Measuring Up: How Do We Align Aid With Priorities? David Wheeler - PowerPoint PPT Presentation

Measuring Up: How Do We Align Aid With Priorities? David Wheeler Center for Global Development

Allocation Calculus N    W R Objective Function 0 i  1 i    S = Scale of donor activity V i p R S 1 i Vulnerability Reduction V = Scale of vulnerability i 0 i p = Project success prob. N   c = Unit cost of donor activity c B I Budget Constraint i i T I = Total sectoral budget  i 1 N      V p W S 1 i i Welfare Function 0 0 i  1 i * S V p  i i i First-Order Conditions * V p S j j j

Allocating Resources: Where? How Much? Main Ideas • Some Representation for All Countries • Policies and Institutions (PI) Affect Project Outcomes • Likelihood of Project Success is Proportional to PI • Valuation of Impacts is the Same Everywhere

Allocating Resources: Where? How Much? If we expect all projects to succeed: Country Share of Country Share = Total Investment of Total Problem To account for different success rates: Country Share Country Share of = of Total Problem, Total Investment Weighted by Success Rate

Measuring Up: World Bank Investment Priorities 2000-2004

Deaths From Waterborne Disease

Effectiveness of Policy and Institutions: CPIA Ratings

Probability of Project Success: OED Ratings

Optimal Water and Sanitation Investment

Actual Water Supply and Sanitation Loans* *Investments included are the environmental components, including non-bank co-financing of currently active World Bank water supply and sanitation projects and urban environmental projects and a fraction of environmental institutional development projects.

Overall Impressions • Problems Have Very Different Patterns • Big Gaps Between Actual & Optimal • Actual Loans Are Too Concentrated • Some Regional Imbalances Are Clear

Measuring Up: GEF Resource Allocation 2004-2005

Combined Biodiversity Threat Areas

WWF Ecoregions

Measuring Up: Allocating Adaptation Assistance 2011

Sea-Level Rise, 2007 - 2100 LDC Population Displaced (Millions) 300 250 200 150 100 50 0 1 2 3 4 5 Sea-Level Rise (Meters)

Agricultural Productivity Loss: 2008-2080 (IPCC Model A2) Losses 25+ % 15-25% 5-15% 0-5% Gains 25+ % 15-25% 5-15% 0-5% Not Source: Global Warming and Agriculture: Available Impact Estimates by Country William R. Cline CGD, 2007

Projected Agricultural Productivity Through 2080 Developing-Country Regions and Sub-Regions* Productivity Loss (%) 60 45 30 15 0 -15 0 20 40 60 80 100 Country Rank * William R. Cline, Global Warming and Agriculture (2007)

Flood Risk Damage Index, 1960-2000 Distribution of Developing Countries* 1000 800 600 400 200 0 0 20 40 60 80 100 Country Rank * Wheeler, Center for Global Development (2007)

Global Climate Risk, 1970-2008: Probability of Being Affected by an Extreme Weather Event* (Per 100,000) 4500 3500 2500 1500 500 1970 1975 1980 1985 1990 1995 2000 2005 * 11-Year Centered Moving Average

% of Countries With Extreme Weather Impacts 1970-2008* 70 60 50 Americas 40 Asia 30 Africa 20 Europe 10 0 1970 1980 1990 2000 2010 * 5-Year Moving Average

Adaptation to Climate Change: (1) Physical Impacts* Three Views of Assistance Priorities * Extreme Weather Sea Level Rise Agricultural Productivity Loss Source: Center for Global Development

Adaptation to Climate Change: (2) Vulnerability* Three Views of Assistance Priorities * Extreme Weather Sea Level Rise Agricultural Productivity Loss Source: Center for Global Development

Adaptation to Climate Change: (3) Project Factors* Three Views of Assistance Priorities * Extreme Weather Sea Level Rise Agricultural Productivity Loss Source: Center for Global Development

Africa: Physical Climate Impacts Source: Center for Global Development

Africa: Physical Climate Impacts Source: Center for Global Development

Africa: Physical Climate Impacts Source: Center for Global Development

Africa: Physical Climate Impacts Source: Center for Global Development

Measuring Up: How Do We Align Aid With Priorities? David Wheeler Center for Global Development