Weather-Based Crop Insurance (WBCI) Premium for Rainfed Wheat in Miyaneh County: D-Vine Copula Approach Application

Document Type : Research Paper

Author

Abstract

Risk is an unavoidable but manageable element in agriculture. Agricultural insurance is an effective scheme in risk management. Nevertheless, traditional insurance schemes have problems, such as high transaction costs, challenge of asymmetric information, i.e. adverse selection and moral hazard. Therefore, in this research paper weather-based crop insurance (WBCI) is presented for rainfed wheat in Miyaneh county which is an efficient tool in risk management, and does not have current insurance’s problem. In this regards, we collected the data of yield of "Sardari rainfed wheat variety" and "weather variables" during 1987-2013, respectively, from "Iran Agricultural Organization" and "Iran Meteorological Organization". In recent years, the "Vine copula functions" have been very successful in measuring of dependence structure and expression of joint distribution functions in different fields. Consequently, in this study, dependent structure between weather indices and product performance with utilization of Vine copula functions was measured, and in the end, premium amounts and indemnity function were calculated. The D-Vine model was used to compute insurance premium for rainfed wheat and description of joint distribution. We calculated insurance premium in four levels of coverage (50, 80, 90 and 100 percent) that its amount in 80 percent coverage level is 578827 Rials. The computing premium in WBCI is less than current insurance premium, which is reasonable. Moreover, the result of indemnity function indicates that "relativity humidity variable" has most dependence with Miyaneh rainfed wheat yield. Its "trigger value" and "stop-loss", respectively, are 51.83 and 23.07 percent.

Keywords

Main Subjects

References

اردستانی ح، (1391). امکان سنجی استفاده از شاخص آب هوا در مدیریت بیمه گندم دیم. پایان نامه کارشناسی ارشد، دانشگاه تهران، دانشکده کشاورزی.
افقی ر، کیانی راد ع و عزیزنصیری س، (1390). بیمه کشاورزی بر پایه شاخص‌های آب و هوایی ابزاری کارآمد در مدیریت ریسک کشاورزی در ایران. بیمه کشاورزی، 8(29و30): 25 - 51.
جهاد کشاورزی، (1393). مرکز آمار و اطلاعات، بانک هزینه تولید محصولات زراعی.
سلامی ح ا، قهرمان‌زاده م، حسینی ص و یزدانی س، (1387). بیمه درآمدی راه‌کاری برای کاهش ریسک تولید و نوسانات قیمت در صنعت طیور کشور. اقتصاد کشاورزی، 3(4): 1-30.
صندوق بیمه کشاورزی، (1392). گزارش عملکرد صندوق بیمه محصولات کشاورزی طی سال‌های اخیر. گروه خدمات مدیریت و برنامه ریزی.
قهرمان‌زاده م، دشتی ق، افراسیابی س، حسین‌زاد ج و حیاتی ب ا، (1393). زمینه‌یابی ایجاد بیمه شاخص آب و هوایی پیشنهادی در محصول گندم دیم شهرستان اهر. تحقیقات اقتصاد و توسعه کشاورزی ایران، 45(2):383 -393.
Aas K, Czado C, Frigessi A and Bakken H, (2009). Pair-copula constructions of multiple dependence. Insurance: Mathematics and Economics, 44: 182–198.
Anderson JR, (2003). Impacts of climate variability in Australian agriculture. Review of Marketing and Agricultural Economics. 49 (31).
Aziznasiri S, 2011. Weather-Based crop insurance as a viable instrument for agricultural risk management in Iran. Master of Science thesis, Allameh Tabatabai University, E.C.O. College of Insurance.
Bedford T and Cooke RM, (2001). Probability density decomposition for conditionally dependent random variables modeled by Vines. Annals of Mathematics and Artificial Intelligence, 32:245–268.
Bedford T and Cooke RM, (2002). Vines: A new graphical model for dependent random variables. Annals of Statistics 30: 1031–1068.
Bokusheva R, (2010). Measuring the dependence structure between yield and weather variables. ETH Zurich, Institute for Environmental Decisions.
 Brechmann EC, Czado C and Aas K, (2010). Truncated regular Vines and their applications. Canadian Journal of Statistics, 40(1 ): 68–85.
Brechmann EC and Czado C, (2011). Risk management with high-dimensional Vine copulas: An analysis of the Euro Stoxx 50. Submitted for publication.
Brechmann EC and Schepsmeier U, (2012). Modeling dependence with C- and D-Vine copulas: The R-package CDVine. To appear in the Journal of Statistical Software.
Chen S, Wilson WW, Larsen R and Dahl B, (2013). Investing in agriculture as an asset class. Department of Agribusiness and Applied Economics Agricultural Experiment Station North Dakota State University.
Czado C, Brechmann EC and Gruber L, (2014). Selection of Vine copulas. technische Universitat Munchen.
Dißmann J, Brechmann EC, Czado C and Kurowicka D, (2013). Selecting and estimating regular Vine copula and application to financial returns. Computational Statistics & Data Analysis. 59: 52–69.
Goodwin B.K., (2012). Copula-based models of systemic risk in US. agriculture: implications for crop insurance and reinsurance contracts. The NBER conference on Insurance Markets and Catastrophe Risk in Boston.
Joe H, (1997). Multivariate models and dependence concepts. Chapman and Hall, London
Kurowicka D and Cooke RM, (2006.( Uncertainty analysis with high dimensional dependence dodelling. John Wiley & Sons Ltd.
Scholzel C and Friederichs P, (2008). Multivariate non-normally distributed random variables in climate research introduction to the copula approach. Nonlinear Processes in Geophysics. 15: 761–772.
Schulte GM and Berg E, (2011). Modeling farm production risk with copula instead of correlations. Institute of Food and Resource Economics, University of Bonn, Germany.
Turvey C and Belltawn BC, (2009). Weather risk and the viability of weather insurance in western China. Conference of the American Agricultural Economics Association, Milwaukee, Wisconsin.
Varangis P, Skees J and Barnett B, (2002). Financial risk management with weather hedges in weather indexes for developing countries. World Bank, chapter. 16: 280-292.
Zhu Y, Ghosh S and Goodwin B, (2008). Modeling dependence in the design of whole farm insurance contract a copula-based approach. Contributed paper at the Annual Meeting of the AAEA, Orlando, USA, July 27-29.
 
Agricultural Economics
Volume 9, Issue 3 - Serial Number 3
November 2015
Pages 37-62

Files

Share

How to cite

Statistics