INSTITUTIONS AND SMME DEVELOPMENT IN BOTSWANA: EVIDENCE FROM EXPLORATORY FACTOR ANALYSIS

Transcription

1 Institutions Asian-African and Journal SMME of Development Economics and in Botswana: Econometrics, Evidence Vol. from 16, No. Exploratory... 1, 2016: INSTITUTIONS AND SMME DEVELOPMENT IN BOTSWANA: EVIDENCE FROM EXPLORATORY FACTOR ANALYSIS 1 Okurut, F.N; 2 Ama, N.O; 3 Mookodi, L; 4 Okurut, M.L.A; 5 Ama, H.A Abstract: The study used exploratory factor analysis (EFA) to investigate the role of institutions in promoting the development and growth of SMMEs in Botswana from a gender perspective. The SMME owners agree that the role of financial institutions can be best described in terms of provision of bank technical advice, business planning guide, bank regulations and bank interest rates and charges. The mean distribution of the male responses are higher as compared to women and statistically significant for access to credit and bank technical advice (p<0.05). Both men and women SMME owners agree that the key factors that can boost SMME development in Botswana include government support to SMMEs, capacity building, finance, SMME regulatory framework and SMME management. The male and female are significantly divergent in their views on government support for SMMEs and SMME regulatory framework (p < 0.05). The perceptions of men and women SMME owners on whether institutions for SMME development provide special gender support revealed some disparity. The mean scores with regard to institutional support were lower for women SMME owners compared to male SMME owners and the mean differences were statistically significant (p<0.05). This is indicative of institutional discrimination against women by financial institutions, Government agencies (CEDA, LEA), Local Governments, NGOs and business associations. The issue as to whether women and men face equal treatment when they seek help from support institutions was further examined. The mean score for men was higher and statistically different from the women (mean for men 3.66, mean for women 3.55, p < 0.05). This is further evidence of discrimination against women. The study recommends that all institutions should adopt gender neutral policies so as to enhance development and growth of female owned SMMEs. Key Words: Gender, Institutions, SMME, Development, Botswana 1. INTRODUCTION Institutions are argued to be important means of supplementing and complementing resource constrained SMMEs to enhance their growth and market performance (Cumbers et al., 2003). 1 Associate Professor of Economics, Department of Economics, University of Botswana, Okurutf@mopipi.ub.bw (corresponding author). 2 Professor of Statistics, Department of Statistics, University of Botswana, Gaborone. 3 Senior Researcher, BIDPA, Botswana, Gaborone. 4 PhD student, University of Pretoria, South Africa. 5 PhD student, Department of Educational Management, University of Botswana, Gaborone.

2 40 Okurut, F. N., Ama, N.O., Mookodi, L., Okurut, M.L.A. and Ama, H.A. According to Kailer and Scheff (1999), SMMEs are faced with many challenges which include constrained internal resources, limited technical and business operation knowledge.. A number of institutions, namely, government ministries, public institutions (government agencies), private institutions and SMMEs organizations (Siropolis, 1994; Kailer and Scheff, 1999, Zeng et al., 2009) have the mandate to support, facilitate and promote the development of SMMEs in various countries Government ministries The significant degree of interactions between domestic non-governmental actors and the business world community (Yanez et al., 2008) are said to be very important in guaranteeing local governance and ensuring the development of non-governmental organizations (including SMMEs). Government ministries develop and implement policies, develop regulatory measures and strategic programs aimed at supporting and promoting the development of SMMEs in the domestic economy (Libutti, 2000; Powell, 1990). This is done through, provision of subsidies to SMMEs, development of policy measures that aim at strengthening ties between SMMEs and research institutions and putting in place policy measures that will encourage SMMEs to undertake product and process innovation (Matt and Wolff, 2004). There are also government and quasi-government credit guarantee schemes which encourage commercial banks to lend to SMMEs on the understanding that a percentage of the issued loan will be reimbursed (either by the government or the quasi-government) if the SMMEs default payment (Levitsky, 1997). Such credit guarantee schemes play a very important role in bridging the gap between SMMEs capital needs and the risk concerns of commercial banks by offering a guarantee system which is adequately backed financially, thereby enhancing credence before the eyes of the lenders (CGC, 1993). Another important role of government ministries is to establish public institutions to support, facilitate and promote the development of SMMEs (Biggs and Shah, 2006). The establishment of these public institutions is to a large extent brought about by the challenges that exist in governing and managing collaborations between government ministries and SMMEs (Keast and Hampson, 2007). The broader government policy literature has advocated for government to cooperate with SMMEs through government agencies or public institutions to allow government ministries to focus on other issues of governance (Powell, 1990). In the case of Botswana, the key government ministries engaged in SMME development include Ministry of Trade and Industry, Ministry of Local Government, and Ministry of Finance and Development Planning Public Agencies These are government funded agencies 1 whose main role is to implement government policies, regulatory measures and strategic programmes that are aimed at supporting and promoting the development of SMMEs (Zeng et al., 2009). Government policy measures that public agencies are tasked with implementing include: financial policies; industrial policies; patenting policies (intellectual property rights). In essence these entail financial assistance, capacity building and other strategic programmes such as business incubation, development of innovation hubs and

