The Role of Microfinance on Growth of Small-Scale Agribusinesses in Malawi : A Case of Lilongwe District

The emergence and proliferation of Microfinance Institutions (MFIs) in Malawi gave rise to the need for empirical research to assess their role on growth of small-scale agribusiness entrepreneurs. The paper gives the details of the results of a study which was conducted in Malawi to analyze the role of microfinance on the growth of small-scale agribusinesses in Lilongwe District. A financing constraint approach was applied using logit model to determine factors affecting investments of small-scale agribusiness entrepreneurs. The approach stipulates that entrepreneurs in areas with significant presence of MFIs (unconstrained) rely less on internal funds (average profits) for their investment decisions than areas with limited presence of MFIs (constrained). A T-test was also used to compare investment levels of unconstrained and constrained firms to support the results obtained from the financing constraint approach. Loans were among the products which were found to be offered by MFIs although their accessibility was affected by, among others, high interest rates. The logit model revealed that for each additional profit the probability of investment decreased by 46 percent in constrained firms and 39 percent in unconstrained firms. However, the T-test results revealed no significant difference in levels of investments between unconstrained firms and constrained firms. These results show no significant role of MFIs on growth of small-scale agribusiness entrepreneur. The results have insinuated the review of MFI loans conditions such as interest rates if they are to have a significant role on growth of small-scale agribusiness entrepreneurs.


Introduction
Microfinance has for more than 30 years been portrayed as a key policy and program intervention for poverty reduction and "bottom-up" local economic and socio development (Bateman, 2011).Microfinance is widely acknowledged to be an important catalyst for economic growth and poverty alleviation in poor countries such as Malawi (Littlefield, 2005) where formal financial services through commercial banks reach no more than 20 per cent of the population, most of whom are the rich (Berenbach & Churchill, 1997;Robinson, 2001).The majority of the population, who are typically low income households and poor, are outside established networks of the formal financial services sector.It is with this realization and concern in mind that innovative financial institutions (FIs), in the form of microfinance institutions (MFIs), have emerged and do exist to alleviate constraints to financial access faced by this subsection of the population that yearns for sustainable self-employment opportunities as business entrepreneurs (Hulme, 1999).

Historical Overview of Microfinance Sector in Malawi
The microfinance sector in Malawi emerged in the 1990s.Before then, market for credit to small farmers was in form of smallholder inputs through a state run organization called Smallholder Agricultural Credit Administration (SACA), established in the early 1970s as a department in the Ministry of Agriculture, providing subsidised interest rate credit.From 1991 to 1994 through a partial liberalized marketing policy regime, Malawi Government reduced its role in credit administration.This therefore saw agricultural credit delinked from core responsibilities of Ministry of Agriculture (e.g.agricultural extension).In addition, prior to the first multiparty general elections in 1994, political parties had campaigned on promises of writing-off smallholder agricultural loan debt leading to widespread loan default, eventually the collapse of SACA in 1994, and the establishment of semi-autonomous Malawi Rural Finance Company (MRFC) in 1994 as a successor provider of agricultural credit (Zeller & Meyer, 2002;Diagne, 1998;Burritt, 2006).It is the limited access of credit among the rural poor that has occurred in a liberalized and democratic political environment that has facilitated the proliferation of micro credit schemes or microfinance institutions in Malawi since 1994.Since then a number of developments have occurred in relation to lending to small business entrepreneurs.For example, 2010 saw the formation of the Malawi Microfinance Network (MAMN) which is a formal association of microfinance institutions to develop, promote, coordinate and regulate microfinance activities in the country (GoM, 2002).Starting from two MFIs before 1994; seven in 2000, there are now 21 MFIs which are members of MAMN striving to fill the financial access gaps created by the unwillingness of formal commercial banks and financial institutions to service MSMEs (GoM, 2012).

