Innovation

The risk of unfavourable weather conditions is the single most important risk faced by hundreds of millions of poor rural households around the world. Governments have implemented a range of programs to address these risks, most notably crop insurance programs and disaster relief aid. Programs which tie payments to individual farmer's experience may suffer from two serious problems: moral hazard, whereby farmers may not exert as much effort to avoid risk or its consequences; and adverse selection, whereby farmers with higher risk are more likely to take up such products. Contracting innovations have de-linked indemnification from individual production by basing insurance against losses arising from poor weather on an observable index (e.g. local rainfall or aggregate local crop yields) which is not directly linked to individual production. Such 'index-based' micro-insurance products promise to offer a financially sustainable mechanism to reduce the risk faced by agricultural households. While there are some examples of success, by and large farmers have been reluctant to hedge substantial amounts of risk with these instruments. It is therefore of central importance to understand the determinants of demand for these products, and quantify their ability to affect household's economic decisions and improve well-being. This review will synthesize the emerging body of evidence surrounding two specific types of index-based insurance: (1) weather insurance and (2) area-yield based crop insurance. The review will concentrate on the various issues associated with these forms of insurance, provide the best synthesis possible using existing evidence, and suggest priorities for future research.

Rainfall index insurance is a theoretically attractive financial product that has achieved only limited adoption. This paper seeks to understand the structure of demand for rainfall index insurance in India. The authors develop two approaches to estimating households' valuation of rainfall insurance and evaluate them against an experiment in which fixed prices are randomly assigned. The first approach uses a simple structural model of index insurance demand that includes basis risk - the possibility that policy-holders may suffer a negative shock yet receive little or no payout. The authors use survey data from members of an insurance pilot in Gujarat, India to fit the model and estimate the willingness to pay (WTP) for rainfall insurance coverage. Relative to the choices observed at randomly assigned fixed prices, the structural model significantly overestimates demand. The second approach uses a Becker-Degroot-Marschak (BDM) methodology to empirically elicit WTP from potential insurance customers at the time of marketing. Researchers find that BDM does a better job of predicting fixed price purchasing behavior, but the distribution of stated willingness to pay has large mass points at focal points. Finally, directly comparing the two approaches and find the theoretical model has weak predictive power for WTP as elicited by BDM. The authors explore which household characteristics are correlated with WTP and determine that recent experiences with rainfall and insurance are important factors not captured in our static model, suggesting that learning dynamics may be a promising direction for future analyses.

This report concludes that weather index-based insurance (or insurance which pays out when weather variables such as rainfall reach certain predetermined levels) is an effective, market-mediated solution to promote agricultural development and to help protect the poorest against weather hazards. At the same time, this type of ex-ante (or before the event) risk management approach can reduce the need for costly emergency operations.  For example, rather than providing assistance after a drought when a farmer is unable feed her family or cover the cost of operating her farm, a payment from a weatherindex insurance policy can help this farmer meet urgent household needs without selling important productive assets – like land – or defaulting on loans used to buy seeds and fertilizer. As a result, this family is better able to recover productivity and does not need costly emergency assistance.