# **Box 1. Examples of drought risk management contracts in Ethiopia and Mexico**

In 2005 the United Nations World Food Program, with technical assistance from the World Bank, entered into the first-ever humanitarian aid weather insurance contract with a leading European reinsurer (WFP, 2005; WFP 2007; Syroka and Wilcox, 2006). The contract provided contingency funding in case of an extreme drought during Ethiopia’s 2006 agricultural season. The policy was based upon a calibrated index of rainfall data gathered from twenty-six weather stations across Ethiopia. Payment would have been triggered when data gathered over a period from March to October indicated that rainfall was significantly below historic averages, pointing to the likelihood of widespread crop failure. While the experimental pilot transaction only provided a small amount of contingency funding – a maximum payout of US$7.1 million for a premium of US$930,000 paid by USAID – the funds would have been available to WFP at harvest-time which would allow for an intervention four to six months earlier than the traditional appeals-based system. If a catastrophic drought had occurred in 2006, WFP would have used these funds to assist 65,000 households in November 2006. WFP are currently working with the Government of Ethiopia, World Bank and DFID on a second-phase drought risk financing program in Ethiopia for 2008-2010 (Hess, Wiseman and Roberson, 2006).

Since 2003 the Government of Mexico, through its government-owned reinsurance company, has been insuring the drought disaster relief response budgets of federal and the state governments using rainfall index-based approaches. The program was launched to address amongst other things financial disruptions to other government programmes to fund emergency responses as a result of weather shocks. In 2007 approximately 1,900,000 hectares were insured against drought. The risk was transferred to the international weather market through 230 weather stations for a sum insured of US$90 million at a premium of US$9.7 million. The program was successfully tested in 2005 by a US$10.5 million triggered payout as a result of severe drought in several states (Agroasemex, 2006; Vasquez & Castellanos, 2007).

In order to implement a successful weather risk transfer program, however, the primary technical precondition is that the data used to construct the underlying weather indexes must adhere to strict quality requirements, including: reliable and trustworthy on-going daily collection and reporting procedures; daily quality control; an independent source of data for verification; a long, clean, and internally consistent historical record to allow for a proper actuarial analysis of the weather risks involved—at least 25-30 years of daily data are ideally required, with less than 3-5 percent missing (ISMEA, 2006).<sup>4</sup> The strict nature of these criteria is to ensure the underlying weather data used is objective, easily accessible and independently verifiable, thus ensuring that the balance of information between the two entities is shared equally and the nature of the risk being transferred is transparently communicated. Experience shows that in most countries, including least developed countries (LDCs) that often have a long history of monitoring weather for agriculture, there is often enough weather stations and data to consider an index-based risk management approach at the national level with a little additional investment.<sup>5</sup> One advantage of weather-indexed products, over products based on more subjective loss assessments, is that they create market access opportunities: the risk can be transferred from the country in question to the commercial portfolios of actors that actively seek this risk. Secondly, by using a proxy measure of risk, such as rainfall that is available on a real-time basis, a contract

> 4 Nearly all weather contracts executed in the insurance and derivative market are written on data collected from official National Meteorological Service (NMS) weather stations; ideally, although not necessarily, these are automated stations that report daily to the United Nations World Meteorological Organization’s (WMO) Global Telecommunication System (GTS) in internationally recognized standard format and then undergo standard WMOestablished quality control procedures.

> 5 Investments include, for example, upgrading some meteorological or communication equipment or by cleaning (i.e. in-filling missing or correcting erroneous entries) historical weather data (MDA Federal, 2006, 2007).

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