{"title":"Factors Affecting Loan Repayment Performance of Smallholder Farmers in Ethiopia","authors":"Simachew Dubale, H. Beshir","doi":"10.11648/j.aff.20200903.15","DOIUrl":null,"url":null,"abstract":"Farm credit has been described as one of the pre-requisites for farmers to increase the agricultural production. However, the majority of Ethiopian population comprises small farmers, who cannot implement a technology without credit. Even though, there are attempts to solve these rural financial difficulties by government being collateral and extending microfinance institution, associated to different factors, a number of farmers are becoming defaulters and the lending institution faces a problem. This study focused on the analysis of factors affecting loan repayment performance of farmers in Simada District, South Gondor Zone and Amhara Regional State. In this study primary data collected from 150 randomly selected borrowers using structured questionnaire. Descriptive statistics such as mean, standard deviation, maximum, minimum and percentages were used to describe socio-economic and institutional characteristics of the respondents. The t-test and Chi-square test statistics were employed to compare defaulter and non-defaulter groups with respect to some explanatory variables. Finally, a Tobit regression model was employed to identify factors affecting loan repayment and intensity of loan recovery among smallholder farmer. Variance inflation factor and coefficient of contingency were calculated to detect multicollinearity and association among the continuous and discrete variables, respectively. A total of 14 explanatory variables were included in the empirical model and out of these, 8 were found to be statistically significant. Education level, Land holding size, total livestock holding, non farm income, expenditure on social festivals, number of years of experience in agricultural extension services, saving habit and source of credits were highly important in influencing loan repayment performance as evidenced by the model statistic. Therefore, the study suggests that improving the livestock sector, educating households, giving attention in promoting non-farm activities and saving habit, minimize traditional ceremonies are some of the important priority areas for the success of future intervention strategies aimed at the promotion technological transformation, increasing production and to minimize loan defaults..","PeriodicalId":7466,"journal":{"name":"Agriculture, Forestry and Fisheries","volume":"135 1","pages":"75"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agriculture, Forestry and Fisheries","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11648/j.aff.20200903.15","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Farm credit has been described as one of the pre-requisites for farmers to increase the agricultural production. However, the majority of Ethiopian population comprises small farmers, who cannot implement a technology without credit. Even though, there are attempts to solve these rural financial difficulties by government being collateral and extending microfinance institution, associated to different factors, a number of farmers are becoming defaulters and the lending institution faces a problem. This study focused on the analysis of factors affecting loan repayment performance of farmers in Simada District, South Gondor Zone and Amhara Regional State. In this study primary data collected from 150 randomly selected borrowers using structured questionnaire. Descriptive statistics such as mean, standard deviation, maximum, minimum and percentages were used to describe socio-economic and institutional characteristics of the respondents. The t-test and Chi-square test statistics were employed to compare defaulter and non-defaulter groups with respect to some explanatory variables. Finally, a Tobit regression model was employed to identify factors affecting loan repayment and intensity of loan recovery among smallholder farmer. Variance inflation factor and coefficient of contingency were calculated to detect multicollinearity and association among the continuous and discrete variables, respectively. A total of 14 explanatory variables were included in the empirical model and out of these, 8 were found to be statistically significant. Education level, Land holding size, total livestock holding, non farm income, expenditure on social festivals, number of years of experience in agricultural extension services, saving habit and source of credits were highly important in influencing loan repayment performance as evidenced by the model statistic. Therefore, the study suggests that improving the livestock sector, educating households, giving attention in promoting non-farm activities and saving habit, minimize traditional ceremonies are some of the important priority areas for the success of future intervention strategies aimed at the promotion technological transformation, increasing production and to minimize loan defaults..