Small-Scale Enterprises and Agribusiness in Malawi
A vibrant micro, small and medium enterprise (MSME) sector is key to poverty alleviation and growth in poor countries especially those in sub Saharan Africa.They are potential sources of employment and income (Afrane, 2002).In Malawi, Small and medium enterprises have been considered as significant contributors of job creation, development and economic growth.They stimulate competition; provide employment and distribute income (GoM, 2012).In 2012 FINCSOPE surveys revealed that MSMEs collectively created employment for about 1,020,320 Malawian, 98 percent of which are employed by the small enterprises who are part of the economically active population (GoM, 2012) with agribusinesses constituting the largest component of the MSME sector in Malawi in terms of population that operates MSMEs (GoM, 2000).This is so because of the dominance of agriculture in the economy of Malawi where it employs about 80 percent of the country's workforce, accounts for 39 percent of the gross domestic production (GDP) and contributes to more than 80 percent of foreign earnings (GoM, 2010).Despite its prominent economic roles, Malawi's agriculture, in the last 50 years of independence, has remained self-provisioning in character since the majority produce for self-consumption.Government policy that has so far emphasized smallholder production of non-tradable food crops for subsistence and estate production of tradable cash crops for commercial purposes is partly to blame for minimal economic progress witnessed among smallholder farmers in the country.However the paradigm within government is changing; efforts are now in place to help farmers to manage agriculture as businesses.

Microfinance and Small-Scale Agribusiness Entrepreneurs
The vibrancy of the MSME sector resulting from the policy change also means increased demand for financial services to boast capital.Currently, small-scale agribusinesses in poor countries face many challenges in accessing finance capital to enhance operations and increase profitability.Their inability to provide adequate collateral for loans means they cannot access formal credit from commercial banking sector that considers this group of borrowers to be the most risky as they are perceived to be highly likely to default (GoM, 2012).As a result, the lack of finance stifles development of viable small-scale agribusiness projects.Luckily for Malawi, policy (e.g. the second Malawi Growth and Development Strategy) has prioritized agriculture and financial sectors as twin engines for economic growth.In this 'twin engine' microfinance takes centre stage to fill the agriculture-finance gap by providing financial and other business support to small-scale agri-businesses.

Role of Microfinance
One goal for which microfinance is advocated for in international development policy by researchers such as Bateman (2011) and the Grameen Bank is to alleviate or reduce absolute poverty.For this reason, most MFIs in developing countries have developed and are managed around this goal (Hulme & Moore, 2006).Access to microfinance changes investment behavior of poor small-scale entrepreneurs in many ways.Diagne and Zeller (2001) noted that microfinance alleviates capital constraints that poor households face thereby enabling them to acquire productive inputs for investments that would otherwise not be possible without the microfinance facility.It also reduces the opportunity cost of capital-intensive assets relative to family labour by encouraging labor-saving technologies and raising labor productivity of the poor (Diagne & Zeller, 2001).

Evidence of the Role of Microfinance in Malawi
The development literature (e.g.Morduch, 1999;Aghion & Morduch, 2005;Disney, Fichera, & Owens, 2008) suggested the possibility of good welfare impact arising from MFIs and crowding out of informal loans in Malawi.The other seminal contributions to research of MFIs are on impacts by Diagne (1998) who assessed the impact of access to credit on income and food security in Malawi on the rural households.Other studies by Diagne and Zeller (2001) assessed access to credit and its impact on welfare in Malawi.Stewart, Majoro, and Dewett (2010) conducted a systematic review of the evidence of impact of microfinance on poor people in the Sub-Saharan Africa.While they make seminal contributions to understanding complex interactions between microfinance interventions, livelihoods and different dimensions of poverty reduction and empowerment, all studies focused on rural households and little on urban households especially SME agribusiness operators in Malawi.

