Journal of Social and Economic Policy, Vol. 12, No. 2, December 2015, pp. 65-76 FACTORS INFLUENCING MICRO AND SMALL ENTERPRISES ACCESS TO FINANCE IN BOTSWANA MALEFHO K * AND MOFFAT B ** Abstract: This study determines factors that influence Micro and Small Enterprises (MSEs) access finance in Botswana. The study involved a survey of MSEs in the manufacturing sector. Structured questionnaires were randomly administered to MSEs and a total of forty seven responses were obtained from the industrial areas. The study used the Binary Logistic model with the loan outcome as the dependent variable and the independent variables included period of operation, size of the firm, financial performance and level of formality. The best model selected was based on the Omnibus Tests of model coefficients, the Chi-Square tests, the Cox and Snell R-Square and the Nagelkerke R-Square values. The importance of each factor was determined using the Wald statistic value. The results indicated that the level of formality and financial performance were important factors in influencing access to finance. There is a need for micro finance packages that would be tailor made towards the informal sector. Keywords: Micro and Small Enterprises, Finance, Botswana INTRODUCTION Finance is important in an economy as it contributes to economic growth, poverty reduction and employment creation. It is, therefore, important to design policies that can make its contribution a reality especially for the Micro and Small Enterprises (MSEs) sector. MSEs are considered the forefront engines of economic development and growth as they are the major sources of employment and wealth creation in most economies around the world (Moaisi, 2005). For instance, Nasr (2010) found that, in Egypt, the small scale sector made up about 99% of private enterprises, accounted for 85% of non-agriculture private sector employment and almost 40% of total employment. In Botswana, the MSEs play a crucial role in the economy in terms of generating employment. According to the 2005/06 Labour Force Survey (LFS) the total number of informal sector workers was 156,515 which accounted for about twenty percent of the labour force (CSO, 2007). Even though the small scale sector is an important source of employment in the country, access to finance is identified by researchers such as (Okurut, Olalekan, & Mangadi, 2011) and (Mwobobia, 2012) constraining the growth and development of this sector. One of the constraints in accessing finance from formal financial institutions is their lending policies displayed in the form of prescribed minimum loan amounts, complicated application procedures and restrictions on credit for specific purposes (Atieno, 2001). In Botswana, (Okurut & Ama, 2013) found out that the eligibility criteria * Department of Economics, University of Botswana, Gaborone, Botswana ** Department of Economics, University of Botswana, Private Bag UB 705, Gaborone, Botswana, E-mail: boitumelo.moffat@mopipi.ub.bw
66 MALEFHO K. AND MOFFAT B. to access government credit is no different from that used by formal commercial banks which focuses on assessment of business plans, historical financial statements and collateral. Compared to large firms, micro and small firms are often not able to access finance in financial institutions as they are deemed risky and likely to default on their payments. Globally MSE s credit limitations in access to formal finance has been mainly attributed to the high administrative costs of small scale lending, asymmetric information, the high risk attributed to their lack of collateral and inadequate capacity to prepare business plans and local applications. These reasons tend to be more significant in developing countries where institutions underpinning credit markets are often less developed (Nasr, 2010). The type of institution and its policy often determine the access problem to financial services by MSEs (Schmidt & Kropp, 1987). Therefore, the views presented by researchers in explaining access to finance motivated the present study to establish factors that have major impact in influencing MSE s to access finance in Botswana. The Government of Botswana has had extensive microfinance packages since 1982 and the private sector has also joined the government in providing financial assistance to the small scale sector but its impact on the growth of small scale business are yet to be seen. Mwobobia (2012) stated that lack of access to finance is identified by many authors as the most significant barrier for the start-up and growth of MSEs in Botswana. Therefore, there is a need for an explanatory study in order to establish factors that influence micro and small enterprises to access finance in Botswana as there is extensive microfinance packages which looks like they are not reaching the target population. This study intends to determine those factors that influence MSEs accessing finance in a country that is under pressure and for a long time has been trying to achieve the goals of economic diversification, employment creation, poverty reduction and an inclusive growth. The study aims to determine factors that influence MSE s access to finance from formal financial institutions in Botswana. EMPIRACLE ISSUES ON ACCESS TO FINANCE BY MSES Empirical findings from past studies suggest that there are certain factors that influence access to finance by firms. These include formality of the business, size of the firm, firm profile, business sector in which the firm operate, asset base, performance of the firm as well as the ownership structure of the firm. There is no consensus in empirical literature on which factors are the most important in influencing access to finance by enterprises especially the small scale enterprises. Musamali and Tarus (2013) are of the view that extant literature associate firm profile to the ability of firms to access finance while Mabhungu et al. (2011) realized that some authors are in consensus that firm size matters when it comes to access credit from formal financial institutions, that is large firms have an advantage in accessing credit from banks than small-scale firms because MSEs are considered to have high financial risk. Mabhungu et al. (2011) in their explanatory study of factors influencing micro and small enterprises access to finance since the adoption of multi-currency system in Zimbabwe, employed a Generalized Linear Modelling using Binary Logistic Model to assess if formality of business, type of business sector, length of period of business operation, assets owned, size of the enterprise as measured by number of employees,
