Download Teil I - IIASA

Modelling, Measuring and Managing of Extreme Risks
Vortragender: Dr. Mag. Stefan Hochrainer-Stigler
IIASA-International Institute for Applied Systems Analysis
Laxenburg, Austria
Website for ppt: http://user.iiasa.ac.at/~hochrain/KIT2013/
Allgemeines:
Vorlesung -> mündliche oder schriftliche Prüfung (80 Prozent)
Seminar -> ohne Prüfung, aber Vortrag (30 Prozent) und
Ausarbeitung (50 Prozent)
• Bachelor-Studierende einen Vortrag und arbeiten ihn schriftlich aus,
• Master- und Diplom-Studierende, erweiterte Seminararbeit.
Anwesenheitspflicht
Mitarbeit (alle) (20 Prozent): Selbständiger Versuch der Berechnung der Beispiele.
Überblick
Zeiteinteilung:
Dienstag: 20.05:
Teil I: 10:30-13:30: 3h -> 4 EH
Teil I: 14.30-16:45: 2h.15 ->3 EH
Teil II: 17.00-18.00: 1h->2 EH
Mittwoch: 21.05:
Teil III: 8:00-9:30: 1h.30 ->2 EH
09:30-12:30: 3 -> 4 EH
Teil VI: 13:30-15:00: 1.30 -> 2 EH
Teil IV: 15:00-18:00: 3h -> 4 EH
Donnerstag: 22.05:
Teil IV: Präsentationen: 8:30-14:45: 6h.15 -> 7 EH
Insgesamt: 28 EH
Überblick
Teil I:
• 4 Stunden: Einführung, Motivation, Risiko, Nutzenfunktion, Risikoaversion,
Prämien (Beispiele rechnen)
• 1.5 Stunde : Arrow Lind Theorem, Ausnahmen, Diskussion, Katastrophen, Naturkatastrophen
Teil II: Risikoinstrumente, Naturkatastrophen, Extreme, Maßzahlen
• 2.5 Stunde: Risiko öffentlicher Sektor etc. Einführung
• 2.5 Stunde: Risikomanagement Methoden (Beispiel rechnen)
• 1 Stunde: Versicherungslösungen für Katastrophen
Teil III:
• 2.5 Stunde: Extremwertstatistik I + II
• 2 Stunde: Katastrophenmodelle, Simulationsmethoden
• 1 Stunde: Fiskalische Risikomatrix
Teil IV:
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•
•
•
Spezialthemen
Anwendungsbeispiele
Aktuelle Anwendungs- und Forschungsgebiete
Abschliessende Diskussion
Motivation
Example Natural Disasters
• Only a few global databases of past natural
disaster events exist, most important ones
are.
- EmDat: The International Disaster Database CRED,
Catholic University of Louvain, Brussels (Belgium) ,
http://www.emdat.be, publish reports annually
- Munich Re: Special issue: Topics (published
annually)
- Swiss Re: Special issue: Sigma (published annually)
Munich Re: Topics, Swiss Re: Sigma
www.munichre.com
www.swissre.com
Motivation
• Different definitions of disasters:
Munich Re
SwissRe
Em-Dat
Adjustment for inflation
• Swiss Re example based on Floods in UK:
29 October-10 November 2000
EMDAT starts from 1900
* EM-DAT 2005
Munich Re Figures: 1980-2010
Munich Re 2011
Munich Re Figures
Munich Re 2011
Munich Re Figures
Munich Re 2011
Munich Re Figures
Munich Re 2011
Munich Re Figures
Munich Re 2005
Swiss Re: Insured Losses
Swiss Re 2011
Average losses per income group
*
250
Fatalities/event
200
150
100
**
50
0
High income
Middle income
Low income
Per capita income country groups
* NatCatService 2005
** NatCatService 2005
Average losses per income group
Losses as % of GDP
14
12
10
8
6
4
2
0
High income
Middle income
Low income
Per capita income country groups
* NatCatService 2005
** NatCatService 2005
Methodology for comparison
Hochrainer, 2006
Honduras
Impact of disasters on GDP growth in
Honduras
6.0
5.0
4.0
3.0
2.0
1.0
0.0
1996
1997
1998
1999
2000
2001
2002
2003
2004
-1.0
-2.0
Growth without Mitch or drought
Growth with Mitch and drought
1.Actual GDP growth in Honduras with events vs. projected growth without events
Source: Zapata, 2008
Honduras
GDP in Honduras
7,500
7,000
6,500
Indirect
development loss
6,000
Projected w/o event-ECLAC
Projected w/o event-IIASA
Observed
5,500
Observed GDP in Honduras with events vs. projected growth
without events. Source: Zapata, 2008; World Bank, 2007; own
calculations
1.GDP trajectories
Source: WDI, 2007; own calculations
2004
2003
2002
2001
2000
1999
1998
1997
5,000
1996
Million constant 2000 USD
8,000
Direct effect due
to wealth loss
Currently Paradigm shift
Government assistance
(taxes)
Kinship arrangements
Donor assistance
Reactive
Traditional approach to risk
financing
Insurance and reinsurance, microinsurance
Catastrophe bond, weather derivatives
Contingent credit, reserve fund
Proactive
Turkey: Insurance Pool (2000)
India: Weather derivatives (04)
Mexico: Cat bond (06)
India, Colombia, Mexico etc: Funds
Colombia: Contingent credit (05)
Caribbean: Regional insurance pool (2006)
Pacific: Regional insurance pool (in the
making)
Global: GFDRR, GIRIF (2008)
All with donor support
Planning and mainstreaming disaster risks into
developmental planning
Planning disaster risk into
development
Source: Bettencourt et al., 2006
Planning and mainstreaming disaster risks into
developmental planning
Planning disaster risk into
development
Source: Bettencourt et al., 2006
Planning and mainstreaming disaster risks into
developmental planning
Planning disaster risk into
development
Source: Bettencourt et al., 2006
Planning and mainstreaming disaster risks into
developmental planning
Planning disaster risk into
development
Source: Bettencourt et al., 2006
Planning and mainstreaming disaster risks into
developmental planning
Planning disaster risk into
development
Source: Bettencourt et al., 2006
Planning and mainstreaming disaster risks into
developmental planning
Planning disaster risk into
development
Source: Bettencourt et al., 2006
Planning and mainstreaming disaster risks into
developmental planning
Planning disaster risk into
development
Source: Bettencourt et al., 2006
Planning and mainstreaming disaster risks into
developmental planning
Planning disaster risk into
development
Source: Bettencourt et al., 2006
Planning and mainstreaming disaster risks into
developmental planning
Planning disaster risk into
development
Source: Bettencourt et al., 2006
Planning and mainstreaming disaster risks into
developmental planning
Planning disaster risk into
development
Source: Bettencourt et al., 2006
Planning and mainstreaming disaster risks into
developmental planning
Source: Bettencourt et al., 2006
Planning and mainstreaming disaster risks into
developmental planning
Source: Bettencourt et al., 2006