Measures of the Role of Microfinance
One method which has been used by other researchers to study the role of microfinance involves the financing constraints approach.It is used to investigate whether microfinance institutions improved access to credit for microenterprises and small-scale enterprises.Pioneered by Fazzari, Hubbard, and Petersen (1988), the theory in financing constraint approach is that microenterprises with improved access to credit rely less on internal funds to finance their investments.The approach tests for differences in sensitivity of investment to internal funds in enterprises with different levels of information opacity by splitting a sample enterprise into sub samples defined according to suitable theoretical priors that characterize constrained and unconstrained firms.A Logit model is then applied to study investment decisions by small-scale firms in transition economy (for example, Johnson, McMillan & Woodruff, 2002).In this approach, investment is modeled as a function of enterprise internal funds which are usually defined as profits as well as controls for enterprise specific characteristics and investment opportunities (Hubbard, 1998).
The financing constraints approach has been used mostly in transition countries.For example, Hartarska and Nadolnyak (2008) applied the financing constraint approach in a study of Bosnia and Herzegovina to examine whether microfinance institutions improved access to credit for microenterprises.Through an investment sensitivity to internal funds of microenterprises, the study compared municipalities with significant presence of MFIs (unconstrained) and municipalities with no (or limited) presence of MFIs (constrained).The evidence suggested that MFIs alleviated micro businesses' financing constraint.Using the financing constraints approach similar results have been reported in Nigeria (Abiola, 2011).A survey of the literature on Malawi, however, yielded no evidence to suggest that the financing constraint approach has ever been employed to study the role of MFIs on growth of small-scale agribusiness entrepreneurs.It is with this knowledge gap in mind that this research was conducted.The research seeks to provide greater understanding than hitherto available of the extent to which microfinance in Malawi has alleviated financing constraints of the small-scale agribusinesses.
In this study, the Hartarska and Nadolnyak (2008) and Abiola (2011) financing constraint approach was used due to lack of literature in Malawi on the analysis of the role of MFIs.The approach was modified to suit the data which was collected.During the study it was noted that Lumbadzi which was chosen as a constrained area had a few number of agribusiness operators as such the results could not be statistically significant.This necessitated the use of clients (access to MFI services) as unconstrained firms while as non-clients (non-access to MFI services) as constrained firms.

Study Design
The study involved both quantitative and qualitative data assessment.The qualitative approach was adopted because it sought to gather an in-depth understanding of microfinance and challenges being faced by small-scale enterprises.In addition, a quantitative approach was also adopted to investigate factors affecting growth of small-scale agribusiness entrepreneurs and compare the investment levels of constrained and unconstrained firms.

Selection of the Study Area
The study was conducted in Lilongwe City (urban area) and Lumbadzi (peri-urban area) of Lilongwe district of central Malawi and focused on small-scale agribusiness entrepreneurs.In Lilongwe city the study was conducted in areas 23 and 25 which were the areas where both the MFIs were operating.One qualified to be agribusiness operator if they were involved in supply of farm inputs, services to agricultural farming, trading farm produce in its original or partly transformed state, storing and transportation of agricultural produce in its originally, partly or fully transformed state, processing into immediate and finished products and retailing of farm produce for consumption (Agar, 2014).

Sampling Design
A purposive systematic random sampling technique was used to select a representative sample of 140 respondents.The sampling frame comprised both clients and non clients of MFIs who had one to twenty employees in the purposively selected two areas.The list of the clients was provided by the MFIs while listing of non-clients was done in the areas of study.To enable comparability of the results, two MFIs namely PRIDE Malawi and Opportunity Bank of Malawi operating in both Lilongwe City and Lumbadzi were selected for the study.In these two study areas, there were a total of 3950 small-scale entrepreneurs.Out of the total SME, 242 were agribusiness operators.From the 242 agribusiness entrepreneurs, OIBM had a total of 90 clients while PRIDE had 152 clients.The study took into account for the ratio of 60 participants: 40 counterfactual (Edriss, 2013).Therefore 60% of 140 = 84 participants and non-participants/counterfactuals were 40% of 140 = 56 were interviewed during the study.Probability Proportional to size (PPS) was employed to determine the total number of respondents to be interviewed from the two MFIs as presented in Table 1.Note.The clients were from OIBM and PRIDE Malawi while non-clients were those who have never accessed loans from any available MFI in the area.

Data Collection
Data collection was done in October, 2013.Primary data was collected from the 140 sampled respondents using a semi-structured questionnaire.Individual interviews were conducted at their respective homes and business places.

