Flexible Weather Index Insurance Design with Penalized Splines

REFERENCES

• Arrow, K. 1963. Uncertainty and the welfare economics of medical care. The American Economic Review 53 (5):941–73.
   Web of Science ®Google Scholar
• Bielza, M., J. Stroblmair, J. Gallego, C. G. Conte, and C. Dittmann. 2007. Agricultural risk management in Europe. No 9252, 101st Seminar, July 5–6, European Association of Agricultural Economists, Berlin Germany.
   Google Scholar
• Bontems, P., and A. Thomas. 2000. Information value and risk premium in agricultural production: The case of split nitrogen application for corn. American Journal of Agricultural Economics 82 (1):59–70. doi:10.1111/0002-9092.00006
   Web of Science ®Google Scholar
• Brockett, P. L., M. Wang, and C. Yang. 2005. Weather derivatives and weather risk management. Risk Management and Insurance Review 8 (1):127–40. doi:10.1111/j.1540-6296.2005.00052.x
   Google Scholar
• Cai, R., J. D. Mullen, J. C. Bergstrom, W. D. Shurley, and M. E. Wetzstein. 2013. Using a climate index to measure crop yield response. Journal of Agricultural and Applied Economics 45:719–37. doi:10.1017/S1074070800005228
   Google Scholar
• Carter, M. R., L. Cheng, and A. Sarris. 2016. Where and how index insurance can boost the adoption of improved agricultural technologies. Journal of Development Economics 118:59–71. doi:10.1016/j.jdeveco.2015.08.008
   Web of Science ®Google Scholar
• Champion, R., C. Lenard, and T. Mills. 1998. Actuarial science and variational splines. In Proceedings of the International Conference on Mathematical Methods for Curves and Surfaces II, ed. Morten Dæhlen, Tom Lyche, and Larry L. Schumaker, 49–54. United States: Vanderbilt University.
   Google Scholar
• Chantarat, S., A. G. Mude, C. B. Barrett, and M. R. Carter. 2013. Designing index-based livestock insurance for managing asset risk in northern Kenya. Journal of Risk and Insurance 80 (1):205–37. doi:10.1111/j.1539-6975.2012.01463.x
   Web of Science ®Google Scholar
• Chavas, J.-P., and M. T. Holt. 1990. Acreage decisions under risk: The case of corn and soybeans. American Journal of Agricultural Economics 72 (3):529–38. doi:10.2307/1243021
   Web of Science ®Google Scholar
• Chen, L., and Y. Shen. 2018. On a new paradigm of optimal reinsurance: A stochastic Stackelberg differential game between an insurer and a reinsurer. ASTIN Bulletin 48 (2):905–60. doi:10.1017/asb.2018.3
   Web of Science ®Google Scholar
• Cheung, K. C., S. C. P. Yam, and Y. Zhang. 2019. Risk-adjusted Bowley reinsurance under distorted probabilities. Insurance: Mathematics and Economics 86:64–72. doi:10.1016/j.insmatheco.2019.02.006
   Web of Science ®Google Scholar
• Chi, Y., K. S. Tan, and S. C. Zhuang. 2020. A Bowley solution with limited ceded risk for a monopolistic reinsurer. Insurance: Mathematics and Economics 91:188–201.
   Web of Science ®Google Scholar
• Clarke, D. J. 2016. A theory of rational demand for index insurance. American Economic Journal: Microeconomics 8 (1):283–306.
   Web of Science ®Google Scholar
• Coble, K. H., and B. J. Barnett. 2013. Why do we subsidize crop insurance? American Journal of Agricultural Economics 95 (2):498–504.
   Web of Science ®Google Scholar
• Cole, S., X. Giné, J. Tobacman, P. Topalova, R. Townsend, and J. Vickery. 2013. Barriers to household risk management: Evidence from India. American Economic Journal: Applied Economics 5 (1):104–35.
   PubMed Web of Science ®Google Scholar
• Conradt, S., R. Finger, and M. Spörri. 2015. Flexible weather index-based insurance design. Climate Risk Management 10:106–17.
