DETERMINANTS OF SMMEs GROWTH IN …serialsjournals.com/serialjournalmanager/pdf/1468235492.pdfprovide financial support to unemployed youths who have dropped out of school to venture

International Journal of Economic Issues, Vol. 9, No. 1 (January-June, 2016) : 23-44© International Science Press

DETERMINANTS OF SMMEs GROWTH INBOTSWANA1

OKURUT, F. N., AMA, N.O., MOOKODI, L., OKURUT, M.L.A., & AMA, H. A.

Abstract: The investigates the factors that influence the growth of Small, Medium andMicro Enterprises (SMMEs)2 in Botswana. The study used the econometric modeladapted from Mateev and Anastasov (2012)with some modifications. From theeconometric model estimation, the growth of SMMEs is positively and significantlyinfluenced by labour productivity, capital productivity, access to credit, age of theentrepreneur, and having primary edcation. However SMME growth is negativelyinfluenced by the labour laws which prohibit access to cheap foreign labour. Policyrecommendations to promote SMME growth in Botswana include (i) Introduction ofnew funding models for SMME development especially for SMMEs run by women.The current funding for women under the Department for Gender Affairs could beenhanced to the level of the Youth Development Fund (YDF) in order to cater for womenwho are constrained access to credit and (ii) Government should simplify the tax systemfor SMMEs and the registration process for new businesses.Key Words: Gender, Institutions, SMME Growth, Botswana

1. INTRODUCTION

Small and medium scale enterprises (SMEs) are argued to promote inclusive growththrough creation of employment opportunities for people especially women (Mead,1994; Wohlmuth, et al., 2009; Lin & Lin, 2001; Daniels, 1999). As such, most policymakersdeem the promotion of the SME sector to be highly important for an economy. Thepursuit of this pro-poor growth strategy through promoting, facilitating andsupporting entrepreneurship is a desirable policy objective but the full potential ofSMEs in terms of poverty reduction, social protection and empowerment, particularlyfor women is yet to be fully harnessed.

SMEs face a number of constraints that hinder their growth potential such as lackof access to external finance (Pissarides et al., 2003; Lin and Lin, 2001; Beck andDemirguc-Kunt , 2006; Manson & Mat, 2010), technology, innovation and expertise(Lall and Peedoly, 2006), regulatory and tax constraints (Levy, 1993; Djankov et al.,2000) and these entail that SMEs face problems of low productivity and competitivenessand often struggle to survive in markets that are increasingly open and integratedwithin the global economy.

* Department of Economics, University of Botswana, E-mail: [email protected]

24 / OKURUT, F. N., AMA, N. O., MOOKODI, L., OKURUT, M.L.A. & AMA, H. A.

Moreover, when viewed through a gender lens, the available - albeit patchy -evidence on gender, employment and entrepreneurship reveals that women are evenfurther disadvantaged in starting up and operating SMEs as a result of the interplayof social, cultural and economic disadvantages within the domestic arena and inwider society (inequitable access to education and training, collaterals, networking,funding, amongst others). In particular, the ability of women to formalize and growtheir businesses, to create jobs, to enhance productivity and to promote enterprisedevelopment is hampered where legal and institutional barriers exist that affect men’sand women’s enterprises differently. Furthermore there is also some evidence-especially at the micro level-that indicates that gender disparities not onlydisadvantage women as entrepreneurs but can also thwart the economic potentialof SMEs in national and regional growth. Richardson et al. (2004) pointed out thatother factors that affect SME entrepreneurship include motivation, determination,abilities, experience, market information and resources. Bardasi et al. (2011) arguedthat an appreciation of gender issues is important when considering strategies toimprove Africa’s competitiveness in the world and ways to promote private-sectordevelopment.

2. INSTITUTIONAL SUPPORT AND SMES DEVELOPMENT IN BOTSWANA

There are different categories of SMEs, namely, micro enterprises, small scaleenterprises, and medium scale enterprises (Government of Botswana, 1999) and thesetend to vary in terms of ownership structure by gender. CSO (2009) observed that inBotswana micro enterprises mainly operate in the informal sector and the majority ofpersons employed in micro enterprises were females (56.2%). Women in the microenterprise sector were also more likely to be self-employed without employees (75.0%)as compared to males. Most micro enterprises were also owned by women (67%)implying that the livelihood of women in Botswana is derived mainly from SMEactivities in the informal sector.

In Botswana, the public sector institutions which support SMEs include the CitizenEntrepreneurial Development Agency (CEDA), the Local Enterprise Authority (LEA),the Youth Development Fund (YDF), and Young Farmers Fund (YFF). The privatesector institutions include commercial banks, microfinance institutions and non-government organizations (such as Women in Business Association Botswana [WIBA]).CEDA was established by the Government of Botswana as a company limited byguarantee on April 12, 2001 to provide financial and technical support for businessdevelopment with a view of promoting viable and sustainable citizen owned SMEs.CEDA provides different lines of credit to SMEs which include debt finance for retailoperations, debt finance for services operations, the credit guarantee scheme, andinvoice discounting (CEDA, 2013). The Local Enterprise Authority (LEA) wasestablished by the Small Business Act, Number 7 of 2004 as a Statutory Authority ofthe Government of Botswana to build the capacity of entrepreneurs to developsustainable SMEs. LEAs mandate includes provision of highly specialized developmentand support services which include facilitation of business planning; providing training,mentoring and advisory services; identifying business opportunities for existing and

DETERMINANTS OF SMMES GROWTH IN BOTSWANA / 25

future enterprises; facilitating access to markets; facilitating exploitation of governmentand large firms’ procurement opportunities by enterprises; facilitating access to finance;facilitating technology adoption and diffusion; promoting general entrepreneurshipand SME awareness (LEA, 2013).