Data Analysis
Factors affecting investment decisions of the small-scale agribusiness entrepreneurs were determined using the logit model.The logit model used is similar to the one used by Johnston et al. (2002) to study investments decisions by small scale firms in transitions and developing economies.The study modified the model used by other researchers such as Hartaska ( 2008) and Abiola (2011) who used financing constraint to study the impact of microfinance and recommended the approach to be used in other countries.
Letting y i be the fact that the i th entrepreneur invests in assets and 1 -y i be the contrary fact that the i th entrepreneur does not invest in assets.If we let probability of y i , P(y i = 1) = π i and P(y i = 0) = 1 -π i , then; 0 Where, α is the log odd of an entrepreneur investments without any effect from the covariates; β i measures coefficients of a unit change in covariate X i holding all other covariate constant, X i are covariates (various characteristics of the enterprises).Since logit model assumes logistic distribution of the probability of an event, thus it can be estimated as below: Where, INV = 1 is investment, I is the variable for internal funds (Average profit), IO is the investment opportunity (market and skill) variable, Z is a vector of variables that captured various characteristics (Note 1) of the enterprises.

Characteristics of Microfinance Services Offered to Small-Scale Agribusinesses
Microfinance as defined in literature such as Burrit (2006), Ledger (1999), and Wright (1999) is the provision of a broad range of financial services which includes savings, loans, transfers, insurance and remittances.It is in view of this definition that the study wanted to find out the characteristics of services which are being provided by the MFIs in Malawi.However, depending on the locations and nature of SMEs, not all services that are supposed to be offered are available.

Products and Services Being Offered
The study found out that MFIs offer a wide range of loans which include agricultural loans, educational loans, asset financing, Mthandizi (Note 2) so that entrepreneurs have wider choices and other products such as savings and insurance.The major concentration of the study was on business and agricultural loans which the MFIs were providing to the small-scale agribusinesses.However, the loan amounts allowed ranged from Malawi Kwacha (MK) 20,000 (44.8United States Dollar (US$)) (Note 3) to over MK100,000 (224.2US$) depending on the stages and conditions.The loans were provided in levels which ranged from MK50,000 (112 US$) to MK600,000 (1345 US$) were of limited amounts due to the nature of businesses these borrowers do and the majority about 70.2 percent of the respondents were only allowed mostly up to MK100,000 (224.2US$) with 29.8 percent getting above this amount.

Loan Conditions
The study revealed that those SMEs who had a minimum age of 18 were eligible people who accessed the loans from MFIs.Mutual group guarantee was found to be the collateral requirement for the SMEs to access a loan from MFIs.This requirement is in line with the principals of group lending or solidarity approach which is traced to the Grameen Bank of Bangaldesh.Weekly and fortnight repayments were also found to be some of the loan conditions being provided by MFIs.The study also found out that the MFIs were offering a range of 51 to 89 percent interest rates on the group loans against the Reserve Bank of Malawi base lending of 24 percent.
The respondents further highlighted factors which were not conducive to business environment and loan conditions such as high interest rates offered by MFIs, weekly and fortnight repayments and contribution for non-payments.In addition respondents also highlighted lack of business skills due to lack of business training institutions and lack of proper information on business operations and tough repayment conditions attached to the loans.The most highlighted problem associated with these services was high interest rates attached to the borrowing represented by 82.1 percent.The effective interest rates which were found to range from 51 percent to 89 percent per annum against the Reserve Bank of Malawi base lending rate of 24 percent were prohibitive and are only benefiting the MFIs.These conditions are prohibiting SMEs to have access to MFI services in Malawi.