FACTORS INFLUENCING MICRO AND SMALL ENTERPRISES ACCESS TO FINANCE IN BOTSWANA 67 and the business financial performance measured in terms of number of losses made in the last five years influences MSE s access to finance. The results indicated that all the factors were important in influencing MSE s access to finance but firms level of formality and the value of assets owned by the firm were found out to be the most important factors in influencing MSE s access to finance in Zimbabwe after the adoption of the multi-currency system. Furthermore they stated that collateral poses an obstacle for the MSE s because many banks only accept very limited types of tangible fixed assets such as buildings or lease of land as collateral and these factors influence access of MSE s to bank credit. Mukiri (2008), using a total of 218 small scale manufacturing enterprises that had been in business for an average of 6.72 years set out to examine the effects of entrepreneurial orientation on access to bank credit by MSEs in Kenya. The study found out that entrepreneurial orientation is a direct determinant of access to credit by MSEs and that knowledge based resources are associated with greater levels of entrepreneurial orientation, knowledge based resources influences access to bank credit indirectly. An important finding of the study is that entrepreneurial orientation is related to bank credit in small scale manufacturing enterprises in Kenya. Even though empirical literature that shows that there is a positive relationship between firm size and bank financing, Musamali and Tarus (2013) embarked on a study to find out if firm profile influences financial access among small and medium enterprises in Kenya using multiple regression analysis. They found out that risk exposed sectors may not access as much finance as compared to other less risky sectors while less profitable sectors may be disadvantaged in accessing finance. In their study a major conclusion was that firm specific characteristics affect the ability of firms to access finance. On the other hand Bigsten et al. 2009 found out that large firms are more likely to receive loans and have better access to credit than small firms. Atieno (2009) stated that linkages between the enterprises and financial institutions enable firms to access financial services. Furthermore she found out that membership to association network appears to be important in facilitating access to financial services. Atieno (2001) carried out an empirical assessment to investigated the role of the institutional lending policies of formal and informal credit institutions in determining the access to and use of credit facilities by small scale entrepreneurs in rural Kenya and an important finding was that access to finance depends on the business sector in which the MSEs operates, its level of formality, its asset base, its performance and also its ownership structure. The study used descriptive and analytical methods. Okurut and Ama (2013) assessed factors that affect women and youth microentrepreneurs in Botswana came up with the conclusion that CEDA and formal banks are not well suited to meet the credit needs of micro enterprises because they rely heavily in the traditional banking models when assessing a potential borrower. The traditional banking models for access to external finance includes use of collateral for loans, historical financial statements and projected cash flow statements. The use of traditional banking model according to literature poses an obstacle for MSE s as emphasis is based on collateral which most of the small scale enterprises do not have. Rather than banks focussing attention on evaluating income streams flowing from an
68 MALEFHO K. AND MOFFAT B. investment, the banks pays too much attention on the value of collateral available therefore business with collateral that has high value will be able to access finance than those who do not have. METHODOLOGY This section outlines the methods and tools employed in determining factors influencing access to finance by MSEs in Botswana. The study was explorative in nature as it used survey method in data collection. Primary data was collected in order to make sure that all the relevant information needed for the study were obtained. Target population Given the presence of nation-wide MSEs in different sectors of the economy in Botswana, the study targeted MSEs that are in the manufacturing sector while operating in Gaborone and areas that are close by. All the manufacturing industries were included in the study. The manufacturing sector was chosen on the basis of the following reasons; Manufacturing is a key driver for the rapid long-term sustainable economic growth Manufacturing success has been the path for economic growth for developed countries Micro and Small manufacturing enterprises are linked to employment creation, poverty reduction and diversification of economic activities that add value. Lastly for the past two decades in Botswana the emphasis on economic diversification has been on developing the manufacturing sector but the sector remains at an infancy stage, as compared to other sectors it contributes