The Government of Botswana also set up the Youth Development Fund (YDF)3 toprovide financial support to unemployed youths who have dropped out of school toventure into SMEs to generate income and self-employment opportunities (MYSC,2006). The Youth Farmers Fund (YFF), which is administered by the CEDA but undera separate institutional arrangement, was created by the Botswana Government in2005 to catalyze a growth in agricultural enterprises owned and operated by Batswana18-35 years old (MFDP, 2006). The YFF targets graduates of agricultural institutionsto set up agricultural related SMEs.

Commercial banks provide SMEs with loans for start-up or expansion of theirbusinesses, though evidence suggests that microenterprises are constrained in theiraccess to formal bank credit (Okurut et al., 2011).

Both public and private sector institutional support to SMEs target both femaleowned and male owned SMEs, hence this study will investigate the extent to whichinstitutions have contributed to the development and growth of SMEs from thegender perspective (i.e. for female owned and male owned SMEs). The genderperspective of institutional analysis is critical because of the gender differences inthe ownership structures of different kinds of SMEs, with varying degrees of accessto institutional support. In the case of Botswana, the SME policy identifies threedifferent categories of SMEs: microenterprises, small enterprises, and medium sizedenterprises (Government of Botswana, 1999). A micro enterprises are defined ashaving less than six workers including the owner and an annual turnover of lessthan P60,000 (US$7,500)4. A small scale enterprise is defined as one employing lessthan 25 paid employees with an annual turnover of between P60,000 and P1,500,000(US$7,500 and US$187,500). A medium size enterprise is defined as one employingless than 100 paid employees with annual turnover of between P1,500,000 andP8,000,000 (US$187,500 and US$1,000,000). Evidence by CSO (2009) suggests thatmost of the micro enterprises are female owned (67%) and operate mainly in theinformal sector.

Despite the important role played by SMEs as instruments for poverty reduction(Mead, 1994; Wohlmuth, et al, 2009) and the key role played by institutions inpromoting the development and growth of SMEs (ILO, 2010), little empiricalinstitutional analysis has been done to investigate the factors that influence SMMEgrowth in Botswana.

3. OBJECTIVES OF THE STUDY

The study is based on the following specific objectives:(i) To analyse the factors that influence the development and growth of SMMEs.in

Botswana.(ii) To make policy recommendations to promote the development and growth

of SMMEs in Botswana.


4. LITERATURE REVIEW

4.1. Theoretical Literature

Firm performance is also theoretical ly influenced by enterprise specificcharacteristics, entrepreneur characteristics, and the government regulatoryenvironment (Mateev and Anastasov, 2010; Liedholm, 2002; Keith, 1998; Davidssonand Henrekson, 2002). Firm size can be measured by the number of employees hiredby a firm in a given year, assets or business earnings (Liedholm, 2002; Keith, 1998).Liedholm (2002), using the number of employees hired in a given year as ameasure of enterprise growth, observed that enterprise growth is influenced by urbanlocation, age of the enterprise, and human capital (vocational training or priorbusiness experience). Keith (1998), also using the number of employees hired as ameasure of firm size, noted that firm growth is significantly influenced by urbanlocation.

Mateev and Anastasov (2010), using total assets as a measure of firm size, notedthat firm specific characteristics that are significant in explaining enterprise growthand performance include leverage, current liquidity, future growth opportunities,factor productivity, and internally generated funds. Davidsson and Henrekson (2002)observed that government regulatory institutions and policy created disincentives forentrepreneurial activity in some sectors in Sweden.

According Siropolis (1994) SME growth defies easy definition, there are manyyardsticks used to measure the growth of SMEs. Common yardsticks include; theincrease in the firm’s total assets, annual turnover and number of employees. Eachyardstick has points in its favor, but the number of employees has more points in itsfavor than any other yardstick. The strength of this yardstick lies in the fact that, it isinflation proof, transparent (easy to see and understand) and easily measurable.However there are no restrictions on the yardsticks to use, but there are differences inthe theoretical views on factors that influence the growth of SMEs, irrespective of theyardstick used to measure growth.

According to Storey (1994) the growth of SMEs depends on the entrepreneur andfirm characteristics. Entrepreneur characteristics include the entrepreneur’s age,managerial experience, education qualification and his or her motivation for startingthe business. Firm characteristics on the other hand include the firm sector, age andlocation. Storey (1994) asserts that SME growth is positively associated with highmanagerial experience; high education qualification; firm experience (age); and urbanlocation.

Davidsson and Henrekson (2002) however argued that firm growth is not onlyexplained by the entrepreneur characteristics and external firm attributes such as firmsector, age and location. There are internal firm characteristics that pertain to thefinancial structure and production efficiency of the firm that highly explains SMEgrowth. These internal firm characteristics include; degree of firm leverage, liquidity,physical capacity and factor productivity.


4.2. Empirical Literature

SMME groth and development is influenced by environmental factors, entrepreneurcharacteristics, and firm specific characteristics. The environmental factors includegovernment taxation, business registration, capacity building.

