Community-based risk management arrangements: Implications for Social Funds

1. Community-based risk management arrangements: Implications for Social Funds Ruchira Bhattamishra, World Bank Christopher B. Barrett, Cornell University November 10, 2008

2. Motivation I • There is growing recognition in the development community that: • vulnerability to adverse shocks is a defining characteristic of poverty • risk management is central to poverty reduction policy because uninsured risk exposure is both cause and consequence of poverty. Uninsured risk Poverty

3. Motivation II • There is also growing recognition in the development community that: • community-based and community-driven development can be effective in filling key gaps between national- and household-level strategies. • But there’s a major gap in the literature on community-based risk management arrangements (CBRMAs) … hence this survey.

4. Objectives • Convey importance of social protection to economic growth and poverty reduction • Provide catalog of existing community-based risk management arrangements (CBRMAs) • Discuss strengths and weaknesses of CBRMAs • Stimulate discussion of implications for SP projects, especially as implemented by Social Funds

5. Essential Role of Social Protection • Insuring downside risk can stimulate significant technology uptake, investment and other behaviors that foster growth, especially among the poorest and most risk averse subpopulations. • Effects of social protection are especially pronounced in places characterized by “poverty traps” with multiple welfare equilibria: • Ex post effect—prevents the numbers of chronically poor from growing in the wake of a shock that destroys productive assets; • Ex ante effect—improves incentives, ‘crowds in’ private asset accumulation and new technology uptake, making sustainable escape from poverty more feasible. • Both effects reduce the number of households needing assistance, which lets true humanitarian assistance $ go further. • Let’s look a bit more at the economics that underlie these claims…

6. The Potential of Social Protection Barrett, Carter and Ikegami (2008) offer simulation-based evidence on the impacts of social protection. (Solid blue is with social protection, green is autarky, red is targeted transfers.)

7. Typology of risks I • Covariate risk vs. Idiosyncratic risk • Covariate risk affects households in the same locate at the same time (e.g., weather, disasters, war, prices, financial crises, etc.). • Idiosyncratic shocks are (the component) specific to one household (e.g., illness, crop yield shocks, property loss due to fire or theft, etc.). • CBRMAs can help households cope with idiosyncratic shocks, less so with covariate shocks, unless risk is reduced or transferred outside the community. • The empirical literature suggests that idiosyncratic risk is considerable, implying significant scope for risk pooling within communities. • Even covariate risk can be managed within communities through risk reduction efforts (e.g., through NRM) and external risk transfer (e.g., through index-based insurance).

8. Typology of risks II • Asset risk (loss of human capital, livestock, land, etc.) vs. income risk (loss of current period revenue) • Long-term (structural ) vs. one-off (transitory) • Stunting due to drought in Zimbabwe in 1980s caused 14 percent reduction in lifetime earnings (Alderman et al.2006). • Implications for poverty persistence: poverty traps or at least very slow recovery and thus high persistence of shock-induced poverty. • CBRMAs can not only address one-off income risk but also, and perhaps more importantly, longer-term asset risk by developing community/ individual capabilities.

9. Risk management Typology of strategies under SP Social Risk Management (SRM) framework (Holzmann and Jorgensen 1999): 1) Risk reduction: ex ante; reduce exogenous income variability and/or probability of asset loss (e.g., water control, EGS). 2) Risk mitigation: ex ante; reduce endogenous income variability and/or probability of asset loss through portfolio diversification, insurance, hedging, etc. 3) Risk coping: ex post behavioral adjustment (investment and consumption adjustment, asset sales, borrowing) and/or risk transfer. • Households employ a combination of strategies. But poor households typically have limited recourse to 1 and 2 and resort to 3, often through transfers (gifts, food aid, etc.).

10. Importance of risk sharing • Incomplete financial markets leave uninsured risk. • Sale of assets restricted to those that have assets, typically not the poorest, and may seek to asset smooth. • In the event of common shock, assets and income may move together, limiting ability to consumption smooth. • The poorest (such as disabled, female-headed households) often unable/unwilling to access public works programs. • Informal risk sharing often the only avenue open to poor households, but social invisibility/exclusion a problem for the poorest and most marginal populations (e.g., Santos and Barrett (2008) in Ethiopia, Vanderpuye-Orgle and Barrett (forthcoming) in Ghana).

11. Definitions Community based risk management arrangements (CBRMAs) • Define “community” loosely in order to include agents whose relations have an informal and non-market character • Include all coordinated strategies used and managed by social groupings of individuals for the purpose of protection against the adverse effects of various types of risk. • Include both indigenously developed, “informal” and externally-initiated, “semi-formal” arrangements.