Factors Affecting Investments of Small-Scale Agribusiness Entrepreneurs
The study also determined factors affecting investments of small-scale agribusiness entrepreneurs.Logit regression model as in Equation 2 was performed to analyze factors affecting investments done by constrained and unconstrained firms.The dependent variable investment was coded as 1 if there was investment done and 0 if the small-scale agribusinesses did not invest.A special emphasis was on sensitivity of investments to internal fund (average profits) which could determine if the emergence of MFIs has alleviated the financing constraints of the small-scale agribusiness entrepreneurs.Note.*** donates significance at p-value < 0.01; ** denotes significance at p-value < 0.05 and * denotes significance at p-value < 0.10.
As is indicated in Table 3, average profit, market skills, age of the business, age of the respondent and education were statistically significant in the whole sample and unconstrained firms at different levels of confidence while only average profit and age of the respondent were significant in constrained firms.Variables such as gender, location and number of employees were found to be statistically insignificant.The results were in consistent with the findings of Hartarska andNadolnyak (2008), andAbiola (2011).
Average profit is an important variable in this model because it represented the sensitivity of investments to internal fund.It transpired through the Logit model that statistically, average profit was all significant ranging from the whole sample and in both constrained and unconstrained firms.This suggested that the profitability of a business venture strongly affected the likelihood of individuals to invest.From the findings it transpired that an increase in average profit reduces the probability of investments by 39.7 percent in unconstrained area firms (clients) while an increase in average profit reduces the probability of investments in constrained firms (non-clients) by 46 percent.The results are contrary to the expected results where average profit could have positively affected the investment decisions of the small-scale agribusiness entrepreneurs.The results could have been affected due to the exaggerated opinions on profits realized.This showed that investment decisions of unconstrained firms were less dependent on internal funds (average profit) than investment decisions of constrained firms.However the results are consistent with the findings of Hartarska and Nadolnyak (2008) and Abiola (2012) who found out that investments in constrained area were more sensitive to internal fund than in unconstrained area.
Market and Skills determine the investment opportunities.This is another important variable which was found to be statistically significant in unconstrained firms and not significant in constrained firms.The results presented in Table 3 showed that, any additional increase in the availability of markets and skills increased the probability of investment by 16 percent while any increase in unconstrained firms increases the probability of investments by 14 percent.The coefficient for market and skills was found to be positive although statistically insignificant in the constrained firms.The findings were also similar to the findings of Abiola (2011) who found out that market and skills were significant in unconstrained area and in significant in constrained area.
The number of years that households run the business was also one of the factors that had a multiplicity of outcomes ranging from the whole sample, constrained and unconstrained firms.The results showed that the older the business the less likelihood of investment.Increases in the years of the doing business, reduced the probability of investment by 1 percent for both unconstrained firms and constrained firms.This is consistent with the findings of Abiola (2011); Hartarska and Nadolnyak (2008) whose findings were consistent with a notion that SMEs have a life cycle with heavier investments being done at earlier age than older age.However these findings were contrary to another notion by Ahiawodzi (2012) that older firms grow (where growth is measured by investments) faster than younger ones because of the experience over the years.The results obtained showed that investments in assets was negatively affected by any increase in the number of years that one had been running business.
Age was found to be significant in the whole sample, constrained and unconstrained firms as indicated in Table 3.
The results however revealed a negative relationship between age of the respondent and investment decisions of small-scale agribusiness entrepreneurs.Any additional increase in the age of the respondents reduced the probability of investments by 1 percent in unconstrained firms and 2.9 percent in constrained firms.This was supported by earlier findings on distribution characteristics of the respondents where it was found that 81 percent of unconstrained firms and 67 percent of constrained firms were above 30 years of age.This is in support of literature by Storey (1994) that middle aged entrepreneurs are more likely to grow their businesses as compared to older entrepreneurs.
Additionally the results form Table 3 showed no significant relationship between number of employees and investment in fixed assets.However, there was a negative relationship between number of employees and investments in unconstrained area.This shows that any increase in the number of employees results into a reduction in the investment opportunities by 6 percent in unconstrained firms and 3 percent in constrained firms.
The figures showed that any increase in number of employees also increased the overheads which could not be supported by the profits being recovered hence no substitutability between hiring more employees and investments.
Literacy level tends to influence general performance notably of small-scale enterprises (Aworemi, 2010).
Education in this study was found to be significant at 1 percent in the whole sample and un-constrained firm respectively.It is however expected that entrepreneurs with higher level of education would be more likely to grow than those with low levels of education.The results are contrary to that expectation as they showed that the probability of investments was negatively affected by 5 and 4 percent in unconstrained and constrained firms respectively.The descriptive analysis showed that 44 percent of the clients were educated to upper primary school level which could have directly affected the profit maximization of their businesses and decision to invest.
Gender is one of the most important aspects as it has a significant influence on business performance in line with the findings of Aworemi (2010).According to Chirwa (2008), women are increasingly venturing into ownership of micro and small enterprises, either on their own or in partnership with male entrepreneurs as opposed to findings by Kimuyu (2002) which showed that female owned SMEs perform significantly worse than male owned enterprises.In addition to this the results found an increase in female participation and this was found to be due to the relative access to credit from MFIs which targets mostly female than male (Chirwa, 2008).In this study gender was found to be insignificant at all levels but the coefficients showed that there was a negative relationship between gender and investments.

