Use of Catastrophe Risk Models in Assessing Sovereign Food Security for Risk Transfer

Discusses how catastrophe crop risk models can be used to assess food security need at the sovereign level for the purpose of risk transfer

Abstract

This paper discusses how catastrophe crop risk models can be used to assess food security needs at the sovereign level for the purpose of risk transfer. The rationale for a system to evaluate food security needs at the national level is discussed.

The role of technology and remote sensing data availability as an enabler of catastrophe crop risk models is discussed followed by a description of the framework of catastrophe crop models for droughts, representing the peril for which catastrophe models have had the most success.

The integration of the output of catastrophe crop models with a food security vulnerability assessment model is described next. Recent advances in analytical modeling of various types of shocks in assessing food security are described but the operational use of these analytical models in the development of food security assessment for risk transfer is seen to be limited for now because of the complexity of these analytical models.

The food security vulnerability modeling in the African Risk Capacity, ARC, model is then described as showing a practical solution to the complex problem of assessing food security via a model. Lastly, the challenges faced in risk transfer of sovereign food security risks are discussed.

This working paper received financial support from the Department for International’s Humanitarian Innovation Evidence Programme (HIEP) Sovereign Disaster Risk Finance and Insurance Project.

Citation

Sharma, Mohan.; Hohl, Roman. ; Use of Catastrophe Risk Models in Assessing Sovereign Food Security for Risk Transfer. Policy Research Working Paper;No. 7360. World Bank, Washington, DC. © World Bank. (2015)https://openknowledge.worldbank.org/handle/10986/22233 License: CC BY 3.0 IGO.

Use of Catastrophe Risk Models in Assessing Sovereign Food Security for Risk Transfer

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