Effects of Microfinance on Micro andSmall Enterprises (Mses) Growth inNigeria

Abiola Babajide (Department Of Banking andFinance, Covenant University, OtaP.M.B 1023,Ota, Ogun State, Nigeria)

Citation: Abiola Babajide (2012) “Effects of Microfinance on Microand Small Enterprises (Mses) Growth in Nigeria” Asian Economic andFinancial Review. Vol.2, No. 4 pp...

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Author(s)

Abiola Babajide Department Of Bankingand Finance, CovenantUniversity, Ota P.M.B1023, Ota, Ogun State,NigeriaEmail:abiola.babajide@covenantuniversity.edu.ng

Effects ofMicrofinance onMicro and SmallEnterprises(Mses) Growth inNigeria

Abstract

This paper investigates the effects ofmicrofinance on micro and small businessgrowth in Nigeria. The objectives are:one, to examine the effects of differentloan administration practices (in terms ofloan size and tenor) on small businessgrowth criteria. Second, to examine theability of Microfinance-Banks (MFBs)(given its loan-size and rates of interestcharged) towards transforming micro-businesses to formal small scaleenterprises. The paper employed panel dataand multiple regression analysis toanalyze a survey of 502 randomly selectedenterprises finance by microfinance banksin Nigeria. We find strong evidence thataccess to microfinance does not enhancegrowth of micro and small enterprises inNigeria. However, other firm levelcharacteristics such as business size andbusiness location, are found to havepositive effect on enterprise growth. Thepaper recommends a recapitalization of theMicrofinance banks to enhance theircapacity to support small business growthand expansion.

Keywords: Small Firms, Micro firms, Entrepreneurship, Microfinance,Regression Analysis, Nigeria

Introduction

Since Nigeria attainedindependence in 1960,

considerable efforts have beendirected towards the nation’sindustrial development. Theinitial efforts were government-

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led through the vehicle of largeindustry, but lately emphasishas shifted to Small and MediumEnterprises (SMEs) following thesuccess of SMEs in the economicgrowth of Asian countries (Ojo,2003). Thus, the recentindustrial development drive inNigeria has focused onsustainable development throughsmall business development.Prior to this time, particularlyjudging from the objective ofthe past National 4-YearDevelopment Plans, 1962-68 and1981-85, emphasis had been ongovernment-ledindustrialization, hinged onimport-substitution.

Since 1986, government hadplayed down its role as themajor driving force of theeconomy by a process ofcommercialization andprivatization. Emphasis,therefore, shifted from large-scale industries mainly to smalland medium scale industries,which have the potentials fordeveloping domestic linkages forrapid and sustainable industrialdevelopment. Attention wasfocused on the organized privatesector to spearhead subsequentindustrialization programmes.Incentives given to encourageincreased participation in thesesectors were directed at solvingand/or alleviating the problemsencountered by industrialists inthe country, thereby giving themgreater leeway towards

increasing their contribution tothe national economy.

Lack of access to finance hasbeen identified as one of themajor constraints to smallbusiness growth (Carpenter,2001; Anyawu, 2003; Owualah,2007; Lawson, 2007). The reasonis that provision of financialservices is an important meansfor mobilizing resources formore productive use (Watson andEverett, 1999). The extent towhich small enterprises couldaccess fund is the extents towhich small firms can save andaccumulate own capital forfurther investment (Hossain,1988). However, small businessenterprises in Nigeria find itdifficult to access formalfinancial institutions such ascommercial banks for funds. Theinability of the SMEs to meetthe standard of the formalfinancial institutions for loanconsideration provides aplatform for informalinstitutions to attempt to fillthe gap usually based oninformal social networks, andthis is what gave birth tomicro-financing. In manycountries, people have relied onmutually supportive and benefit-sharing of the social networkingof these sectors for thefulfilment of economic, socialand cultural needs and theimprovement of quality of life(Portes, 1998). Networks basedon social capital exist in

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developed as well as developingcountries, including Nigeria.

In order to enhance the flow offinancial services to the Micro,Small and Medium Enterprises(MSME) subsector, Governmenthas, in the past, initiated aseries of programmes andpolicies targeted at the MSMEs.Notable among such programmeswere establishment of IndustrialDevelopment Centres across thecountry (1960-70), the SmallScale Industries CreditGuarantee Scheme - SSICS (1971),specialized financial schemesthrough development financialinstitutions such as theNigerian Industrial DevelopmentBank (NIDB) 1964, Nigerian Bankfor Commerce and Industry (NBCI)1973, and National EconomicRecovery Fund (NERFUND) 1989.All of these institutions mergedto form the Bank of Industry(BOI). In 2000, the governmentalso merged the NigeriaAgricultural Cooperative Bank(NACB), the People’s Bank ofNigeria (PBN) and FamilyEconomic Advancement Programme(FEAP) to form the NigerianAgricultural Cooperative andRural Development Bank Limited(NACRDB). The bank was set up toenhance the provision of financeto the agricultural and ruralsector. Government alsofacilitated and guaranteedexternal finance by the WorldBank (including the SME I andSME II loan scheme) in 1989, andestablished the National

Directorate of Employment (NDE)in 1986.

