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Abstract
Index insurance is an alternative to crop insurance that bases payouts on a variable
that is highly correlated with income but beyond the control of individual households, such as
rainfall, temperature, or area-yields (i.e., output per hectare in a large area). Index insurance
offers risk protection while avoiding the incentive problems that plague traditional crop
insurance, and as a result is seen by many as a promising antipoverty tool. However,
participation in index insurance to this point has generally been in low. In this paper, we explore
one factor that might potentially depress demand for index insurance: mistaken beliefs among
farmers with respect to the distribution of the insured risk. Our experiences from an area-yield
insurance pilot project for cotton farmers in the Pisco valley of Peru suggest that such errors are
common. Lower demand means that not only are the benefits of index insurance not realized by
households, but econometric measurement of the these benefits is more difficult due to low
precision. One way to counteract these effects is a “randomized encouragement design,” i.e., the
random assignment of positive economic incentives for the purchase of area-yield insurance,
such as discount coupons. We examine the implications of a randomized encouragement design
for econometric evaluation.