Large scale extreme risk assessment using copulas: an application to drought events under climate change for Austria

Stefan Hochrainer-Stigler (), Juraj Balkovič (), Kadri Silm () and Anna Timonina-Farkas ()
Additional contact information
Stefan Hochrainer-Stigler: IIASA-International Institute for Applied Systems Analysis
Juraj Balkovič: IIASA-International Institute for Applied Systems Analysis
Kadri Silm: University of Vienna
Anna Timonina-Farkas: University of Vienna

Computational Management Science, 2019, vol. 16, issue 4, No 6, 669 pages

Abstract: Abstract Droughts pose a significant challenge to farmers, insurers as well as governments around the world and the situation is expected to worsen in the future due to climate change. We present a large scale drought risk assessment approach that can be used for current and future risk management purposes. Our suggested methodology is a combination of a large scale agricultural computational modelling -, extreme value-, as well as copula approach to upscale local crop yield risks to the national scale. We show that combining regional probabilistic estimates will significantly underestimate losses if the dependencies between regions during drought events are not taken explicitly into account. Among the many ways to use these results it is shown how it enables the assessment of current and future costs of subsidized drought insurance in Austria.

Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://link.springer.com/10.1007/s10287-018-0339-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:comgts:v:16:y:2019:i:4:d:10.1007_s10287-018-0339-4

Ordering information: This journal article can be ordered from
http://www.springer. ... ch/journal/10287/PS2

DOI: 10.1007/s10287-018-0339-4

Access Statistics for this article

Computational Management Science is currently edited by Ruediger Schultz

More articles in Computational Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().