2025-06-02-世界银行-全球社会经济对自然灾害的抵御能力（英）_60页_6mb

Summary: Global Socio-economic Resilience to Natural Disasters

This report examines the impact of natural disasters on global well-being and socio-economic resilience, using a novel microsimulation model across 132 countries.

Key Findings

• Traditional risk assessments focus on physical asset losses, while this study introduces well-being losses and socio-economic resilience:
  • Socio-economic resilience measures the ratio of economic asset losses to resulting well-being losses
  • Higher-income countries demonstrated greater resilience, while low-income countries experienced disproportionately higher well-being impacts
• On average, $1 in asset losses equates to $2 in national consumption drops in terms of well-being loss
• The poorest 20% of households incur 9% of national asset losses but account for 33% of well-being losses

Methodology

• Uses a microsimulation model with 5 income quintiles per country
• Incorporates innovative approach to translate asset losses into well-being impacts through consumption and utility functions
• Leverages data from:
  • Global Infrastructure and Resilience Index (GIRI)
  • World Bank Poverty and Inequality Platform
  • Findex Database
  • Penn World Table
  • Early warning system indicators

Socio-economic Resilience and Inequality

• Resilience decreases with greater income inequality (negative correlation exists)
• Countries with robust social protection systems and higher financial inclusion show enhanced resilience
• Recovery times vary by country income level and household wealth:
  • High-income countries recovered 36-28% faster than low-income countries across all hazards
  • Within countries, wealthier households generally recover faster

Policy Evaluation

• Simulated 10 policy options categorized into:
  1. Asset-focused measures (reducing exposure/vulnerability)
  2. Structural socio-economic changes (income growth, employment, diversification)
  3. Risk finance options (post-disaster support, insurance)

Most Effective Policies:

• Post-disaster support targeting poor households (40% of asset losses) offers $10.58 in benefits per dollar in LICs
• National insurance covering 20% of asset losses provides $7.11 in benefits per dollar
• Reducing self-employment rates (policy option 7) yields substantial gains in LICs
• Income diversification (option 8) and formal employment promotion (option 7) significantly improve resilience

Global Risk Data

• $314 billion in global asset losses estimated
• $620 billion in global well-being losses calculated
• Average global resilience stood at 51%
• LICs showed limited resilience capacity (36%), while HICs demonstrated up to 76% resilience

Limitations and Future Directions

• Model assumes constant elasticity in consumption
• Simplifications exist in supply chain impacts and minimum subsistence lines
• Liquidity estimation represents lower bounds
• Limited country coverage due to data scarcity
• Validation challenges exist due to unobservability of well-being metrics

The study emphasizes that targeting the poorest populations yields higher returns on investment for disaster risk reduction, particularly for cash transfer programs. The metric of well-being losses complements traditional asset-focused approaches in evaluating intervention effectiveness.