Stein, Daniel
(2011)
Rainfall index insurance in India.
PhD thesis, London School of Economics and Political Science.
Abstract
This thesis provides three works which each contribute to understanding of the promising
yet struggling market for rainfall index insurance in India. The first chapter contains an
analysis of the willingness-to-pay (WTP) for rainfall insurance by poor farmers in Gujarat,
India. It develops a theoretical model to predict individual WTP and contrasts it with
emprical estimates of WTP using the Becker-DeGroot-Marshalk (BDM) mechanism. We
find that BDM works well as a predictor of WTP, but that our model significantly overestimates
WTP. The second chapter seeks to provide a possible explanation for demand being
lower than theoretical predictions by looking at the dynamics of insurance demand. Using
a panel dataset of insurance purchasers in India, it shows that people who receive an insurance
payout are 9-22% more likely to purchase insurance the following year. The results
are consistent with a dynamic model of insurance demand featuring loss aversion, in which
receiving an insurance payout shifts the reference point such that people become more risk
averse the following season. I provide evidence against other possible explanations, such as
increased trust and learning about insurance, and direct effects of bad weather. The final
chapter explores the possibility that combining rainfall insurance with savings may result
in a more attractive financial product than insurance on its own. We conduct a laboratory
experiment with Indian farmers that uses the BDM mechanism to assess the valuation of
various insurance/savings combinations, which we title WISAs (Weather Insured Savings
Accounts). We find that, contrary to theoretical predictions, most people prefer both pure
savings and pure insurance to any combination of the two. This paper hopefully provides
valuable contibutions to solving the puzzle of how to shield poor farmers from uncertain
rainfall.
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