   Web of Science ®Google Scholar
• Currie, I. D. 2016. On fitting generalized linear and non-linear models of mortality. Scandinavian Actuarial Journal 2016 (4):356–83. doi:10.1080/03461238.2014.928230
   Web of Science ®Google Scholar
• Currie, I. D., and M. Durban. 2002. Flexible smoothing with P-splines: A unified approach. Statistical Modelling 2 (4):333–49. doi:10.1191/1471082x02st039ob
   Web of Science ®Google Scholar
• Currie, I. D., M. Durban, and P. H. Eilers. 2004. Smoothing and forecasting mortality rates. Statistical Modelling 4 (4):279–98. doi:10.1191/1471082X04st080oa
   Web of Science ®Google Scholar
• de Boor, C. 1978. A practical guide to splines. Vol. 27. New York: Springer.
   Google Scholar
• Dierckx, P. 1995. Curve and surface fitting with splines. New York: Oxford University Press.
   Google Scholar
• Doherty, N. A., and H. Schlesinger. 1983. Optimal insurance in incomplete markets. Journal of Political Economy 91 (6):1045–54. doi:10.1086/261199
   Web of Science ®Google Scholar
• Eilers, P. H., and B. D. Marx. 1996. Flexible smoothing with B-splines and penalties. Statistical Science 11 (2):89–102. doi:10.1214/ss/1038425655
   Web of Science ®Google Scholar
• Eubank, R. L. 1999. Nonparametric regression and spline smoothing. Boca Raton: CRC Press.
   Google Scholar
• Forfar, D., J. McCutcheon, and A. Wilkie. 1988. On graduation by mathematical formula. Journal of the Institute of Actuaries 115 (1):1–149. doi:10.1017/S0020268100042633
   Google Scholar
• Giné, X., R. Townsend, and J. Vickery. 2007. Statistical analysis of rainfall insurance payouts in southern India. American Journal of Agricultural Economics 89 (5):1248–54. doi:10.1111/j.1467-8276.2007.01092.x
   Web of Science ®Google Scholar
• Glauber, J. W., and K. J. Collins. 2002. Risk management and the role of the federal government. In A comprehensive assessment of the role of risk in U.S. agriculture, ed. Richard E. Just and Rulon D. Pope, 469–88. Boston, MA: Springer.
   Google Scholar
• Goodwin, B. K., and L. A. Vado. 2007. Public responses to agricultural disasters: Rethinking the role of government. Canadian Journal of Agricultural Economics 55 (4):399–417. doi:10.1111/j.1744-7976.2007.00099.x
   Web of Science ®Google Scholar
• Green, P. J., and B. W. Silverman. 1993. Nonparametric regression and generalized linear models: A roughness penalty approach. New York: Chapman and Hall/CRC.
   Google Scholar
• Hazell, P., R. Sberro-Kessler, and P. Varangis. 2017. When and how should agricultural insurance be subsidized? International Labour Organization and the International Finance Corporation. Washington, DC: World Bank.
   Google Scholar
• Holzmann, R., and S. Jørgensen. 2001. Social risk management: A new conceptual framework for social protection, and beyond. International Tax and Public Finance 8 (4):529–56.
   Web of Science ®Google Scholar
• Jensen, N. D., C. B. Barrett, and A. G. Mude. 2016. Index insurance quality and basis risk: Evidence from northern Kenya. American Journal of Agricultural Economics 98 (5):1450–69. doi:10.1093/ajae/aaw046
   Web of Science ®Google Scholar
• Likhachev, D. 2017. Selecting the right number of knots for B-spline parameterization of the dielectric functions in spectroscopic ellipsometry data analysis. Thin Solid Films 636:519–26. doi:10.1016/j.tsf.2017.06.056
   Web of Science ®Google Scholar
• Manfredo, M. R., and T. J. Richards. 2009. Hedging with weather derivatives: A role for options in reducing basis risk. Applied Financial Economics 19 (2):87–97. doi:10.1080/09603100701765166
   Google Scholar
• Marsh, L. C., and D. R. Cormier. 2001. Spline regression models. Number 137. Thousand Oaks, CA: SAGE Publications, Inc.
   Google Scholar
• Marx, B. D., and P. H. Eilers. 1999. Generalized linear regression on sampled signals and curves: a P-spline approach. Technometrics 41 (1):1–13. doi:10.1080/00401706.1999.10485591
   Web of Science ®Google Scholar
• Menapace, L., G. Colson, and R. Raffaelli. 2013. Risk aversion, subjective beliefs, and farmer risk management strategies. American Journal of Agricultural Economics 95 (2):384–89. doi:10.1093/ajae/aas107
   Web of Science ®Google Scholar
• Okhrin, O., M. Odening, and W. Xu. 2013. Systemic weather risk and crop insurance: The case of China. Journal of Risk and Insurance 80 (2):351–72. doi:10.1111/j.1539-6975.2012.01476.x
   Web of Science ®Google Scholar
• Porth, B., L. Porth, W. Zhu, M. Boyd, K. S. Tan, and K. Liu. 2020. Remote sensing applications for insurance: A predictive model for pasture yield in the presence of systemic weather. North American Actuarial Journal 24 (2): 333–54.