In 2003, the Small and MediumEnterprise Development Agency ofNigeria (SMEDAN), an umbrellaagency to coordinate thedevelopment of the Small andMedium Enterprises (SME) sectorwas established. In the sameyear, the National CreditGuarantee Scheme for SMEs tofacilitate its access to creditwithout stringent collateralrequirements was reorganised andthe Entrepreneurship DevelopmentProgramme was revived. In termsof financing, an innovative formof financing peculiar to Nigeriacame in form of interventionfrom the banks through itsrepresentatives ‘the Banker'sCommittee’ at its 246th annualgeneral meeting held on December21, 1999. The banks agreed toset aside 10% of their profitbefore tax (PBT) annually forequity investment in small andmedium scale industries. Thescheme aimed, among otherthings, to assist theestablishment of new, viableSmall and Medium Industries(SMI) projects; therebystimulating economic growth, anddevelopment of local technology,promoting indigenousentrepreneurship and generatingemployment. Timing of investmentexit was fixed at minimum of 3years. By the end of 2001, theamount set aside under thescheme was in excess of 6billion naira, which then rose

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to over N13 billion and N41.4billion by the end of 2002 and2005 respectively, but stood atN48.2 billion by the end ofDecember, 2008.

Despite all these efforts, thecontribution of SME to NigeriaGross Domestic Product (GDP)remains very poor, hence; theneed for alternative fundingwindow. In 2005, the FederalGovernment of Nigeria adoptedmicrofinance as the mainfinancing window for micro,small and medium enterprises inNigeria. The Microfinance PolicyRegulatory and SupervisoryFramework (MPRSF) was launchedin 2005; the policy among otherthings, addresses the problem oflack of access to credit bysmall business operators who donot have access to regular bankcredits. It is also meant tostrengthen the weak capacity ofsuch entrepreneurs, and raisethe capital base of microfinanceinstitutions. The coreobjective of the microfinancepolicy is to make financialservices accessible to a largesegment of the potentiallyproductive Nigerian population,which have had little or noaccess to financial services andempower them to contribute torural transformation.

The microfinance arrangementmakes it possible for MSMEs tosecure credit from MicrofinanceBanks (MFBs) and otherMicrofinance Institutions (MFIs)

on more easy terms. It is onthis platform that we intend toexamine the impact ofmicrofinance on small businessgrowth. Therefore, the studywill fill the gap in literatureon the impact of both thefinancial and non financialservices on small businessgrowth and to examine thecapability of microfinance totransform small enterprises tosmall scale industries throughtheir technology/asset relatedloans.

Literature Review

Role of the Entrepreneurs inBusiness Formation and GrowthThese theories considereddifferences in attitudes andabilities among individuals ascritical issues in determiningwhy some small firms grow andothers do not. Two schools ofthought, the Austrian School andthe Classical Economist were thefirst to acknowledge the role ofthe entrepreneur in smallbusiness development; theyrecognise the entrepreneur as anindividual with specialcharacteristics. Knight (1921)described an entrepreneur assomeone that has the willingnessand superior ability to makedecisions, raise capital andassume the risk of failure. Inthe same vein, Schumpeter (1939)added among other things, thefact that an entrepreneur hasthe superior ability to perceivenew market opportunities. He

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sees the entrepreneur as aninnovator.

According to the Austrianschool, people have certaincharacteristics that areassociated with the productivityfor entrepreneurship.Individuals who have more ofthese characteristics are morelikely to become entrepreneursthan those who have fewer. Anindividual chooses to create anew business so as to maximizehis expected utility. Thisutility is a function ofentrepreneurial activity or wageincome, and of attitudes thataffect the utility that theperson derives fromentrepreneurial activity, suchas one's taste toward workeffort, risk, independence,working close to customers, etc.Income, in turn, depends on theindividual's ability to generateprofit, such as managerialabilities to raise capital, andabilities to perceive new marketopportunities and to innovate(Papadaki and Chami, 2002).

The classical school, haveextended analysis of thedecision to start a business tothat of the decision to grow thebusiness. According to Davidson(1989, 1991), firm growth is anindication of continuedentrepreneurship. Davidson notesthat economic theories take thewillingness to grow a businessfor granted, by assuming profitmaximization. However, empirical

evidence suggests that smallbusiness owners are reluctant togrow even if there is room forprofitable expansion and thatprofitable firms of differentsizes co-exist withinindustries.

According to Papadaki and Chami(2002), theories on smallbusiness growth and developmentview business growth from anorganizational life cycleperspective, which sees growthas a natural phenomenon in theevolution of the firm, otherperspective sees growth as aconsequence of strategic choice.It is obvious that attributes ofthe business owner,organizational resources andenvironmental opportunities arecrucial in expanding the firmand in overcoming the barriersto the evolution of the firmfrom one stage to the next.Sexton and Smilor (1997), andCarland et al., (1984)distinguished between a businessowner and an entrepreneur.According to them, anentrepreneur is committed to thegrowth of the business. Growthis the very essence ofentrepreneurship," andcommitment to growth is whatprimarily distinguishes smallbusiness owners andentrepreneurs.

SMEs and GrowthIt is evident from literaturethat not all small businessesare growth oriented and for

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certain firms’ growth is avoluntary choice (Masurel andMontfort, 2006). An empiricalstudy of SMEs growth pattern byKolvereid and Bullvag (1996)concluded that growth intentionsmay be used to predict actualgrowth, that past intentions arerelated to later intentions, andthat change in growth intentionsare associated with changes ingrowth patterns. Arbaurgh andSexton (1996) provided empiricalevidence that most new firms donot grow into large ones andthat there is no relationshipbetween the age of a firm andits size. Chaston and Mangles(1997) opined that there is nosingle strategy to firm growth.Hence, the probability ofachieving growth is increased byavoiding excessive emphasis onsingle–strategy transformationinitiatives, and by givingdifferent capabilities prioritydepending upon the developmentstage of the firm. Theyidentified three factors thatcould limit the growth of smallbusiness to include ability,need and opportunity. Kolveired(1992) concluded that smallbusiness entrepreneurs whowanted their firms to growstarted their business in orderto achieve just that. Theprocess of mutual adjustmentbetween proprietors and theiremployees was identified byGoffee and Scase (1995) as amajor constraint limiting factorto small business growth.

