Transcript Applications in World Bank Operations

Socioeconomic Benefit Analysis:
Applications in World Bank Operations
Daniel Kull
Global Facility for Disaster Reduction and Recovery (GFDRR)
The World Bank
Geneva, 8 April, 2013
Meeting of the WMO Forum:
Social and Economic Applications and Benefits of
Weather, Climate and Water Services
Modernization of NHMSs
• NMHS capacity often not adequate and considerably degraded
during the last 15-25 years.
• Since 1990s World Bank invests in modernization of NHMSs,
currently scaling-up system-wide investments .
• International support is still significantly below priority needs – high
World Bank client demand.
• International support in NMHS modernization in developing
countries so far largely unsuccessful due to:
– Lack of government understanding of NMHS’s value and
commitment to maintain NMHS operations.
– Poor project design (reliance on unsustainable solutions,
inadequate attention to capacity building, limited scope of
investment, etc.).
– Inadequate coordination among donors.
– Technical complexity and small size of the projects.
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Key Principles for Modernizing NMHSs
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Modernization of NMHSs in developing countries is a high value investment,
providing a positive return to the national economy, while improving public
safety and security.
The financing and scope of modernization must be sufficient to be
transformative.
Clear legal and regulatory frameworks for providing weather, climate, and water
services – which articulate the roles and responsibilities of the NMHSs –
increase effectiveness.
Large-scale modernization programs should typically include three
components:
– Institutional strengthening, capacity building, and implementation support
– Modernization of observation infrastructure and forecasting
– Enhancement of the service delivery system
Modernization of NMHSs should be considered within the wider regional and
global context.
The World Bank and development partners have a vital role in strengthening
NMHSs.
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Source: World Bank (2013). "Weather, Climate and Water Hazards and Climate Resilience:
Effective Preparedness through National Meteorological and Hydrological Services“ (in press).
Justifying and Leveraging Investment
• Better estimates of the socioeconomic
costs and benefits of NHMSs needed for
financing approvals.
• Better communication of such results
needed.
• Concerned NHMSs and governments
directly requesting support for such
analysis.
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Development Context
• Risk reduction benefits = avoided or reduced potential damages.
• Enhanced productivity of weather/climate-sensitive sectors.
• Weather extremes are stochastic events, so most benefits are
probabilistic.
• Need to account for changes due to current and future climate,
socioeconomics, land-use and other trends.
• Socioeconomic vulnerability and productivity are multidimensional
concepts encompassing a large number of factors.
• Challenges:
– Lack of data.
– Lack of expertise.
– High resource demands.
– Uncertainties in future conditions.
– Exposure of people, assets and environment difficult to quantify.
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Specific NHMS Challenges
• Lack of established techniques of economic assessment
understandable to NMHS staff.
• Lack of in-house economic expertise.
• Lack of baseline economic data, particularly data on
losses from weather events.
• Insufficient priority attached to economic assessment by
some NMHS management.
• Poor interactions with clients/beneficiaries.
• Lack of resources for studies.
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Summary of Utilized Approaches
World Bank projects use a combination of:
• Sector-specific assessments
• Customized sociological surveys
• Simplified benchmarking
• Probabilistic assessment of avoided
damage and loss
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Sector-specific Assessment
Data collection and/or surveys of experts:
•Level of damages and losses from hazardous weather events and
adverse weather conditions;
•Estimated changes in preventable damage and losses due to a more
accurate and timely information/forecasts.
Evaluate marginal effects from modernization for each sector and
the integral effect for the economy:
•Dependence on weather conditions and hazards, amount and quality
of information used, and current efficacy of information uses.
•Potential demand for information types and presentation formats,
accuracy and timeliness of each element/event forecast, requirements
for optimal performance, recommendations and proposals on service
improvement and customization.
Source: World Bank (2008). Weather and Climate Services in Europe and Central Asia: A
Regional Review. World Bank Working Paper No. 151., Washington, D.C., pp. 70.
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Customized Sociological Survey
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Captures household benefits.
Based on contingent valuation approach.
Customized for national context.
Willingness-to-pay for:
– Detailed weather forecast for the next month
– NHMSs out of own pocket
– Insurance against weather-related disasters
• Limited by partial inconsistency with economic
models of rational choice and unavoidable biases.