Government Taxation

According to Hagen and Sannarnes (2007) high government taxes discourageentrepreneurship and increases the failure rate of existing firms and deters marketentry of new firms (Boadway and Tremblay, 2005). The UK Employment Departmentreviewed the impact of the 1980 tax cut on the UK economy and found that businessinvestment grew as a result of the tax cut. The implication is that the high pre 1980 taxrates was impeding business investment (Wren and Storey, 2002). Davidsson andHenrekson (2002) found business growth in Sweden to be negatively affected bybusiness taxes especially in sectors where tax rates are relatively high. However somestudies have found out that there are enterprises which benefits from the governmenttaxes in the form of, tax deduction on business expenses and low social securitycontributions (OECD, 1994; Holtz EaKin, 2000).

Business Registration

The occupational choice model asserts that bureaucratic business registrationprocedures impact negatively on domestic entrepreneurship and the economy as awhole as it impedes entry of new firms into the market (Davidsson and Henrekson,2002). Studies have found the desire to start-up firms and early stage growth of firmsto be low in countries where business or company registration is characterized bylong and complex procedures (Djankov et al., 2002). He observed that until recenttimes, the process of starting a business in Italy involved more than sixteen proceduresat a total cost of US$4000.00 and a waiting period of sixty-two days for the completionof the business permit. This explains why business entry rate was low in Italy especiallyamong SMEs as compared to countries like Canada where starting a business involvesonly two procedures at a total cost of US$280.

Institutional factors

The institutional factors measure the impact of both public and private institutions onthe performance and growth of SMEs. These are institutions whose mandate is topromote the development of SMEs through business funding, capacity building andbusiness incubation (Davidsson and Henrekson, 2002). Private institutions have beenfound to be highly effective in promoting SMEs development compared to publicinstitutions in Australia (Davidsson and Henrekson, 2002). This is because until recenttimes, public institutions were not common in Australia with almost one-half of SMEssourcing assistance from private accountants, banks and corporate lawyers. Robsonet al. (2008) found the take up rate of public institutions support programs to be lowamong immigrants and minority ethnic groups who often survive on informal businessactivities. Other studies have however found both private and public institutions tobe equally effective in the development of SMEs. According to Bosma et al (2004) both


public and private institutions have a significant and positive impact in the survivaland growth of SMEs. Wren and Storey (2002) assessed the impact of British EnterpriseInvestment Scheme (a public scheme in Britain) on the performance and growth ofSMEs and found it to be having a positive and significant impact on the performanceand growth of medium-size firms but not on small firms.

In addition to institutional factors, there are also other factors that influence SMEdevelopment and growth. The factors can be broadly classified as entrepreneurcharacteristics (age, education level, gender, marital status), firm specific characteristics(experience, training, location, access to credit, ICT adoption, sector, degree of leverage,current liquidity, ownership structure, and factor productivity).

Age of the entrepreneur

Most empirical studies have found age of the entrepreneur to be having a positiveand significant influence on the performance and growth of SMEs. There is howeverdifferent views on the actual age group that exerts a positive influence on the growthof these enterprises. According to Storey (1994) SMEs owned or managed by youngand middle aged individuals perform better than those managed by olderentrepreneurs. The argument advanced is that young and middle aged managers havethe energy, motivation and commitment necessary to run any enterprise to higherlevels. These entrepreneurs (young and middle aged) are also usually not risk averseand hence they are more likely to invest in projects which bring forth high rates ofreturn. The study on ‘Profitability of Small Grocery Shops in South Africa’ by Chiliya(2012) also found firms managed by young and middle aged individuals to experiencefaster growth than those managed by older entrepreneurs. This phenomenon,according to Chiliya (2012) is explained by the highly innovative minds of young andmiddle age entrepreneurs who often invest in defensible niche products and services.On the contrary, Akoten et al (2006) and Woldie et al (2008) in their respective studiesfound firms owned by middle aged and older entrepreneurs to perform better andexperience more growth than firms owned by young entrepreneurs. Akoten et al (2006)measured SME growth by firm accessibility to credit and pointed out that lendinginstitutions usually prefers to lend to older entrepreneurs because of their averseattitude towards risky projects.

Education Level of the entrepreneur

Carter and Jones-Evans (2002) asserted that basic education equips the entrepreneurwith necessary numeric and reading skills to operate a successful business. Accordingto this study there is a positive relationship between business growth and theeducation qualification held by the business owner or manager. High businessperformance and growth are common in firms owned by entrepreneurs with higheducational qualification. Woldie et al. (2008) also found the education qualificationof the owner to be having a significant and positive effect on the performance andgrowth of SMEs in Nigeria. He found SMEs owned by entrepreneurs who holddiploma, degree and post graduate qualifications to attract large profits andexperience rapid growth than those owned by entrepreneurs whom their highest


education level is primary and secondary school. Akoten et al (2006) and Chiliya(2012) also found a positive relationship between SME growth and the educationqualification held by the SME entrepreneur. Garoma (2012) studying “factorsinfluencing microenterprise success in the urban informal sector of Addis Ababa”found the influence of educational qualification of the SME owner to be positive butinsignificant in influencing the performance and growth of SMEs. He argued that agood educational background of the firm owner is necessary but not sufficient forbusiness growth.

