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Economic Value of Weather Forecasting Systems Information: A Risk Aversion Approach

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  • Emilio Cerdá
  • Sonia Quiroga Gómez

Abstract

Extreme meteorological events have increased over the last decades and it is widely accepted that it is due to climate change (IPCC, 2007; Beniston et al., 2007). Some of these extremes, like drought or frost episodes largely affect agricultural outputs and risk management becomes crucial. The goal of this paper it is to analyze farmers’ decisions about risk management, taking into account climatological and meteorological information. We consider a situation in which the farmer, as part of crop management, has available a technology to protect the harvest from weather effects. This approach has been used by Murphy et al. (1985), Katz and Murphy (1990 and 1997) and others in the case that the farmer maximizes the expected returns. In our model we introduce the attitude towards risk. Thus we can evaluate how the optimal decision is affected by the absolute risk aversion coefficient of Arrow-Pratt, and compute the economic value of the information in this context, while proposing a measure to estimate the amount of money that the farmer is willing to pay for this information in terms of the certainty equivalent.

Suggested Citation

  • Emilio Cerdá & Sonia Quiroga Gómez, 2009. "Economic Value of Weather Forecasting Systems Information: A Risk Aversion Approach," Working Papers 2009-04, FEDEA.
  • Handle: RePEc:fda:fdaddt:2009-04
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    References listed on IDEAS

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    1. Palacios-Huerta, Ignacio & Serrano, Roberto, 2006. "Rejecting small gambles under expected utility," Economics Letters, Elsevier, vol. 91(2), pages 250-259, May.
    2. A. E. Baquet & A. N. Halter & Frank S. Conklin, 1976. "The Value of Frost Forecasting: A Bayesian Appraisal," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 58(3), pages 511-520.
    3. Gomez-Limon, Jose A. & Arriaza, Manuel & Riesgo, Laura, 2003. "An MCDM analysis of agricultural risk aversion," European Journal of Operational Research, Elsevier, vol. 151(3), pages 569-585, December.
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