IDEAS home Printed from https://ideas.repec.org/a/ags/revi24/341425.html
   My bibliography  Save this article

Estimation of the Agricultural Probability of Loss: evidence for soybean in Paraná State

Author

Listed:
  • Ozaki, Vitor Augusto
  • Olinda, Ricardo
  • Faria, Priscila Neves
  • Campos, Rogério Costa

Abstract

: In any agricultural insurance program, the accurate quantification of the probability of the loss has great importance. In order to estimate this quantity, it is necessary to assume some parametric probability distribution. The objective of this work is to estimate the probability of loss using the theory of the extreme values modeling the left tail of the distribution. After that, the estimated values will be compared to the values estimated under the normality assumption. Finally, we discuss the implications of assuming a symmetrical distribution instead of a more flexible family of distributions when estimating the probability of loss and pricing the insurance contracts. Results show that, for the selected regions, the probability distributions present a relative degree of skewness. As a consequence, the probability of loss is quite different from those estimated supposing the Normal distribution, commonly used by Brazilian insurers.

Suggested Citation

  • Ozaki, Vitor Augusto & Olinda, Ricardo & Faria, Priscila Neves & Campos, Rogério Costa, 2014. "Estimation of the Agricultural Probability of Loss: evidence for soybean in Paraná State," Revista de Economia e Sociologia Rural (RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 52(1), January.
    • Handle: RePEc:ags:revi24:341425
    DOI: 10.22004/ag.econ.341425
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/341425/files/Vitor%20Augusto%20Ozaki.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.341425?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Richard H. Day, 1965. "Probability Distributions of Field Crop Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 47(3), pages 713-741.
    2. Francis X. Diebold & Til Schuermann & John D. Stroughair, 2000. "Pitfalls and Opportunities in the Use of Extreme Value Theory in Risk Management," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 1(2), pages 30-35, January.
    3. Bruce A. Babcock & Chad E. Hart & Dermot J. Hayes, 2004. "Actuarial Fairness of Crop Insurance Rates with Constant Rate Relativities," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(3), pages 563-575.
    4. C. Robert Taylor, 1990. "Two Practical Procedures for Estimating Multivariate Nonnormal Probability Density Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 72(1), pages 210-217.
    5. Paul Gallagher, 1987. "U.S. Soybean Yields: Estimation and Forecasting with Nonsymmetric Disturbances," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 69(4), pages 796-803.
    6. Richard E. Just & Quinn Weninger, 1999. "Are Crop Yields Normally Distributed?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(2), pages 287-304.
    7. Gallagher, Paul W., 1987. "U.S. Soybean Yields: Estimation and Forecasting with Non-Symmetric Disturbances," Staff General Research Papers Archive 10779, Iowa State University, Department of Economics.
    8. Goodwin, Barry K. & Roberts, Matthew C. & Coble, Keith H., 2000. "Measurement Of Price Risk In Revenue Insurance: Implications Of Distributional Assumptions," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 25(1), pages 1-20, July.
    9. Charles B. Moss & J. S. Shonkwiler, 1993. "Estimating Yield Distributions with a Stochastic Trend and Nonnormal Errors," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 75(4), pages 1056-1062.
    10. Longin, Francois M, 1996. "The Asymptotic Distribution of Extreme Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 69(3), pages 383-408, July.
    11. Carl H. Nelson & Paul V. Preckel, 1989. "The Conditional Beta Distribution as a Stochastic Production Function," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 370-378.
    12. Jon Danielsson & Casper G. De Vries, 2000. "Value-at-Risk and Extreme Returns," Annals of Economics and Statistics, GENES, issue 60, pages 239-270.
    13. repec:adr:anecst:y:2000:i:60:p:10 is not listed on IDEAS
    14. Vitor Ozaki & Barry Goodwin & Ricardo Shirota, 2008. "Parametric and nonparametric statistical modelling of crop yield: implications for pricing crop insurance contracts," Applied Economics, Taylor & Francis Journals, vol. 40(9), pages 1151-1164.
    15. Keith H. Coble & Thomas O. Knight & Rulon D. Pope & Jeffery R. Williams, 1997. "An Expected-Indemnity Approach to the Measurement of Moral Hazard in Crop Insurance," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 216-226.
    16. Viswanath Tirupattur & Robert J. Hauser & Nabil M. Chaherli, 1996. "Crop Yield and Price Distributional Effects on Revenue Hedging," Finance 9612004, University Library of Munich, Germany.
    17. Octavio A. Ramirez & Sukant Misra & James Field, 2003. "Crop-Yield Distributions Revisited," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 108-120.
    18. Barry K. Goodwin & Alan P. Ker, 1998. "Nonparametric Estimation of Crop Yield Distributions: Implications for Rating Group-Risk Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 139-153.
    19. Vitor Ozaki & Ralph Silva, 2009. "Bayesian ratemaking procedure of crop insurance contracts with skewed distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(4), pages 443-452.
