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Abstract
We investigate the sources of variance in crop output and measure their relative im-
portance in the context of weather index insurance for smallholder farmers. We use
parcel-level panel data from South Asia and a multilevel modeling approach to isolate
the different sources of variance. We then measure how large a role weather plays in
explaining variance in yields. Using Bayesian methods, we draw the underlying distri-
bution of the random error term responsible for weather uncertainty, which is highly
skewed and non-normal. We find that variance in weather accounts for a small but
important fraction of total variance in crop output. We also derive pricing and payout
schedules for actuarially fair weather index insurance. Our results shed light on the
low uptake rates of index insurance in South Asia and provide direction for designing
index insurance with less basis risk for farmers.