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Open Access Publications from the University of California

Subsidy Policies with Learning from Stochastic Experiences

  • Author(s): Cai, Jing;
  • de Janvry, Alain;
  • Sadoulet, Elisabeth
  • et al.

Many new products presumed to be privately beneficial to the poor have a high price elasticity of demand and ultimately zero take-up rate at market prices. This has led gov- ernments and donors to provide subsidies to increase the take-up, with the hope of reducing the subsidies once the value of the product is better known. In this study, we use data from a two-year field experiment in rural China to define the optimum subsidy scheme that can insure a given take-up for a new weather insurance product for rice producers. We estimate both reduced form causal channels and a structural model of learning from stochastic expe- rience which we use to conduct policy simulations. Results show that the optimum current subsidy necessary to achieve a desired level of take-up rate depends on both past subsidy levels and past payout rates, implying that subsidy levels should vary locally year-to-year.

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