This paper investigates informal risk sharing against health shocks in the presence of multiple risk sharing networks. We use a panel household survey data from rural Ethiopia that covers the period 1994--2004. We find that neither short-term nor long-term health shocks are insured through transfers from networks such as friends, neighbors, and members of informal associations. However, networks related along bloodline such as extended family members provide assistance when health shocks are long-term such as disabilities. The results show that these networks strategically complement planned component of their transfers which are made on a regular basis such as remittance, entitlement, or chop money (small cash sums for household expenses). Moreover, we find significant history dependence in transfers from not only genetically distant networks but also extended family members as well as formal institutions, which seems to discourage dependency. Finally, the findings suggest significant heterogeneity in transfers.
In the absence of third party and prepayment systems such as health insurance and tax-based healthcare financing, households in many low-income countries are exposed to the financial risks of paying large medical bills from out-of-pocket. In recent years, community based health insurance schemes have become popular alternatives to fill such void in the healthcare financing systems. This paper investigates the impact of these schemes on out-of-pocket spending based on three rounds of nationally representative data from Rwanda. We estimate an Extended Two-Part Model to address endogeniety in insurance enrollment and censoring in healthcare expenditure data. We find that community based health insurance program has non-linear and mixed impacts on out-of-pocket expenditure. While the program significantly increases the probability of overall spending, it decreases the amount of per capita spending on healthcare. The program also significantly reduces spending on drug but increases outpatient spending with no detectable impact on inpatient services. Furthermore, we find notable heterogeneity in treatment effects in which households in the top income distribution realize the highest reduction in out-of-pocket spending.