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.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:542909 |
| Date | January 2011 |
| Creators | Stein, Daniel |
| Publisher | London School of Economics and Political Science (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.lse.ac.uk/167/ |
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