Niskanen and Niskanen (2007)investigated the determinants ofgrowth in a sample of small andmicro Finnish firms. Firm growthis examined on a number of firmspecific and relationshiplending characteristics. Thedata set provides an excellentopportunity for investigatingthe effects that firm specificfactors have on firm growth. Thestudy investigated therelationship between firm growthand relationship lendingvariables. They are also able toprovide new information on therole that legal form has on firmgrowth by using more detailedownership variables. The resultson relationship lending effectssuggest that an increase in thenumber of lending banksdecreases growth rates in thelarger firms and that anincrease in the number of banksoperating in the county wherethe firm is located enhancesgrowth of the larger firms anddecreases growth rates of thesmaller firms. It could,therefore, be argued that closelending relationships enhancegrowth for all firms, but thatonly the larger firms in thesample benefit from morecompetitive banking markets.

Brown, Earle and Lup (2004),employed panel data techniquesto analyze a survey of 297 newsmall enterprises in Romaniacontaining detailed informationfrom the start-up date through2001. They found strong evidence

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that access to external creditincreases the growth of bothemployment and sales, whiletaxes appears as constrain togrowth. The data suggest thatentrepreneurial skills havelittle independent effect ongrowth, once demand conditionsare taken into account. Theevidence for the effectivenessof technical assistance is weak:only assistance provided byforeign partners yields apositive effect. A wide varietyof alternative measures of thebusiness environment (contractenforcement, property rights,and corruption) are tested, butnone are found to have any clearassociation with firm growth.While the literature showsdifferent perception onenterprise growth, there is apaucity of studies of howfinancing with microcreditcontributes to MSE growth in thespecific context of Nigeria.However, there have been anumber of survey-based studiesthat highlight the microcreditand microenterprise developmentin Nigeria.

Research Design

A two-method strategy wasadopted for this study toenhance the authenticity of thestudy, which combined primarysurvey based data with secondaryinformation from bank records.The idea behind this was toobtain cross-referencing dataand some independent

confirmation of data, as well asa range of opinions. Thisresearch identified two-in-oneaggregation or study groups;these are Microfinance Banks(MFBs) in Southwest Nigeria andthe Microfinance Banks (MFB)clients who are micro and smallenterprise operators,particularly those that havebenefited at one time or theother from the financial andnon–financial services renderedby the MFB in Nigeria. Accordingto the CBN record as at March31st 2009, there were 305microfinance banks in SouthwestNigeria geo-political zone. Outof the 305, only 169 haveobtained their final license tooperate as microfinance banks.The other 136 are reportedlyhaving provisional approval. Forthe purpose of this study, thepopulation of Microfinance Banksadopted for the study is the 169MFBs that have obtained finallicense to operate asmicrofinance banks in south-westNigeria.

The sample frame for this studyis determined from thepopulation of MSMEs operatorsusers of MFBs, we rely on thefindings of an assessment studycarried out by USAID (2005) onfinancial service demand surveyfor micro, small and mediumenterprises in Nigeria. Thefindings suggested that only 10%of MSMEs operators have accessto microfinance owing to limitednumber of microfinance

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institutions in Nigeria (USAID,2005). Using this parameter, wedevelop the sample frame for thestudy as micro and smallenterprise operator users ofmicrofinance bank.

In choosing the sampling sizeand secure representative’sresponses, the size of thesample was based on statisticalestimation theory developed byBartlett, Kotrliik and Higgins,(2001) for research of thisnature and a simple randomsampling technique was employedto select 623 enterprises forthe study out of which only 502are useful and upon which theanalysis was based.

Model SpecificationThe hypothesis was structured toascertain the extent to whichmicrofinance facilities canenhance the expansion capacityof small business in the study.This was expressed as:Y=αo+β1EAge1+β2EE2+β3MS3+β4EG4+β5Bizage5+β6Bizform6+β7Bizsize7+β8Bizloc8+β9Bizreg9+β10ALS10+β11ALD11+β12ALR12 +β13 LI13 + β14 TT14 +µ…. …………(2) WhereY = Small Business Growth (SBG)proxied by annual sales growthrate over the five years ofstudy. It is defined as Gr ={(St/S0)1/n – 1} x 100 where St isthe current sales level, So isthe base year 2004, n is thenumber of years considered forstudy while Gr is the annual

rate of growth. (Niskanen &Niskanen, 2007). Key predictor of MSEs expansionis given as EAge1 = Entrepreneur Age, EE2 =Entrepreneur Education, MS3 =Marital Status, EG4=Entrepreneur Gender, Bizage5 =Business Age, Bizform6 =Business form, Bizsize7=Business Size, Bizloc8= Businesslocation, Biz reg9 = Businessregistration, ALS10 = Asset LoanSize received from MicrofinanceBank, ALD11, = Asset LoanDuration, ALR12 = Asset LoanRepayment, LI13 = Loan Interest,TT14 = No. Technology Trainingreceived by entrepreneur or hisstaff in the last year,

Result Analysis

Multiple Regression AnalysisThe field survey for this studywas carried out between Octoberand December 2009, on factorsthat influence growth of microand small enterprises in South-West Nigeria. The first part ofthe questionnaires was filled bythe small business operatorsusing standard definitions ofkey concepts (particularly tomeasure such variables as grossprofit margin, sales growth,productivity, and capitalemployed micro loan and microsavings). The second part of thequestionnaire containedinformation on the businessenterprise extracted from bankrecords with the help of Loan

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Officers who work directly withthe respondents. It is a fiveyear summary of the businessenterprise on loan history andsavings as well as sales,profits, capital employed andassets.