3 Institutions and SMME Development in Botswana: Evidence from Exploratory collaborations with SMEs in research and development projects (Zeng et al., 2009; Powell, 1990). There are also government regulatory agencies which exist at both the central and local government levels (Siropolis, 1994). The regulatory agencies are tasked with issuing and enforcing business regulation measures (Zeng et al., 2009). The purpose of these regulatory measures is to promote and protect the interests of entrepreneurs and the society at large through establishment of laws targeting anti-competitive behavior, regulation of the banking sector (to protect business and public savings), protection of the environment from pollutants emitted by firms (Siropolis, 1994; Leung, 2003). However, the regulatory system is also considered to be a great impediment to the development and growth of SMMEs. According Siropolis (1994), new and aspiring entrepreneurs are often discouraged by complex business licensing procedures, countless environmental protection requirements and also massive paperwork involved in opening a business. To cope with this unfriendly business regulatory environment, new firms often resort to engaging the legal expertise of private institutions (consultants, lawyers) to deal with the registration and licensing technicalities on their behalf. The services rendered by these private institutions is critical in assuring that the new firm abide by the business registration and licensing laws and its business operation is within the spectrum of permitted business activities Private Institutions Private institutions provide SMMEs with services that include legal assistance in business registration, management training, identifying viable business opportunities for SMMEs, risk insurance (Siropolis, 1994). The effectiveness of these private institutions is based on the quality of the product offered (e.g quality of training), correspondence between supply and demand of the product offered, quality of the cooperation with SMMEs and transparency in the private institutional sector (Kailer and Scheff, 1999). Within the broad class of private institutions, there exist private companies which offer free assistance to SMEs through their social investment arms (Ace, 2013). The main target of these social investment initiatives are usually small and micro enterprises owned by women, youth and other minority groups in the society. Common assistance issued by these private institutions includes provision of grants, business skills training and mentorship with a broad aim of developing the firms and the communities in which they are situated SMMEs Associations The main purpose of SMMEs organizations or associations is to provide a platform where SMMEs can meet and discuss mutual business challenges and opportunities (Siropolis, 1994). These organizations are usually made up of SMMEs who are in the same line of business or share certain demographic characteristics. An example of these organizations in Botswana include Botswana Chamber of Commerce Industry and Mines(BOCCIM), Women in Business Associations (WIBA). There are however certain factors that impedes the maximum utilization of these institutions by SMMEs. Some of these factors include; overload of SMEs management with day to day

4 42 Okurut, F. N., Ama, N.O., Mookodi, L., Okurut, M.L.A. and Ama, H.A. business routines (which means limited time for collaboration with these institutions) and also most of these institutions lack practical and problem relevance (which increases the perception that these institutions offer limited value for money) (Kailer and Scheff, 1999; Storey, 1998) 1.5. Legal Framework According to Ekpe et al. (2011) the legal system provides the framework necessary for the control of resources and promotion of equitable distribution of those resources in an alliance relationship. Controlling opportunistic behavior in any form of alliance depends on the ability of the institutional environment to appropriately match controls (legal framework) with known hazards. Poppo and Zenger (1998) asserted that the ability of formal contracts to effectively control opportunism depends on the country s legal system. The fear of opportunistic behavior in alliance relationships among SMMEs will always be high in countries whose institutional environment lacks a legal obligation to enforcement of contracts and property rights. La Porta et al., (1999) also argued that the legal origin of the constitution of a nation dictates how enforcement of property rights and contracts affect perceptions on opportunistic behavior in SMME alliances. 2. OBJECTIVES OF THE STUDY The objectives of the study were: (i) To explore the role of institutions in the development of SMMEs in Botswana (ii) To explore the gender disparity in institutional support in the development and support of SMMEs in Botswana (iii) To suggest policy recommendations to improve the development of SMMEs in Botswana 3. LITERATURE REVIEW The institutions that influence SMME development include financial institutions, capacity building institutions, regulatory institutions, government agencies, non-government organizations. Market and technological developments avail opportunities that are not perfectly visible or obvious to every member in the society. These opportunities are discovered and exploited by individuals with eccentric market information and relevant resources. Market information and resources are acquired through education, prior work or business experience and societal networks, and are differentially available across gender lines. Women generally have limited access to resources, low level of experience and education compared to men. The observed differences in the rate, size, scale and sector of business participation between men and women are, therefore, explained by the differences in resource ownership, work/business experience and education level (Kalleberg and Leicht, 1991). Government legislation and policy plays a crucial role in promoting women participation in business (PWC, 2007). In first world countries, various laws and gender-mainstreaming policies have been adopted to promote gender equality and women economic empowerment. Women issues (including women entrepreneurship) form an integral part of many government

