The Effect of Shocks: An Empirical Analysis of Ethiopia

Abstract

Beside striving for the increase of production and development, it is also necessary to reduce the losses created by the shocks. The people of Ethiopia are exposed to the impact of shocks having natural and manmade origin. Following this, policy makers, governmental and nongovernmental organizations need to identify the important shocks and their effect and use as an input. This study was conducted to identify the food insecurity shocks and to estimate their effect based on the conceptual framework developed in Ethiopia, Amhara National Regional State of Libo Kemkem District. Descriptive statistical analysis, multiple regression, binary logistic regression, chi-square and independent sample T-test were used as a data analysis technique. The study shows eight shocks affecting households which are weather variability, weed, plant insect and pest infestation, soil fertility problem, animal disease and epidemics, human disease and epidemics, price fluctuation problem and conflict. Weather variability, plant insect and pest infestation, weed, animal disease and epidemics create a mean loss of 3,821.38, 886.06, 508.04 and 1,418.32 Birr respectively. In addition, human disease and epidemics, price fluctuation problem and conflict affect 68.11%, 88.11% and 14.59% of households respectively. Among the sample households 28.1 percent were not able to afford their food need throughout the year while 71.9 percent could. The result of the multiple regression models revealed that weed existence (? =-0.142, p<0.05), plant insect and pest infestation (? =-0.279, p<0.01) and soil fertility problem (? =-0.321, p<0.01) had significant effect on income. Asset was found significantly affected by plant insect and pest infestation (? =-0.229, p<0.01), human disease and epidemics (? =0.145, p<0.05), and soil fertility problem (? =-0.317, p<0.01) while food production was affected by soil fertility problem (? =-0.314, p<0.01). Binary logistic regression model reveals that food availability of the households was highly affected by the asset (Exp (B) = 1.00, p<0.1), and food production (Exp (B) = 1.379, p<0.01).