5.5 P RESENTATION AND ANALYSIS OF RESULTS ACCORDING TO THE O BJECTIVES OF THIS STUDY
5.5.2 Objective 1: To examine the challenges faced by SMEs in Zimbabwe
5.5.2.7 Regression Model on the predictability of limited access to finance
This section shows a regression model for the predictability of limited access to finance by making reference to a set of finance related variables that were set up in the study. A standard multiple regression was done in which each independent variable was evaluated in terms of its predictive power, over and above that offered by all the other independent variables (Pallant, 2007: 147). On the model summary footnote (a) shows the predictors or the independent variables that were used on the model and footnote (b) shows that the dependent variable is limited access to finance. Shown in Table 5.13 and Table 5.14 are the model summary and the Analysis of Variance (ANOVA) respectively:
Table 5. 13 Regression Model for limited access to finance
b. Dependent Variable: LIMITED ACCESS TO FINANCE
Model R R Square Adjusted R Square Std. Error of the Estimate
1 0.634a 0.402 0.302 0.74567
a. Predictors: (Constant), USE OF SEDCO SERVICES, BANK LOANS, START-UP CAPITAL, BOOK- KEEPING SKILLS, LACK OF A TRACK RECORD, DEBIT AND CREDIT CONTROL, TAX CALCULATIONS, SEDCO, FINANCIAL STATEMENT PREPARATION, ECONOMIC UNCERTAINTIES, BUSINESS LOSSES, BUDGETING SKILLS, COLLATERAL REQUIREMENTS
154 Table 5. 14 ANOVA
Model Sum of Squares df Mean Square F Sig.
1 Regression 29.124 13 2.240 4.029 .000b
Residual 43.370 78 0.556
Total 72.494 91
The Regression results in Table 5.13 show a statistically significant model of the predictability of limited access to finance based on financial skills and application for financial assistance, (F = 4.029, p < .05, and R Square is .402. Since Sig. (.000) is less than .05 the model is statistically significant. This implies that the independent variables in the model can predict the limited accessibility of finance for SMEs. Multiplying the R Square value (0.402) by 100 shows that the model explains 40.2 percent of the variance in limited access to finance. The Tolerance and Variance Inflation Factor (VIF) show whether or not the variables in the model have violated assumptions for a regression model. A Tolerance level of more than 1 and a VIF value of 10 indicates multicollinearity which is a violation of the regression assumption (Pallant, 2007:156).
The table shows that Tolerance for every predictor is less than 1 and the VIF level is less than 10, therefore there are no violations of the assumptions.
Table 5. 15 Predictors of the Regression model
Model Beta Sig. Tolerance VIF
Start-up -0.075 .420 0.889 1.125
SEDCO -0.001 .990 0.767 1.303
Bank Loans -0.222 .016 0.938 1.066
Lack of Track Record 0.233 .044 0.593 1.685
Collateral -0.075 .577 0.430 2.327
Business Losses -0.081 .468 0.618 1.618
Economic Uncertainties -0.170 .112 0.684 1.462
Debit and Credit Control 0.248 .022 0.683 1.463
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The statistically significant predictors of limited access to finance for this model include SMEs which consider financial statement preparation to be an important financial management skill, (β
= 0.304, p = .004). Financial statement preparation makes the strongest unique contribution to explaining the dependant variable (β = 0.304), when the variance explained by all other variables in the model is explained for. This shows that SMEs financial statement preparation is able to statistically predict limited access to finance. In this regard, it is important for small businesses to be endowed with financial statement preparation skills as this is will ensure that the business is less likely to face the challenge of limited access to finance. An increase in a small business’
financial statement preparation skills will increase their likelihood of accessing finance.
Debit and Credit control is the second highest statistically significant predictor, (β = 0.248, p = .004) of limited access to finance. Debit and credit control skills, in this model, are able to predict the limited access to finance. In this light it is important for SMEs to be skilled in debit and credit control as this will influence whether or not they have a challenge of the inaccessibility of finance. Small businesses with debit and credit control skills are less likely to have limited access to finance as a challenge. Thus an increase in debit and credit control skills will increase an SME’s likelihood of gaining access to finance.
The lack of a track record is a statistically significant predictor, (β = 0.233, p = .044) of the limited access to finance for SMEs. This shows that an SME’s decision to apply for a bank loan based on proving its track record has a statistically significant influence on whether or not it views limited access to finance as a challenge. This finding dovetails with that of the National Policy and Strategy for SMEs in Zimbabwe (2002:9) which noted the lack of a track record to be
Financial Statement Preparation 0.304 .004 0.721 1.387
Budgeting Skills 0.090 .444 0.566 1.768
Book-keeping Skills -0.067 .579 0.529 1.890
Tax Calculations -0.122 .191 0.899 1.112
Use of SEDCO services 0.115 .237 0.831 1.204
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one of the biggest challenges contributing to the limited access of finance among SMEs. In this light therefore, an SME with a proven and credible track record is more likely to have access to finance
Bank loan applications are also statistically significant predictors (β = -0.222, p = .016) of the limited access to finance. This implies that an SME’s decision whether to apply for a bank loan or not statistically predicts that SME’s access to finance. The results of this study in section 5.5.2.6 showed that there is a statistically significant correlation between the cost of finance and the limited access to finance. Bank loan applications have requirements such as providing a track record and collateral requirements which constitute the cost of finance. The predictability of limited access to finance by bank loan application shows that the easing up of loan application processes will improve the accessibility of finance to small businesses. This is so because an increase in bank loan application will lead to a resultant decrease in the limited access to finance The regression model also shows that financial management skills (financial statement preparation skills, debit and credit control), requirements for loan application and bank loan application are important predictors of limited access to finance. Small businesses with adequate financial management skills will be better positioned to overcome the challenge of limited access to finance. Similarly, it is important for small businesses to have the requirements for bank loan application as this will have an impact on the ease of access to finance. SMEs with requirements for bank loan application are less likely to have problems with accessing finance. Small businesses that apply for bank loans are less likely to report the limited access to finance as a challenge. In this light it is important for SMEs to apply for bank loans as this mitigates the inaccessibility of finance.
5.5.3 Objective 2: To analyse the extent to which the Policy and Strategy Framework for