The study was designed to coverall firms that had stayed withthe microfinance bank for aperiod of at least five yearsand had received microloan atone point or the other in theperiod covered. The success ofthe survey is attributed to thefact that the researcher had thesupport of the Loan Officers inapproaching the enterpriseoperators. Out of 623 of suchenterprises, 502 results wereuseful. Our main goal is limitedto the “internal validity” andissue of assessing “the effectof treatment on the treated.”Our micro loan figures wereextracted from the banks recordsdirectly and not just relying onthe respondents for theinformation. When we segregatethe analysis to see the effectcommon to a segment such as thelegal status of the business,the coefficients are identifiedoff the variation within eachsampled firm. The results fromthis analysis may be generalizedonly to enterprise similar tothose in our sample, that isfirms that are consistently beenfinance by MFBs over a minimumof five year periods and oneshould be cautious about

extrapolations to firms lackinga common statistical support.

Microfinance on Small BusinessGrowth by Category of Business Table 1 (see appendix) presentsresults from regressing theaverage sales growth rate ondifferent variablescharacterizing the firm andmicro financing. The equation incolumn I of table 1 representsthe total sample. In columns IIand III we split the sample intosmall firms and micro firms.Column II presents observationsfrom small firms (firms withmore than 10 employees). Incolumn III we presentobservations from micro firms(firms with less than 10employees). This classificationinto small and micro firms isbased on the definition appliedby the National policy sponsoredby SMEDAN in 2007 and adoptedfor implementation by theNational Assembly of Nigeria.Our dependent variable isdefined as average sales growthduring the five year studyperiod of 2004 – 2008. Theconstant, which is theintercept, shows that when allthe variables are zero, saleswill grow at 15.3% for the totalsample and at 9% and 16% forsmall firms and micro firmsrespectively. The resultobtained for the three columnsare all significant at 1%.

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On impact of ownerscharacteristics variables onexpansion capacity of MSEs, theresult obtained shows thatentrepreneurs age has a positiverelation with expansion capacityof the firm but notstatistically significant forthe three samples. The resultobtained for owner’s educationshows that a unit increases inowners’ education will increasesales growth by 0.15% and 0.7%for total sample and small firmsrespectively, and they are bothstatistically significant at 5%.The result obtained for microfirms shows that a unit increasein owner’s education willincrease sales growth by 0.8%but the result obtained is notstatistically significant, henceit cannot be relied upon forinference, even though it iscorrectly signed as expected insmall business theory. Theresult on gender shows there isa positive relationship betweengender and micro firm expansionand it is statisticallysignificant at 5%. The gender ofthe entrepreneur may also affectfirm growth. Male – ownedenterprise tend to performbetter and over time grow fasterrelative to female ownedenterprise (Daniels and Mead,1998; Fafchamps & Gabre-Madhin,2001). Women are oftendisadvantaged by less educationand constrained by social normswhich limit their mobility andaccess to other productive

resources (Fafchamps, 2003;Mitra, 2002).

The results obtained on firmcharacteristic variables showsthat business age has an inverserelationship with small businessgrowth and expansion capacityproxied by sales growth. Thegeneral pattern between firm ageand growth seems to be thatyoung firms are more likely togrow faster. The result showsthat a unit increase in firm agewill decrease sales growth by0.01% for total sample and 0.07%and 1.9% for small firms andmicro firms respectively, andthey are all statisticallysignificant at 1% for totalsample and micro firmsrespectively and at 5% for smallfirm sample. This implies that older firmsgrow less rapidly than youngerfirms, Davidson et al. (2002),Almus and Nerlinger (1999) alsofound an inverse relationshipbetween firm age and growth. Theresults obtained confirmprevious findings on therelationship between firm ageand growth. The variable takes anegative and statisticallysignificant coefficient in allthe three columns suggestingthat younger firms grow fasterthan older firms. On businesssize proxy by number of paidemployee in the business, theresults obtained show a positiveand highly significant sign fortotal sample and micro firms,while a negative and

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statistically significantcoefficient for small firms.This suggests that the growthrate initially increases withfirm size but then start todecrease after a certain level.The result obtained onrelationship between firm growthand firm size in other studiesare not equally unanimous, inmost studies on small firms,Caves (1998) founds a positiverelationship between firm sizeand growth while Eyiah and Cooks(2003) found a negative relationbut they use data on largerfirms. The result obtained onbusiness location shows apositive and high significantcoefficient between businesslocation and firm growth for thethree samples. Most of the firmsin these samples are located inthe urban area. Storey (1994)suggests that there are somelocations in which firms aremore likely to grow faster. Heprovided evidence using U.K dataand proof that firms located ina rural area can be expected togrow faster than those in urbanareas. Almus and Nerlinger(1999) use regional populationdensity as their locationvariable, and found weakevidence that location affectsgrowth. Their findings show thatfirms located in denselypopulated areas exhibits highergrowth rates.

