This paper explores determinants of loan default by Agribusiness entities in the Tamale Metropolis of Ghana. Data to examine the causes of loan default was obtained from owners through structured questionnaire and descriptive statistics, Kendall coefficient of concordance and logistic binary regression was used to analyse the data. Financial variables were more significant than demographic characteristics of agribusiness entities to cause loan default. This suggests financial institutions must apply appropriate adjustments to financial variables in order to minimize loan default risk considering the agricultural sector.
Determinants of Household Food Security and Coping Strategies: The Case of Bule-Hora District, Borana Zone, Oromia, Ethiopia (Published)
Now a day food security issues become one of the critical concern and top priority area for developing countries. Having clear picture on food security status and its major determinants helps policy makers and planners to devise new policies that enhance food security. Hence, this study was conducted to determine the status of food security in the study area, to identify the major determinants of food security among the rural household, and to identify coping strategies employed by different food security status groups to cope with food insecurity. In order to achieve these objectives biophysical; demographic and socio-economic data were collected from 140 randomly selected households in Bule-hora District of Borana Zone, Oromia Regional State. A two-stage sampling procedure was used to select 5 PAs. A survey was conducted to collect primary data from sample respondent. Secondary data were collected from various sources. The data were analyzed using descriptive statistics such as mean, standard deviation, percentage and frequency distribution. Univariate analysis such as one way ANOVA and Chi-square tests were also employed to describe characteristics of food secure, food insecure without hunger, food insecure with moderate hunger and food insecure with sever hunger categories. The survey result shows that about 23% of sampled farmers were food secure. Ordered logit regression model was fitted to analyze the potential variables affecting household food insecurity in the study area. Among 14 explanatory variables included in the logistic model, 6 of them were significant at less than 5% probability level. These are; Cultivate Land Size (LAND SIZE), Livestock holding (TLU) and Improved seed (SEEDUSE), SEX of household head, Soil fertility status (SOIL FER) and non-farm income (INCOMEON). The estimated model correctly predicted 85.2% and different recommendations were made based on the findings of the study.