5 Institutions and SMME Development in Botswana: Evidence from Exploratory and non-governmental organizations in these countries. In Sweden, the government developed special departments within each of its ministries that deal primarily with supporting and promoting women interests. The Spanish government has also enacted a business legislation that compels large corporations to have gender parity on their boards of directors. However, as observed by Bajdo& Dickson (2001) factors affecting women participation in business differs across the world. Policies and laws adopted in developed economies may not be applicable and relevant in the context of developing economies, where women are highly marginalized and illiteracy continues to impede women participating in formal business. In many countries, government policies and laws are skewed towards promotion of women education and representation in positions of political leadership and decision making structures. Substantial female education policy interventions have been adopted in most of these countries, to boost women access to basic education and bridge the education-gender gap between men and women. Efforts are also made to increase women representation in positions of political leadership and decision making structures (Sadie, 2005). The Southern African Development Community (SADC), have set a target of 30% women representation in parliamentary structures of all member states, and some countries have reached this target. India has also successfully reached its target of one-third representation of women in districts and parliamentary seats. All these policies and legislations directly and indirectly enhance women participation in business (PWC, 2007). Many institutions have recognized the important role played by women enterprises in fostering economic development and growth (ILO, 2005; UNIFEM, 2008). There has been a significant degree of collaboration between different institutions and women enterprises across the world (Yanez et al., 2008). Collaborations of this nature have been highly instrumental in promoting women economic participation in business (Kailer and Scheff,1999). Cumbers et al., (2003) pointed that, the critical role played by institutions in funding, training, mentoring, monitoring and incubating women enterprises have contributed immensely to the growth and establishment of highly innovative women enterprises. Businesswomen associations have also been commended by many re searchers for the role they play in nurturing and supporting women enterprises (Siropolis, 1994). These associations provide a platform for women entrepreneurs to meet and discuss mutual business challenges and opportunities. In addition, the financial contributions made in these associations are often used to assist individual members in acquiring legal advice or paying for expert consultations, if need be. Institutional factors that influencesme developmentinclude the business environment and technological development factors (Hofstede, 1983; House et al., 2004). The Business Environment The business environment factors include access to credit, corporate tax, and business regulations (Riding and Swift, 1990; Evans and Leignton, 1989; World Bank, 2005; Kalleberg and Leicht, 1991).

6 44 Okurut, F. N., Ama, N.O., Mookodi, L., Okurut, M.L.A. and Ama, H.A. Access to credit Constrained access to external finance is one major factor that hinders the development of SME, especially among women (Bigsten et al. 2003; May, 2007, CSO, 2008). Evidence by May (2007) suggested that women entrepreneurs in Nigeria were greatly constrained in access to credit due to lack of collateral security. Okurut and Ama (2013)also foundwomen entrepreneurs in Botswana were credit constrained.other studies also found evidence indicating banking institutions practiced systemic discrimination against women enterprises in formal credit markets (Coleman, 2000; Cavaulluzzo et al., 2002; Riding and Swift, 1990). Coleman (2000) observed that the lending conditions tend to favour men as compared to women. The lending conditions to women businesses often entailed high interest rates and stringent collateral requirements relative to those of men. Riding and Swift(1990), studying women business owners and terms of credit in Canada, noted that the financing conditions for women owned enterprises were less favorable than for men owned enterprises. This was accounted for by the fact thatthe business profiles of most women enterprises were less favorable for investors (lenders). Most of the women ventures tended to be very small (in terms of assets size), unincorporated and having lower rates of sales growth relative to men investment ventures. Treichel and Scott (2007) assessing women entrepreneurship and access to bank credit in the US arrived at a similar conclusion. The authors observed that while the loan applications of most women owned firms were highly likely to be rejected in formal credit markets, there was no significant evidence to suggest any gender bias or any form of systemic discrimination. The major explanation for this trend was the strict screening and selection models used by banks in issuing loans which includes credit history, risks and business characteristics(such as, size, experience and industry), but not gender. Business/Corporate Tax High business taxes hamper SMME development and also increases the proportion of enterprises in the informal sectorespecially among women (Evans and Leignton, 1989; Verhuel et al.,( 2006); Folster, 2002, World Bank, 2007). Evans and Leignton (1989) observed that the increase in FICA 2 tax significantly decreased the likelihood of women participating in self-employment activities. Unincorporated (informal) women self- employment activities tend to increase with the increase in the FICA tax. The key argument was that high tax rates increase tax avoidance practices which include establishment of unregistered and unlicensed enterprises. Verhuel et al., (2006) also noted that tax evasion explains the high participation rate of women in the informal sector in both rich and poor countries. World Bank (2007) also observed a strong negative relationship between tax rates and participation in business. World Bank (2007) argued that the impact of tax rates on entrepreneurship is non-gendered, thus both the level of men and women participation in business is equally affected by high business tax rates. Business Regulations Complex bureaucratic business registration and licensing procedures (business regulations) SME development (World Bank, 2005; Kalleberg and Leicht, 1999; World Bank, 2012). In

