2015年-世界发展银行全球_Alternative_Social_Safety_Nets_in_South_Sudan___Costing_and_Impact_on_Welfare_Indicators_--_Poverty_Note_36页_2mb

Summary of Alternative Social Safety Nets in South Sudan: Costing and Impact on Welfare Indicators

Core Content

This document explores the potential of implementing Alternative Social Safety Nets (SSNs) in South Sudan to reduce poverty and improve welfare indicators. It outlines the costs and impacts of different targeting strategies, including perfect targeting, universal targeting, geographic targeting, and proxy means targeting (PMT), and discusses how these can be used to build a more resilient and sustainable social protection system in the country.

Main Objectives

• To assess the monetary cost of implementing various SSN targeting schemes.
• To evaluate the impact of SSNs on poverty indicators, including incidence, depth, and severity.
• To provide policy guidance on the most suitable SSN approach for South Sudan, considering the country's context and limited institutional capacity.
• To support the development of a long-term integrated social protection system.

Key Findings

1. Context and Challenges

• South Sudan has been affected by ongoing conflict, repeated shocks, and historically low institutional capacity.
• The poverty rate increased from 50.6% in 2008 to 57% in 2015, with food insecurity also rising sharply.
• The oil price decline and conflict have significantly impacted the economy and welfare indicators, leading to economic instability and increased vulnerability.
• The Government lacks the capacity to implement large-scale SSN programs, and donors have traditionally funded such programs in a fragmented manner, with heavy focus on food distribution.

2. Types of Social Safety Nets

• Perfect targeting: Theoretical benchmark that reduces poverty headcount from 57% to 46% at the lowest cost (4.57% of GDP). However, it is not practical in South Sudan due to underreporting of income and informal economic structures.
• Universal targeting: Achieves the same poverty reduction as perfect targeting but at a higher cost (7.97% of GDP). It is feasible but inefficient.
• Geographic targeting: Reduces poverty by 7 percentage points (from 52% to 45%) at a cost of 4.57% of GDP. It covers 57% of the population and 72% of the poor, with a leakage rate of 31%. However, it is susceptible to political capture and may not effectively target vulnerable areas.
• Proxy Means Targeting (PMT): A more practical approach that reduces poverty to 51% at a cost of 4.57% of GDP. It covers 57% of the population and 77% of the poor, with a leakage rate of 31%. PMT is less discriminatory and more fair, as it uses proxy indicators to identify the poor, such as household characteristics.

3. Key Considerations

• Self-targeting mechanisms can help reduce leakage, but they may also deter poor individuals if too cumbersome.
• Rural poverty reduction is more expensive than urban poverty reduction due to the higher proportion of the population in rural areas and the need for larger transfers.
• A peaceful South Sudan with full oil extraction capacity could generate US$ 0.5 to 1.5 billion in annual net revenues, enabling self-sustaining SSN programs.
• The World Bank supports a dual-track strategy, combining short-term humanitarian and long-term development interventions, and emphasizes the need for strategic planning, capacity building, and rigorous impact evaluation.

Conclusion

The document concludes that proxy means targeting is the most suitable approach for South Sudan, given the challenges of perfect targeting and the high cost of universal targeting. It highlights the importance of targeting to reduce leakage, increase efficiency, and support long-term development. The analysis also underscores the need for policy coherence, technical know-how, and sustainable funding to build a robust social protection system in the country.

Key Figures and Tables

• Figure 1: Rural and urban poverty estimates from 2009 to 2015.
• Figure 2: South Sudan Food Security Index.
• Figure 4: Population shares by urban/rural and major towns.
• Figure 5: Internally displaced population and refugees (Dec 2013–Feb 2015).
• Figure 6: Poverty headcount, depth, and severity before and after the conflict.
• Figure 7: Poverty rate by counties (2008 & 2015).
• Figure 8–24: Simulated results for different targeting schemes, including cost as a percentage of GDP, coverage, leakage, and impact on poverty indicators.

Policy Implications

• SSNs can help reduce dependency on humanitarian aid and alleviate reliance on patronage networks.
• Targeting should be carefully designed to ensure effectiveness and equity.
• PMT is recommended as a practical and fair alternative for targeting the poor in South Sudan.
• Long-term planning is essential to create a coherent and sustainable social protection system.