved in fulltime business are more likely to join the joint responsibility borrowing groups, this is no surprise since fulltime businesses people tend to have larger business than part timers.
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Table:7 Results for the Heckman selection model:
Lnloanaces agesq sizehsel sexhead edusq lnsize lnwealth othercredit cons Selection model agesq sizehsel edusq fod lnsize lnwealth fulltime cons Mills lambda sigma Lambda
Coef.
Std. error
t
p
.0000252 .0131576 -.0181306 -.0017551 .400935 -.0931652 .0878964 6.606237
.0000756 .0314077 .0717359 .0009733 .0569372 .1076122 .1578169 .7485085
0.33 0.42 -0.25 -1.80 7.04 5.87 0.56 8.10
0.739 0.675 0.800 0.071* 0.00*** 0.047** 0.578 0.000
-.0000488 .1005284 -.001788 -.0061312 .1993676 .0773685 .6964761 -2.27346
.0001213 .04398084 .0014972 .0397828 .0608037 .2284696 .2284696 .6806239
-0.40 2.29 -1.19 -0.15 3.28 0.44 3.04 -3.34
0.687 0.022** 0.232 0.878 0.001*** 0.662 0.002*** 0.001
.6286703 .66654144 .62867034
.3423597
1.84
0.066*
.3423597
Source: Field data Note: *Significance at 10% ** Significance 5 % *** Significance 1 % Table 8: Results for the logit model
Variable Constant wea fod hhsize headhseld Edu Agehead k-rep dum kwftdum kadetdum
Coefficient -.81616288 -.02768702 -.27085159 .06738075 -.70364182 -.00322728 .01779930 .23846750 .01074530 -.69689990
Std. error 1.23826944 .00839209 .25484010 .06961234 .28975303 .04709062 .01594885 .78133825 .75545375 .80940690
P Value .5098 .0010*** .2879 .3331 0152** .9454 .2644 .7602 .9887 .3892
Source: Field data Note: *Significance at 10% ** Significance 5 %
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Mean of X 42.7623762 .50495050 4.41089109 .52970297 9.98019802 34.40559406 .19801980 .58515842 .19306931
*** Significance 1 %
The logit model has that a positive impact after a microfinance intervention depends on the pre-existing socioeconomic status of the participating household and that wealthier households are more likely to have positive impact. Other empirical studies have also come to similar conclusion, in a paper measuring impact Coleman (2006) also found that wealthier households receiving microfinance had significant positive impact while the impact on less well off household was insignificant. The study also shows that femaleheaded households are likely to get worse off on accessing microfinance. Empirical studies have found that female-headed households were more vulnerable in terms of poverty, yet it is this vulnerability that makes microfinance institutions to be able to impose strict regulations on their borrowers. According to Roodman and Qureshi (2006), poor borrowers have no options of other better financial services and have no option but to adhere to the strict regulations of microfinance institution. Kiriti-N (2006) also had a similar finding that where as microfinance was really assisting the less poor women to improve their welfare, the poorer women became worse off.
