1. United Nations
Development Programme
Building capacities for increased public investment in integrated climate change adaptation and disaster risk reduction:
Regional Workshop on Probabilistic Risk Assessments
Bangkok, October 15-17, 2014

2. Global Assessment Report
The Global Assessment Report has, since 2009, produced information on countries’ risk.

3. Building capacities for unified climate change adaptation (CCA) and disaster risk reduction (DRR)
3-year initiative by UNISDR in partnership with UNDP to strengthen capacities for disaster risk management
Objectives:
Increasing Loss & Risk Knowledge
Improving decisions to invest scarce resources in DRR and CCA
Risk-Proofing public investment in DRR and CCA
Analyzing DRR/CCA investment portfolios and prioritizing actions (Cost Benefit Analysis of risk reduction investments)
Defining DRM/CCA strategies: how much risk should be reduced, how much retained and how much transferred

4. Implemented in 3 independent but tightly interrelated components **
Disaster loss and damage accounting:
40 New National Disaster Loss Databases
2. Probabilistic Risk Profiles and Assessments:
30 New Country Profiles
3. Increased risk-sensitive planning and investment:
20-30 Policy dialogs with countries**
** Which should open the door for the implementation of many other risk management tools

5. Implemented as parallel process in 6 Regions
LAC:
Mexico, Panama, Guatemala, Costa Rica, Colombia, Peru (now in C3)
Caribbean Region:
7 East Caribbean Countries, Via partnership with UNDP and with GFDRR ACP/EU funding
Indian Ocean Comission:
4 member states in the Indian Ocean Commission IOC (Madagascar, Mauritius, Seychelles, Comoros and Zanzibar), plus Tanzania, Rwanda and/or Malawi
Asian Region:
Myanmar, Cambodia, Laos, Mongolia, Maldives and Sri Lanka in Asia (UNDP-APCR partnership) and Pakistan (with WB).
Pacific Region:
A regional system (20 countries) plus 2 to 4 drill down countries in the Pacific. Fiji, Solomon, and PNG, are initially identified via partnership with SOPAC/SPC.
West Africa and IOC:
Niger, Burkina-Faso, Sénégal, Togo, Mali, and Sierra Leone, via partnership with UNDP

6. A large number of locally recruited data collectors and specialists
Component 1: disaster loss data collectors, researchers, environment and IT specialists, DM staff
Component 2: probabilistic risk specialists, with knowledge in engineering, GIS and possibly hazard/risk modelling)
Component 3: specialists with knowledge in economics, public finance and public policy
Countries will/have received from UNISDR/UNDP the proposed profiles for the data collectors and specialists.

7. Example Timeline of activities: country

8. COMPONENT 1

9. Typical contents of a DesInventar Disaster database
The actual screen for data capture.
It can be customized by users.
Standard Effects (killed, injured, affected, etc.)
Extension (Sectorial detail information)

10. National Disaster databases
Disaster Inventories record and analyse the occurrence and effects of natural disasters
Disaggregated information is provided in tabular and graphical form (maps and charts)

11. Madagascar: Historical Loss Profile
Composition of disasters: frequency by hazard
Data for
Composition of disasters: mortality by hazard.
Composition of disasters: economic loss of disasters by hazard.

12. Madagascar: Empirical Loss Profile
Spatial Distribution
Spatial distribution of economic loss from disasters ( )
Spatial distribution of Mortality from Cyclone disasters.

13. Loss exceedance curve – Empirical
Madagascar
Loss exceedance curve – Empirical 13

14. Component 1:
Disaster loss and damage accounting
National Workshops Loss data
Past Disaster Loss Data Collection/Validation
Analysis/estimation of economic losses
Resources: trainers, data collectors, analysts

15. COMPONENT 2

16. HAZARD: Constructed from Global model

17. Exposure and Vulnerability: enriched and validated with country level data

18. Vulnerability functions for all Hazards and selected structural types
Vulnerability is represented using mean damage ratios and variance values at different hazard intensities for each characteristic construction type
Vulnerabiltiy functions link the intensity of the hazard with the degree of loss of the exposed asset. Each of these measure is not deterministic, as each point of the curve is associated to a probability distribution (usually a gamma distribution) 18

