The design of multiple crop insurance in Indonesia based on revenue risk using the copula model approach

References

• Atina Ahdika, Dedi Rosadi, Adhitya Ronnie Effendie, and https://www.researchgate.net/profile/Gunardi-Gunardi Gunardi Gunardi, Modeling indemnity of revenue-based crop insurance in Indonesia using time-varying copula models. AIP Conference Proceedings. 2192 (2019), pp. 030001. doi: https://doi.org/10.1063/1.5139121.
   Google Scholar
• U. Cherubini, E. Luciano, and W. Vecchiato, Copula Methods in Finance, John Wiley & Sons, Hoboken, NJ, 2004.
   Google Scholar
• G.V. Duarte, and V.A. Ozaki, Pricing crop revenue insurance using parametric copulas. Rev. Brasileira Econ. 73 (2019), pp. 325–343.
   Google Scholar
• K. Durukan, H. Orkcu, and E.K. Kara, Risk premium for dependent risks using utility copulas and risk aversion. İstatistik J. Turkish Stat. Assoc. 12 (2019), pp. 1–12.
   Google Scholar
• C. Genest and J. Nešlehová, Copulas: Introduction to the Theory and Implementation in R with Applications in Finance and Insurance, In course material for the workshop presented at the 38th Annual Meeting of the Statistical Society of Canada, Quebec (QC), 2010.
   Google Scholar
• S. Ghosh, J.D. Woodard, and D.V. Vedenov, Efficient estimation of copula mixture model: an application to the rating of crop revenue insurance. No. 321-2016-11250, 2011.
   Google Scholar
• B.K. Goodwin, and A. Hungerford, Copula-based models of systemic risk in US agriculture: Implications for crop insurance and reinsurance contracts. Am. J. Agric. Econ. 97 (2015), pp. 879–896.
   Web of Science ®Google Scholar
• J. Harwood, R. Heifner, K. Coble, J. Perry, and A. Somwaru, Managing risk in farming: Concepts, research, and analysis. Agricultural Economics Report No. 774, Economic Research Service, US Department of Agriculture, USA, 1999.
   Google Scholar
• M. Hofert, M. Mächler, and A.J. Mcneil, Likelihood inference for Archimedean copulas in high dimensions under known margins. J. Multivar. Anal. 110 (2012), pp. 133–150.
   Web of Science ®Google Scholar
• R. Jane, L. Dalla Valle, D. Simmonds, and A. Raby, A copula-based approach for the estimation of wave height records through spatial correlation. Coastal Eng. 117 (2016), pp. 1–18.
   Web of Science ®Google Scholar
• E.K. Kara, and S.A. Kemaloglu, Portfolio optimization of dynamic copula models for dependent financial data using change point approach. Commun. Faculty Sci. Univ. Ankara Ser. A1 Math. Stat. 65 (2016), pp. 175–188.
   Google Scholar
• S.A. Kemaloglu, and E.K. Kara, Modeling dependent financial assets by dynamic copula and portfolio optimization based on CVaR. Commun. Faculty Sci. Univ. Ankara Ser. A1 Math. Stat. 64 (2015), pp. 1–13.
   Google Scholar
• E. Kole, K. Koedijk, and M. Verbeek, Selecting copulas for risk management. J. Bank. Financ. 31 (2007), pp. 2405–2423.
   Web of Science ®Google Scholar
• C.-H. Ling, Representation of associative functions. Publ. Math. Debrecent 12 (1965), pp. 189–212.
   Google Scholar
• MÁ Martínez-Damián, J.D.J. Brambila-Paz, and E. González-Estrada, Modelando riesgo de ingreso: un enfoque de cópulas. Agrociencia 51 (2017), pp. 581–590.
   Google Scholar
• S. Mishra, C. Würsig, & C. Bordin, and I. Palu, Multivariate scenario generation – an Arima and Copula approach. Int. J. Model. Optim. 9. (2019), pp.146–149. doi:https://doi.org/10.7763/IJMO.2019.V9.700.
   Google Scholar
• R.B. Nelsen, An Introduction to Copulas, Springer Science & Business Media, Berlin, 2007.
   Google Scholar
• A. Osama, and S. Teresa, Economic analysis of the introduction of agricultural revenue insurance contracts in Spain using statistical copulas. Agri. Econ. 46 (2015), pp. 69–79.
   Web of Science ®Google Scholar
• A.J. Patton, Copula-based Models for Financial Time Series. Oxford Financial Research Centre, OFRC Working Papers Series. (2008), doi: https://doi.org/10.1007/978-3-540-71297-8_34.
   Google Scholar
• M. Sklar, Fonctions de repartition an dimensions et leurs marges. Publ. Inst. Statist. Univ. Paris 8 (1959), pp. 229–231.
   Google Scholar
• B.P. Statistik, Statistik Tanaman Sayuran dan Buah-Buahan Semusim Indonesia, Badan Pusat Statistik, Jakarta, 2017.
   Google Scholar
• H.A. Tejeda, and B.K. Goodwin, Modeling crop prices through a Burr distribution and analysis of correlation between crop prices and yields using a copula method, No. 382-2016-22380, 2008.
   Google Scholar
• P.K. Trivedi, and D.M. Zimmer, Copula modeling: an introduction for practitioners. Found. Trends® Econom. 1 (2007), pp. 1–111.
   Google Scholar
• Y. Zhu, S.K. Ghosh, and B.K. Goodwin, Modeling dependence in the design of whole farm—a copula-based model approach, No. 382-2016-22619, 2008.
   Google Scholar