Informal Transfers

Informal transfers involve transfers or exchanges between households of cash, food, clothing, informal loans, and assistance with work or child-care.  Depending on their size, informal transfers can affect household income and consumption, investments in human capital, fertility rate, and an individuals' savings and wealth.  They can also transmit patterns of inequality across generations and interact with social protection programs.  These transfers present a challenge to the effective design of public programs that is different from the challenge presented by transfer programs of non-governmental organizations or private firms.

What is the magnitude of informal transfers and the effect on poverty reduction?

For those countries where data exists, the evidence is that patterns of private transfers vary according to local conditions.  Estimates are that transfers account for between 2 and 41 percent of income for net receivers and between 1and 8 percent of income for net givers.  The patterns of informal transfers reveal the following general trends:

Some general trends in informal transfers have been studied.  Evidence suggests that the bulk of informal transfers flow from older to younger households.  Poor and vulnerable households are more likely to receive private transfers, while non-poor households are more likely to give private transfers. Informal transfers may therefore equalize the distribution of income.  Household characteristics other than income (such as gender of household head, education level, ethnicity) also affect the pattern of informal transfers.  For example, female-headed households appear to be more likely to receive transfers.  In the United States, at least, the probability of both giving and receiving private transfers increases with the level of education (MacDonald 1990; Cox and Raines 1985).

How effective are private transfers in the risk management?

Empirical evidence suggests that informal transfers are generally weak in facilitating risk management by households, particularly for covariate risks.  Rosenzweig 1988, estimates that Indian transfers typically amount to less than 10 percent of the size of typical income shocks in bad periods.  Following the 1984 drought in the Sahel, Reardon, Matlon, and Delgado found that transfers comprised less than 3 percent of losses for the poorest households.  Similarly, Czukas, Fafchamps and Udry 1995 find little evidence that transfers offset income shocks in the Burkina Faso droughts between 1981 and 1985.

But in more "normal" circumstances, informal insurance may be more effective.  While Cox and Jimenez 1997, for example, find that just 40 percent of black South African households either give or receive private transfers, the level of transfers is relatively high for net recipients, comprising 37 percent of income on average.  Similarly, while fewer than 10 percent of white South Africans report giving or receiving transfers, private transfers made up 25 percent of income for net recipients.  For black South Africans, the transfers tend to go from young to old individuals, suggesting that the transfers largely address low- frequency shocks (like aging and chronic health problems), not the sorts of high- frequency shocks considered elsewhere.  While the reported transfers are far from ubiquitous, they do appear to matter for a substantial minority of households, and generalizations should be made with care.

Is the crowding out of private programs an issue?

First, evidence suggests that while private transfers are important, and may be critical to some poor households, they are not fully adequate substitutes for public action in many aspects of social protection in many countries.  A rationale for public intervention and programs arises because informal transfers often fail to protect the ultra-poor (Morduch 1997).  Public intervention is also needed when income shocks are covariate (Subbarao et. al. 1997); when delivery mechanisms are costly (Morduch 1994); when the severity of the income shock is extraordinary, such as droughts, epidemics, or macroeconomic shocks (Coate and Ravallion 1993); and when shocks are repeated (Deaton 1992).  Furthermore, informal transfers may lead to poverty traps by either solidifying economic and social barriers along ethnic, gender, generational, and class lines (La Ferrara 1997; Fafchamps, 1992; Platteau, 1996; Hoff, 1997) or by creating inefficiencies that ultimately undermine economic progress over time (Banerjee and Newman 1997). As a result, crowding out some informal transfers or mechanisms may be an acceptable cost, or even a desired goal (see Morduch 1997).

Second, a central concern is whether public programs ‘crowd out’ private transfers in a way that is less than sub-optimal. When it comes to ‘crowding out’ it is not whether or not it exists at all that is important but whether a given option for a public program results in a better social protection system, when all the benefits of the program (which might include more complete coverage of the vulnerable, or more complete assistance to those reached) are weighed against all its costs, including some "crowding out" of private transfers.

What are the implications of informal transfers for the design of Social Protection programs?

As mentioned above, crowding out is cause for policy concern only if it implies that public resources are inefficiently allocated. Thus, some studies of transfers have tried to identify the appropriate recipients of transfers and the magnitude of these transfers in relation to the private safety net already in place in each country. In estimating cost-effectiveness analysis of public programs, crowding out should be included as an additional cost. The costs of crowding out are higher if public safety net programs are crowding out well functioning informal transfers; or if public programs undermine existing informal systems of self-help while encouraging a culture of dependency among the poor.