Measuring the dependence structure between yield and weather variables

Raushan Bokusheva ()

MPRA Paper from University Library of Munich, Germany

Abstract: The design and pricing of weather-based crop insurance and weather derivatives is strongly based on an implicit assumption that the dependence structure between yields and weather variables remains unchanged over time. In this paper, we prove this assumption based on empirical time series of weather variables and farm wheat yields from Kazakhstan over the period from 1961 to 2003. By employing two different methods to measure dependence in multivariate distributions – the regression analysis and copula approach – we reveal statistically significant temporal changes in the joint distribution of relevant variables. These empirical results indicate that greater effort is required to capture potential temporal changes in the dependence between yield and weather variables, and subsequently to consider them in the design and rating of weather-based insurance instruments.

Keywords: weather-based index insurance; dependence structure; copula estimation; Bayesian hierarchical model; Kazakhstan. (search for similar items in EconPapers)
JEL-codes: C11 C32 G22 (search for similar items in EconPapers)
Date: 2010-04
New Economics Papers: this item is included in nep-agr and nep-ias
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/22786/1/MPRA_paper_22786.pdf original version (application/pdf)

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:pra:mprapa:22786

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().