12. Definitions (cont.) • Key similarities between indigenous and externally-driven CBRMAs: Use of interpersonal relations in management & contract enforcement. • Key differences: see below

13. Contextualizing CBRMAs in the SRM matrix

14. Contextualizing CBRMAs in the SRM matrix (cont.)

15. Role for Social Protection • Limitations of indigenous CBRMAs • Exclusion of poorest or other marginalized sub-populations • Inability to manage covariate risk • Role for SP intervention… • SFs can potentially build on existing institutional networks to support CBRMAs • Can use large size of networks for risk pooling purposes • Can build on experience with participatory approaches to develop innovative, demand-driven risk management products.

16. Range of possible approaches • Promote inclusion by provision of subsidies • Support start-up of viable MFIs • Expand menu of projects • Support provision of risk-reducing public goods • Support risk coping after covariate shocks via intermediaries

17. Enabling inclusion • Identify cleavages in existing CBRMAs. • Can design safety nets schemes explicitly aimed at reducing costs of social interaction between different social groups. • E.g., Macedonia Community Development Project. • Can subsidize cost to poorest households to enable their inclusion. • E.g., subsidize ex ante contributions for health insurance associations.

18. Provision of subsidies (community-level) • Cover start-up costs of viable financial institutions. • E.g., microfinance institutions. • Some relevant insights from behavioral economics • Cognitive difficulties in assessing risk; choice bracketing; representativeness; etc.

19. Expanding menu • Include innovative programs. • Can go beyond thinking of SF as instrument for primarily developing “brick-and-mortar” outputs and providing basic services. • Design safety nets schemes explicitly aimed at creating behavioral change and supporting risk management, both for one-off income risk as well as long-term asset risk. • E.g., can develop PTAs in addition to building schools.

20. Reducing exposure to covariate shocks • Provision of risk-reducing public goods and services through community arrangements • Builds longer-term capacity of community. • Addresses not only one-off income risk but also more long-term asset risk.

21. Supporting risk coping after covariate shocks via intermediaries • Build capacity of communities to tap into reinsurance markets • Emphasize risk management rather than crisis management. • Underwrite start-up costs associated with creating risk-transfer products • E.g., underwrite cost of developing data series for pricing index-based insurance products. These are non-manipulable, suitable for risk-layering. In addition, they can support risk coping for both slow-onset (e.g., drought) as well as sudden-onset risk (e.g., earthquake). • Use community information for effective two-tier allocation of disaster assistance (Alderman 2001).

22. Potential problems • Specific problems affecting Social Fund intervention for risk-management • Administrative concerns • Other problems (which affect community initiatives in general) • Scalability, crowding-out, etc • Manipulation by local elites • Corruption • Limits of community decision-making • See also Mansuri and Rao (2004), Conning and Kevane (2002), Ensminger (2007).

23. Administrative concerns • Differences in administering periodic investment/ preparing proposal vs. overseeing regularly running program. • Expanding menu to include innovative programs implies need for new training for program managers.

24. Scalability concerns • Range of CBRMAs • Differences in membership and leadership structure, the nature of activities, history, longevity, etc. • Differences in political economy and socio-economic environment. • Differences between informal and semi-formal arrangements in level of technical/financial and accounting assistance required. • CBRMAs will have different abilities to effectively absorb external assistance, depending on the nature of activities, history, etc… • Lack of existing evidence on impact of scaling up…

25. Crowding-out concerns • Disruption of existing CBRMAs • “Rockefeller” effect: external assistance can change characteristics of a previously effectively functioning group. • E.g., Gugerty and Kremer (2008) study in Kenya.

26. Vulnerability to manipulation • Project benefits captured by local elites • Corruption • Decentralized, community-led approaches can result in rampant misappropriation of project benefits, given the absence of well-functioning checks and balances, remote governance structures, absence of media, and low levels of education. • E.g., Ensminger (2007) study in Kenya.

27. Limitations of community management • Limitations in technical decision-making and management • Positive impact of community participation in non-technical decision-making (such as targeting/project choice) but not so for technical decision-making. • E.g., Khwaja (2004) study in Pakistan. • More complex accounting/financial knowledge needed for “semi-formal” versus “informal” CBRMAs.

28. Moving forward…. • Need for econometric or experimental evidence comparing community-based models with other models (e.g., social marketing, public-private partnerships, etc.) that do not use community for project design or project delivery. • Compare impact, cost-effectiveness: Social Funds can provide valuable crucible for such analyses. • Address key questions • What are some of the main constraints and opportunities for SF programs supporting risk management? • How can these interventions achieve the right scale of implementation?