Source: World Bank (2008). Weather and Climate Services in Europe and Central Asia: A
Regional Review. World Bank Working Paper No. 151., Washington, D.C., pp. 70.
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Simplified Benchmarking
Stage 1
•Parameters set to average values, scaled to national GDP.
– Average annual losses from adverse and dangerous weather conditions:
0.45% of GDP; range of annual losses: 0.1 to 1.0 % of GDP.
– Average annual level of preventable weather losses: 40% of total losses
– Weather sensitive sectors of the economy: 50% of GDP
– Share of agriculture: 15% of GDP
– Meteorological vulnerability: “average”.
– Status of hydrometeorological service provision: “satisfactory”
Stage 2
•Benchmarks adjusted following rapid assessments of national
context.
•Adjusted benchmarks used to assess the marginal efficiency of the
existing NMHS and of modernized services.
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Source: World Bank (2008). Weather and Climate Services in Europe and Central Asia: A
Regional Review. World Bank Working Paper No. 151., Washington, D.C., pp. 70.
Example: Europe and Central Asia
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Source: World Bank (2008). Weather and Climate Services in Europe and Central Asia: A
Regional Review. World Bank Working Paper No. 151., Washington, D.C., pp. 70.
Probabilistic Avoided Damage and Loss
• Probabilistic risk assessment
• Assumptions on potential damage and loss
reduction due to modernized NHMS services
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Source: G20 - Mexico & World Bank: Improving the Assessment of Disaster Risks to Strengthen Financial
Loss-frequency curve
• Also called “Exceedance
probability curve” represents
the relationship between
disaster frequency and
severity.
• Area under the lossfrequency curve = Average
Annual Losses (AAL)
• For this example:
AAL = $12’900/year
• Eliminate losses up to $25’000,
then AAL = $4’200/year
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Yemen example
Hazard
Flood
Storm surge
Landslide
Tsunami
Dust storm
Total
Annual Damage
(USD mn)
74
1.0
0.005
0.83
5.08
80.7
Loss reduction
%
USD mn
5%
3.69
5%
0.05
5%
0.0002
5%
0.04
2%
0.1
3.88
Combined with
economic
productivity
increases based on
benchmarking
approach
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Pragmatic Approach
Project phase
Purpose
Resources
Identification
Provide broad overview of costs and
♦
benefits
Preparation
Identify most effective measures for
further more detailed evaluation
Appraisal
Detailed evaluation of accepting,
modifying or rejecting project
Evaluation (ex-post)
Evaluation of project after completion
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Based on: Kull, D., Mechler, R. and Hochrainer, S. (2013). “Probabilistic Cost-Benefit Analysis of Disaster
Risk Management in a Development Context.” Disasters, doi: 10.1111/disa.12002.
Overcoming Challenges: Transparency
Consistent approaches/frameworks to identify and communicate:
• Analysis methods.
• Key data, their reliability and sources.
• Externalities and how these are incorporated.
• Assumptions and the basis on which they are made.
• Sensitivity analysis and their implications for the results.
Building the basis for evaluating the validity of the results:
• Issues such as willingness to take action, warning reliability and
potential costs of taking inappropriate action.
• Distributional aspects.
• Conservative analysis comparing the lowest potential benefits with
the highest potential costs instills greater confidence.
Source: Moench, M. and The Risk to Resilience Study Team (2008). Understanding the Costs and Benefits
of Disaster Risk Reduction under Changing Climatic Conditions, From Risk to Resilience Working
Paper No. 9, eds. Moench, M., Caspari, E. & A. Pokhrel, ISET and ProVention, Kathmandu, 38 pp.
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Looking Ahead
• Closer collaboration between World Bank, WMO &
members, and other partners on NMHS modernization,
including socioeconomic benefit analysis (SEB).
• Joint development of guidance on SEB for weather,
climate and water services for World Bank staff and
clients, also in support of WMO commitments.
• More robust investigation and global database on
baselines for benchmarking.
• Technical support and capacity development for NHMSs to
perform SEB also to strengthen user engagement.
• Joint advocacy to raise profile and recognition of NHMSs’
added value with government, public, media, etc.
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