Marital Status of the entrepreneur

The amount of literature available on the influence of the marital status of the SMEowner on the performance and growth of the firm is very limited. Few studies havetested the influence of this variable on the performance and growth of SMEs. Akotenet al (2006) are among the few researchers who tested the influence of this variableand found SMEs owned by married entrepreneurs to perform better and experiencehigh growth levels than those owned by unmarried entrepreneurs. According toAkoten et al (2006) in Kenya married entrepreneurs have a greater access to financialassistance from commercial banks than unmarried entrepreneurs.

Entrepreneur’s Gender

Research shows that male owned firms tend to perform better than firms owned bywomen (Mead and Liedholm, 1998; Garoma, 2012). Some of the reasons advanced forthis phenomenon are that women have limited access to financial assistance ascompared to men. In addition more often women have to split themselves betweenbusiness and household duties, this divided attention adversely affect the performanceand growth of women owned firms (Riding and Swift, 1990; Carter and Jones-Evans,2002). Some studies however have found the gender of the entrepreneur to have aninsignificant influence on the performance and growth of SMEs, arguing that bothmen and women have equal potential to run successful business (Woldie et al., 2008;Copper et al., 1994; Cliffe, 1998)

Managerial and business Experience

Empirical studies have found the level of firm growth to be high among SMEs ownedby individuals who have managerial experience or have prior experience as SMEowners or managers (Storey et al., 1989; Hallberg 2000; Temtime and Pansiri 2004).Hallberg (2000) found that SMEs owned by inexperienced individuals in the UKattracted low business earnings. These firms often find it very hard to survive becauseof lack of business acumen that comes with experience. Temtime and Pansiri (2004)studying ‘Small firms’ Critical Success/ Failure determinants in Botswana’ found thathuman resource development is one factor that limits the success of many small firmsin Botswana particularly lack of experienced personnel. Some studies however havenot found any relationship between the entrepreneur’s experience and the growth ofSMEs. The study by Kalleberg and Leicht (1991) on SMEs in the US found no significantrelationship between the manager’s experience and the performance of the firm,


arguing that firm growth is not an outcome of experience but rather of theenterprenuer’s innovative, proactive behavior and sound expansion strategies.

Business training

Business training according to Foreman-Peck et al. (2006) gives the SME owner/manager the wisdom to provide what the market wants and the necessary skills tokeep and manage business accounts. This attributes in turn increases the competencyand growth rate of the firm. According to Foreman-Peck et al. (2006) it is vital forentrepreneurs to invest in business training programs to enhance their business skills.Temtime and Pansiri (2004) also shared the same sentiments arguing that lack ofmanagerial skills is one of the factors that limit the success and growth of SMEs. Thestudy by Temtime and Pansiri (2004) however revealed that lack of affordable businesstraining facilities worked against the desire by most entrepreneurs to acquire businesstraining. Cosh et al. (2000) studying the relationship between business training andemployment growth in SMEs in the UK also found a positive link between employmentgrowth and acquisition of business skills by firm owners. Chatterji et al (2003) testingthe signaling hypothesis found that firms operated by owners who have under gonesome business training programs attract high levels of business earnings and hencegrow faster than firms owned by entrepreneurs with no business training. Both Coshet al. (2000) and Chatterji et al (2003) argued that trained entrepreneurs experiencehigh growth rate because most of them employ modern day business expansionstrategies such as online advertisement to promote their products.

Access to credit

Investment and growth of SMEs has been found to be positively influenced byaccessibility to business credit (Kapunda et al., (2007); Bigsten et al., 2003). Differentstudies have found that most SMEs do not have access to credit, a phenomenon thatlowers investment and growth of SMEs (Oshikoya, 1994; Morewagae et al., 1995).Kapunda et al. (2007) investigating the relationship between ‘SMEs funding,development and trade in Botswana’ found that government finance schemes such asCEDA have not solved the problem of limited access to credit by SMEs, particularlyfor female owned small and micro enterprises. This according to the study explainsthe poor performance of these firms. Bigsten et al. (2000) studying the performance ofthe manufacturing sector in African countries found that the return to physical capitalin the manufacturing sector is low in Africa due to scarcity of credit among otherfactors. CBS, ICEG, and K-Rep (1999) also found that the main reason for businessclosure in Kenya was lack of business credit. Access to credit is therefore an importantvariable that explains not only the performance and growth of SMEs but also thesurvival of these firms.

ICT Adoption

This variable measures the impact of the use of modern technological products/services such as websites, on-line sales and computerized production system on thegrowth of SMEs. Levy and Yetton (2002) found SMEs involved in e-commerce to


attract high earnings and hence grow faster because of their ability to cover a widerange of potential buyers at a low operational cost. According to Oliner and Sichel(2000) and Goss (2001) productivity growth of SMEs in the late 1990’s in the US wasto large extent explained by the high degree of technological adoption in theirbusiness operation. The use of technological products and services such as on-linesales is not common in SMEs in Africa, failure to adopt this technological products/services limit the growth of these firms (OECD, 2002). The same study by the OECD(2002) however highlighted that in most parts of Africa internet accessibility is stilla challenge and this explains why the use of online business operations is low inAfrica

Location of the business

This variable has been measured in different ways by different researchers. Somestudies compared the growth of firms operating in urban areas against thoseoperating in rural areas. Other studies looked at growth of firms operating at home(household) against those operating outside home (street markets, CBDs etc). Glancey(2008) found that firms in urban areas grow faster than those located in rural areas.The reason advanced is that urban firms have access to a large market of consumerswith high purchasing power compared to firms operating in rural areas. Garoma(2012) dichotomized the location of the business into; firms operated or run at homeand firms operated outside home. He found firms operated at home to performbetter and more likely to grow faster than firms operated outside home because oflow operational cost (free rent) enjoyed by home operated firms. Mead and Liedholm(1998) however reached a different conclusion concerning the performance andgrowth of home operated firms and those operated outside home. They foundfirms operated in open spaces such as streets markets to be profitable and morelikely to expand than firms operated at home because of their exposure to a largemarket.