19. Loss Exceedance Curve Mauritius (proxy)
Results: Essential risk metrics: Annual Average Loss, Probable Maximum Loss, Pure Risk Premium…
Loss Exceedance Curve Mauritius (proxy)
Hazard
AAL (Mill US$)
Wind
182.67
Earthquake
-----
Total 19

20. Madagascar: Probabilistic Loss Profile AAL spatial distribution
Historical economic loss distribution
( )

21. Results: AAL per district Mauritius (proxy)

22. Results:
PML Curve Mauritius 22

23. Results: Integrated analytical and empirical (“Hybrid”) curves
Results: Integrated analytical and empirical (“Hybrid”) curves. Seychelles
Seychelles
Hazard
AAL (Mill US$)
Wind
0.59
Earthquake
Total
Empirical AAL:
(independent set or hazards,
not cyclone/earthquake)
TOTAL AAL : Million USD
(aprox) 23

24. Probabilistic Risk Profiles and Assessments
Component 2:
Probabilistic Risk Profiles and Assessments
Hazard Training Regional workshop
Hazard data collection/processing
Exposure/Vulnerability Regional workshop
Exposure/Vulnerability data collection/processing
Risk model and follow-up Regional workshop
Generation of hybrid loss exceedance curves/model

25. COMPONENT 3

26. What has been lost & how much can be lost
Component 3:
Mainstreaming Risk Knowledge into Public Investment and Planning.
From Components 1 and 2:
What has been lost & how much can be lost
Component 3 will focus on public investment in DRR and work closely with Ministry of Finance or Planning.
The aim is to determine the impact of DRR on economy, identify the impact of DRR investment policy using CBA, look at optimal use of resoueces and help countries consider strategy for risk proof public investment.
More concretely, what we aim to implement in this component is the capacity building for policy impact analysis at macro and micro levels, investment tracking, and multi-stakeholder discussion on risk sensitive public investment planning.

27. Mainstreaming Risk Knowledge into Public Investment and Planning.
Component 3:
Mainstreaming Risk Knowledge into Public Investment and Planning.
Working with Finance and Planning entities on
Determining impact of Disasters and DRR on Economy
Identifying impact of DRR investments (Cost Benefit analysis)
Looking at optimal use of resources and tools (Risk Reduction, Retention, Transfer, etc.)
Use Cases: risk-proofing public investment
Component 3 will focus on public investment in DRR and work closely with Ministry of Finance or Planning.
The aim is to determine the impact of DRR on economy, identify the impact of DRR investment policy using CBA, look at optimal use of resoueces and help countries consider strategy for risk proof public investment.
More concretely, what we aim to implement in this component is the capacity building for policy impact analysis at macro and micro levels, investment tracking, and multi-stakeholder discussion on risk sensitive public investment planning.

28. Risk curve gives insights on DRM strategy…
Extensive
Extensive
Risk
Layer:
Risk reduction
Middle
Risk
Layer:
Risk avoidance
Contingency budget & credit
High
Risk
Layer:
Transfer
Intensive
The important link between component 1 and 2 is that risk profile gives an important insight for the total scale of DRM finance and allocation of money between several risk management techniques, because appropriate policies are different depending on risk layers.
For small scale but frequent risk which we call extensive risk, it is known that disaster risk reduction is the most cost-effective. On the other hand, to prepare for large but infrequent risk which we call intensive risk, insurance is better be applied. Countries need to consider all risk layers they are facing and create a comprehensive strategy addressing all risk layers.
In this initiative, UNISDR’s focus would be more concerned about extensive risk and DRR investment while the World Bank promotes risk transfer to address high risk layers. The division of labour between the WB and us is clear and it is complementary.
Residual
Risk

29. Scenario 1 (strong DRR) DRR makes risk curve move inward… Scenario 2
(New risk generation)
Scenario 1
(strong DRR)
In target countries we are emphasizing that the risk curve is not fixed. Risk curve is calculated based on current hazard, exposure and vulnerability. If countries think in longer perspective, they can move this curve inward. If the country invests in DRR strongly, then the curve moves inward, which means decrease of expected loss for every levels of frequency.
But if the country does not invest in DRR, then considering current trend of urbanization and economic growth all over the world, it will increase exposure and vulnerability and make the curve outward, which should be avoided for future generations of the country.

