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The Efficiency of Risk-Sharing Within Households in Kenya

Development Challenge

Individuals in developing countries are often subject to considerable financial risk, but most lack access to formal financial services that would allow them to insure themselves against unexpected income shocks like medical expenses or natural disasters. Instead, households often use informal systems of gifts and loans from friends or family to cope with large unplanned expenses. While these informal networks do provide some protection against shocks, they also face substantial problems of enforcing the payment of transfers from one individual to another. Existing evidence suggests that such barriers to informal insurance are one reason that informal insurance is rarely, if ever, able to fully insure individuals against unexpected shocks. 

Context

The towns of Busia, Sega, and Ugunja in Western and Nyanza Provinces of Kenya are semi-urban areas located along a major highway. Though many people in the area earn their living from agriculture, a substantial fraction earns at least some income from self-employment. The individuals in this study are drawn from samples of men who work as bicycle taxi drivers - called boda bodas in Kiswahili - and women who sell produce and other items in the marketplace. Daily income earners are targeted in this study because their informal employment makes them more susceptible to income shocks. 

Formal savings accounts are very rare in this sample (just over 1% of respondents have a savings account in a bank or microfinance institution). However, 63% of men and 44% of women participate in Rotating Savings and Credit Associations (ROSCAs), a system where a group of individuals saves money together, and each week one individual from the group gets to take home the collective savings from that week. Similarly, formal credit is nearly unheard of, but the vast majority of both men and women have access to informal credit in the form of gifts and loans from friends and family.

Evaluation Strategy

This study presents results from a field experiment in Kenya designed to test whether intra-household risk-sharing arrangements such as loans and gifts are efficient and, if not, whether limited commitment can account for some observed behaviors. One hundred and forty-two married couples were followed for eight weeks.  Each week both spouses were visited by a trained enumerator who administered a detailed monitoring survey that included questions on consumption, expenditures, income (and income shocks), and labor supply over the previous seven days. 

Additionally, every week, individuals had a 50% chance of receiving a 150 Kenyan shilling (US$2) income shock, equivalent to roughly 1.5 days’ income for men and 1 week’s income for women. As these shocks are, by definition, random, the experimental design makes it possible to compare the difference in the responsiveness of individual private consumption between weeks in which an individual receives the shock himself and weeks in which his spouse receives the shock. If the household pools risk efficiently, increases in private consumption should be the same for both types of shocks.

Results and Policy Implications

The study rejects both the unitary theory of the household (in which the household behaves like a single decisionmaker), and the collective model of the household in which members fully insure each other against shocks. In weeks in which they receive the shock, men increase their expenditures on privately consumed items by 21%. However, there is no change in men’s expenditures in weeks in which their wives get the payout. 

In contrast, women do not increase their own expenditures either when they receive the shock themselves or when their husbands receive it. Women do, however, transfer 16% of the shock to their husbands, whereas husbands transfer none of their shock to their wives. 

Overall, the study suggests significant barriers to efficient risk sharing among these couples. Since this study evaluated relatively small shocks, the failure of intra-household risk sharing is likely to be even more pronounced for bigger shocks such as a poor harvest or major illness.

Timeline

2006