7 Institutions and SMME Development in Botswana: Evidence from Exploratory many studies, the ease or complexity of business regulationshave been proxied by the time and money cost associated with compliance (Bullough, 2008; World Bank, 2005). According to World Bank (2012), complex business regulations impact negatively on women entrepreneurship. However, the study did not find sufficient evidence to suggest that the problem of business regulation on the business community is gender based. According to World Bank (2012), there are very few business regulation differences between women and men. However, Kalleberg and Leicht, (1999) assessing gender and organizational performance in South Central Indiana, found business regulations to be more burdensome for women who wish to start up companies than men. They pointed that on average, women tend to have less knowledge and experience in dealing with business registration and licensing procedures as compared to men. A more recent study by Verhuel et al., (2006) however found the impact of business regulation on women participation in business to be insignificant in transition and developed economies. The argument was that business registration and licensing procedures were very basic, and easy to follow. Technological Development Technological development promotes establishment of innovative enterprises and reduce transaction costs associated with communication and information sharing (Casson 1995, Wennekers et al. 2002; Cumbers et al., 2003). Entrepreneurs can benefit directly from technological developments (through production of new innovative products) and indirectly (through the use of cost effective modern day technological communication and advertisement techniques). Gurmeet and Belwal (2008) however, found a negative relationship between women participation in the SME sector and technological development in Ethiopia. They argued that most women in Ethiopia do not have the necessary skills to enable them to reap maximum benefits from technological developments. Verheul et al. (2006), using the level of investment in research and development (R&D) to proxy technological development, found technological development to be having a negative but insignificant influence on women participation in business in most transition economies. However the study found the relationship to be negative and significant in the case of men entrepreneurship. They argued that it is possible that the technological developments in most of these countries is increasing economies of scale and scope for enterprises with high technological skills, thereby reducing business opportunities for smaller firms (for both men and women). However, in the long run when the knowledge on the use of computers and technological products and services is common to all men and women, the relationship between these two variables might change in significance and sign. Alam et al. (2011) found the influence of technological development (proxied by ICT usage) to be insignificant in influencing women participation in business and the success of women enterprises in Malaysia. They highlighted that the result may be explained by the fact that, the majority of the women in the study reported having no access to ICT. 4. METHODOLOGY 4.1. Sampling and Sample Sizes This study took place between July 2014 and December 2015 and covered all institutions (private and public) that are engaged in promoting SMMEs in Botswana and the SMME owners/managers.

8 46 Okurut, F. N., Ama, N.O., Mookodi, L., Okurut, M.L.A. and Ama, H.A. A nationally representative stratified random sample of 700 SMMEs owners/managers were selected for the study. The sampling of SMMEs took into account the ownership structure (female owned and male owned); size of SMME (micro enterprises, small scale enterprises, medium scale enterprises); main sector of SMME (trade, services, agriculture, manufacturing); geographical location of SMMEs (rural and urban). This sample size is about twice the statistically accepted sample size at a 95% confidence interval and allowing an error margin of 5%, as recommended by Survey Systems (2012) but was taken to ensure adequate coverage of the SMMEs in the country and an increased the power of the statistical analyses Data Sources Three types of data sources were used in the study, namely, documentary review, institutional survey, and cross-sectional survey of SMMEs. The documentary review focused on key documents from institutions such as annual operational reports, business plans, and audited financial statements. The specific objective of the documentary review underscore the goals and objectives of each institution; the type of product/services provided to SMMEs; the specific target group of SMME owners (women, men, or both); the eligibility criteria for SMMEs to access institutional products/services; the operational policies and procedures for delivery of institutional products/services to SMMEs; the quantity of output to the SMME sector in the past 2 years (number of beneficiaries by gender, quantity of products delivered to SMME i.e. total amount of credit disbursed); the legal and regulatory environment that institutions operate in (i.e. Acts of Parliament, policy framework). The outcome of the documentary review was a comprehensive list of all institutions that are engaged in the development and growth of SMMEs. The institutional survey collected data from all institutions identified from the documentary review. A structured survey questionnaire was administered to all institutions involved in the development and growth of SMMEs. The data collected included, the goals and objectives of the institution, the target group of their intervention (female owned, male owned SMMEs or both); the key products/services delivered to SMMEs(finance, capacity building, policy advocacy); the policies and procedures for delivery of products/services to SMMEs(e.g. the eligibility criteria for SMMEs to access institutional products/services); quantity of key institutional outputs (e.g. number of SMME beneficiaries, number of trainings held); the legal and regulatory environmental under which institutions operate in (e.g. constraints faced and policy recommendations to address such constraints); the perception of institutions on how their support to SMMEs has contributed to the development and growth of SMMEs; the challenges they face in dealing with SMMEs. The SMME survey collected data from the nationally representative SMMEs. The information captured from the SMME survey included, main sector of their operation; ownership structure of SMMEs; years of experience of SMMEs; products/services produced by SMME; number of persons employed by SMME; profitability of SMME; the products/services received by SMMEs from various institutions (credit, capacity building) and how these products have contributed to the development and growth of their SMMEs; the policies and operational procedures of institutions and their implications on SMME growth; the legal and regulatory

