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Social Impact Assessment of Microfinance Programmes - weman

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Table – 7.9<br />

UPAP – Children’s Education<br />

Variables Category Mean Standard<br />

Deviation<br />

t-<br />

value<br />

Significance<br />

Level<br />

School Going Children % Active Borrowers 90.3040 19.46766 -.758 .449<br />

New and Non-<br />

Borrowers<br />

91.7132 17.43449<br />

School Going Children - Boys Active Borrowers<br />

%<br />

82.8616 31.74271 .068 .946<br />

New and Non-<br />

Borrowers<br />

82.6027 34.52412<br />

School Going Children - Girls Active Borrowers<br />

%<br />

76.4683 38.97037 -2.027 .043<br />

New and Non-<br />

Borrowers<br />

84.7039 33.07633<br />

Children going to Private Active Borrowers<br />

School %<br />

43.2434 45.20299 1.249 .212<br />

New and Non-<br />

Borrowers<br />

37.8462 45.66167<br />

Monthly Expenditure on Active Borrowers<br />

Education<br />

506.0400 617.97444 1.442 .150<br />

New and Non-<br />

Borrowers<br />

427.2304 525.06299<br />

Note: There are 315 and 363 respondents in each category respectively. t-value greater than<br />

1.6 indicates the mean difference between two categories is statistically significant. The<br />

negative t indicates that average value <strong>of</strong> category 2 is greater than the average value <strong>of</strong><br />

category 1.<br />

In t case <strong>of</strong> Household Assets Ownership, we find no significant difference between<br />

Active Borrowers and the other two categories, except that more Active Borrowers have<br />

savings in Gold – Table 7.10. The differences between the two categories in terms <strong>of</strong><br />

Business Assets is also not significant, except that we again find the surprising result that<br />

Active Borrowers have lower Business Assets than do New and Non-Borrowers, and that<br />

the value <strong>of</strong> the Machinery Assets <strong>of</strong> Active Borrowers are significantly lower – Table<br />

7.11.<br />

24

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