less to the local economy. Sampling Frame and Sampling Technique The sampling frame for the study included all the manufacturing MSEs in Gaborone and near-by areas while the sampling size was fifty. The sampling size represented MSEs that access finance from formal financial institutions. Formal financial institutions where chosen in order to determine factors that influence access to finance in this institutions because they are considered to be the main sources of finance. Simple random sampling technique was used in the study. The technique is defined as a probability sampling method which draws a portion of the population so that each member of the population has an equal chance of being selected. Random sampling was used because of the fact that a sample drawn at random is unbiased in the sense that no member of the population has any more chance of being selected than any other member. Model specification The general Binary Logistic Model was used to assess factors that influence MSE s access to finance. It is a multiple regression model where the loan outcome is made the
FACTORS INFLUENCING MICRO AND SMALL ENTERPRISES ACCESS TO FINANCE IN BOTSWANA 69 dependent variable. The independent variables are; period of operation, size of the firm, financial performance and level of formality. The statistical model is adopted from Mabhungu et al. (2011). Since the Logit and Probit model almost give similar results, in this case the Logit model was used because of its comparative mathematical simplicity. The specification of the model was as follows: Where: is chances of accessing a loan. 1- is chances of not accessing a loan. a is a constant s is an estimates from the regression X s are the explanatory variables where X 1= Period of operation X 2= Size X 3 =Financial Performance X 4= level of Formality. Log e ( /1- ) = a + 1 X 1 + 2 X 2 + 3 X 3 + 4 X 4 As the dependent variable is the loan outcome, it is a binary logistic which takes the value of 1 when the outcome was successful and the value 0 if the outcome was unsuccessful. Measurement of explanatory variables Period of Operation: this is measured by the number of years that the firm has been in operation since its inception. Abor and Biekpe (2009) suggest that a firm which has operated for long has reputation that it has established over the years and it is understood by the financial markets. As this is measured by the number of years that the firm has been operating, we expect firm that has been operating for a long time to have better access to finance than start-up firms. Extent literature associate firm profile to the ability of a firm to access finance (Musamali and Tarus, 2013). Size of MSE: this is measured by the number of employees that the firm has. The firms were classified on the basis of being micro and small. Literature associates firm size with better access to credit. Bigsten et al. (2009) stated that large firms are more likely to receive loans and have better access to credit than small firms while Mukiri (2008) found out that there is a positive relationship between firm size and banking finance. Financial Performance: this is measured by number of profits that the firm has made in the last five years. Cull and Xu (2005) found out that Chinese banks tend to allocate funds to firms that have better performance outcomes as identified in a review of a firm s accounting statements.
70 MALEFHO K. AND MOFFAT B. Level of formality: this considers form of business ownership, registration with tax authorities, registration for Value Added Tax (VAT), number of employees with written employment contract, separation of business from personal finance and form of financial records kept. This is coded as a dummy variable (1= meeting all the above requirements and 0=not meeting all the above variables). Therefore, firms that meet the criteria of being formal enterprises are expected to have better access to finance. Data sources Data on manufacturing enterprises was obtained from Botswana Exporters and Manufacturers Association (BEMA) membership list. Number of total manufacturing enterprises operating in Botswana was collected from Statistics Botswana. The survey s main sample was focused on the demand, meaning that the borrowers being the MSE s while the lenders being the financial institutions were consulted in order to learn about the criteria that they use when financing small scale enterprises. Evaluation techniques Data was entered and analyzed using SPSS version 22. The importance of each factor was adopted onto the model on the basis of its Wald statistic value, the factors that had high Wald statistic values were more important than others in determining influence to finance. An omnibus test of model coefficients was used to test the significance of steps generated from the backwald Wald procedure. The Nagelkerke R- square was used to measure the explanatory power of the model. The P-value was used to determine the significance of the stated variables. RESULTS A descriptive survey method using structured questionnaires was used in this study. A total of fifty questionnaires were hand delivered to the respondents and forty seven were completed. The location distribution of the sampled MSEs from which questionnaires were collected from is presented in table below. Business Location Table 1 Sample Participants by Location Number of Enterprises Interviewed Gaborone Industrial Areas 30 Mogoditshane Industrial 10 Tlokweng Industrial 4 Phakalane Industrial 3 Source: field survey results As it can be seen from the above table, most of the manufacturing MSEs are concentrated in Gaborone since it is the capital city and the economic hub of the country. Out of forty seven participants in the study, forty one indicated that they were successful while six were unsuccessful in obtaining a loan. Loan outcome form the survey is presented in the table below.