9 Institutions and SMME Development in Botswana: Evidence from Exploratory environment under which SMMEs operate their business; and policy recommendations to address constraints faced by SMMEs. In addition to the quantitative data, qualitative techniques (Key Informant Interviews [KII] and Focus Group Discussions [FGD]) were used to collect qualitative data to corroborate the findings from quantitative results. Key informant interviews were held with key officers in institutions engaged in the development and growth of SMMEs. The key informant interviews focused on the following themes: mission of institution; target group; institutional products/services provided to SMMEs; eligibility criteria for SMMEs to access products/ services; how the products/services enhance the growth of SMMEs; constraints faced by institution; and policy recommendations to address the constraints. Key informant interviews will also be held with key community leaders (such as members of parliament, chiefs) on their perception on how institutions have contributed to the development of the SMME sector. Focus Group Discussions (separate for female and male SMME owners) were held to get the perception of the role played by institutions in promoting SMMEs; the quality of the products/services received by SMMEs from institutions; the challenges faced by SMMEs in accessing institutional products/services; policy recommendations to improve the performance of institutions in service delivery to SMMEs. The present paper is based on the survey of the SMME owners/managers Data Analysis The exploratory factor analysis was used to identify the key constructs (latent variables) that best answer the objectives of the study. 5. FINDINGS OF THE STUDY 5.1. Factors acting as catalyst in the development of SMMEs in Botswana The analysis was based on 20-item variables to which the SMME owners responded to the question, From the list of factors, assess on a scale of 1 to 5, the extent to which each factor may help or act as a catalyst in the development of your business on a five-point Likert Scale of 1 = Very Little Extent, 2 = Little extent, 3= Neutral, 4 = Great Extent and 5 = Very Great Extent. A factor analysis was carried based on the responses and results show that there are five basic constructs that explains the catalyst to the development of SMMEs in Botswana. These constructs explained 68.4% of the variation in the variables and both the Kaizer-Meyer-Oklin Measure of Sampling Adequacy for the EFA > 0.7 and the Bartlett s test of sphericity (p < 0.005), at 5% level of significance showed that the use of EFA was appropriate. The constructs, with factor loadings, are: Factor 1-Compliance to regulations This factor was found to be heavily loaded on issuing of licenses (0.566), labour laws (0.714), paying taxes (0.782), Government policies on SMMEs including Fiscal Measures or otherwise (0.733), SMME Associations (Association of Jewellery etc.) (0.689), political and social stability (0.500).

10 48 Okurut, F. N., Ama, N.O., Mookodi, L., Okurut, M.L.A. and Ama, H.A. Factor 2-Finance and logistics The factor was heavily loaded on access to finance from commercial banks (0.82), access to finance from sources other than commercial banks (0.825), Cash Flow Management (0.623) and Logistics (Transport, Warehousing, IT) and Infrastructure (0.541). Factor 3: Government support The factor was heavily loaded on 3 variables namely: knowledge about the business and market risks (0.747), operational costs (e.g VAT payments) (0.679), support of Government Agencies (LEA, CEDA Youth Development Fund, etc) (0.604). Factor 4- Markets The factor was heavily loaded on 3 variables, namely, demand for products and services (0.715), market access (Local and Regional) (0.798) and availability of appropriate skills (0.666). Factor 5- Production capacity The factor was heavily loaded on managerial experience (0.669), production capacity (0.721) and availability of raw materials quality of products (0.821). The descriptive analysis, carried out for each of the factors by the sex of the SMME owners/ managers, is displayed in Table 1. The table shows that for the male and female- owned SMME, finance and logistics (mean = 4.16 for male and 4.13 for female), markets (mean = 4.22 for male and 4.28 for female) and production capacity (mean = 4.21 for male and 4.35 for female) were the top influencing factors of SMME development. There are significant differences (p < 0.05) in the opinions of the male and female SMME owners/managers with regards to the impact of Finance and logistics, and Markets on SMME development. The responses are highly skewed for most of the factors and for the males and females (skewness < -1) and platykurtic peaked (with excess kurtosis < 0) Table 1 Descriptive Statistics: Factors Affecting Development of SMME and test of equality of means Mean Std. Deviation Skewness Kurtosis Sig. (2 tail) Male Female Male Female Male Female Male Female Compliance to regulations Finance and logistics Markets Government support Production capacity Factors acting as impediment/barrier in the development of SMMEs This objective was assessed with responses of the SMME owners on 20-item variables to the question, Assess on a scale of 1 to 5, the extent to which each factor may act as an impediment/ barrier in the development of your business, where the five point Likert scale was given as 1 =