On business registration status,it is observe from our samplesthat sampled firms operate as

both registered firms andunregistered firms. Results fromprevious studies show thatregistered firms grow fasterthan unregistered firms. Inlarge firms, registrationenhances credibility, opens upaccess to rationed resources andreduces transaction costs whendealing with other firms, thusaiding growth and performance(Sleuwaegen & Goedhuys, 2002).This is interpreted to implythat registered firms owners aremore willing to invest in riskyventures that may foster firmgrowth than unregisteredbusiness since most of them aremore likely to make use ofinternally generated funds.Mitullah (2003) argued thatunregistered firms areunprotected and the environmentin cities is not conducive forbusiness for them. Unregisteredbusinesses in cities areconstantly disrupted bymunicipal authorities inconflict over licensing,taxation, site operation,sanitation, and workingconditions. The resultsobtained for this study show apositive and significantcoefficient for total sample andsmall firms because most of theregistered business falls in thetwo samples but the resultsobtained for micro firm sampleshow positive but notstatistically significant. Mostof the firms in the micro firmsamples are unregisteredbusiness.

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On micro finance variables,results on size of assets loanon expansion capacity of theMSEs show that a unit increasein size of assets loan willincrease sales growth by 0.03%and 0.16% for total sample andsmall firms respectively, butthe results obtained were notstatistically significant, thismay be because the asset loangiven by most microfinance bankis too small, even though it iscorrectly signed as expected inmicrofinance theory but notsignificant. For micro firmsample, the result obtainedshows a positive correlationbetween size of asset loan andfirm growth and it issignificant at 5%. This impliesthat asset loan enhance growthof micro enterprise, but thesize of the loan is too smallfor any meaningful impact onsmall firms. Duration of assetsloan shows a positive relationwith sales growth for the entiresample, but not statisticallysignificant for total sample andsmall firms, meaning that theduration of the asset loan istoo short for any meaningfulimpact on MSEs growth. Theresult obtained for micro firms’shows that if duration of assetloan is increased by one month,annual sales growth willincrease by 0.1% and it isstatistically significant at 5%.This implies that the asset loanduration is suitable for microfirms only.

On repayment of asset loan, theresults obtained show a negativecorrelation with sales growth,which is in support of economictheory but negates micro financetheory because of the frequencyof repayment. The resultobtained for total sample andsmall firms revealed that iffrequency of repayment isincreased by a unit, salesgrowth decreases by 0.07% and1.9% respectively, although itis not statically significant,hence the result cannot berelied upon to make inference.But for micro firms, the resultrevealed that a unit increase inrepayment period will causeannual sales growth to decreaseby 0.6% and it is statisticallysignificant at 1%. On interestcharge on loan, only the resulton micro firm is reliable andstatistically significant at 5%,but the result for total sampleand small firms sample are notstatistically significant.

Result obtained on technologyrelated training received by theentrepreneurs, shows thattechnology related trainingreceived by entrepreneurssignificantly affect salesgrowth, thereby enhancing theexpansion capacity of MSEs.Specifically, the resultobtained shows that a unitincrease in technology relatedtraining received by theentrepreneur will cause annualsales growth to increase by

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0.029% for total sample and 1.0%and 0.1% for small firms andmicro firms samplesrespectively. They are allstatistically significant at 5%and 1% respectively. Previousstudy provides strong evidenceof a positive associationbetween the use of technologyand business performance, withobserved differences in profitlevel across enterprises andsectors reflecting varyinginnovative environments (Bigstenet al., 2003; Chapelle & Plane,2005; Daniels, 2003).

The coefficient ofdetermination, that is the R2

for the three columns is 0.12,0.11 and 0.17 for the totalsample, small firm and microfirms samples respectively whilethe adjusted R2 of 0.09, 0.07and 0.05 shows the variation inthe dependent variable (SmallBusiness Growth) jointlyexplained by the explanatoryvariables for the three samples.In studies such as this (primarydata and multiple regression)emphasis is usually placed onthe significant of individualexplanatory variables (Gujarati,1995). The decision rule is thatwe reject the null hypotheses ifthe calculated F-value issignificant. In this case, thecalculated f-value is 0.362 isnot significant for all thethree samples so we reject ouralternative hypothesis andaccept our null hypothesis.Hence, the study concludes that,

microfinance as practice byMicro-finance Banks (MFBs) inNigeria does not enhance MSEsgrowth and expansion capacity.But variables such asEntrepreneur’s education, firmage, firm size, firm locationand firm registration enhancesales growth, while otherfactors such as size of assetloan, duration of asset loan andfrequency of repayment of loanas practice in Nigeria’smicrofinance bank do not enhancesales growth.

Multiple Regression Analysis ofEffect of Microfinance on SmallBusiness Growth by Kind ofBusiness ActivitiesThe result on expansion capacityof MSEs was also split into kindof business activities to knowthe variables that aresignificant to different kind oftrade. To facilitate comparisonacross different sector of theeconomy as used in this study,the significance and marginaleffects of explanatory variablesis discussed in order ofappearance across the fivemodels. As expected there issubstantial variation of growthperformance both within andacross individual sectors andfirm characteristics as well asmicrofinance variables. Theobserved differences inenterprise growth andperformance across sectorsreflect the general businessenvironment in which enterprise

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operate and its effect onspecific sector/marketstructures, including the levelof financial and human capital,value added/output per employee,nature and level of competitionand ability of firm to adapttheir pricing policy to internaland external changes (Fafchamps& Gabre-Madhin, 2001). Forexample, performance in themanufacturing sub sector isaffected by inefficiency, poorregulation and other structuralproblems including seasonalfluctuations in operations(Fagbenle, Adeyemi, & Adesanya,2004).

