2020
DOI: 10.1108/afr-02-2020-0020
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Using a regional climate model to develop index-based drought insurance for sovereign disaster risk transfer

Abstract: PurposeExamine the usability of rainfall and temperature outputs of a regional climate model (RCM) and meteorological drought indices to develop a macro-level risk transfer product to compensate the government of Central Java, Indonesia, for drought-related disaster payments to rice farmers.Design/methodology/approachBased on 0.5° gridded rainfall and temperature data (1960–2015) and projections of the WRF-RCM (2016–2040), the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotrans… Show more

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Cited by 17 publications
(12 citation statements)
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“…The loss expectation can be determined using historical burn rate method (HBR), which is the mean historical losses (Guerrero-Baena and Gómez-Limón, 2019; Hohl et al, 2020;Mortensen and Block, 2018;Shirsath et al, 2019).This method is widely applied in the insurance industry, however, requires sufficient data in order to be accurate. For smaller datasets considering uncertainty, expected values can be evaluated by fitting loss data to a probability density function (Aizaki et al, 2021;Bokusheva, 2018;Bucheli et al, 2021;Eze et al, 2020;Kath et al, 2019;Salgueiro, 2019;Sacchelli et al, 2018;Vroege et al, 2021;Ward et al, 2020).…”
Section: Financial Methods and Risk Pricingmentioning
confidence: 99%
See 1 more Smart Citation
“…The loss expectation can be determined using historical burn rate method (HBR), which is the mean historical losses (Guerrero-Baena and Gómez-Limón, 2019; Hohl et al, 2020;Mortensen and Block, 2018;Shirsath et al, 2019).This method is widely applied in the insurance industry, however, requires sufficient data in order to be accurate. For smaller datasets considering uncertainty, expected values can be evaluated by fitting loss data to a probability density function (Aizaki et al, 2021;Bokusheva, 2018;Bucheli et al, 2021;Eze et al, 2020;Kath et al, 2019;Salgueiro, 2019;Sacchelli et al, 2018;Vroege et al, 2021;Ward et al, 2020).…”
Section: Financial Methods and Risk Pricingmentioning
confidence: 99%
“…Deterministic models were applied for income reduction impacts, especially for crop insurance. Additionally, some models were related only with one explanatory variable (one index) was the most common solution found in the in-depth analysis (Aizaki et al, 2021;Bokusheva, 2018;Bucheli et al, 2021;Hohl et al, 2020;Kath et al, 2019;Mortensen and Block, 2018;F et al, 2020;Vroege and Finger, 2020;Ward and Makhija, 2018). There is evidence that machine learning techniques improve loss modeling from different sources and present different time and spatial scales (Eze et al, 2020).…”
Section: Vulnerability Analysismentioning
confidence: 99%
“…It is ideally appropriate to weather threats that are wellcorrelated over a large area and when weather and agricultural output are closely related. The strongest associations, as per Hohl et al (2020), often entail a single crop, a distinct rainy season, and no irrigation. Until now, the majority of weather-based index insurance initiatives have concentrated on the risk of rainfall deficiency (drought).…”
Section: Principles Of Weather-based Index Insurancementioning
confidence: 99%
“…Weather extremes can have long-lasting impacts on smallholder farmers' livelihoods through at least two channels. First, they destroy assets and production, and to make up for the lost income households may resort to costly coping strategies (Hohl, 2020).…”
Section: Role Of Weather-based Index Insurance In Support Of Agricult...mentioning
confidence: 99%
“…In Indonesia, where some rice farming communities are vulnerable to sea-level rise, scholars are experimenting to identify rice cultivars with high yields under different salinity levels (Sembiring et al, 2020). Hohl et al (2021) used a regional climate model to develop index-based drought insurance products to help the Central Java government make drought-related insurance payments to rice farmers. Aprizal et al (2021) utilized land-use conditions and rain variability data to develop a flood inundation area model for the Way Sekampung sub-watershed in Lampung, Sumatra.…”
mentioning
confidence: 99%