   Web of Science ®Google Scholar
• Price, M. J., C. L. Yu, D. A. Hennessy, and X. Du. 2019. Are actuarial crop insurance rates fair?: An analysis using a penalized bivariate B-spline method. Journal of the Royal Statistical Society: Series C (Applied Statistics) 68 (5):1207–32.
   Web of Science ®Google Scholar
• Raviv, A. 1979. The design of an optimal insurance policy. The American Economic Review 69 (1):84–96.
   Web of Science ®Google Scholar
• Richards, S. J. 2020. A Hermite-spline model of post-retirement mortality. Scandinavian Actuarial Journal 2020 (2):110–27. doi:10.1080/03461238.2019.1642239
   Web of Science ®Google Scholar
• Roberts, M. J., W. Shilenker, and J. Eyer. 2012. Agronomic weather measures in econometric models of crop yield with implications for climate change. American Journal of Agricultural Economics 49 (2):236–43. doi:10.1093/ajae/aas047
   Google Scholar
• Santeramo, F. G., and A. F. Ramsey. 2017. Crop insurance in the EU: Lessons and caution from the U.S. EuroChoices 16 (3):34–39. doi:10.1111/1746-692X.12154
   Google Scholar
• Singla, S., and M. Sagar. 2012. Integrated risk management in agriculture: An inductive research. Journal of Risk Finance 13 (3):199–214. doi:10.1108/15265941211229235
   Google Scholar
• Smith, V. H. 2017. Achieving rational farm subsidy rates. R Street Policy Study No. 113. Washington, DC: R Street Institute.
   Google Scholar
• Smith, V. H., and J. W. Glauber. 2019. The future of U.S. farm policy. EuroChoices 18 (1):42–48. doi:10.1111/1746-692X.12223
   Web of Science ®Google Scholar
• Tan, K. S., and C. Weng. 2014. Empirical approach for optimal reinsurance design. North American Actuarial Journal 18 (2):315–42. doi:10.1080/10920277.2014.888008
   Google Scholar
• Tan, K. S., C. Weng, and Y. Zhang. 2011. Optimality of general reinsurance contracts under CTE risk measure. Insurance: Mathematics and Economics 49 (2):175–87. doi:10.1016/j.insmatheco.2011.03.002
   Web of Science ®Google Scholar
• Turvey, C. G. 2001. Weather derivatives for specific event risks in agriculture. Applied Economic Perspectives and Policy 23 (2):333–51.
   Google Scholar
• Ullah, R., D. Jourdain, G. P. Shivakoti, and S. Dhakal. 2015. Managing catastrophic risks in agriculture: Simultaneous adoption of diversification and precautionary savings. International Journal of Disaster Risk Reduction 12:268–77. doi:10.1016/j.ijdrr.2015.02.001
   Web of Science ®Google Scholar
• Ullah, R., and G. P. Shivakoti. 2014. Adoption of on-farm and off-farm diversification to manage agricultural risks: Are these decisions correlated? Outlook on Agriculture 43 (4):265–71. doi:10.5367/oa.2014.0188
   Web of Science ®Google Scholar
• USDA. 2019. 2014-18 Agricultural Resource Management Survey. Washington, DC: United States Department of Agriculture.
   Google Scholar
• Wood, S. N. 2003. Thin plate regression splines. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 65 (1):95–114. doi:10.1111/1467-9868.00374
   Web of Science ®Google Scholar
• Xiao, L., Y. Li, and D. Ruppert. 2013. Fast bivariate P-splines: The sandwich smoother. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 75 (3):577–99. doi:10.1111/rssb.12007
   Web of Science ®Google Scholar
• Zhang, J., K. S. Tan, and C. Weng. 2019. Index insurance design. ASTIN Bulletin 49 (2):491–523. doi:10.1017/asb.2019.5
   Web of Science ®Google Scholar
• Zhu, W., L. Porth, and K. S. Tan. 2019. A credibility-based yield forecasting model for crop reinsurance pricing and weather risk management. Agricultural Finance Review 79 (1):2–26. doi:10.1108/AFR-08-2017-0064
   Web of Science ®Google Scholar