-
Financial Management of Flood Risks in Developing CountriesRisk
Sharing and Risk Transfer
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DISASTER LOSSES ARE ON THE RISE Source: MunichRe (2000)
Chart14
276.871.1
4711.7127.8
6324.7198.6
86109.1607
Number of events
Insured Losses
Economic Losses
Losses in USD billions
Number of events
Chart1
276.871.1
4711.7127.8
6324.7198.6
86109.1607
Number of events
Insured Losses
Economic Losses
Number of great natural disaster eventsand Losses in USD
billions.
Sheet1
Number of eventsInsured LossesEconomic Losses
1960s27771
1970s4712128
1980s6325199
1990s86109607
1950s20040
Sheet1
000
000
000
000
Number of events
Insured Losses
Economic Losses
Number of great natural disaster eventsand Losses in USD
billions.
Chart5
000
000
000
000
Number of events
Insured Losses
Economic Losses
Losses in USD billions
Number of events
Chart6
2050
570
760
1740
2640
580
Loss events
Loss events (8,350)
Chart7
339430
10910
6820
112380
409790
16480
Economic Losses in USD millions
Economic Losses (USD 896 billion)
Chart8
116940
420
610
29990
17640
4330
Insured Losses in USD millions
Insured Losses (USD 170 billion)
Sheet2
36930
35540
22390
7900
429090
4390
Fatalities
Fatalities (536,250)
Sheet3
Loss eventsEconomic Losses in USD millionsInsured Losses in USD
millionsFatalities
N. America2,050339,430116,94036,930
S. America57010,91042035,540
Africa7606,82061022,390
Europe1,740112,38029,9907,900
Asia2,640409,79017,640429,090
Austral.58016,4804,3304,390
2050
570
760
1740
2640
580
Loss events
Loss events (8,350)
339430
10910
6820
112380
409790
16480
Economic Losses in USD millions
Economic Losses (USD 896 billion)
116940
420
610
29990
17640
4330
Insured Losses in USD millions
Insured Losses (USD 170 billion)
36930
35540
22390
7900
429090
4390
Fatalities
Fatalities (536,250)
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Country Vulnerability is KeyCountries that can afford their
risks, eg AustriaCountries that can afford their risks, but with
regions that cannot, eg HungaryCountries that cannot afford their
risks, eg El Salvador
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Chart1
360
575
585
6000
Linerooth & Quijano, IIASA (2000)
Estimated Total Direct Losses in USD millions(exchange rate at
time of disaster)
chart2
7401739407814
1760110013206820
3700
11000
Linerooth & Quijano, IIASA (2000)
Commercial / Industrial
Public
Residential
Agriculture
Estimated Total Direct Losses in USD millions(exchange rate at
time of disaster)
Chart3
15.175.7420.09Northridge '94
6333154
42
115
Linerooth & Quijano, IIASA (2000)
Commercial
Public
Residential
Agriculture
Estimated Total Direct Losses in USD billions (exchange rate at
time of disaster)
Chart4
1927
34057
84844
123058
301654
390.160.9
301060
Linerooth & Quijano, IIASA (2000)
insured losses
state aid
non-reimbursed
Percentage of Losses reimbursed and not reimbursed
Chart5
390.160.9
301060
123058
34057
301654
84844
14148
Linerooth & Quijano, IIASA (2000)
insured losses
state aid
non-reimbursed
Percentage of Losses not reimbursed
Chart6
199
397
892
1288
3070
3070
3961
Linerooth & Quijano, IIASA (2000)
insured losses
uninsured losses
Percentage of Total estimated Losses which were uninsured
Chart7
7401739407814
1760110013206820
168004620205800
6325033350149503450
Commercial / Industrial
Public
Residential
Agriculture
Estimated Direct Losses by Sector in Percent
Chart8
14257
34057
84844
123058
301060
331651
390.160.9
insured losses
state aid
non-reimbursed
Losses reimbursed from insurance and government assistanceas a
percentage of AREDL
Chart9
99
97
92
88
70
67
61
60
Uninsured Losses as a Percentage of AREDL
Chart10
2.7877697842
2.3560696991
0.6045775155
0.5462141795
0.1677315076
0.0417860554
0.0316967257
0.0158977917
Direct Losses (AREDL) as a Percentage of Country year GDP
Sheet1
total lossesuninsured losses %uninsured lossesinsured losses
%insured losses
rhine 953606021640144
rhine 9357570402.530172.5
easter58561356.8539228.15
umbria6000995940160
poland37009234048296
midwest11000889680121320
northridge4180070292603012540
kobe110000971067003330064020
total174020155959.3518060.6514760.65
percentage insured losses of total (incl. Kobe)10.4
percentage insured losses of total (excl. Kobe)23.1
Chart11
14257
34057
84844
123058
301060
331651
390.160.9
insured losses
state aid
non-reimbursed
Losses reimbursed from insurance and government assistance as a
percentage of AREDL
61%
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The Upper Tisza
Study___________________________________________________________________________________________________________________
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Public/Private Insurance
System___________________________________________________________________________________________________________________
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_1091110845.doc
Figure 6: The Dominican Republic's Financing Gap (Financial
Vulnerability)
0
0
1148
0
500
1000
1500
2000
2500
3000
1-in-20
years
1-in-50
years
1-in-100
years
probability of occuring
USD
Mill.
Shortfall
External credit market
External credit IDB/WB
Domestic credit
New taxes
Budget realloc
Aid
_1091863677.doc
El Salvador's Financing Gap
(Financial Vulnerability)
0
0
1148
0
500
1000
1500
2000
2500
3000
1-in-20
years
1-in-50
years
1-in-100
years
probability of occuring
USD
Mill.
Shortfall
External credit market
External credit IDB/WB
Domestic credit
New taxes
Budget realloc
Aid
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Pre- and Post-Disaster Financing Options(Mitigation)Catastrophe
fundInsuranceOther hedging instruments, eg Cat bondsContingent
creditBudget diversionsBorrowinginternalexternalLoan
diversionsTaxesAid
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Stability vs. Growth
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Catch 22The countries that can benefit from pre-disaster
financing instruments are those that can least afford it.
Challenge:
Can we design new forms of "pre-disaster" aid to developing
countries that willenable them to insure against disaster risks,
and that link this insurance with loss mitigation measures?
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ProposalTo transfer developing country risks into the global
financial markets through
International financial institutionsPrivate "charitable"
investorsInstitutional "charitable" investors
