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Measuring the dependence structure between yield and weather variables

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  • Bokusheva, Raushan

Abstract

The design and pricing of weather-based crop insurance and weather derivatives is strongly based on an implicit assumption that the dependence structure between yields and weather variables remains unchanged over time. In this paper, we prove this assumption based on empirical time series of weather variables and farm wheat yields from Kazakhstan over the period from 1961 to 2003. By employing two different methods to measure dependence in multivariate distributions – the regression analysis and copula approach – we reveal statistically significant temporal changes in the joint distribution of relevant variables. These empirical results indicate that greater effort is required to capture potential temporal changes in the dependence between yield and weather variables, and subsequently to consider them in the design and rating of weather-based insurance instruments.

Suggested Citation

  • Bokusheva, Raushan, 2010. "Measuring the dependence structure between yield and weather variables," MPRA Paper 22786, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:22786
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    1. Vedenov, Dmitry V., 2008. "Application of Copulas to Estimation of Joint Crop Yield Distributions," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6264, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Skees, Jerry*Gober, Stephanie*Varangis, Panos*Le, 2001. "Developing rainfall-based index insurance in Morocco," Policy Research Working Paper Series 2577, The World Bank.
    3. Trivedi, Pravin K. & Zimmer, David M., 2007. "Copula Modeling: An Introduction for Practitioners," Foundations and Trends(R) in Econometrics, now publishers, vol. 1(1), pages 1-111, April.
    4. Zhu, Ying & Ghosh, Sujit K. & Goodwin, Barry K., 2008. "Modeling Dependence in the Design of Whole Farm---A Copula-Based Model Approach," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6282, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Wei Xu & Guenther Filler & Martin Odening & Ostap Okhrin, 2010. "On the systemic nature of weather risk," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 70(2), pages 267-284, August.
    6. Skees, Jerry & Hazell, P. B. R. & Miranda, Mario, 1999. "New approaches to crop yield insurance in developing countries:," EPTD discussion papers 55, International Food Policy Research Institute (IFPRI).
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    9. Jerry R. Skees & J. Roy Black & Barry J. Barnett, 1997. "Designing and Rating an Area Yield Crop Insurance Contract," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(2), pages 430-438.
    10. Oliver Musshoff, 2008. "Indifference Pricing of Weather Derivatives," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 979-993.
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    13. Bokusheva, Raushan & Breustedt, Gunnar, 2008. "Ex Ante Evaluation Of Index-Based Crop Insurance Effectiveness," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 43957, European Association of Agricultural Economists.
    14. Vedenov, Dmitry V. & Barnett, Barry J., 2004. "Efficiency of Weather Derivatives as Primary Crop Insurance Instruments," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(3), pages 1-17, December.
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    Cited by:

    1. Schulte-Geers, Matthias & Berg, Ernst, 2011. "Modelling farm production risk with copulae instead of correlations," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 115996, European Association of Agricultural Economists.

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    More about this item

    Keywords

    weather-based index insurance; dependence structure; copula estimation; Bayesian hierarchical model; Kazakhstan.;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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