1.2 RECURSOS SANITARIOS ASOCIADOS A ENFERMEDADES TERMINALES

Out of the sixteen variables hypothesized to influence the loan repayment performance of borrowers, six were found to be statistically significant. The maximum likelihood estimates of the logistic regression model shows that education (EDUHH), number of livestock (nolive), amount of input credit borrowed by the household (amoucred), experience of the household in credit use (expcrehh), income of the household from off-farm and non farm activity (offnfin) and Appropriateness of the repayment period (apptime), were important factors influencing the loan repayment performance of member borrowers in the study area. More specifically, the coefficients amount of input credit borrowed by the household was statistically significant at less than 1 percent probability level. The variables, experience of the household in credit use, education level of the household, off farm and non form income of household and Appropriateness of the repayment period were statistically significant at less 5% and number of livestock was also significant at less 10% level of significance. On the other hand, the coefficients of 10 explanatory variables, namely age of the household (agehh), family size of the household (famlisiz), total farm size of the household (totfsiz),Expense of the household for social ceremony (expcerm), other credit borrowed by the household (othcred), income of the household from crop (cropinc), cooperative membership of the household (coopmsh), training access of the household (trainhh), supervision of borrower by loan committee of MPC (loancs) and effect of natural calamity (natucalam) on loan repayment were less powerful in explaining loan repayment performance of the sample borrowers. Regarding the signs of the coefficients of variables three variables namely family size, appropriateness of the time for repayment and effect of natural calamity have negative sign whereas the rest variables have positive sign. The results of the logit regression analysis are shown in Table 35.

Table 35: Logistic regression estimates of loan repayment performance in kilteawulalo Woreda

Explanatory variables Coefficient Wald test Sig. Exp(B)

agehh .034 1.465 .226 1.035 Educhh .185 4.140 .042** 1.203 Familshh -.133 1.339 .247 .875 Coopmsh .006 .009 .926 1.006 Cropinco .000 1.793 .181 1.000 nolivst .207 2.717 .098* 1.230 Offnfinc .000 4.598 .032** 1.000 Totfrsiz .300 .318 .573 1.350 Expcerm .000 1.495 .221 1.000 Expcrehh .179 4.275 .039** 1.196 Amoucred .008 9.086 .003*** 1.008 Othecred .000 .745 .388 1.000 trainhh(1) .567 1.340 .247 1.763 natucalam(1) -.633 1.047 .306 .531 loancsp(1) .154 .083 .773 1.167 apptime(1 -1.230 5.571 .018** .292 Constant -3.221 5.943 .015 .040 Chi-square value 54.6*** -2 Log Likelihood 125.397

Over all sum 76.2

Sample size 130

Source: Model out put

*, ** and ***, significant at 10, 5 and 1 per cent probability level, respectively The interpretations of significant variables were present as follow.

Level of education of the household head (educathh):-

dependent variable showing that educated household heads were more able to recognize the advantage of loan repayment in time and willing to take credit. A possible explanation for a positive relationship is that education reflects acquired knowledge of socio-economic amenities.

All other things held constant, the odds ratio suggests that farmers who have attended formal education are more likely to repay their debts in time than farmers who have not attended formal education and showing interest to be non-defaulter by a factor of 1.203 for literate household heads. Similarly Gebrehiwot (2006) reported a positive relation between loan repayment and educational level of the households.

Amount of input credit borrowed by the household (amoucre):- The result of logit model

showed that this variable has higher positive significant influence on loan repayment performance in the study area. This is consistent with prior expectation. The model output revealed that increase in loan amount enables the borrower to generate more farm income as it creates access for the household to use the required amount of farm input. Input credit is one of the financial services being rendered by cooperatives in the wereda. In the process of credit provision for those who are the poorest of the poor, loan size is the main concern of the lenders and the borrowers. The cooperative societies had been trying to fulfill their members’ credit demand with that of limited capital resource, and borrowers are interested to get increased loan amount.

Result reported by Kebede (2003) and Gebrehiwot(2006) corroborates the results obtained in the present study regarding the significance of an amount of credit supplied to the rural household. Moreover, according to Babatunde et al. (2007), this is the ability of the household to obtain large amount of credit for household’s production purpose. Production credit could

increase household’s income and could allow him/her to repay their debt on due date.

Assuming ceteris paribus, the odds ratio suggests that farmers who have got large amount of credit are expected to repay their debt in time than borrowers who have got small amount.

Experience of the household in formal credit utilization (expcre):-

The results of the logit model show that this variable affects loan repayment positively. This is consistent with a prior expectation. This variable is significant at less than 5 per cent level of significance. This might be because of the fact that borrower with long experience have better and efficient utilization of loan. This ultimately improves the loan repayment performance of the farmers. In addition those farmers with long experience have a better knowledge in the rules and regulation of financial institutions and more aware of the consequence of loan default on the availability of credit for the next year.

The odds ratio result reveals that farmers with better years of experience in credit utilization from formal institutions are more likely to repay their debts in time than farmers who have lower experience and showing interest to be non-defaulter by a factor of 1.196 for experienced household heads. Similarly Amare (2005) reported a positive relation between loan repayment and experience of households in credit utilization.

Total livestock unit of the household.

Total livestock ownership (LIVSTKNO) is, as expected, positively related to the dependent variable (significant at less 10% level). The implication is that, Livestock are sources of cash in rural Ethiopia and serve as security against crop failure. Farmers who owned more livestock are able to repay their loans even when their crops fail due to natural disaster. In addition, as a proxy to oxen ownership the result suggests that farmers who have larger number of livestock

have sufficient number of oxen to plough their field timely and as a result obtain high yield and income to repay loans.

The odds ratio result reveals that farmers with more number of livestock are more likely to repay their debts in time than farmers who have small number of livestock and showing interest to be non-defaulter by a factor of 1.23 for experienced household heads. Similar result was also reported by Amare (2006).

Appropriateness of repayment period

The results of the logit model show that this variable relates negatively with loan repayment at less than 5% level of significant. This is consistent with the prior expectation. The negative relation of the variable with loan repayment shows inappropriateness of the existing repayment period for borrowers to repay their loan. The possible explanation here is that as the time length between harvesting and due date of loan repayment was too short farmers may not have a chance to choose best time for marketing of their product. This is because during January and February market price for farm product special for grain is relatively low as most farmers sell their product to celebrate social ceremony and also to repay different loans. Then farmers may need extra time to procure the farm product until market price start to rise,

Moreover odds ratio in favor of non-defaulter was decreasing by a factor 0.292 for borrowers, if the period of repayment existing as it is (unchanged). But the result is contrary to Hunte (1996), findings that, extended repayment period in loan contract led to high default risk and low repayment.

Off farm and non farm activities of the house hold (offnfinc)

Getting income from off-farm and non-farm activities are another economic factor that were positively and significantly affected loan repayment performance of smallholder farmers. This

might be due to the fact that; off-farm and non-farm activities were additional sources of income for smallholders and the cash generated from these activities could back up the farmers’ income to settle their debt even during bad harvesting seasons and when repayment period coincides with low agricultural prices.

The odds ratio in favor of non-defaulting was increasing by a factor of 1.00 as the borrower’s participated in off-farm and non-farm activities. However, this result is contrary to Bekele’s (2001), findings that, off-farm income was negatively related with loan repayment performance of farmers. But Amare (2005) reported that off-farm and non-farm activities were positively related with loan repayment,