Determinants of participation and earnings in the rural nonfarm economy in Eastern Ethiopia

This paper investigated the push and pull factors that influence the participation decision of rural households in non-farm activities (RNFA) and the income earned from this sector. Multinomial logistic regression was applied to estimate the likelihood of participation in RNFA and a censored income determinant function (tobit) was estimated to understand factors influencing nonfarm income share in the study area. Results show that only 21% of the total household income was derived from different nonfarm activities with activity rate of 46%. In disaggregated functional categories, 21% and 24.6% of the total sampled households participated in wage employment and self-employment, respectively. However, income from each activity accounted for only 10.3% and 11% of total income. The multinomial logit analysis showed that the likelihood of earning income from non-farm economic activities was significantly influenced by capacity variables such as wealth and human capital. Having better education, land holding, access to irrigation and number of adult members positively influenced the likelihood of involvement in non-farm activities. The result was associated with access to irrigation and implies that households with better economic condition are pulled to the non-farm sector attracted by the better return from the non-agricultural sector. Female-headed households were found more likely to participate in own business than male-headed ones. Estimation of the tobit model revealed that having access to credit, better land size, livestock and number of adults in the household significantly and positively influenced the share of income from rural non-farm employment (RNFE). It was also found that age and sex (male) of household head had positive effect on the share of income from RNFE. The findings of the study suggest that efforts should focus on the promotion of nonfarm opportunities that do not impose barriers to entry through provision of physical infrastructure such as road, improving credit provision, improving educational status and improving irrigation water accessibility. These efforts can be expected not only to directly raise the income levels of the disadvantaged but also to reduce inequality by raising wages received by those who remain employed as non-agricultural laborers