11 Institutions and SMME Development in Botswana: Evidence from Exploratory Very Little Extent, 2 = Little extent, 3= Neutral, 4 = Great Extent and 5 = Very Great Extent. The responses were subjected to Factor Analysis and only two constructs, finance and technical capacity, and Government regulations explaining 74.41% of the variation in the variables, explained the impediments to SMME s development in Botswana were extracted. The Kaizer- Meyer-Oklin Measure of Sampling Adequacy for the EFA 0.954> 0.7 and the Bartlett s test of sphericity (p < 0.005), at 5% level of significance showed that the use of EFA was appropriate. Factor 1-Finance and technical capacity The factor was heavily loaded on 10 variables, namely, cash flow management (0.84), logistics (Transport, Warehousing, IT) and infrastructure (0.83), market access (Local and Regional) (0.82), demand for products and services (0.82), availability of appropriate skills (0.81), production capacity and availability of raw materials (0.79), quality of products (0.78), access to finance from sources other than commercial banks (0.77), managerial experience( 0.76), access to finance from commercial banks (0.74), and knowledge about the business and market risks (0.71). This factor explained 43.9 % of the total variance. Factor 2- Government regulations This factor was heavily loaded on 9 variables: SMME Associations (Association of Jewellery etc.) (0.77), Government policies on SMMEs including Fiscal Measures or otherwise (0.76), labour laws (0.76), paying taxes (0.75), issuing of licenses (0.75), political and social stability (0.71), support of Government Agencies (LEA, CEDA, Youth Development Fund, etc.) (0.65), and Operational costs (e.g. VAT payments) (0.61). It explained 30.49% of the total variation. Table 2 shows the means, standard deviation, skewness and kurtosis for the factors that act as impediment in the development of SMMEs in Botswana. The results show that while the male SMME owners are of the view that finance and technical capacity and government regulations act impediment/barrier to SMME development to a great extent (mean 3.8 and 3.7), the female owners are almost neutral (mean = 3.3). The distribution of the male SMME owners are highly skewed (skewness < -1) and platykurtic( excessskewness<0) while those of the female respondents are moderately skewed (skewness between -1 and and platykurtic (excess kurtosis < 0). The male and female SMMEs are significantly different (p < 0) in their opinions on how both factors act as impediments to SMME development. Table 2 Descriptive on factors acting as impediment/barrier in the development of SMMEs and test of equality of means Mean Std. Deviation Skewness Kurtosis Sig. (2 tail) Male Female Male Female Male Female Male Female The finance and technical capacity Government Regulations

12 50 Okurut, F. N., Ama, N.O., Mookodi, L., Okurut, M.L.A. and Ama, H.A Extent of awareness of the finance sources for SMME development in Botswana The respondents were asked to assess on a scale of 1 to 5: where 1 = Least Aware, 2 = Little extent, 3= Neutral, 4 = Great Extent and 5 = Most Aware the extent to which you are aware of the source of finance in the past 2 years. The responses were subjected to factor analysis and results show the three constructs (factors) namely, Credit sources, short term loans and nonbanking sources that explain the extent to which SMME owners are aware of the financial sources available for the development of SMMEs in Botswana. The three constructs jointly explained 62.81% of the variation in the variables. The Kaizer-Meyer-Oklin Measure of Sampling Adequacy for the EFA > 0.7 and the Bartlett s test of sphericity (p < 0.005), at 5% level of significance showed that the use of EFA was appropriate. Factor 1- Credit sources This factor was heavily loaded on the 8 variables, delay payments to suppliers (0.83), venture capital/ Angel Finance (0.81), Shareholders/Director loan (0.79), Factoring/ Invoice discounting(0.78), Trade credit (0.77), Equity financing Scheme (0.76), Hire purchase/leasing (0.70), and Micro-credit/finance (0.53) with total explained variance of 31.32%. Factor 2-Short-term loan This constructs was heavily loaded on 5 variables: short- term loans from commercial banks (0.71), Savings (0.0.68), Retained profits (0.66), Long Term loans from commercial banks (0.65), and Bank overdrafts (0.58) with explained variance of 16.36%. Factor 3-The non-banking sources The factor was heavily loaded on the variables family members (0.80), Grants (Ongoing for business expansion) (0.77) and Start-up grant scheme (0.72) with explained variance of 15.13%. Table 3 shows the descriptive for the three factors, credit sources, short term loan, and non-banking sources that best describes the SMME awareness of the financial sources for SMME development in Botswana. The results show that the male and female SMME owners are aware of the financial sourcesalmost to a great extent (mean = 3.71 for male and 3.5 for female). They are either almost neutral or aware of the credit sources and nonbanking sources to a little extent (mean < 3.5). The test of equality of mean responses shows that the male and female SMME owners are significantly differentin their opinions with regards to the three factors. The distribution of the opinions are also highly skewed and also platykurtic. Table 3 Descriptive for extent of awareness of the finance sources for SMME development in Botswana and test of equality of means Mean Std. Deviation Skewness Kurtosis Sig. Male Female Male Female Male Female Male Female Creditsources Shorttermloan Nonbankingsources

