Climate Change, Weather Insurance Design and Hedging Effectiveness

Kapphan, Ines; Calanca, Pierluigi; Holzkaemper, Annelie

doi:10.1057/gpp.2012.8

Cited by 28 publications

(25 citation statements)

References 37 publications

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“…For example, Iizumi et al (2012b) generated a 2000-yrlong precipitation series using the LARS-WG to analyse the statistical characteristics of daily precipitation indices in Japan (Iizumi et al 2012b). Also, Kapphan et al (2012) generated 1000 yr of weather records to examine the weather insurance design for agricultural production (Kapphan et al 2012).…”

Section: The Elpis Baseline Scenariosmentioning

confidence: 99%

Validation of ELPIS 1980-2010 baseline scenarios using the observed European Climate Assessment data set

Semenov¹,

Pilkington-Bennett²,

Calanca³

2013

Clim. Res.

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Local-scale daily climate scenarios are required for assessment of climate change impacts. ELPIS is a repository of local-scale climate scenarios for Europe, which are based on the LARS-WG weather generator and future projections from 2 multi-model ensembles, CMIP3 and EU-ENSEMBLES. In ELPIS, the site parameters for the 1980−2010 baseline scenarios were estimated by LARS-WG using daily weather from the European Crop Growth Monitoring System (CGMS) used in many European agricultural assessment studies. The objective of this paper was to compare ELPIS baseline scenarios with observed daily weather obtained independently from the European Climate Assessment (ECA) data set. Several statistical tests were used to compare distributions of climatic variables derived from ECA-observed daily weather and ELPISgenerated baseline scenarios. About 30% of selected sites have a difference in altitude of > 50 m compared with the CGMS grid-cell altitude that was selected to represent agricultural land within a grid-cell. Differences in altitude can explain significant Kolmogorov-Smirnov test (KS-test) results for distribution of daily temperature and in t-tests for temperature monthly means, because of the well-known negative correlation between temperature and elevation. For daily precipitation, the KS-test showed little difference between generated and observed data; however, the more sensitive t-test showed significant results for the sites where altitude differences were large. Approximately 11% of sites showed small positive or negative bias in monthly solar radiation, although 86% sites showed > 3 significant t-test results for monthly means. These results can be explained by differences in conversion of sunshine hours to solar radiation used in CGMS and LARS-WG. We conclude that, considering the limitations above, ELPIS baseline scenarios are suitable for agricultural impact assessments in Europe.

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Section: The Elpis Baseline Scenariosmentioning

confidence: 99%

Validation of ELPIS 1980-2010 baseline scenarios using the observed European Climate Assessment data set

Semenov¹,

Pilkington-Bennett²,

Calanca³

2013

Clim. Res.

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“…Second, increasing drought risk changes the pure risk (Collier et al, 2009). In consequence, insurance parameters have to be adjusted over time to effectively hedge future weather risk (Kapphan et al, 2012).…”

Section: Hedging Effectivenessmentioning

confidence: 99%

Hydrological drought index insurance for irrigation districts in Spain

Maestro

Bielza

Garrido

2016

Span. j. agric. res.

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reducing the availability of surface and groundwater sources, and giving rise to water shortages both for consumption uses and for environmental flows. Water scarcity in irrigated farming systems results in potentially greater economic losses than in rainfed systems, due to the higher investments being made on the farm.To manage water scarcity, deficit irrigation has been studied and implemented, particularly to ligneous crops, showing satisfactory results (Ruiz-Sanchez et al., 2010). Water markets are commonly used in Aus- RESEARCH ARTICLE OPEN ACCESS AbstractHydrological droughts are a major risk for irrigated agriculture in many regions of the world. The aim of this article is to propose an insurance tool to help irrigators manage the risk of water scarcity in the framework of the Spanish Crop Insurance System (SCIS). Only the United States Insurance System provides this type of coverage, but has very restrictive conditions. To determine the type of insurance scheme that better fits with the SCIS and to the Spanish irrigated agriculture, an expert panel was held with the participation of all stakeholders involved in crop insurance. Following the expert panel conclusions, an hydrological drought index insurance (HDII) addressed to irrigation districts (ID) is proposed. It would compensate water deficits suffered in the whole ID. We detail the conditions that the ID should fulfill to be eligible for HDII. HDII is applied to the Bardenas Irrigation District V (ID-V) in Spain, and the hedging effectiveness of the instrument is analyzed comparing ID-V's gross margins with and without the insurance contract. Results suggest that the proposed insurance scheme could provide an effective means of reducing farmers' vulnerability to water shortages and there is no major impediment for it to be included as a new line in the SCIS. This type of insurance can be generalized to any ID fulfilling the conditions mentioned in this paper.

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“…Next, Thornton et al [22] use 30 repetitions to estimate the first two statistical moments, while only 25 runs are used by Finger and Calanca [23] to estimate also skewness. Finally, Kapphan et al [24] use 1000 crop yield simulations in order to estimate climate-related risks and to design optimal crop yield insurance contracts.…”

Section: Introductionmentioning

confidence: 99%

Sample Size Requirements for Assessing Statistical Moments of Simulated Crop Yield Distributions

et al. 2013

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Abstract:Mechanistic crop growth models are becoming increasingly important in agricultural research and are extensively used in climate change impact assessments. In such studies, statistics of crop yields are usually evaluated without the explicit consideration of sample size requirements. The purpose of this paper was to identify minimum sample sizes for the estimation of average, standard deviation and skewness of maize and winterwheat yields based on simulations carried out under a range of climate and soil conditions. Our results indicate that 15 years of simulated crop yields are sufficient to estimate average crop yields with a relative error of less than 10% at 95% confidence. Regarding standard deviation and skewness, sample size requirements depend on the degree of symmetry of the underlying population's distribution. For symmetric distributions, samples of 200 and 1500 yield observations are needed to estimate the crop yields' standard deviation and skewness coefficient, respectively. Higher degrees of asymmetry increase the sample size requirements relative to the estimation of the standard deviation, while at the same time the sample size requirements relative to the skewness coefficient are decreased.

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Climate Change, Weather Insurance Design and Hedging Effectiveness

Cited by 28 publications

References 37 publications

Validation of ELPIS 1980-2010 baseline scenarios using the observed European Climate Assessment data set

Validation of ELPIS 1980-2010 baseline scenarios using the observed European Climate Assessment data set

Hydrological drought index insurance for irrigation districts in Spain

Sample Size Requirements for Assessing Statistical Moments of Simulated Crop Yield Distributions

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