Modelling, Measuring and Managing of Extreme Risks
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.
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/
Zeiteinteilung:
Dienstag: 20.05:Teil I: 10:30-13:30: 3h -> 4 EHTeil I: 14.30-16:45: 2h.15 ->3 EHTeil 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 EHTeil VI: 13:30-15:00: 1.30 -> 2 EHTeil 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:• Spezialthemen• Anwendungsbeispiele • Aktuelle Anwendungs- und Forschungsgebiete• Abschliessende Diskussion
Überblick
MotivationExample 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
• Different definitions of disasters:
Motivation
Munich Re
Em-Dat
SwissRe
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
0
50
100
150
200
250
High income Middle income Low income
Per capita income country groups
Fata
litie
s/ev
ent
Average losses per income group
*
**
* NatCatService 2005** NatCatService 2005
0
2
4
6
8
10
12
14
High income Middle income Low income
Loss
es a
s %
of G
DP
Per capita income country groups
* NatCatService 2005** NatCatService 2005
Average losses per income group
Methodology for comparison
Hochrainer, 2006
HondurasImpact of disasters on GDP growth in
Honduras
-2.0
-1.0
0.0
1.0
2.0
3.0
4.0
5.0
6.0
1996 1997 1998 1999 2000 2001 2002 2003 2004
Growth without Mitch or drought Growth with Mitch and drought
1.Actual GDP growth in Honduras with events vs. projected growth without eventsSource: Zapata, 2008
Honduras
1.GDP trajectoriesSource: WDI, 2007; own calculations
GDP in Honduras
5,000
5,500
6,000
6,500
7,000
7,500
8,000
1996
1997
1998
1999
2000
2001
2002
2003
2004
Mill
ion
cons
tant
200
0 U
SD
Projected w/o event-ECLACProjected w/o event-IIASAObserved
Direct effect due to wealth loss
Indirect development loss
Observed GDP in Honduras with events vs. projected growth without events. Source: Zapata, 2008; World Bank, 2007; own calculations
Currently Paradigm shift
Government assistance (taxes)Kinship arrangementsDonor assistance
Insurance and reinsurance, microinsuranceCatastrophe bond, weather derivativesContingent credit, reserve fund
Turkey: Insurance Pool (2000)India: Weather derivatives (04)Mexico: Cat bond (06)India, Colombia, Mexico etc: FundsColombia: Contingent credit (05)Caribbean: Regional insurance pool (2006)Pacific: Regional insurance pool (in the making)Global: GFDRR, GIRIF (2008)
Traditional approach to risk financing
ProactiveReactive
All with donor support
Source: Bettencourt et al., 2006
Planning and mainstreaming disaster risks into developmental planningPlanning disaster risk into
development
Planning and mainstreaming disaster risks into developmental planning
Source: Bettencourt et al., 2006
Planning disaster risk into development
Planning and mainstreaming disaster risks into developmental planning
Source: Bettencourt et al., 2006
Planning disaster risk into development
Planning and mainstreaming disaster risks into developmental planning
Source: Bettencourt et al., 2006
Planning disaster risk into development
Planning and mainstreaming disaster risks into developmental planning
Source: Bettencourt et al., 2006
Planning disaster risk into development
Planning and mainstreaming disaster risks into developmental planning
Source: Bettencourt et al., 2006
Planning disaster risk into development
Planning and mainstreaming disaster risks into developmental planning
Source: Bettencourt et al., 2006
Planning disaster risk into development
Planning and mainstreaming disaster risks into developmental planning
Source: Bettencourt et al., 2006
Planning disaster risk into development
Planning and mainstreaming disaster risks into developmental planning
Source: Bettencourt et al., 2006
Planning disaster risk into development
Planning and mainstreaming disaster risks into developmental planning
Source: Bettencourt et al., 2006
Planning disaster risk into development
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