世界发展银行-Socioeconomic-Resilience-in-Sri-Lanka-_-Natural-Disaster-Poverty-and-Wellbeing-Impact-Assessment_63页_2mb

Summary of Policy Research Working Paper 9015: Socioeconomic Resilience in Sri Lanka

Core Content

This paper introduces a new framework for assessing disaster impacts in Sri Lanka that goes beyond traditional asset loss metrics to include socioeconomic resilience and wellbeing losses. It highlights the limitations of focusing solely on asset losses and proposes a more comprehensive approach to evaluate disaster effects on poverty and wellbeing.

Main Viewpoints

• Traditional Risk Assessment: Relies on asset losses as the primary metric for disaster severity, which provides only a partial view of the total cost.
• Socioeconomic Resilience: A key component of the new framework, capturing the ability of households to maintain consumption, save or borrow for reconstruction, and cope with the decreasing returns of consumption.
• Wellbeing Losses: Reflect the total impact of disasters on individuals' quality of life, accounting for both direct and indirect effects such as lost income, consumption cuts, and delayed recovery.
• Disaster Impacts on Poverty: Flooding events can push tens of thousands of Sri Lankans into transient poverty, undermining recent progress in poverty reduction.
• Income and Consumption Poverty: These metrics reveal how disaster impacts are not only financial but also affect the ability of households to maintain basic needs and long-term development prospects.
• Spatial and Sectoral Analysis: Asset losses are highly concentrated in Colombo district, while wellbeing losses are more evenly distributed across the country.
• Cost-Benefit Analysis: The paper evaluates the effectiveness of adaptive social protection systems, such as the Samurdhi program, in reducing wellbeing losses and enhancing resilience.

Key Information

1. Asset Losses

• Concentration: Asset losses from precipitation flooding are heavily concentrated in greater Colombo, accounting for over 50% of total losses.
• District-Level Data:
  • Colombo: US$40.2 million
  • Rathnapura: US$8.19 million
  • Kalutara: US$7.43 million
  • Gampaha: US$6.93 million
  • Total: US$78.02 million

2. Wellbeing Losses

• Annual Estimate: US$119 million per year in average annual wellbeing losses due to fluvial flooding.
• Disproportionate Impact: The poorest quintile suffers 32% of total wellbeing losses despite only accounting for 7% of total asset losses.
• Recovery Time: The poorest districts take longer to recover from disasters, with coastal areas in the northern half of the country showing the slowest recovery.

3. Impact on Poverty and Prosperity

• Transient Poverty: Regular flooding can push over 5,600 Sri Lankans into transient consumption poverty annually.
• Long-Term Effects: Large-scale disasters, such as 50-year floods, can affect nearly 34,000 individuals and some may remain in poverty for up to 10 years.
• Vulnerability: Poor households are more likely to cut basic needs and suffer long-term wellbeing consequences due to limited access to financial tools like insurance, savings, and credit.

4. Adaptive Social Protection

• Samurdhi Program: Can act as an adaptive social protection system, providing emergency support to households affected by flooding.
• Benefits: Such systems can reduce wellbeing losses and enhance resilience, even without directly reducing asset losses.
• Cost-Benefit Analysis: Highlights the efficiency of targeted post-disaster support and the importance of inclusive policies that consider the needs of vulnerable populations.

5. Methodology

• Agent-Based Model: Used to simulate household-level recovery and reconstruction processes.
• Data Sources: Combines flood data from the SSBN model with household income and expenditure surveys (HIES).
• Wellbeing Function: A classical welfare function is used to translate consumption losses into wellbeing losses, incorporating decreasing returns to consumption.

6. Policy Implications

• Targeted Interventions: The framework supports more targeted and efficient disaster risk management (DRM) strategies.
• Resilience Building: Investments in financial inclusion, social safety nets, and disaster preparedness are essential to reduce the impact on the poor and vulnerable.
• Need for Disaggregation: Traditional metrics fail to capture the full scope of disaster impacts, emphasizing the need for disaggregated analysis at the household level.

Conclusion

This paper advocates for a shift in disaster risk assessment from asset losses to wellbeing losses, which provide a more accurate measure of disaster impacts on the poor and vulnerable. By integrating socioeconomic resilience, the analysis offers a new perspective on disaster management, highlighting the importance of inclusive and adaptive social protection systems in mitigating the long-term effects of natural disasters on poverty and shared prosperity in Sri Lanka.