# **4. Designing a Livestock Insurance Program**

# **_4.1. Index-based Livestock Insurance_**

Attempts to develop individual livestock insurance in Mongolia have been unsuccessful in recent years. This traditional form of insurance, where indemnities are calculated for each insured farmer on the basis of individual claims, simply cannot work in Mongolia because (i) individual historic data are not available and thus insurer cannot have adequate information on individual herders, creating classic moral hazard and adverse selection problems, (ii) collection of individual data would necessitate tremendous equipment and personnel investments in the vast geographic area of Mongolia, and (iii) individual loss adjustments would be very costly or nearly impossible.

An alternative approach is to develop a collective system for indemnifications: indemnity payments are based on an external index designed to reflect the loss incurred by the herders. Such schemes are known as index-based insurance. Area-yield insurance programs, where the index is the aggregate yield in a given geographical area, have been implemented in India, Mexico or Spain. Weather-based insurance contracts, where the index is based on some weather parameters (e.g., rainfall, temperature) have been investigated in numerous countries and implemented in Canada and in India. These schemes present some advantages (e.g., reduction of moral hazard and adverse selection, lower administrative costs), but their main impediment is the presence of basis risk, i.e., the imperfect correlation between the insurance indemnity and the individual loss.

Weather-based insurance was considered as a first alternative to individual insurance because Mongolia has reasonable historical weather records to support the risk analysis. However, the infrastructure of the weather system is under-funded and has stations that are far apart, limiting the information needs required for weather-based insurance. Furthermore, winter _dzuds_ are complex events, consisting of multiple weather phenomena over a period of time, and sometimes non-weather factors, making the classification of risk highly problematic.<sup>4</sup> Skees and Enkh-Amgalan (2002) proposed to design an index-based insurance product that would indemnify herders based on the mortality rate of adult animals in a given area. The index-based livestock insurance (IBLI) would pay indemnities whenever the adult mortality rate exceeds a specific threshold for a localized region (e.g., the _soum_ in Mongolia). It is simpler than weatherbased insurance, and is less prone to moral hazards, adverse selection, and high administrative costs of individual insurance. Importantly, this system provides strong incentives to individual herders to continue to manage their herds so as to minimize the impacts of major _dzud_ events: if a better herder has no losses when their neighbors has large losses, the better herder is rewarded for the extra effort by receiving a payment based on the area losses. Finally, a 33 year time series on adult animal mortality is available for all _soums_ and for the five major species of animals. Such data are critical for developing actuarial information and for understanding the potential cost of alternative designs.

# **_4.2. Layering Livestock Risk_**

Previous government efforts to develop viable agricultural insurance programs in many developed countries and developing countries have been frustrated by the inherent lack of clarity regarding the objectives that range from social safety nets to commercial insurance. Governments have started to realize that these programs are no longer financially sustainable. For example, Government of India has recently decided to reform the current crop insurance scheme and to

> 4 Initial results showed a low correlation between livestock mortality rates and weather parameters (rainfall, minimum temperature, maximum temperature). However, options will be further considered for linking the index-based livestock insurance product to other indicators such as weather data and/or indices for range vegetation conditions (e.g. normalized, differentiated vegetation index – NDVI).

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