Sector of the Firm

Most studies have found the sector of the firm to be having a significant influence onthe performance and growth of SMEs (Mead & Liedholm, 1998; Niskanen andNiskanen, 2005; Garoma, 2012). It has also been found that the structure of the sectorsdiffers from country to country hence sectoral performance of SMEs will also differfrom country to country. Mead & Liedholm (1998) found that SMEs in all sectors inKenya expanded more rapidly than those in the retail trade sector. Garoma (2012)found the service sector in Ethiopia to be the most profitable sector and hence SMEsoperating in this sector are more likely to expand faster than those in other sectors.Niskanen and Niskanen (2005) compared SMEs in the manufacturing sector and thosein the non-manufacturing sector in Finland. He found that SMEs in the manufacturingsector perform better and experience high growth levels than those in the non-manufacturing sector. Some studies however have found the sector in which the firmoperates in to be insignificant influencing the performance and growth of SMEs(Barkham, 1992; Storey et al., 1987).


Business Experience

The age of the firm is one of the most investigated variables affecting the performanceand growth of SMEs (measured by the number of years the firm has been in existence).The variable captures the influence of firm experience on the growth of SMEs. Akotenet al. (2006) and Kira and He (2012) found the relationship between firm experiencethe growth of SMEs to be positive. According to them commercial banks usually preferto give loans to enterprises which have been operating for a longer period of time. Thebelief is that experience enhance competence in doing business, hence highlyexperienced firms are more likely to attract high profits and less likely to default loanpayment. Woldie et al. (2008) also found that older firms are more likely to grow fasterthan younger firms because of the social capital (experience) they have gathered overtime. Some studies have however found younger firms to perform better and experiencefaster growth than old firms.

Olutunla and Obamunyi (2008) studying ‘factors associated with the profitabilityof small and medium - firms in Nigeria’ found the relationship between the age of thefirm and business growth to be negative. They found younger SMEs to perform betterand grow faster than old enterprises. They attributed this phenomenon to the factnew firms are more innovative and more likely to easily adapt to the current businessenvironment than older firms. Glancey (2008) and Niskanen & Niskanen (2005) alsofound that young enterprises have a significantly higher profits and growth rates thanthe older firms. They argued that accumulation of experience by older firms does notgive them a competitive advantage over new firms. Salman & Yazdanfa (2012) howeverfound the influence of firm experience on SME growth to be negative but statisticallyinsignificant in Sweden.

Degree of Leverage

This variable measures the amount of debt used to purchase the firm’s physical capital,relative to the owner’s equity. If the debt highly exceeds the firm’s equity then thefirm is said to be highly leveraged (Goddard, 2005). The degree of leverage has beenidentified by a number of studies as an important factor in explaining SME growth(Leung and Yu 1996; Goddard et al. 2005; Mateev and Anastasov 2012). Leung and Yu(1996) and Goddard et al. (2005) found the relationship between SME growth anddegree of leverage to be negative. Arguing that firms that are highly leveraged oftenfind it hard to meet there debt obligations, in extreme cases resulting in repossessionof firm assets by lending institutions and hence adversely affecting firm growth. Mateevand Anastasov (2010) and Honjo and Haranda (2006) found the relationship betweenSME growth and leverage to be positive. According to Mateev and Anastasov (2010)this results shows that SMEs in growing economies need increased access to externalcapital to finance their assets growth. However Honjo and Haranda (2006) arguedthat the positive relationship between SME growth and leverage holds only when thefirm’s profits exceed the loan cost.

Current liquidity

Current liquidity measures the capability of SMEs to maintain short-term liquidity.The variable is often captured by the proportion of current assets to current liabilities


(Mateev and Anastasov, 2010). Goddard et al. (2005) found current liquidity to bepositively and strongly associated with SME growth. They pointed that high liquidityenables the firm to respond quickly to changes in the business environment and thisenhance the level of their growth. Nickell and Nicolitsas (1999) studying the impact offinancial pressure on SMEs also found the relationship between liquidity and firmgrowth to be positive, arguing that firms that are able to maintain high liquidity arenot exposed to the risk of failing to meet their financial obligations. Deloof (2003)however argued that even though current liquidity has a positive effect on firm growth,holding high proportion of liquid assets may constrain the firm from taking advantageof long term investment opportunities and hence compromise future growth. Thisline of thought was supported by Mateev and Anastasov (2010) who found theinfluence of current ratio on firm growth to be negative. According to them, this resultreflect that enterprises with better business investment opportunities will opt tomaintain low levels of liquidity to finance future growth.