4. Concluding Remarks To understand microfinance and poverty reduction one needs to understand the contextual poverty situation; more so in its relative form. This is because joint liability borrowing does not attract the wealthier of society, and it may not benefit the vulnerable in society. The impact on the active poor who receive microfinance is also differentiated by a number of variables that determine outcome. The most important of the variables being the actual motivation as to why the household is involved in the program; whether for survival or as an opportunity, and the associated household entrepreneurship and managerial capacity and also the question of availability of market for the goods and services produced. Whereas some households may experience marginal improvements in welfare after a microfinance intervention, there is also the issue of utilization of unpaid labour, among other social costs. There are also threatening debt management issues by the microfinance participants. Excess debt can deplete household capital assets and other basic livelihood assets, thereby leaving the household exposed and vulnerable. Excess debt can also increase the propensity for financial crisis and it can have poor households locked up in vicious debt cycles as they seek more debts to repay other debts. Currently loan repayment by the poor is not a big worry to the policy maker; the poor have already proved that they can repay. What should instead worry the policy maker is the cost at which these loans are being repaid. It is generally accepted that many poor people borrow from moneylenders at even higher interest rates for their consumption, so willingness or ability to repay should not be assumed to demonstrate the profitability of investments. At the moment at least in the case study there are no indications that microfinance is leading towards the path of rural development through entrepreneurship as expected. There are stressful debt management schedule that could possibly lead to undercapitalization of enterprises as well as threaten the existing social networks. There is also a glaring absence of markets for diversified goods and services and therefore in a bid to meet strict debt regulations, rural entrepreneurs compete in over supplied and fast moving products but with marginal returns, thereby exerting a downward pressure on prices and therefore profitability. If household incomes continue to be low then rural entrepreneurship and the overall rural economic system can not be propelled to the next 20
stage where we expect increased (paid) job opportunities in relatively larger enterprises, and less micro-sole proprietorship due to diminishing returns in management. Currently households are trapped in to micro- sole proprietorships as they continually get involved in survival entrepreneurship. We come to the conclusion that more than ever there is need to create policies that create demand for goods and services in the rural areas. As well as an urgent need to set up a microfinance regulatory frame work that protects pre-existing properties of the borrowers. As expected such a regulatory policy is likely to change the course of microfinance institution as they attempt to reduce the eminent risk, given that the poor would no longer be pushed below their current welfare to repay their loans. Finally, there is currently a receptive attitude in the national and international community towards microfinance instruments, and by and large the microfinance institution still has the ‘polite and respectable image’ among many donors and governments. It is also true that there is no major apparent crisis in the microfinance institutions. However policies implemented in tranquil times can help prevent major problems in the future.
Limitations of the study The study is open to two main criticisms; first it could be argued that the study uses a relative poverty measure and therefore the welfare measure may not objectively apply in another context. Where as this could be true, it is also true that poverty itself is relative in nature and it is the relativity in poverty that is of more relevance to the policy maker. Second; it could also be argued that eighteen months are far too few to make any concrete remarks about welfare effects of microfinance. Whereas the reader may not be absolutely wrong, I also wish to point to the fact that microfinance offers very short term financial services to the poor. For example a poor person is expected to get US 50 $ loan at about 30 % interest to repay within 6 to 12 months on weekly or monthly installments, plus $ 5.6 forced monthly savings. Given the short term nature of financial transactions between borrowers and lenders for every loan, it is not an absolutely far fetched idea to evaluate microfinance also in the short term. The crucial evidence of what is happening on the ground can provide important impressions of how the long term is likely to look like.
NOTES Assets used for wealth ranking are electronics (mobile phones, radios and televisions); domestic animals (goats, sheep, cows, oxen, donkey and hen); household dwelling (floor of main house, roofing of main house and walls of main house, presence of a toilet and bathroom facility, ownership of borehole and type of fuel used by housedhold); capital assets (ownership of donkey cart, sawing machines, plough, rental houses and oxcart, household cutlery like china ware and aluminum cooking pots and furniture such as sofa chairs, tables, stools, beds, clothing such as “good” bed linen, and “good” clothing fabrics).
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Moll, H., (2005) Microfinance and Rural Development: A long term perspective: Journal of microfinance, Vol. 7 (2) pg 13 -23. Morduch, J. (2000) The Microfiance Schism. World Development Vol 28, No. 4,pp.617629 Roodman, D. and Qureshi, U. (2006), Microfiance as Business, Centre for Global Development Working paper No. 101, Washington DC. Schreiner, M. (2003), A Cost-Effectiveness Analysis of the Grammen Bank of Banglandesh. Development policy Review, 21 (3): 357-382. Zeller, M. and Meyer, R.L (2002), The triangle of Microfinance: Financial Sustainability, Outreach and impact. John Hopkins for the International Food Policy research Institute, Baltimore.
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