Defining Drought for Insurance

Economics Research

Economics Research

Index-based insurance requires matching a climate variable  with crop loss. Poor availability or quality of either climate or crop data can limit the advancement of index-based insurance products. Some data are harder than other kinds to collect and verify.

Crop yield is an obvious source of data for use in evaluating climate risk to farming, but such data are often not available. When such data is available, it’s often aggregated at administrative regions that encompass thousands of small fields, so it isn’t of a high enough resolution to use.  

Farmers can be a rich source of information for understanding growing conditions in past years. Current processes of collecting data from farmers are time and resource intensive, requiring researchers to visit farmers and conduct a series of participatory exercises. Such processes are challenging to implement on a large scale. While technology presents the possibility to scale up the collection of information, the depth and quality of data collected could decline if such plans are not carefully developed.

Focal group participants in Malawi identify the nine worst drought years since 1983. Photo: Vicky Boult

Malawi-Based Research

In Malawi, we have several research questions that aim to address this challenge. One is to examine if changing the method or type of tool used to collect information from farmers changes that resulting information. In this case, the information scientists are collecting is on which years were the worst in terms of dry growing conditions. So, if using a new method/technology results in a different set of “bad years” from the results that were generated with a more tested and proven method, it probably won’t be a good idea to use that new tool going forward. But if newer methods and technology can replicate the more labor-intensive methods, there’s promise for providing index insurance to millions of more farmers.

Another research aim is to understand the main factors that shape a farmer’s perception about defining and reporting drought risk. For example, how do they weigh the various biophysical, sociodemographic, psychological, and social influence variables that relate to drought risk? Understanding these factors will help in developing the new methods mentioned above.

We also want to test the latest climate products available for index insurance. So, we want to understand if new products like TAMSAT-ALERT can do a better job than other sources at matching up with farmer-based data.

Senegal-Based Research

We’re also conducting fieldwork in Senegal. This research focuses on the problem of index insurance payouts not always matching with the times a farmer feels they need a payout. This mismatch is often referred to as basis risk, and when such a mismatch occurs, it can erode trust in index insurance and lead to farmers not wanting to invest in the product.

Efforts are being made to decrease the chance of a basis risk event, but another important component of managing this risk is to improve the communication of it. If farmers are aware of  basis risk, they may be able to plan accordingly in their overall risk management strategies. In Senegal, the research will evaluate how providing information to farmers about the impacts of basis risk affects how those farmers make decisions about purchasing index insurance. We also want to evaluate how satisfied farmers are with an index insurance product when basis risk is fully considered.