Comparison of Levels of Investment between MFI Clients and Non-Clients
Values of assets purchased by the respondents, which were classified as constrained and unconstrained firms were used as a proxy for investment levels.To support the results of the financing constraint, a t-test was applied to find out if there was a significant difference between the investment levels between these two groups.In this test, the study tested the null hypothesis that there was no significant difference between the investments of constrained and unconstrained firms.Table 4 gives the output of the t-test that was done.As noted from table 4 the t-value was found to be 0.511 with significance level of 0.61, which was greater than 0.05.This meant that there were no significant differences in the investment levels of clients and non-clients.This could be because of the earlier findings that conditions attached to the loans were unfavorable for the growth of small-scale entrepreneurs.It is the MFIs that mostly gain from the high interest rates charged and not the borrowers who were forced to repay the loans with higher interest rates.
Although lack of access to finances was found to be among the major challenges as presented by 22.9 percent, with other common highlighted challenges such as lack of markets (44.3 percent), lack of business skills (12.1 percent) and transport costs (11.4 percent), MFIs have not significantly alleviated the financing constraints of the SMEs in Malawi.

Conclusions
The study revealed that the available MFIs in Malawi have several services that could be accessed by small-scale agribusiness entrepreneurs.These services included loans such as agricultural education, business, asset financing and Mthandizi and other products like savings and insurance.Despite all these services, accessing loans proved to be tough due to the conditions such as high interest rates, repayment conditions and lack of information on the detailed services and loan conditions provided by the MFIs.
A statistical difference on the use of internal funds (average profit) between constraint and unconstrained firms indicates how efficient MFIs have been to small-scale agribusiness enterprises in Lilongwe district.Based on the Logit model results, it transpired that average profit, market and skills, age of the business, age of the respondent and education are some of the factors affecting investment decisions of SMEs.However with the financing constraint approach, enterprises with improved access to credit rely less on internal funds to finance their investments.The study revealed that unconstrained firms (clients) were using fewer profits for their investments as compared to constrained firms (non-clients).However the t-test results showed no significant differences in levels of investments between a client and a non-client.It was noted that the investment levels of the clients and non-clients were the same which could have been due the prohibitive conditions of the MFIs.
In conclusion, although unconstrained firms are using fewer profits for their investment as compared to constrained firms which is an indication of improved access to credit, the t-test revealed no significant differences in the investment levels between clients and non-clients.These study results showed that MFIs in Malawi specifically in Lilongwe urban do not play a significant role on growth of Small-scale agribusinesses entrepreneurs.The review of loan conditions such as interest rates is necessary for them to alleviate the financing constraints of the SMEs.

Table 1 .
Sample size distribution by location (sample size 84)

Table 2 .
Summary statistics of main variables in the model Table2above shows the mean annual average profit ofMK1,193,327 (2675 US$)for unconstrained firms and MK1,259,866 for constrained firms.More than half of the respondents mentioned Market and skills as one of the major challenges being faced as noted by a mean of 0.65 for both unconstrained and constrained firms respectively.It was further noted during the research that most of the respondents had one employee and the mean age of the businesses were 11 years for unconstrained firms and 8 years for constrained firms.

Table 3 .
Logit model results