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28
Jun
2014

THE IMPORTANCE OF MONITORING AND ENTREPRENEURSHIP CONCEPT AS FUTURE DIRECTION OF MICROFINANCE: Multiple Regression Analysis

THE IMPORTANCE OF MONITORING AND ENTREPRENEURSHIP CONCEPT AS FUTURE DIRECTION OF MICROFINANCE: Multiple Regression AnalysisThe results of multiple regression analysis showed that the independent variables – age, educational level, number of dependents and work experience did not show positive and significant coefficients. However, experience showed that the variable coefficient is positive and significant for the AIM program participants (t = 3.608, p <0.001). While TEKUN (t = -2.682, p <0.05) showed a significant negative coefficient. But the results of the tests on the overall samples (n = 395) and LZS program respondents show that the coefficient is negative and not significant. This situation explained that the longer the work experience acquired by the AIM program respondents the higher would be their ability acquired to generate business income. Instead, TEKUN participants’ shorter period of work experience enable them to enhance their ability to generate business income. It is clear that a long period of work experience for the TEKUN participants is not a prerequisite to their business success.

Test results on the variable “total income before” the participants’ involvement with the program showed positive and significant coefficient for the TEKUN participants (t = 2.590, p <0.05) and for overall participants (t = 5.552, p <0.001, n = 395). But for the participants of AIM and LZS it shows positive coefficients and insignificant. This situation explained that the higher the income of the participants before getting involved with the program, the higher would be their ability to generate business income. The results also confirmed that only participants who are relatively poor and vulnerable poor are able to generate higher profitability compared to the hardcore poor participants.
Regression test results for “business classification” in Table 8 show that the coefficient is positive and significant for the AIM program participants (t = 1.650, p <0.1) and for overall participant (t = 1.640, p <0.1). While the TEKUN and LZS programs show negative and insignificant coefficients. This proves that the classification of business also affects the ability of participants to generate profits. Results of multiple regression tests for ‘business’ period in Table 8 show that the coefficient is positive and highly significant for the AIM program participants (t = 3.246, p <0.001) and for overall participants (t = 2.934, p <0.05, n = 395). While TEKUN and LZS programs showed negative coefficients and are not significant. These results clearly prove that the longer is the business period for overall participants and AIM’s participants the higher would be their ability to generate higher business profits. Regression test results for the ‘initial capital’ also show that the coefficient is positive and significant for TEKUN participants (t = 2.511, p <0.05), LZS (t = 2.348, p <0.05) and for overall participants (t = 1.945, p <0.05, n = 395). While the AIM program shows a negative coefficient and is not significant. This means that the higher the amount of initial capital used the higher would be the ability of participants to generate higher business profits.
Multiple regression test results for “initial capital source” show that program members of TEKUN (t = -1.612, p<0.1), LZS (t = -4.633, p<0.001) and for overall participants (t = -1.602, p<0.1) have negative coefficient values but are significant, while that of AIM has a positive coefficient value and is not significant. Current study test results explain the fact that the higher the initial capital sources, either from own savings or from family members, to start a microenterprise the higher would be the ability of program members to generate higher business. These results prove that the program members should not be fully dependent on the micro funds to start their microenterprises. Multiple regression test results on “frequency of monitoring” show for overall (t = 3.579, p<0.001, n=395) a positive coefficient value and is very significant. However, similar test results for TEKUN and LZS show positive coefficient values but are not significant. Understandably, multiple regression tests cannot be carried out for AIM program due to the existence of constant values attached to the frequency of monitoring. This is purely because of the weekly scheduled meetings strictly imposed on all AIM program members. These test results prove that, on average, frequency of monitoring has a very strong impact on the effectiveness of micro funds to generate higher business income and profits for the program members.

Table 8: Summary of Multiple Regression Analysis

Independent Variables TEKUN(N=134) AIM(N=180) LZS(N=49) YBK(N=32) Oveall(N=395)
Age 0.629(0.484) 0.855(-0.183) 0.724(-0.356) # 0.822(-0.225)
Educational Level 0.335(-0.968) 0.609(-0.513) 0.935(0.083) # 0.541(0.612)
Number. of Dependents 0.765(-0.299) 0.748(-0.322) 0.664(0.438) # 0.154(-1.428)
Type of Work Experience 0.404(0.838) 0.767(0.297) 0.139(1.506) # 0.530(0.628)
Period of Work Experience 0.008(-2.682)*** 0.0001(3.608)*** 0.526(0.640) # 0.806(-0.246)
Total Previous Income 0.011(2.590)** 0.398(0.847) 0.138(1.510) # 0.0001(5.552)***
Business Classification 0.417(-0.814) 0.099(1.650)* 0.996(-0.005) # 0.099(1.640)*
Need for Microcredit Funding 0.177(1.357) 0.153(1.436) 0.906(-0.119) # 0.005(2.812)***
Age of Business 0.476(-0.715) 0.001(3.246)*** 0.553(0.598) # 0.004(2.934)***
Total Initial Capital 0.013(2.511)** 0.869(-0.165) 0.023(2.348)** # 0.048(1.985)**
Source of Capital 0.098(-1.612)* 0.139(1.487) 0.0001(-4.633)*** # 0.099(-1.602)*
Total Microcredit Received 0.099(1.663)* 0.0001(3.937)*** 0.152(1.460) # 0.046(2.002)**
Frequency of Microcredit Received 0.827(0.219) 0.675(-0.420) 0.727(-0.351) # 0.277(1.089)
Type of Training 0.902(-0.123) 0.549(0.601) 0.416(0.820) # 0.111(-1.596)
Frequency of Monitoring 0.962(0.048) t.b 0.475(0.720) # 0.0001(3.579)***
Type of Monitoring 0.528(0.632) t.b 0.052(-1.996)* # 0.921(0.099)
Business Location 0.889 0.101 0.263 # 0.495
(0.140) (-1.647) (1.133) (-0.683)
R2 0.132 0.176 0.330 # 0.238
R2 Adjusted 0.112 0.162 0.300 # 0.226
F-Statistics 6.460 12.524 11.090 # 20.024

The results of multiple regression analysis showed that the independent variables – age, educational level, number of dependents and work experience did not show positive and significant coefficients. However, experience showed that the variable coefficient is positive and significant for the AIM program participants (t = 3.608, p <0.001). While TEKUN (t = -2.682, p <0.05) showed a significant negative coefficient. But the results of the tests on the overall samples (n = 395) and LZS program respondents show that the coefficient is negative and not significant. This situation explained that the longer the work experience acquired by the AIM program respondents the higher would be their ability acquired to generate business income. Instead, TEKUN participants’ shorter period of work

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Kevin J. Brandon

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