Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: Using copulas for rating weather index insurance contracts
Authors : Bokusheva, Raushan
DOI : 10.1080/02664763.2017.1420146
Published in : Journal of Applied Statistics
Issue Date: 29-Jan-2018
Publisher / Ed. Institution : Taylor & Francis
ISSN: 1360-0532
Language : English
Subjects : Extreme dependence modeling; Copula; Index-based insurance; Agriculture; Risk
Subject (DDC) : 360: Social problems and social insurance
630: Agriculture
Abstract: This study develops a methodology for a copula-based weather index insurance design. Because the copula approach is better suited for modeling tail dependence than the standard linear correlation approach, its use may increase the effectiveness of weather insurance contracts designed to provide protection against extreme weather events. In our study, we employ three selected Archimedean copulas to capture the left-tail dependence in the joint distribution of the farm yield and a specific weather index. A hierarchical Bayesian model is applied to obtain consistent estimates of tail dependence using relatively short time series. Our empirical results for 47 large grain-producing farms from Kazakhstan indicate that, given the choice of an appropriate weather index to signal catastrophic events, such as a severe drought, copula-based weather insurance contracts may provide significantly higher risk reductions than regression-based indemnification schemes.
Fulltext version : Published version
License (according to publishing contract) : Licence according to publishing contract
Departement: Life Sciences and Facility Management
Organisational Unit: Institute of Natural Resource Sciences (IUNR)
Appears in Collections:Publikationen Life Sciences und Facility Management

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.