Indicators of Disaster Risk – Information Needs

Washington DC, August 18, 2005

Kari Keipi, IDBwww.iadb.org/sds/env

Risk Profile for Latin America and the Caribbean

During the past 30 years disasters have annually caused US3.2 billion in physical losses – half or more of the total annual loan commitment of the IDB in recent years.

Why the IDB has invested resources in developing DRM indicators:

To whom and for what?

The Bank is challenged to keep up with disaster losses experienced by its Borrowing Members.

The indicators developed is a necessary tool to generate knowledge and awareness of the importance of this risk both within the IDB and with borrowing governments and thus integrate DRM into the IDB’s Country Programming and portfolio management.

The “Americas Program” Indicators have on a pilot basis been developed for 12 countries.

Argentina, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Jamaica, Mexico, Peru, and Trinidad and Tobago.

Unlike most existing risk indices, the new indicators can be easily interpreted by a wide range of decision-makers in different fields, rather than only by experts.

Based on composite indicators, the system consists of four major measures. The Disaster Deficit Index The Local Disaster Index The Prevalent Vulnerability Index Risk Management Index (Institutional)

The Disaster Deficit Index

Formula: Macroeconomic loss / supply of funding.

Supply sources: Insurance Disaster reserve funds Aid and donations New taxes Budgetary reallocations External credit Internal credit

*****************Lesson learned: the person seeking for these data must

have training as an economist

The Disaster Deficit Index

DDI and probable maximum loss in 100 years

DDI100, 2000

0.10

0.31

0.37

0.41

0.76

0.86

1.14

1.33

1.77

1.90

2.45

3.53

0 1 2 3 4

ARG

GTM

CRI

CHL

TTO

MEX

ECU

COL

J AM

SLV

DOM

PER

L 100 (US$ million) 2000

187

431

852

800

350

6273

783

3254

845

3773

1361

4479

0 1000 2000 3000 4000 5000 6000 7000

Local Disaster Index The Local Disaster Index evaluates risks from the accumulated

damage caused by recurrent, small-scale disasters. The index takes into account three variables:

Deaths, Number of affected people, and Economic loss in housing and crops

***********************************Lessons learned: 1. Deaths and no. of damaged houses are the easiest to identify2. Official or published information has not necessarily been more

reliable than “informally” obtained data 3. EMDAT and DesInventar complement each other4. DesInventar has been a very useful source for municipal data for

Local Disaster Index

Local Disaster Index

LDI 1996-2000

19

46

65

58

82

90

33

43

67

74

25

24

12

2

44

35

13

42

78

61

84

20

11

4

15

59

20

41

75

39

50

41

32

0 50 100 150 200 250

TTO

J AM

PER

CRI

MEX

CHL

ECU

COL

SLV

DOM

ARG

GTM

IDL.K

IDL.AIDL.L

Prevalent Vulnerability Index PVI is an average of three types of composite indicators

Exposure and susceptibility (susceptible population, assets, investment, production, livelihoods, essential patrimony, and human activities)

Socio-economic fragility (poverty, human insecurity, dependency, illiteracy, social disparities, unemployment, inflation, debt and environmental deterioration).

Lack of resilience (inverted treatment of: human development levels, human capital, economic redistribution, governance, financial protection, collective perceptions, preparedness to face crisis situations, and environmental protection).

***********************Lessons learned:Continuous time series data on poverty and social disparities have been

the most difficult to obtain

Methodology Issues To whom and for what do we

develop/provide data and indicators? How do we define sub-indeces and weights? How is reliability or validity tested? Will the procedures be inductive or

deductive? Use of subjective data when objective

information is not available? Should all the data be quantitative?

Data Issues Which methods are available to

procure data when this is not officially published?

What methods are to be employed to ensure that data is comparable (between countries)?

What measures should be taken when data is missing?

How do we generate confidence in the estimates produced?

The extent to which the indicator represents reality and are relevant to development policy

Which are the exposed elements? (Stocks and flows, indirect impacts)

Distribution of losses? (public-private, poor-rich)

Relevance of maximum probable event vs. smaller often recurring event (the 500 year event vs. the 3 year event)?