13 Institutions and SMME Development in Botswana: Evidence from Exploratory Extent of use of financial sources for SMME development in Botswana The extent to which SMMEs in Botswana used the financial sources available in the development of their SMMEs was assesses with 17-item variables. They were asked to assess on a scale of 1 to 5 the extent to which they use the source of finance in the past 2 years: where 1 = Least Aware, 2 = Little extent, 3= Neutral, 4 = Great Extent and 5 = Most used. The responses were subjected to exploratory factor analysis and the results show that the extent of use of financial sources for SMME development in Botswana can be explained using five constructs, namely, use of Credit Sources, Trade Credit sources, the non-bank credit sources, retained profits and savings and Grants. These constructs explained % of the total variation in the variables. A test of the adequacy and appropriateness of the exploratory factor analysis using the Kaiser- Meyer-Olkin Measure of Sampling Adequacy (0.759 >0.7) and Bartlett s test of sphericity (p < 0.01) reveals this analytical approach adequate. Factor 1- The credit sources This factor was found to be heavily loaded on 5 variables, namely, trade credit 0.76), hire purchase/leasing (0.72), delay payments to suppliers (0.56), venture capital/angel finance (0.56), and shareholders/director loan (0.53) and explaining 15.89% out of the total explained variation by all the constructs. Factor 2- The trade credits This second constructs (factor) was heavily loaded on 2 variables, long term loans from commercial banks (0.79) and bank overdrafts with factor loadings (0.54). The factor explained 10.78% out of the total explained variation. Factor 3- The non-bank credits The non-bank factor was heavily loaded on 2 variables, micro-credit/finance (0.73) and family members (0.51) with factor loadings and explained 9.6% of the variation. Factor 4- The retained profits and savings This construct was heavily loaded on 2 variables, retained profits (0.77) and savings (0.73). The factor explained 9.59% of the variation. Factor 5- The grants The factor was heavily loaded on grants (ongoing for business expansion) (0.78) and start-up grant scheme with factor loadings (0.73) and explained 8.62% of the variation. The descriptive statistics for the five factors that best describe the use of financial sources available for SMME development by SMME owners are shown in Table 4. The table shows that all the available credit sources, trade credits, non-bank credits, the retained profits and savings and the grants are used to a little extent (mean < 3) except for the retained profits and savings where the female SMME owners are almost neutral in their opinions. The mean responses of the SMME owners to the first four factors are shown to be significantly (p < 0.05)

14 52 Okurut, F. N., Ama, N.O., Mookodi, L., Okurut, M.L.A. and Ama, H.A. different and the same for the grants factor. The responses are moderately skewed for four of the factors (skewness lies between -1 and - or - and +1) and also platykurtic. Table 4 Descriptive for extent of use of the finance sources for SMME development in Botswana and test of equality of mean (male and female) Mean Std. Deviation Skewness Kurtosis Sig. Male Female Male Female Male Female Male Female Credit sources Trade credits Non-bank credits The retained profits and savings The grants Functional/Performance characteristics of the financial institutions in Botswana Another issue that was studied was the SMMEs agreement on 20 descriptions about the functioning of financial institutions in Botswanaon a Likert scale 1 to 5: 1 for strongly disagree to 5 for strongly agree. An Exploratory Factor Analysis of the SMMEs opinions shows that the functioning and performance of the financial institutions can best be described using five constructs (factors), namely access to credit, bank technical advice, business planning, bank regulations, and bank interest rates and charges. The five factors explained 74.63% of the total variation in the variables which is relatively high. Both Kaiser-Meyer-Olkin Measure of Sampling Adequacy (0.867>0.7) and the Bartlett s test of sphericity (p < 0.05) indicate the adequacy of the EFA to explore the factors. Factor 1- The access to credit This factor was heavily loaded on the eight variables, existing credit was over withdrawn (0.88), existing credit was reduced (0.86), solutions offered do not meet my requirements (0.86), additional bank facility refused (0.85), frequent change of the contact person (0.074), excessive requirement with respect to financial information (0.72), lengthy process to obtain approval (0.70) and excessive requirement with respect to business information (0.70). The factor explained 28.32% of the variation in the variables. Factor 2- The bank technical advice The factor was heavy on the three variables, it would be of great help if my bank official assists in formulating the finance needs of my business (0.89), there should be a standard reporting format for the preparation of financial statements for SMMEs/Business plan (0.82) and the official at my bank should possess more relevant knowledge about our line of business (0.80). It explained 13.93% of the variation in all the variables.

15 Institutions and SMME Development in Botswana: Evidence from Exploratory Factor 3- The business planning The factor was heavy on the 3 variables, SMMEs need guidance on how to construct a wellpacked viable business plan (0.79), Banks do not provide helpful feedback/advice to SMMEs when a loan is declined (0.74) and Banks should advise more on alternative sources of finance (i.e. non-banking finance) rather than on solely banking products (0.70). It explained 11.43% of the variation. Factor 4- Bank Regulations The factor was heavy on the variables, SMMEs miss the flexibility and helpfulness in their bank s approach (0.80), Banks require more knowledge about small businesses and their specific conditions (0.78) and Banks have a perception problem with respect to SMMEs (0.65). It explained 10.9% of the variation. Factor 5-The Bank interest rates and charges The factor was heavy on the three variables, bank charges are too high (0.85), interest rates too high (0.76) and poor service (0.53). The factor explained 10.05% of the variation. The SMME owners (male and female) agree that the financial institutions can be best described by providing bank technical advice, business planning guide, bank regulations and bank interest rates and charges (mean greater than 3.5) (Table 5). There are no significant differences (p >0.05) in their opinions with respect to the business planning, bank regulations and interest rates and charges but significant differences exist with respect to the access to credit and the bank technical advice (p < 0.05). The distribution of the male responses are highly skewed for the bank technical advice and the bank interest rates and charges (skewness < -1) and moderately skewed for the rest (skewness between -1 and -0.5) as for the female. The values of the kurtosis show that the distribution is platykurtic (excess kurtosis < 0). Table 5 Descriptive for functional/performance characteristics of the financial institutions in Botswana and test of equality of means Mean Std. Deviation Skewness Kurtosis Sig. Factors Male Female Male Female Male Female Male Female The access to credit The bank technical advice The business planning Bank regulations The bank interest rates and charges 5.6. Measures to improve the general development of SMME in Botswana The SMMEs were asked to indicate to what extent they agree with the some identified measures/ recommendations that would improve the general development of SMMEs in Botswana on a scale 1 to 5: 1 for strongly disagree to 5 for strongly agree. The responses based on 12-item

