Microcredit uses social control as a substitute to formal collateral and in this way makes it possible to provide credit to poor people. Many investigations including those by World Bank, provide evidence of the positive impact of microcredit. In most cases, the studies have focused on the direct effects of microcredits on household income and expenditure. In this study the indirect impact of Grameen Bank microcredit on primary and secondary schooling of the borrowers children is investigated. The hypothesis is that the increase in income associated with micro credit loans increases the probability that the children attend school.

The results of Khandker and Pitt (1998) indicate that microcredits has a positive effect on children's schooling in Bangladesh. However, the data used in their study was collected in 1991/92, and the educational situation In Bangladesh has changed during the last decade. While Pitt and Khandker investigate the overall effect of microcredit on the schooling of children aged 5-17, we study the effect on primary and secondary schooling separately..

The statistical design of this study is a cross sectional comparison of Grameen Bank member households on the basis of number of years in the Bank. We investigate if the length of membership in the Bank is positively correlated with the schooling of the borrowers children.The data used in this study consists of 509 female Grameen Bank borrowers, and was collected through interviews during May and June 2001. Out of the borrowers, 183 are members of the Puranapail Joipurhat branch in the Rajshahi region, and 326 are members of the Dhamsona Savar and the Ashulia Savar branches in the Dhaka region. The two regions are analyzed separately.

All persons who become members of the Grameen Bank belong to the landless poor, and they all possess the enterprising spirit to dare take a loan and to start a micro business. Hence, in this study we assume all borrowers to be comparable in the aspect of initial material and human resources. Naturally, there are still factors, other than length of membership in the Bank, that may differ among the borrowers and that may influence the schooling of the children. We have tried to correct for these eventual biases by collecting additional information on the following factors of the borrower: age, civil status, number of micro credit loans taken, number of children (boys and girls respectively), if loans have been taken in other microcredit programs, and finally if the borrower herself did go to school.

In order to obtain comparable groups of short-time and long-time borrowers, data were classified as follows: in the Dhaka region sample borrowers that have been members of the bank for 1-2 years were classified as short-time borrowers, and those that had been members for 3-5 years as long-time borrowers. In the Rajshahi region we classified short-time borrowers as those who have been members 1-5 years and long-time borrowers as those with 6-14 years in the Bank. The reason for this difference in classification between the two regions, is that Grameen Bank had been present in the Rajshahi region for a longer time, and that consequently, the number of new borrowers in this region was smaller. Data were also classified into subgroups based on the number of children of the borrower. In case the number of observations in a subgroup was too small to enable statistical inference (i.e. less than five) the observations of two subgroups were added. To test the hypothesis jointly for all groups the chi-square statistics for the separate groups were added. The results are presented below.

 

Region / School Level	No of Children	Short Time Borrowers		Long Time Borrowers		X2	P
		Proportion	Sample Size	Proportion	Sample Size
Dhaka, Primary	1	0.84	44	0.91	58	1.11	-
	2	1.59	32	1.79	34	2.01	-
	3-4	2-4	10	3.68	14	15.75	0.005
Dhaka, Secondary	1	0.37	32	0.55	47	2.33	-
	2	0.94	17	1.4	30	3.66	0.100
	-	-	-	-	-	5.99	0.100
Rajshahi, Primary	1	0.89	27	0.93	29	0.30	-
	2-3	1.67	6	1.20	19	1.21	-
	-	-	-	-	-	1.51	-
Rajshahi, Secondary	1-2	0.682	22	1.07	56	7.952	0.005

In the Dhaka region we obtain significant results on primary and secondary schooling at the 5 per cent and 10 per cent level respectively. We even get significant tests for each of the groups with three to four children in primary school and two children in secondary school. In the Rajshahi sample, the null hypothesis is only rejected for secondary school attendance.

Number of years in Grameen Bank has a significant positive effect on primary school attendance in the Dhaka region and on secondary school attendance in both the Dhaka and the Rajshahi regions. The effect on primary school attendance in the Rajshahi region is not significant. The age of the borrower is significant and negative in the case of primary school in the Dhaka region. However, the effect is not significant when all other variables are included in the model. For the Rajshahi region the education of the borrower is significantly positive.

There are several possible explanations for the insignificant result of microcredit on children's primary schooling in the Rajshahi region. Firstly, the number of observations is smaller than in the case of the Dhaka region. Secondly, on average the borrowers in the Rajshahi sample have been members of Grameen Bank for a longer time than those in the Dhaka region. If the effect of microcredit on primary schooling takes place at an early stage, it may be the case that for the great majority of the borrowers in the Rajshahi sample this effect has already occurred. Thirdly, the Rajshahi region is wealthier than the Dhaka region. Consequently, a higher proportion of the population can afford having their children in school and thus the effect of microcredit on children's primary schooling is not as strong.

In the Dhaka primary school regression, the age of the borrower is negative and significant. The reason may be that younger borrowers have been more receptive to the educational campaigns that have been conducted by the Government during the last years and therefore value education more than older borrowers. The variable "education of the borrower" is significant in the Rajshahi secondary school model, but not in the other models. However, the sign of the coefficient is positive in all models. It is thus possible that this effect exists also in the other cases, but that our sample is too small to estimate it.

The marginal effect of "number of years in Grameen Bank" in the Dhaka region is larger for secondary than for primary school attendance. This result is in accordance with what we would expect. Primary school is compulsory and free and thus accessible for most people. Consequently primary school is easier to afford than secondary, which is associated with direct costs such as school fees. In addition secondary aged children are probably more valued as labor than primary aged children are. The marginal effect of microcredit on secondary schooling in the Rajshahi region is smaller than in the Dhaka region. As in the case of primary schooling, one possible explanation for this may be the fact that the Rajshahi region is wealthier than the Dhaka region.

We have obtained significant positive effects of microcredit on the schooling of the borrowers' children in the Dhaka region. These results are consistent with the findings of Khandker and Pitt (1998). In the case of the Rajshahi region the result is significant at secondary but not at primary level. The positive impact on children's schooling probably stems from the increase in family income that makes it possible to afford the direct and indirect costs associated with schooling.

Hulme, D. and Mosley, P., 1996, Finance Against Poverty, Vol. 1 (London: Routledge). Kamal, M.M., 1999, Measuring Transformation: Assessing and Improving the Impact of Micro Credit Part III, Impact Evaluation Mechanism of the Association for Social Advancement (ASA) in Bangladesh.

Khandker, S.R, 1998, Micro-credit Programmes Evaluation ---- A Critical Review, IDS Bulletin of International Development Studies 29 (4), 11-19.

Khandker, S.R, and Pitt, M.M, 1998, The Impact of Group-Based Credit Programmes on Poor Households in Bangladesh: Does the Gender of Participants Matters ? , Journal of Political Economy 106 (5), 958-996.

Rahman, R.I., 1994, Impact of Credit for the Rural Poor: An Evaluation of Palli Karma Sahayak Foundation's Credit Program, Report Nr: 1207, BIDS, Dhaka.

The World Bank, 1996, Staff Appraisal Report, Bangladesh Poverty Alleviation Micro-finance Report 1, South Asia Region.