In Table 2 (See appendix), thecoefficient on entrepreneurs’age is positive and significantin all models at 5% significantlevel except in manufacturingand artisans sectors. Thepositive correlation in allsectors is in accordance withearlier study (see Fasoranti etal., 2006). The entrepreneurs’age signifies the level ofcontribution the entrepreneurare able to bring into thebusiness. The characteristictable shows that 79% of thetotal sample are in the economicactive age group, that is, agegroup 25 – 54 years. All thingsbeing equal, they have thecapacity to contributesignificantly to the growth ofthe enterprises. The coefficientfor education is positive andsignificant at 5% and 1% in allthe models except for

manufacturing sector where it isnot significant. Level ofeducation is important indetermining the condition atstart-up such as in the form ofcapital saved from earlieremployment and ability to accessmore capital and accumulatewealth (Makasure et al, 2008).The coefficient for maritalstatus is also positive andsignificant for trading,artisans and manufacturingsectors and insignificant inagriculture and service sectors,67% of the total sample ismarried. The coefficient forgender is positive andsignificant in trading sector at5%, among artisans also at 5%significant level and at 1% inthe service sector. The effectof gender is not significant inmanufacturing and agriculturalsector. Although literature hasit that male owned enterprisetends to perform better and overtime grow faster relative tothose owned by femaleentrepreneurs (Daniels andMeads, 1998). Women’s inabilityto perform better in enterprisemanagement is summarised towomen’s relative less educationand inability to accessproductive resources but all ofthe weaknesses are make up forin social capital approachemployed in micro-financing(Fafchamps, 2003).

On firm characteristicsvariable, the coefficient onenterprise age is positive and

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significant in all models at 5%and 1% across the five models.The number of years theenterprise had operated in theyears preceding the survey ispositively associated with firmgrowth. The magnitude of thecoefficients across the fivemodels suggests variability inthe level of impact enterpriseage had on the growth of theenterprise, for example, oneyear increase in enterprise ageamong artisans will bring about1.2% increase in growth of theenterprise while it is just 0.4%in the trading sector and 0.1 inthe manufacturing sector. Thecoefficient for form of businessis positive but not significantacross the five models. Thecoefficient for business size ispositive and significant acrossthe five models except foragricultural sector. This may beowing to the fact that mostagricultural businessparticularly at the micro andsmall level like we have in thisstudy make use of family membersinstead of paid employee who aremore motivated and more skillful(Frazer, 2006). The table showsthe coefficient for geographicallocation is positive andsignificant across the fivemodels which implies thatbusinesses located in the urbanareas are more likely to thrivebetter in South-west Nigeria.Geographical location can have asubstantial impact onmicroenterprise performance.Urban based enterprises tend to

have a better access to a rangeof resources that are criticalto enterprise growth andperformance such asinfrastructure, working inputs,larger and more dynamic markets,and opportunities for networkingwith larger firm and withinmicro enterprise sector (Bogeticand Sanogo, 2005; Fafchamps,2004).

On micro financecharacteristics, the coefficientfor size of asset loan showsnegative and significant impactfor manufacturing andagricultural sectors, whilepositive and insignificantimpact for trading, artisan andservice sector. The coefficientfor duration of asset loan showspositive but not significantrelationship between duration ofasset loan and sales growthacross the five models exceptfor the service sector which ispositive and significant at 1%.On repayment of asset loan, theresult obtained shows an inverserelationship between repaymentof asset loan and annual salesgrowth for enterprises in thetrading, artisans, andmanufacturing sector, the resultobtained for agriculture andservice sector is positive butnot significant. The resultobtained is statisticallysignificant for trading,manufacturing and artisans. Thisimplies that attempt to recoverasset loan early impactnegatively on enterprise in the

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trading, manufacturing andartisans subsectors. The resultobtained on loan interest showsan inverse relationship betweenloan interest and sales growthin all the sub-sectors but onlystatistically significant intrading, agriculture and servicesubsectors. On technologytraining received, the entirecoefficient is positive andsignificant at 1 and 5% level ofsignificance. The coefficientfor manufacturing andagriculture is large at 5.6% and5.5% respectively, compare toothers. This implies that,technology related trainingreceived by entrepreneurstranslates into small businessexpansion. The adjusted R2 forcross section data is acceptedat the level it is for allmodel, but the overall f-valuestatistic shows not significantfor all the models except fortrading sector. This impliesthat we accept our nullhypothesis for all the modelsexcept for trading sector alonewhere we accept alternativehypothesis. This implies thatmicrofinance enhance businessgrowth in trading sub-sector butdoes not enhance growth in themanufacturing, agriculture,artisans and service sector.

Findings and Conclusion

Micro financing and ExpansionCapacity of Small and MicroEnterprises

The main findings of thisresearch revealed that micro-financing as practiced inNigeria microfinance banks donot enhance growth and expansioncapacity of micro and smallenterprise in Nigeria. Thefindings confirmed the viewsexpressed by Olutunla andObamuyi (2008) that the growthof SMEs is not just dependent onaccessing bank loan butaccessing the right size of loanat the right time. Theinsignificant position of theoverall f-statistic led to ourdecision to accept the nullhypothesis for the threesamples, which implies thatmicro finance does not enhancethe expansion capacity of smallbusiness in Nigeria. Looking atthe result critically, it wasalso revealed that among smallfirm sample, variables such astechnology related trainingreceived by the entrepreneur,business location, business ageand business registration inthat order are the variablesthat impact significantly onsmall business growth, none ofthe micro finance variables wasfound to have significant impacton small business growth forsmall firm sample. The resultalso revealed that variablessuch as owners’ education, loaninterest, duration of assetloan, business location,technology related trainingreceived and size of asset loan,all impact significantly onmicro firm growth but the

17

magnitude of the betacoefficient of micro financevariables are so small.