    20. Joseph Atwood & Saleem Shaik & Myles Watts, 2003. "Are Crop Yields Normally Distributed? A Reexamination," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 888-901.
    21. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    22. Tirupattur, Viswanath & Hauser, Robert J. & Chaherli, Nabil M., 1996. "Crop Yield And Price Distributional Effects On Revenue Hedging," ACE OFOR Reports 14766, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ozaki, Vitor Augusto & Olinda, Ricardo & Faria, Priscila Neves & Campos, Rogerio Costa, 2014. "Estimation of the Agricultural Probability of Loss: evidence for soybean in Paraná Stats," Brazilian Journal of Rural Economy and Sociology (Revista de Economia e Sociologia Rural-RESR), Sociedade Brasileira de Economia e Sociologia Rural, vol. 52(1), pages 1-16, March.
    2. Ozaki, Vitor & Campos, Rogério, 2017. "Reduzindo a Incerteza no Mercado de Seguros: Uma Abordagem via Informações de Sensoriamento Remoto e Atuária," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 71(4), December.
    3. Christopher N. Boyer & B. Wade Brorsen & Emmanuel Tumusiime, 2015. "Modeling skewness with the linear stochastic plateau model to determine optimal nitrogen rates," Agricultural Economics, International Association of Agricultural Economists, vol. 46(1), pages 1-10, January.
    4. Arora, Gaurav & Agarwal, Sandip K., 2020. "Agricultural input use and index insurance adoption: Concept and evidence," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304508, Agricultural and Applied Economics Association.
    5. Qiujie Zheng & H. Holly Wang & Qing Hua Shi, 2014. "Estimating bivariate yield distributions and crop insurance premiums using nonparametric methods," Applied Economics, Taylor & Francis Journals, vol. 46(18), pages 2108-2118, June.
    6. Jesse B. Tack & David Ubilava, 2015. "Climate and agricultural risk: measuring the effect of ENSO on U.S. crop insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 46(2), pages 245-257, March.
    7. Chen, Shu-Ling & Miranda, Mario J., 2006. "Modeling Yield Distribution In High Risk Counties: Application To Texas Upland Cotton," 2006 Annual meeting, July 23-26, Long Beach, CA 21392, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    8. Zheng, Qiujie & Wang, H. Holly & Shi, Qinghua, 2008. "Estimating Farm Level Multivariate Yield Distribution Using Nonparametric Methods," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6509, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Ghahremanzadeh, Mohammad & Mohammadrezaei, Rassul & Dashti, Ghader & Ainollahi, Moharram, 2018. "Designing a whole-farm revenue insurance for agricultural crops in Zanjan province of Iran," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 17(02), January.
    10. Vitor A. Ozaki & Sujit K. Ghosh & Barry K. Goodwin & Ricardo Shirota, 2008. "Spatio-Temporal Modeling of Agricultural Yield Data with an Application to Pricing Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 951-961.
    11. Ker, Alan. P & Tolhurst, Tor & Liu, Yong, 2015. "Rating Area-yield Crop Insurance Contracts Using Bayesian Model Averaging and Mixture Models," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205211, Agricultural and Applied Economics Association.
    12. Jesse Tack & David Ubilava, 2013. "The effect of El Niño Southern Oscillation on U.S. corn production and downside risk," Climatic Change, Springer, vol. 121(4), pages 689-700, December.
    13. Jing Wang & Feng Fang & Qiang Zhang & Jinsong Wang & Yubi Yao & Wei Wang, 2016. "Risk evaluation of agricultural disaster impacts on food production in southern China by probability density method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(3), pages 1605-1634, September.
    14. Jesse Tack & Ardian Harri & Keith Coble, 2012. "More than Mean Effects: Modeling the Effect of Climate on the Higher Order Moments of Crop Yields," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(5), pages 1037-1054.
    15. Lu, Yue & Ramirez, Octavio A. & Rejesus, Roderick M. & Knight, Thomas O. & Sherrick, Bruce J., 2008. "Empirically Evaluating the Flexibility of the Johnson Family of Distributions: A Crop Insurance Application," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 37(1), pages 1-13, April.
    16. repec:ags:aaea22:335759 is not listed on IDEAS
    17. Hennessy, David A., 2009. "Crop Yield Skewness and the Normal Distribution," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 34(1), pages 1-19, April.
    18. Ramirez, Octavio A. & Shonkwiler, J. Scott, 2017. "A Probabilistic Model of Crop Insurance Purchase Decision," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 42(1), pages 1-17, January.
    19. Agarwal, Sandip Kumar, 2017. "Subjective beliefs and decision making under uncertainty in the field," ISU General Staff Papers 201701010800006248, Iowa State University, Department of Economics.
    20. Li, Lisha, 2015. "Three essays on crop yield, crop insurance and climate change," ISU General Staff Papers 201501010800005371, Iowa State University, Department of Economics.
    21. Hao, Jianqiang & Bathke, Arne & Skees, Jerry R., 2005. "Modeling the Tail Distribution and Ratemaking: An Application of Extreme Value Theory," 2005 Annual meeting, July 24-27, Providence, RI 19190, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:revi24:341425. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/inrapfr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.