Factor productivity (Capital and Labour productivity)

This variable measures the influence of efficiency in the SME’s operations on theperformance and growth of these firms (Salman and Yazdanfar, 2012). According tothe superior firm hypothesis by Demsetz (1973) the level of efficiency it’s a key factorin distinguishing high performing firms from low performing firms. Jovanovic (1982)studying selection and assessment of firms in different industries found both capitaland labour productivity to be positive and statistically significant in influence firmgrowth. He pointed that highly efficient firms in different sectors increase their outputand grow in size over time while less efficient firms are pushed out of business in thelong run. Wiboonchutikula (2002) studying SMEs growth in Thailand found that SMEsexperience high growth levels when the productivity of both capital and labour isgreater and more persistent. Mateev and Anastasov (2010) also found a positiverelationship between factor productivity and SMEs growth in Central and EasternEurope. Their results indicate that for fast growing firms, on average 1 euro investedin Physical assets generates 9.21 euro in sales revenue and labour productivity is highat a median of 43.31.

Ownership structure

This variable measures the influence of SMEs ownership structure on their performanceand growth. Studies captured this variable in different ways, other studies comparedSMEs owned by sole proprietors against partnerships whilst other compared privateowned SMEs against public owned SMEs. According to Garoma (2012) ownershipstructure affect SMEs performance and growth through the degree of risk taking. Hisargument is that sole proprietors are usually risk averse and more often prefersinvesting in low risk projects which attract low rates of return. On the other handpartnership and joint ventures have a great appetite for risky projects which attracthigh rates of return. SMEs operating as partnerships or joint ventures are thereforemore likely to grow faster than those operating as sole proprietorships. The EthiopianChamber of commerce (2006) report also found that SME growth is high among SMEs


owned through partnerships as compared to those owned through sole proprietorship.The reason advanced for this disparity in growth level between partnerships and soleproprietorships is that SMEs owned through partnership have easier access to externalfunding as opposed to sole proprietorship. Sole proprietors rely mostly on own savingsto finance their business activities. Niskanen and Niskanen (2005) also found soleproprietorship to have a negative impact on SME growth, pointing out that the levelof risk aversion is high among firms owned by individuals.

Wiboonchutikula (2002) and Mateev and Anastasov (2012) assessed the growthrates of public sector and private sector SMEs. Wiboonchutikula (2002) found highSMEs growth rates to be associated with public sector companies. He argued thatpublic sector SMEs have easier access to external funding and hence are more likely togrow at a faster rate than private SMEs. Mateev and Anastasov (2010) found nosignificant difference in the growth rates between public SMEs and private SMEs,concluding that ownership structure is not an important determinant of SMEs growth.

5. METHODOLOGY

5.1. Sampling and Sample Sizes

Nationally representative sizes of institutions and SMEs were selected from Botswana.All institutions (public and private sector institutions) that were engaged in thepromotion of development and growth of SMEs were included in the sample for survey.For SMEs, the nationally representative sample Botswana was 700 SMEs The samplingof SMEs took into account the ownership structure (female owned and male owned);size of SME (micro enterprises, small scale enterprises, medium scale enterprises);main sector of SME (trade, services, agriculture, manufacturing); geographical locationof SMEs (rural and urban). The stratified random sampling technique was used todraw the representative sample. All institutions that were engaged in SMEdevelopment were included in the study.

5.2. Data Sources

Three types of data sources were used in institutional analysis of the role of institutionsin promoting the development and growth of SMEs: documentary review, institutionalsurvey data, and SME survey data.

The documentary review focussed on key documents from institutions such asannual operational reports, business plans, audited financial statements. The specificobjective of the documentary review will be to underscore the goals and objectivesof each institution; the type of product/services provided to SMEs; the specific targetgroup of SME owners (women, men, or both); the eligibility criteria for SMEs toaccess institutional products/services; the operational policies and procedures fordelivery of institutional products/services to SMEs; the quantity of output to theSME sector in the past 5 years (number of beneficiaries by gender, quantity ofproducts delivered to SME i.e. total amount of credit disbursed); the legal andregulatory environment that institutions operate in (i.e. Acts of Parliament, policyframework). The outcome of the documentary review will be a comprehensive list


of all institutions that are engaged in the development and growth of SMEs to besurveyed.

The institutional survey data collected from all institutions identified from thedocumentary review. A structured survey questionnaire was administered to allinstitutions involved in the development and growth of SMEs. The data to be collectedincludes the goals and objectives of the institution, the target group of their intervention(female owned, male owned SMEs or both); the key products/services delivered toSMEs (finance, capacity building, policy advocacy); the policies and procedures fordelivery of products/services to SMEs (e.g. the eligibility criteria for SMEs to accessinstitutional products/services); quantity of key institutional outputs (e.g. number ofSME beneficiaries, number of trainings held); the legal and regulatory environmentalunder which institutions operate in (e.g. constraints faced and policy recommendationsto address such constraints); the perception of institutions on how their support toSMEs has contributed to the development and growth of SMEs; the challenges theyface in dealing with SMEs.

The SME survey data was collected from nationally representative SMEs. Theinformation captured from the SME survey included main sector of their operation;ownership structure of SME; years of experience of SME; products/services producedby SME; number of persons employed by SME; profitability of SME; the products/services received by SME from various institutions (credit, capacity building) and howthese products have contributed to the development and growth of their SMEs; thepolicies and operational procedures of institutions and their implications on SMEgrowth; the legal and regulatory environment under which SMEs operate theirbusiness; policy recommendations to address constraints faced by SMEs.