FACTORS INFLUENCING MICRO AND SMALL ENTERPRISES ACCESS TO FINANCE IN BOTSWANA 71 Table 2 Loan Outcome Outcome Frequency Percent Valid Percent Cumulative Percent Successful 41 87.2 87.2 87.2 Unsuccessful 6 12.8 12.8 100.0 Total 47 100.0 100.0 Source: field survey Model selection Backward stepwise model procedure was used to select the best model. From the backward stepwise logistic regression, four steps were generated with different predictor variables. After the appropriate step was chosen on the basis of Omnibus tests of model coefficients (Table 3), which tests the significance of the steps that are generated by the backward Wald procedure, the Cox and Snell R-Square and the Nagelkerke R- Square values (Table 4), measures overall fitness of the model in logistic regression. Based on the statistics obtained, the best model selected was step one which had all the predictor variables. Step one had a chi-square of 8.439 and a p-value of 0.077 which was significant at 10% level of significance, other steps had negative chi-squares which were negative implying that the chi-square s value has decreased from the previous step. Step four was significant at 10% but had a negative chi-square therefore the step was not chosen as the best model. From table 2 below, step one had a Nagelkerke R- Square of 0.308. The rest of other steps had the Nagelkerke R-Square which was lower than that of step one. Step 1 The tables are presented below; Table 3 Omnibus Tests of Model Coefficients for the Logistic Regression Chi-Square df Sig. Step 8.439 4 0.077 Block 8.439 4 0.077 Model 8.439 4 0.077 Step 2 Step -0.977 1 0.323 Block 7.462 3 0.059 Model 7.462 3 0.059 Step 3 Step -1.396 1 0.237 Block 6.066 2 0.048 Model 6.066 2 0.048 Step 4 Step -2.527 1 0.112 Block 3.540 1 0.060 Model 3.540 1 0.060
72 MALEFHO K. AND MOFFAT B. Table 4 Summary Binary Logistic Model Step -2 Log likelihood Cox & Snell R Square Nagelkerke R Square 1 27.461 a.164.308 2 28.438 a.147.275 3 29.834 a.121.227 4 32.360 b.073.136 The estimate of the constant was -1.922 with a standard error of 0.437 (Table 5). If all the predictor variables are equal to zero, the predicted log odds in favour of access to loan would be -1.922 implying that the chances of accessing a loan are reduced by a multiplicative factor of -1.922. The constant had a p-value of 0.000 which is significant at 1% level. Table 5 Constant Estimate of the Logistic Regression B S.E. Wald df Sig. Exp(B) Step 0 Constant -1.922.437 19.331 1.000.146 Discussion of the statistical results Statistical results are reported in table 6 below; Table 6 Statistical Results B S.E. Wald df Sig. Exp(B) Losses 1.552 1.024 2.295 1.130 4.719 Firm size -1.742 1.198 2.115 1.146.175 FORMALITY_LEVEL 1.631 1.027 2.521 1.112 5.107 Period 1.147 1.206.905 1.342 3.149 Constant -3.845 2.367 2.639 1.104.021 Period of operation: this variable was measured by number of years that the firm has been operating. With regard to this variable, the result from the regression shows that it has no influence to firm s ability to access finance. The variable was insignificant at all level of significance even when the significance is rounded to one decimal place. Therefore we reject the hypothesis that period of operation has a positive influence on MSE s access to finance. Size of MSE: from the regression results, size of the firm is statistically insignificant at any level of significance. With these results we reject the hypothesis that firm size has a positive influence of access to finance. Financial Performance: with regard to financial performance which was measured by number of profits in the last five years, the variable was significant at 10% level of significance. This shows that it has a positive influence on access to finance by MSEs.