When the result was split bytype of business activities, theresult obtained shows variationin the type of variables thatimpact significantly on smallbusiness growth and expansion.In the service sub-sector, onlyowners’ education, gender,business age and size, andduration of asset loan appearsto be statistically significant.In the trading sub-sector,repayment of asset loan, loaninterest, duration of asset loanand business location and otherowner and firm characteristicsvariables were positivelycorrelated with sales growth andstatistically significant too.In the manufacturing sector, itis technology related trainingreceived by the entrepreneurs,loan interest, businesslocation, business registrationand business age that appears tobe statistically significant.Among artisans, the variablesthat are positively correlatedwith business growth andstatistically significant arerepayment of asset loan,duration of asset loan and sizeof asset loan.

In the agricultural subsector,it is technology relatedtraining and businessregistration that significantlyaffects sales growth. Thiscorroborated the findings of

Makasure et al (2008), that thesignificance and impact of eachof these variables on theprobability of an enterprisebeing profitable varies widelyacross the different sub-sectorstherefore it is difficult todraw general and hard-and-fastconclusions as to the impact ofany one factor. However, if weconsider the variation in impactof these factors on theintensity of microenterpriseprofits across the quartileswithin any one sub-sector, it ispossible to define a commonseries of critical factors forsub-sets of firms. One canobserve in all the samples,technology related training andbusiness registration seems tobe highly significance andcorrelated with sales growth.Hence, in formulating policy forthe MSEs technology relatedtraining and mandatory businessregistration should be givenhigh priority.

The MFBs are supposed to servemembers as a source of financialand social support, but theirfinancial capacity is limited.They do not have the capacity toprovide credit that will enhancegrowth and expansion capacity ofsmall business operators ortransform small business intosmall scale industry bysupporting investment intechnology. As a result, usersof the banks remain at thesurvival level in businessdevelopment stage incapable of

18

moving to the next level ofbusiness development. Manyscholars such as Ojo, (2003),Bekele and zeleke (2008) havesuggested that it is prudent tointegrate MFBs with other largerfinancing window available suchas strategic partners ofcommercial banks. Integration isof mutually beneficial to bothparties as it broadens themarket base of banks whileproviding MSEs with easy accessto finance at the same time.This implies that the MFBs willuse the social capital featureof the banks to help formalfinancial sectors to expandtheir lending base at a lessercost, while formal financialinstitutions can provide bankswith access to a large number ofclients with an adequateinformation base and acollective collateral guarantee.

Also, the results suggest thatboth the incidence and intensityof performance vary considerablyacross sub-sectors. For example,across sectors of the economy,activities related to tradingand artisans were bothassociated with a high growthrate, while the opposite is trueof the manufacturing sub-sector.There is even greater variationacross firms within each sub-sector.

While a wide range ofentrepreneur characteristics(level of education and age),firm-specific factors (most

notably business size, businessregistration, geographicallocation) and micro financevariables (size of asset loan,duration of asset loan,repayment of asset loan)influence the magnitude ofgrowth, it is notable that theimpact of any one of thesefactors varies. For example,size of asset loan has negativeimpact on sales growth in themanufacturing and theagricultural sector but haspositive impact in other sectorsbut not significant. Repaymentof asset loan also has negativeimpact on trading, artisans andmanufacturing sectors but haspositive impact on agricultureand service sector. Because thesignificance and impact of eachof these variables on the growthand performance varies widelyacross the five sub-sectors itis difficult to draw general andhard-and-fast conclusions as tothe impact of any one factor.

This study suggests thatpolicies aimed at promoting thegrowth of micro and smallenterprises should adopt asectoral approach and, withinthat, address specific issuesthat affect enterprises at thelower and upper ends of thespectrum of growth andexpansion. Thus, approaches andresources should address themost critical determinants ofgrowth in focal sub-sectors,aiming to augment access tocritical resources and, perhaps,

19

overcome the disadvantages thatcannot be easily varied.

The study recommends that MFBsshould increase the duration oftheir clients' asset loans, orspread the repayment over alonger period of time, orincrease the moratorium. Thiswill enable the clients to havegreater use of the loan over alonger period for theacquisition of capital assetsand technology.

In order to encourage technologyacquisition for MSE expansion,MFBs can categorize their loansinto low and high interestloans. The conventional loans toclients can be maintained ashigh interest loans, while loansfor capital assets or technologyacquisition should be lowinterest loans, which can besecured by a mortgage over thefixed asset so acquired by themicro-borrower. To achieve this,the Microfinance Banks should berecapitalized to enable thebanks to support MSEs growthexpansion adequately.

We also recommend thatenterprise supported by MFBsshould be linked up with largerfinancing window like the Smalland Medium Enterprise EquityInvestment Scheme (SMEEIS) fundor Strategic Partners forexpansion and growth fund aftersurvival. The entrepreneurscould also be linked up withother commercial banks who will

service the entrepreneursthrough the MFBs based on socialcapital. Also, greater emphasiseshould be place on non-financialservices provided by the MFBs.The non- financial services suchas, technology related training,entrepreneurial training, pre-loan training, group membershipare the main tools traditionalmicrofinance institutions use toenhance their sustainability.

