Participation into off-farm activities in rural Ethiopia: who earns more?

This paper analyzes off-farm activities and income among 1343 households in rural Ethiopia using an original panel data set. The key findings are as follows. (a) ‘Non-poor’ households generate a significant amount of income from farming activities. (b) Non-poor participate more in high-earning off-farm activities while, on average, ‘poor’ participate in low-earning off-farm activity. (c) Poor household participate due to push factor while non-poor participate as a choice. (d) Household with more resources are getting better off-farm earnings. (e) Share of off-farm income is higher for poor households, that is, off-farm income constitutes nearly 35% and 18% of household income for poor and non-poor households respectively (in 2008). In general, the finding indicates that the poorer segment of the society relies relatively more on off-farm income and there is an entry barrier for poor households to participate on high-earning activities. Off-farm activities have a potential to reduce poverty and income inequality as it is relatively beneficial to poorer households. However, this requires substantial improvement in terms of increasing off-farm earnings that the poor households engaged in. Otherwise, the contribution of off-farm to the national economy will only be limited to absorbing the poor on lower earning activities. However, it is to be noted that off-farm activity are acting as a safety net for rural society in Ethiopia, no matter what the earning level is, by preventing them from a worst livelihood situations. -- Relevance to Development Studies -- The livelihood of most people in developing countries is highly dependent on agriculture, but the carrying capacity of the sector is decreasing over time due to rate of increase in population growth and the corresponding reduction in farm size. As a result, share of off-farm participation of rural labor force is increasing. It is, therefore, crucial to closely examine the cause and effect of diversification to better understand the situation and explore policy options to rationally address it. This study points out some of the motives behind the decision for diversification and consequences on household income using panel dataset.