FACTORS INFLUENCING MICRO AND SMALL ENTERPRISES ACCESS TO FINANCE IN BOTSWANA 73 Level of Formality: this variable was the most significant than others from the regression results as it was significant at 10 %. From the results we accept the hypothesis that level of formality has a positive influence in access to finance. Importance of Variables Formality of the business had the highest Wald Statistic of 2.521 and a p-value of 0.112 which is significant at 10% level, this implied it was the most important factor in determining loan outcome in MSEs. The second most important factor in determining access to finance by the small scale sector was the financial performance as it had the Wald Statistic of 2.295 and a p-value of 0.130 also significant at 10% level. Firm size was the third ranked with a Wald Statistic of 2.115 and was insignificant (p-value of 0.146) and lastly to be ranked was the period of operation which had a Wald Statistic of 0.905 and an insignificant p-value of 0.342. The results indicates that only two factors investigated had to some extent an important influence on the ability of small scale enterprises to access finance in Botswana, the factors can be deemed as the most important variables in ability to access a loan from a financial institution as they had higher Wald statistic than others and were significant. Formality level of the firm had the most influence in enabling firms to be successful in getting a loan which indicates that formal enterprises were much more likely to get loans than their counterparts which are informal. The same result about the importance of level of formality in influencing access to finance by MSEs were obtained by Mabhungu et al. (2011) in their study in Zimbabwe. Informal enterprises are deemed risky as there are difficult to trace when they default on their loans or do not pay at all the money that they have borrowed. The other important factor in influencing access to finance according to the result is the financial performance of the enterprises. These results are consistent with Atieno (2001) who concluded that profitability of MSEs was an important factor in accessing finance. Providers of finance usually look at the past and projected financial statements to determine the profitability of the enterprise before granting the firm a loan. Therefore these results show that financial institutions were interested in lending to firm that were profitable than loss making firms. Third ranked was the firm size which was measured by the number of people employed by the enterprise. Even though it was not significant it had some importance in influencing access to finance as it is shown by its Wald statistic. The results are in contrast to Bigsten et al. (2009) and Gebru (2009) as they had stated that compared to large firms, small firms are at a disadvantage in accessing finance form financial institution as they are deemed to have higher financial risk. This implies that large firms are more highly likely to access finance than MSEs which are small in size. Therefore compared to micro enterprises, small enterprises are more likely to access finance because of their size. The least ranked factor in terms of the Wald statistic was the period of operation and its results were highly insignificant which showed that it did not have much importance in influencing access to finance. The results contradict that of Abor and Biekpe (2009) who suggested that a firm that has operated for a long period of time is
74 MALEFHO K. AND MOFFAT B. likely to get finance as a result of the reputation that it has managed to build for itself during the past periods. The results are also in contrast to Musamali and Tarus (2013) whom stated that extant literature associate firm profile to the ability to access finance. Firm profile is built during the period of existence and start-up firms do not have the profile which it can use to access finance, therefore period of operation is important in building the profile to take advantage of in getting a loan from financial institutions. RECOMMENDATIONS AND CONCLUSION On the basis of the results from this study, some recommendations can be made in order to improve access to finance by MSEs so that they can be able to fully develop and their contribution in the economy to be realized. A policy on micro financing of informal firms can be formulated in order to better able informal enterprises to access finance in any financial institutions in Botswana. Since informal enterprises had much stake on the 2005/06 Labour Force Survey with a contribution of about 20% of the labour force, the policy makers must formulate policies that are geared towards the informal sector as the sector has major impact in the economy proved by its past contribution to the employment. The study indicates that level of formality and financial performance are the most important factor in influencing access to finance, while the 2005/06 Labour Force Survey indicated that informal sector workers accounted for twenty percent of the labour force. This therefore calls for a need to increase efforts to educating potential and existing entrepreneurs about the changing business environment and on how to create formal business enterprises for them to be better able to access finance. It is argued that education is an important factor that contributes to the success of MSEs because the educated entrepreneur is better able to respond to changing business environment. Government