Persistence of Links in Risk-Sharing Networks: Evidence From Rural Ethiopia

Most rural households in developing countries rely on agriculture for their income. They face related risks due to various shocks. In rural Ethiopia a majority of surveyed households reported to have experienced rainfall related shocks, about a third reported crop pest or diseases related shocks. Given that asset, insurance and credit markets are either missing or poorly developed, households face significant constraints in insuring themselves against these shocks. They often rely on the accumulation and depletion of assets (livestock, etc.), savings, borrowing, diversification of economic activities and on risk-sharing networks. Using a unique feature of an Ethiopian longitudinal dataset collected in 2004 and 2009, we investigate the persistence of links within households' risk-sharing networks. We do this by looking at two types of attributes: i) household characteristics such as demographics, assets, location; ii) link attributes such as relationship between households, types of arrangement (money lending, labor-sharing, etc), co-membership in local groups as well as observable differences in income and assets holdings. We investigate whether households sustain these links more on the basis of economic or financial factors such as wealth or more on the basis of social factors such as geographical proximity and shared kinship. Using logit estimation techniques, we find that many of our proxies for social factors play a significant role in the persistence of links in risk-sharing networks. Livestock and land endowments do not seem to play an important role. Local or governmental institutions aiming at bolstering persistence of informal risk-sharing arrangements could focus on networks which have a more local geographically dense structure, or one based on shared kinship. To our knowledge, this is the first time that both the 2004 and 2009 rounds of this large survey are combined. They have a rare feature: they are refined enough to allow us to identify precisely links or the individuals on whom one relies in case of needs. We can thus identify precisely which links persist (being reported both in 2004 and 2009) and which attributes significantly impact persistence. Given this particular attribute of this dataset we have yet to see in the literature a comparable analysis.