Browsing by Author "Gebrehiwot Tsegay"

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    Determinants of Food Security in Rural Households of The Tigray Region
    (Addis Abeba university, 2009-06) Gebrehiwot Tsegay; G/ Yohannes Emmanuel (PhD)
    This study investigated the determinants of food security and identified the major factors that jointly discriminate the rural households of Tigray region into food secure and food insecure households. The study is made based on the 2004/2005 Household Income, Consumption and Expenditure Survey (HICES) and Welfare Monitoring Survey (WMS) which were conducted by Central Statistical Agency (CSA). To analyze the data descriptive statistics, bivariate and multivariate analyses were used. The descriptive results revealed that about 42% of the households were found to be food insecure while 57% were food secure. The bivariate analysis was performed to investigate the effect of each predictor variable on the household food security status. A priori expectations about the relationships between household food security status and factors influencing it were satisfied for the majority of the cases considered. Moreover, a univariate ANOVA of each predictor variables against the household food security was performed to identify the variables that have significant contribution to the discrimination of the two household groups. Accordingly, distance to input sources, farmland size, TLU, number of oxen, household size were found to be the major discriminating variables. This was further supported by multivariate discriminant function analysis applied to sampled farm households. The importance of the contribution of factors in discriminating the two household groups were ranked by the discriminant function. As a result, distance to input source was ranked first followed by household size, farmland size, livestock ownership, number of oxen, use of fertilizer, gender and educational level of the household head. In addition to this the classification results revealed that 79.7% of the households were correctly classified. This indicates that the discriminant function employed in this study was efficient in discriminating the rural households based on the eight predictors.