16 54 Okurut, F. N., Ama, N.O., Mookodi, L., Okurut, M.L.A. and Ama, H.A. variables were subjected to exploratory factor analysis (EFA) and two factors that best describe the way forward, namely, infrastructure development and capacity building, and government institutional support were extracted. These two constructs explained 56.64% of the total variation in the variables. Both the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (0.874>0.7) and the Bartlett s test of sphericity (p < 0.05) indicate sufficient adequacy and goodness of the EFA for exploring factors that can enhance SMME development in Botswana. Factor 1-Infrastructure development and capacity building This factor was heavily loaded on the variables, improve the physical infrastructure-power, transportation, water and broadband internet (0.78), identify and implement policies that encourage youth to start businesses (0.74), form partnerships to facilitate the transfer of technology to the private sector such as with government and university collaborators (0.69), build programs providing mentorship by experienced SMME entrepreneurs (0.62), reduce bureaucracy associated with starting SMMEs (0.62), and introduce new funding models (0.60). This factor accounted for % of the variation. Factor 2: The government institutional factor This is heavily loaded on merging of existing Government agencies into fewer and more efficient support institutions (0.86), merged institutions to provide support to SMMEs all along the SMME development cycle (i.e. establishment, business planning, strategy, financing, marketing, marketing information, innovation, growth) (0.85) and the need for better hand-holding for budding entrepreneurs by merged institutions (0.76). The factor accounted for 26.09% of the variation. The test of the mean difference in the opinion of males and females show show significant differences (p < 0.05) to the issue of infrastructure development and capacity building but no significant difference in the opinions to the issue of Government institutional support (mean of approximately 4). The distribution of the male ratings for infrastructure development is highly skewed but moderate for the female. For the Government institutional support, it is moderately skewed for the male and female. The distribution of the ratings is platykurtic being less than three. Table 6 Descriptive for measures to improve the general development of SMME in Botswana and test of equality of means Mean Std. Deviation Skewness Kurtosis Sig. Male Female Male Female Male Female Male Female Infrastructure development and capacity building Government institutional support 5.7. Role of Government institutions in SMME development in Botswana In order to find out factors that enhance development of SMME development in Botswana the SMMEs were asked to indicate the extent to which they agree or disagree with the some 29

17 Institutions and SMME Development in Botswana: Evidence from Exploratory statements with regard to the development of SMMEs in your country using a Likert scale, 1= strongly disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = Agree and 5 = strongly agree. An exploratory factor analysis identified five constructs (factors), namely, SMME capacity building, Government support to SMMEs, Finance, SMME regulatory framework and SMME management. The five factors explained 61.4% of the total variation in the variables and both the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (0.927 >0.7) and the Bartlett s test of sphericity (p< 0.05), all point to the adequacy of the EFA for exploring factors that affect development of SMMEs in Botswana. Factor 1- SMME capacity building This factor is heavily loaded on five variables, namely, provide adequate training and development to their management and staff (0.83), help to create business incubators or technology parks for new companies where they can be based for first 1-2 years (0.79), publish more information for SMMEs (0.74), support innovative technological companies (0.74) and create common sharing facilities for SMMEs in the same or similar lines of business (0.55). The factor accounted for 13.91% of the variation. Factor 2- Government support to SMME This factor is loaded on Government policies to support SMMEs access to finance are clear and transparent and readily understandable (0.79), the procedures for starting up a new business are transparent and simple (0.75), Government provides funding to SMMEs for research and development, it assists them to develop new ideas and commercialize the products (0.66), the responsiveness of the government to the needs of SMMEs is high (0.65) and the support from local authorities to SMMEs is insufficient (0.51). The factor to and explains % of the variation in the variables. Factor 3-Finance The finance factor is loaded heavily on help to create the one-stop shop for SMMEs based on existing agencies for SMME support (0.69), facilitate access to financing (establish a special fund that serves as a reserve for loans to SMMEs) (0.67), decrease the number of taxes and simplify the tax system (0.66), simplify the registration of new businesses (0.63), the infrastructure supporting SMME development is poor (0.62), and there are policy inconsistencies and government bureaucracy (0.51). The factor explains 12.76% of the variations in the variables. Factor 4- SMME regulatory framework The SMME regulatory framework is heavy on Government provides adequate information on possible markets (0.69), Government encourages SMMEs to export their products(0.68), Government regulation/compliance costs are expensive for SMMEs (0.59), Government s policies are in favour of large enterprises (0.59), Government has put in place appropriate policies to ease access of SMMEs to technology (0.57), there is lack of coordination between organizations supporting SMMEs (0.54) and Government has a sound policy for providing training to SMMEs (0.51). The factor explains 12.12% of the variations.