6. DATA ANALYSIS

Econometric modelling was used in the analysis of the data. The econometric modelfor estimation of the determinants of SME growth and performance was be adaptedfrom Mateev and Anastasov (2012) with some modifications. The model was specifiedas follows:

Y = � + �X + �Z + �K + µ (1)where:Y = Firm size, which was proxied by business earnings.X = Vector of enterprise specific characteristics which include short-term liquidity,firm’s degree of leverage, capital productivity, labour productivity, experience,ownership structure, sector, locationZ = Vector of socio-economic characteristics of the entrepreneur which include age,education level, vocational training, genderK = Vector of environmental factors faced by SMEs which include access to credit,access to capacity building, government taxation system, labour market regulations(such as minimum wage legislation), licensing regulations, business registration�, �, �, � = parameters to be estimatedµ = error term


The measurement of the variables and the expected sign are summarized andshown in Table 1 below:

Table 1Variables for Econometric Model

Variable Definition ExpectedSign

Dependent Variables

Earnings Net annual business earnings, which is the differencebetween sales revenue and expenditure.

Explanatory Variables

Current ratio Current assets/current liabilities, proxy for short-term liquidity. +/-

Leverage Total debt/total asset, proxy for a firm’s degree of leverage. +Capital productivity Net annual business earnings/tangible assets, proxy for +

capital productivity.

Labour productivity Net annual business earnings/number of employees, +proxy for labour productivity.

Experience Number of years of existence of the firm +Ownership Ownership structure of SME, a dummy that takes +/-

value of 1 if sole proprietor, otherwise zero

Sector Separate dummies for different sectors (trade, services, +/-manufacturing, agriculture). Agriculture will be usedas the reference category.

Location Location of SME dummy (1 = urban, 0= rural) +

Age Age of entrepreneur , in completed years +Education level Education level of entrepreneur, measured in years of schooling +Gender Gender of SME owner dummy (1= female, 0 = male) +/-

Credit Dummy for access to bank credit (1= has access, 0 = no access) +Capacity Dummy for access to business capacity building +

(1 = has access, 0 = no access)

Labour market Dummy for effect of labour market regulations on -regulations performance of SME (1 = adverse negative effect,

0 = no effect)Taxation Dummy for effect of taxation policy on performance of -

SME (1 = adverse negative effect, 0 = no effect)Licensing regulations Dummy for effect of licensing policy on performance of -

SME (1 = adverse negative effect, 0 = no effect)

Business registration Dummy for effect of business registration on -performance of SME (1 = adverse negative effect,0 = no effect)

7. REGRESSION MODEL RESULTS FOR DETERMINANTS OF SMMEGROWTH IN BOTSWANA

The regression model was estimated following Glancey (2008) and Mateev andAnastasov (2010) based on equation 1. The dependent variable proxied by the logarithmof business earnings.


Table 2Regression Model Estimation Results for Determinants of SMME Growth in Botswana

Dependent Variable: Log of business earnings

Explanatory Variables Coeficient Standard Error t P>t

Log of labour productivity 0.7222 0.042259 17.09 0.000 ***Log of capital productivity 0.1894 0.0501911 3.77 0.000 ***Log of leverage -0.0183 0.0118325 -1.55 0.124Log of current ratio -0.0290 0.0325875 -0.89 0.374Log of years of experience 0.1313 0.0666415 1.97 0.050 **Dummy: training 0.0189 0.1089691 0.17 0.862Dummy: bank credit 0.2428 0.1111212 2.19 0.030 **Dummy: Business registation -0.1721 0.0944984 -1.82 0.070 *Dummy: taxes -0.0022 0.1160772 -0.02 0.985Dummy: labour laws -0.0332 0.1117258 -0.30 0.767Dummy: license requirements 0.0093 0.0954075 0.10 0.923Dummy: manufacturing sector -0.0359 0.1324584 -0.27 0.787Dummy: transport sector -0.0376 0.213026 -0.18 0.860Dummy: construction sector 0.2766 0.1197666 2.31 0.022 **Dummy: trade sector -0.1509 0.0919172 -1.64 0.102Log of age 0.3638 0.1916019 1.90 0.059 *Dummy: primary 0.3588 0.1713477 2.09 0.037 **Dummy: secondary -0.1764 0.1122637 -1.57 0.117Dummy: degree 0.0897 0.1155246 0.78 0.438Dummy: voccational -0.1557 0.1020419 -1.53 0.128Dummy: female -0.0817 0.0866034 -0.94 0.347Constant 3.2471 0.8104211 4.01 0.000 **Number of obs 255F( 21, 233) 29.43Prob > F 0.000R-squared 0.7262Adj R-squared 0.7015Root MSE 0.5651

Significance levels: *** = 1%; ** = 5%; * = 10%

The results of the model estimation presented in Table 2 indicate that the modelestimates are jointly statistically different from zero with the probability of the F-statisticbeing significant at 1% level. The adjusted R-Square which measures the goodness offit of the model is 0.7015.

Production efficiency of the firm in this model was proxied by labour productivityand capital productivity. The results indicate that both labour productivity and capitalproductivity have a positive and significant effect on the growth of SMEs. The resultscorrespond to the findings by Mateev and Anastasov (2010) and Wiboonchutikula(2002) who argue that highly efficient SMEs experience rapid growth in output and insales revenue.