The Government should urgentlytackle the problem ofinfrastructure development andmaintenance. These includeelectricity, water and efficienttransportation system whichimpact greater on MSEoperations. The bureaucraticbottleneck involved in smallbusiness registration shouldalso be removed.

Lastly, Government shouldestablish relevant well adaptedand appropriately structuredinstitutions and organizationsto provide support for MSEs insuch aspect as; procurement,supply and distribution of rawmaterial, supply oflocal/imported machines for useon concessional terms, trainingin several technical grades, andcreate favourable marketconditions. They should also setup Tool Design Institute andTesting Centres for rawmaterials and producedgoods/service institute asearlier suggested by Ojo (2006).

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Appendix

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Table-1: Multiple Regression Analysis of Effects of Microfinance onSmall Business Growth by Category of Business

The effect analysis of microfinance on Small and Micro Enterprises(SMEs) expansion. The dependent variable is sales growth over afive year period between 2004 – 2008. Column 1 presents the resultof the total sample, column II and column III split the data intofirms with ten or more employees and less than ten employeesrespectively.

Column ITotal SampleCoefficient t-statistic

Column IISmall FirmsCoefficient t-statistic

Column IIIMicro FirmsCoefficient t-statistic

Constant 15.320*10.561

9.001*6.581

16.631*5.588

OwnersCharacteristicsOwner’s age 0.858

1.0020.7861.134

1.2310.982

Owner’seducation

0.156**1.561

0.796*1.762

0.8981.052

Marital Status 1.4520.871

0.2390.222

1.0111.016

Gender 0.5620.113

1.3141.014

0.886**1.817

FirmCharacteristicsFirm age -0.014*

-1.812-0.075**-1.615

-1.924*-1.823

Form of Business 0.2101.121

0.5241.002

0.5521.014

Firm Size 0.111**1.713

0.022*1.912

0.381*1.645

Businesslocation

0.053*5.569

0.089*4.225

0.018**4.164

Businessregistration

0.027*3.158

0.052**2.041

0.0451.003

MicrofinanceCharacteristicsSize of assetloan

0.0341.393

0.1670.811

0.014**1.598

Duration ofasset loan

4.4030.187

1.5081.448

0.108*1.872

Repayment of -0.079 -1.911 -0.693*

25

asset loan -1.128 -0.721 -2.814Loan interest 0.030

1.3930.1650.611

1.014**2.598

Technologytrainingreceived

0.029**1.586

1.057*1.681

0.114**2.123

R – squared 0.125 0.116 0.172Adjusted R-Squared

0.093 0.079 0.055

No. ofObservation

502 135 367

F-teststatistics

0.362(0.4117) 0.385(0.551) 1.237(0.340)

Source: Field survey, 2009 Note * = 1% level of significance,** = 5% level of significance *** = 10% level of significance

Table-2: Multiple Regression Analysis of Effect of Microfinance onSmall Business Growth by

Category of Kind of Business Activities

The effects analysis of microfinance on Small and Micro Enterpriseexpansion by kind of business. Column I to column V are as detailedbelow.

Column ITradingCoeft-stat

Column IIArtisanCoeft-stat

Column IIIManufacturingCoeft-stat

Coulmn IVAgricultureCoeft-stat

Coulmn VServiceCoeft-stat

Constant 7.613*0.000

6.5810.006

2.071*3.145

5.128**1.566

3.6331.128

OwnersCharacteris

26

ticAge 0.218**

1.7250.0030.319

0.1351.049

0.233**1.644

0.017**1.830

Education 1.079**1.807

0.987**2.624

0.0881.212

0.311*1.884

0.3081.567

MaritalStatus

1.650**3.515

0.093**1.904

0.671**1.700

1.2080.890

0.4011.040

Gender 0.7021.815

0.123**1.561

0.0040.343

0.9230.332

1.236*1.756

FirmCharacteristicEnterpriseage

0.415*1.702

1.230**1.622

0.113**2.175

0.059*1.928

0.073**1.932

Form ofBusiness

0.7101.021

0.0061.402

1.063*1.058

0.0420.194

0.0220.584

BusinessSize

0.618*1.813

0.653**2.402

2.314*1.888

1.2380.980

0.1491.973

Urbanlocation

0.515*3.266

1.109*2.115

0.321*1.821

0.024*2.879

0.182*3.491

Rurallocation

1.045**3.305

1.4131.110

0.010*1.562

0.562*2.129

1.1010.497

MicrofinanceCharacteristicSize ofasset loan

0.4091.093

0.1610.511

-0.027* -1.715

-0.01**-1.891

0.0411.226

Duration ofasset loan

0.0580.870

2.0221.481

0.0991.141

1.3660.202

0.010*3.912

Repaymentof assetloan

-0.312**-1.728

-1.710* -2.890

-7.502**-1.913

1.2931.020

1.3310.619

Loaninterest

-5.755*-2.093

-0.009 -1.411

-0.017-1.015

-0.41** -1.961

-3.841*-2.186

Technologytrainingreceived

0.044**2.685

1.036*1.962

5.666*4.715

5.591**1.699

1.752*0.429

R – squared 0.265 0.172 0.179 0.093 0.231Adjusted R-Squared

0.213 0.143 0.092 0.052 0.192

No. ofObservation

238 86 54 89 33

F-test 2.892 0.821 1.133 0.189 1.18227

statistics (0.0056) (0.423) (0.118) (0.123) (0.309)Source: Field survey, 2009 Note * = 1% level of significance,** = 5% level of significance *** = 10% level of significance

28