30. Impact of DRR on Macro-Economy
JICA DR2AD Model: Pakistan GDP growth estimate
To measure the impact of DRR investment on macro-economy, we have been discussing with JICA on the application of their econometric model called DRAD model. By using the model, we can produce graph like this. Blue and red lines estimate the Pakistan GDP with impact of disaster while the black line shows GDP without impact of disaster. As you see, disaster will impact negatively on GDP in Pakistan, though DRR investment mitigates the negative impact to a certain degree. The strengths of JICA model is its link with MDG because they can also measure the impact of disaster and DRR investment on income distribution.
We are also discussing with IIASA on the application of their CAT SIM model. The strengths of the model is its ability to measure the impact of disaster on public finance and he impact of fiscal gap on macro-economy.
In both models, we utilize loss and risk data from component 1 and 2 as input to produce such economic estimate. The figure like this will be useful for convincing politicians and general public for more investment in DRR. Depending on the regions and discussion with IIASA and JICA, we will apply the DRAD or CAT SIM model.
Source: provided by JICA 30

31. Cost benefit analysis of DRR policy
B/C = Sum of benefits in all project periods/
Sum of costs in all project periods
Benefit = avoided loss
Cost = investment cost + maintenance cost
Discount rate = interest rate, social discount rate
Benefit cost ratios
At micro level, the representative analytical methodology is CBA. CBA is based on the simple principle: If the benefit cost ratio is more than one, then invest. Out of multiple such projects, the higher B/C ratio is, the more preferable the project is. The CBA is not perfect but one of the most important tools for financial decision making around the world and probabilistic cost benefit analysis is being developed and applied in many cases.
The strengths of the CBA is its ability to compare several options. For example, in reducing flood loss, the practical issue that financially constrained government often face is which option they put priorities….EWS, evacuation planning, sea wall construction, building retrofitting etc.. Or in countries that face several hazards, questions are whether to put priorities on risk reduction in earthquake, flood, or cyclones etc…
CBA is an useful tool to provide insights on such prioritization issues. Using risk and exposure data developed in component 1 and 2, we will help countries implement CBA case studies. 2 3
Source: Wethli 2013 cited by the World Bank 31

32. Budget Analysis in Latin American Countries
Country
Report
year
DRR and prevention
Relief and reconstruction
Total
(%)
Bolivia
2011
0.150
Chile
0.030
2013
0.040
Colombia
0.115
0.520
Dominican Republic
0.050
1.000
1.050
Ecuador
0.300
1.600
1.900
El Salvador
0.001
Mexico
0.100
3.100
3.200
Peru
0.180
2012
1.100
Another problem we identified in public investment planning is that many countries do not know how much they actually invest in DRR at this moment. Without knowing current status, how can they make better investment planning? The table shows the DRM budget compared to total budget in LAC countries. The number is taken from HFA Progress Report. Because we do not know how they estimated or counted the percentage, it is not comparable across countries. Still, the number is very insightful. That DRR is much smaller than relief and reconstruction in most countries. We will research their tracking methodologies and other financial tracking system, for example, Rio Marker developed by the OECD to monitor ODA for climate change adaptation and find the common ground which can be utilized as a standard to make possible DRR investment tracking in many countries.
Source: HFA Progress Report 32

33. Summary of Good Practices in Latin American Countries, 2014
COL
CRI
GTM
MEX
PAN
PER
Risk analysis implemented before public investment Y N
Manuals and trainings
DRR Budget tracking
Risk financing instruments (e.g. insurance)
The table shows the summary of good practices by LA country. As you see, country has strengths in different policy and lacks attention or progress in some aspects. Important thing is to advocate these policies “in package” and systematically apply several policies which countries think important and appropriate depending on their needs. We are now collecting manuals, check sheets, training programmes so that we can utilize Latin America and other advanced experience in all target regions.
Source: UNISDR survey (2014) 33

34. Component 3: Increased risk-sensitive planning and investment
1st Regional Workshop on theory
Socio-economic-financial data collection and implementing economic and financial analysis
2nd Regional Workshop on practice
National workshop for mobilizing all stakeholders and raising awareness on the importance of DRR investment
Regional event for dissemination of all results of DEVCO initiatives
We will implement two regional workshops and 1 national workshop for each participating country. Regional WS focuses on capacity building and national workshop is designed more for mobilizing stakeholders and enhancing awareness. As a concluding event, we also deliver regional event.

35. THANK YOU http://www.preventionweb.net/gar http://www.unisdr.org