The influence of firm experience on SME growth is positive and statisticallysignificant at 1% level of significance. By implication, the longer the years of experienceof the SME, the better the performance. This result is consistent with (Storey et al.,1989; Hallberg 2000; Temtime and Pansiri 2004) who argued that the level of firmgrowth tends to be high among SMEs owned by individuals who have managerialexperience or have prior experience as SME owners or managers. Hallberg (2000)found that SMEs owned by inexperienced individuals in the UK attracted low businessearnings and they often find it very hard to survive because of lack of business acumenthat comes with experience.

Access to bank credit has a positive and significant effect on the growth of SMEs.This is consistent with the logic that external finance is critical in enabling SMEs toexpand their operations. This result is consistent with Kapunda et al., (2007) and Bigstenet al., (2003) who pointed out the positive relationship between access to businesscredit and SME growth.

The labour laws have a negative and significant effect on the growth of SMEs inBotswana. The main issue that was raised by SME owners is that they find challengesin getting labour for their SMEs. The citizens are not hard working as compared toforeigners (especially Zimbabweans) but are barred by labour regulations from beingemployed without work permits. The process of obtaining work permits for suchcategory of workers is very challenging.

Being in the transport/communications sector and construction sector havepositive and significant effects on SME growth in Botswana. Even at the macro level,the transport/communication and construction sectors have high growth rates ascompared to other sectors.

The age of the SME entrepreneur has a positive and significant effect at 10%significance level on SME growth. The results are consistent with Akoten et al. (2006)and Woldie et al. (2008) who observed that firms owned by middle aged and olderentrepreneurs perform better and experience more growth than firms owned by youngentrepreneurs.

Being a female entrepreneur has a negative and but insignificant effect on SMEgrowth. These results are consistent with Mead and Liedholm (1998) and Garoma(2012) who observed that male owned firms tend to perform better than firms ownedby women due to limited access to financial assistance by. Other scholars also pointout that women have divided attention between business and household duties whichadversely affect the performance and growth of women owned firms (Riding andSwift, 1990; Carter and Jones-Evans, 2002).

Having primary education has a positive and significant effect on SME performancein Botswana. This result is consistent with Carter and Jones-Evans (2002) who arguedthat basic education equips the entrepreneur with necessary numeric and readingskills to operate a successful business.

The marginal effects model was also estimated and the results presented in Table3 below:


Table 3Marginal Effects Model for Determinants of SMME Growth in Botswana

Marginal Effects Regressiony = Fitted values (predict) = 12.578762

Variable dy/dx Standard Error z P>z X

Log of labour productivity 0.7222 0.0423 17.09 0.000 10.593 ***Log of capital productivity 0.1894 0.0502 3.77 0.000 0.845 ***Log of leverage -0.0183 0.0118 -1.55 0.122 -3.404Log of current ratio -0.0290 0.3259 -0.89 0.373 1.091Log of years of experience 0.1313 0.0666 1.97 0.049 1.571 **Dummy:training* 0.0189 0.1090 0.17 0.862 0.859Dummy: bank credit* 0.2428 0.1111 2.19 0.029 0.835 **Dummy: Business registation* -0.1721 0.0945 -1.82 0.069 0.784 *Dummy: taxes* -0.0022 0.1161 -0.02 0.985 0.780Dummy: labour laws* -0.0332 0.1117 -0.30 0.767 0.784Dummy: license requirements* 0.0093 0.0954 0.10 0.922 0.733Dummy: manufacturing sector* -0.0359 0.1325 -0.27 0.786 0.106Dummy: transport sector* -0.0376 0.2131 -0.18 0.860 0.035Dummy: construction sector* 0.2766 0.1198 2.31 0.021 0.145 **Dummy: trade sector* -0.1509 0.0919 -1.64 0.101 0.439Log of age 0.3638 0.1916 1.90 0.058 3.586 *Dummy: primary* 0.3588 0.1714 2.09 0.036 0.059 **Dummy: secondary* -0.1764 0.1123 -1.57 0.116 0.157Dummy: degree* 0.0897 0.1155 0.78 0.438 0.153Dummy: voccational* -0.1557 0.1020 -1.53 0.127 0.216Dummy: female* -0.0817 0.0866 -0.94 0.346 0.314

Significance levels: *** = 1%; ** = 5%; * 10%(*) dy/dx is for discrete change of dummy variable from 0 to 1

8. CONCLUSION

From the econometric model estimation, the growth of SMEs is positively andsignificantly influenced by labour productivity, capital productivity of capital, accessto credit, age of the entrepreneur, and having primary education. However SME growthis negatively influenced by the labour laws which prohibit access to cheap foreignlabour. Introduce new funding models for SMME development especially for womenSMMEs. The study recommends that the current funding for women under theDepartment for Gender Affairs could be enhanced to the level of the YouthDevelopment Fund (YDF) to cater for women with constrained access to credit.Government should also simplify the tax system for SMMEs and the registrationprocess for new businesses.

Notes

1. This study acknowledges the financial support from IDRC but the views expressed here arethose of the authors only.


2. Elsewhere in the literature, these are refered to as Small and Medium Scale Enterprises (SMEs).

3. The Youth Development Fund is managed by the Ministry of Youth, Sports and Culture.

4. Exchange rate US$1 = P8.

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