and Non-government organizations should step up efforts in educating the business community especially the small scale sector on the importance and benefits of running a formal and profitable business enterprise. This would eliminate the prevalence of many informal enterprises that are not able to survive and sustain themselves due to lack of finance. Since the government has intensified its effort in addressing problems faced by MSEs as it has realized the potential that the sector had, it is important that it continues to make policies that will enable private financiers to better able to help the government in financing the sector. The role of government in fostering a conducive policy environment for microfinance is critical to the sustainable growth of the industry as the government policy is important in supporting the sustainable development of microfinance. The government should continue to engage the private sector in discussing on how to better finance the sector in order to encourage the start-up and growth of this sector. This will help the survival of MSEs and in the development or emergence of new specialized institutions and delivery channels. Microfinance institutions need to emerge so that they can serve or take advantage of the micro and small market niches. As the Local Enterprise Authority is crucial in supporting the MSEs access to finance, it is important for the authority to continue in supporting the sector in accessing finance by equipping the entrepreneurs with current trends of international markets
FACTORS INFLUENCING MICRO AND SMALL ENTERPRISES ACCESS TO FINANCE IN BOTSWANA 75 so that the enterprises can be competent in the global markets and also able to sustain themselves. The Authority should continually carry researches especially on issues of financing MSEs so that they are updated with the changing financing environment. The Authorities need to reach out to the ordinary men on the streets who are running informal enterprises and equip them on how to run formal enterprises that can be able to access finance. Programs that are developed should be more accommodative to the less educated so that people can better relate with them. A further research is needed to supplement this study in determining factors that influence access to finance. This study had limitations and its sample size and timeframe were relatively small, therefore a study that has a large sampling size and framework need to be carried out in order to confirm the conclusions of this study. For instance, a study that includes all sectors of the economy need to be carried out so that factors that are more relevant or important are determined. Since it has been found out that financial providers in Botswana are using the traditional banking model which emphasis more on collateral when accessing MSEs that needs finance and this study did not include the variable of assets, a further study is needed to confirm if the traditional banking model case is true or not. References Abor, J., & Biekpe, N. (2009), How do we explain the capital structure of SMEs in Sub Saharan Africa. Journal of Economic Studies, Vol. 36 No. 1 pp 83-97. Atieno, R. (2001), Formal and Informal Institutions Lending Policies and Access to Credit by Small-Scale Enterprises in Kenya: An Empirical Assessment. Nairobi: African Economic Research Consortium. Atieno, R. (2009), Linkages, Access to Finance and Perfomance of Small-scal Eterprises in Kenya. World Institute for Development Economics Research, Research paper No. 2009/06, 1810-2611. CSO. (2007), Informal Sector Survey Report 2005/06. Gaborone. Cull, R., & Xu, L. (2005), Institutions, ownership and finance: the determinants of profit reinvestment among chinese firms. Journal Financial Economics 77, 117-46. Gebru, G. H. (2009), Financing preferences of Micro and Small Enterprises Owners in Tigray: Does POH hold? Journal of Small Business Enterprises and Development, Vol. 16 Iss 2 pp. 322-334. Mabhungu, I., Masamha, B., Mhazo, S., Jaravaza, D., & Chiriseri, L. (2011), Factors ifluencing micro and small enterprises access to finance since the adoption of multi-currency system in Zimbabwe. Journal of Business Management and Economics, Vol. 2(6) pp. 2141-7482. Moaisi, D. (2005), Facctors Affecting the Growth of Micro and Small Manufacturing Enterprises in Botswana. Capetown: Stellenbosch University. Mukiri, W. G. (2008), Determinants of Access to Bank Credit by Micro and Small Enterprises in Kenya. Musamali, M. M., & Tarus, D. K. (2013), Does Firm Profile Influence financial Access Among Small and Medium Enterprises in Kenya. Asian Economic and Financial Review, 3(6): 714-723.
76 MALEFHO K. AND MOFFAT B. Mwobobia, F. M. (2012), Empowering of small-micro and Medium Enterprises (SMMEs): a case of Botswana. Business and Management Research, Vol 1, No. 4: 1927-601. Nasr, S. (2010), Enhancing Access to Finance for Micro and Small Enterprises in Egypt. 10th Global Conference on Business and Economics. Rome. Okurut, F. N., & Ama, N. O. (2013), Assessing Factors That Affect Women and Youth Microentrepreneurs in Botswana. International Journal of Academic Research in Economics and Management Studies, Vol. 2, No. 1, ISSN: 2226-3624. Okurut, F. N., Olalekan, Y., & Mangadi, K. (2011), Credit Rationing and SME Development in Botswana: Implications for Economic Diversification. Botswana Journal of Economics. Schmidt, R. H., & Kropp, E. (1987), Rural Finance Guiding principles. Eschborn: GTZ.