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Estimating spatial basis risk in rainfall index insurance: Methodology and application to excess rainfall insurance in Uruguay

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  • Ceballos, Francisco

Abstract

This paper develops a novel methodology to estimate the degree of spatial basis risk for an arbitrary rainfall index insurance instrument. It relies on a widelyused stochastic rainfall generator, extendedto accommodate nontraditional dependence patterns—in particular spatial upper-tail dependence in rainfall—through a copula function. The methodology is applied to a recentlylaunched index product insuring against excess rainfall in Uruguay. The model is first calibrated using historical daily rainfall data from the national network of weather stations, complemented with a unique,high-resolution dataset from a dense network of 34 automatic weather stations around the study area. The degree of downside spatial basis risk is then estimated by Monte Carlo simulations and the results are linked to both a theoretical model of the demand for index insurance and to farmers’ perceptions about the product.

Suggested Citation

  • Ceballos, Francisco, 2016. "Estimating spatial basis risk in rainfall index insurance: Methodology and application to excess rainfall insurance in Uruguay," IFPRI discussion papers 1595, International Food Policy Research Institute (IFPRI).
    • Handle: RePEc:fpr:ifprid:1595
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    1. Ceballos, Francisco & Robles, Miguel, 2020. "Demand heterogeneity for index-based insurance: The case for flexible products," Journal of Development Economics, Elsevier, vol. 146(C).

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    Keywords

    rain; rainfall patterns; insurance; weather; precipitation; risk management;
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