Climate derivatives strategies as an alternative to set up guaranteed prices for agricultural producers in México

References

• Alexandridis, A., and A. Zapranis. 2013. “Wind Derivatives: Modeling and Pricing.” Computational Economics 41 (3): 299–326. doi:10.1007/s10614-012-9350-y.
   Web of Science ®Google Scholar
• Aloui, R., S. Hammoudeh, and D. Khuong Nguyen. 2013. “A Time-varying Copula Approach to Oil and Stock Market Dependence: The Case of Transition Economies.” Energy Economics 39 (1): 208–221. doi:10.1016/j.eneco.2013.04.012.
   Google Scholar
• Appendini, K., and V. Almeida Salles. 1980. “Precios de garantía y crisis agrícola.” Nueva Antropología 4 (14): 187–218.
   Google Scholar
• Bachev, H. 2013. “Risk Management in Agri-food Sector.” Contemporary Economics 7 (1): 45–62. doi:10.5709/ce.1897-9254.73.
   Google Scholar
• Barquera, S., J. Rivera-Dommarco, and A. Gasca-García. 2001. “Políticas y programas de alimentación y nutrición en México.” Salud Pública de México 43 (1): 464–477. doi:10.1590/S0036-36342001000500011.
   PubMedGoogle Scholar
• Beaudoin, D., and L. Lakhal-Chaieb. 2008. “Archimedean Copula Model Selection under Dependent Truncation.” Statistics in Medicine 27 (22): 4440–4454. doi:10.1002/sim.3316.
   PubMed Web of Science ®Google Scholar
• Boisier, J. P., P. Ciais, A. Ducharne, and M. Guimberteau. 2015. “Projected Strengthening of Amazonian Dry Season by Constrained Climate Model Simulations.” Nature Climate Change 5 (7): 656–661. doi:10.1038/nclimate2658.
   Web of Science ®Google Scholar
• Cabrera López, B., M. Odening, and M. Ritter. 2013. “Pricing Rainfall Futures at the CME.” Journal of Banking and Finance 37 (11): 4286–4298. doi:10.1016/j.jbankfin.2013.07.042.
   Web of Science ®Google Scholar
• Caporin, M., and J. Preś. 2012. “Modelling and Forecasting Wind Speed Intensity for Weather Risk Management.” Computational Statistics & Data Analysis 56 (11): 3459–3476. doi:10.1016/j.csda.2010.06.019.
   Web of Science ®Google Scholar
• Centro de Estudios para el Desarrollo Rural Sustentable y la Soberanía Alimentaria (CEDRSSA). 2018. Accessed 10 January 2019. http://www.cedrssa.gob.mx/post_n-presupuesto-n-_del_programa_especial_concurrente_para_el_desarrollo_rural_sustentable_-n-2019-n.htm
   Google Scholar
• Cherubini, U., E. Luciano, and W. Vecchiato. 2004. Copula Methods in Finance. John Wiley and Sons. 1st ed. Cornwall, UK: Wiley, Finance.
   Google Scholar
• Clapp, J. 2014. “Financialization, Distance and Global Food Politics.” Journal of Peasant Studies 41 (5): 797–814. doi:10.1080/03066150.2013.875536.
   Web of Science ®Google Scholar
• Clapp, J., and E. Helleiner. 2012. “Troubled Futures? The Global Food Crisis and the Politics of Agricultural Derivatives Regulation.” Review of International Political Economy 19 (2): 181–207. doi:10.1080/09692290.2010.514528.
   Web of Science ®Google Scholar
• Core Team, R. 2018. “R: A Language and Environment for Statistical.” [On line]. Accessed 20 May 2019. https://www.R-project.org/
   Google Scholar
• Delgadillo, J. 1992. “Ensayos sobre el cooperativismo rural en México, Krotz Esteban.” Problemas del Desarrollo 23 (88): 17–23.
   Google Scholar
• Deng, Y., and N. R. Chaganty. 2017. “Hierarchical Archimedean Copula Models for the Analysis of Binary Familial Data.” Statistics in Medicine 37 (4): 590–597. doi:10.1002/sim.7521.
   PubMed Web of Science ®Google Scholar
• Dupuis, D. J. 2007. “Using Copulas in Hydrology: Benefits, Cautions, and Issues.” Journal of Hydrologic Engineering 12 (4): 381–393. doi:10.1061/(ASCE)1084-0699(2007)12:4(381).
   Web of Science ®Google Scholar
• Embrechts, P., F. Lindskog, and A. J. McNeil. 2003. “Modeling Dependence with Copulas and Applications to Risk Management.” In Handbook of Heavy Tailed Distributions in Finance, edited by S. Rachev, 329–384. Rotterdam: Elsevier.
   Google Scholar
• Ender, M., and R. Zhang. 2015. “Efficiency of Weather Derivatives for Chinese Agriculture Industry.” China Agricultural Economic Review 7 (1): 102–121. doi:10.1108/CAER-06-2013-0089.
   Web of Science ®Google Scholar
• Félix Valencia, P., J. E. Ortíz Enríquez, G. Fuentes Dávila, J. G. Quintana Quiróz, and J. Grajeda (2009). “Horas frío en relación al rendimiento de trigo. Folleto técnico.” 63. Accessed 23 May 2019. www.sefoa.gob.mx/simarbc/descargas/TRIGO%20HORAS%20FRIO%20SONORA.pdf
   Google Scholar
• Fernández y Fernández, R. 1946. “Problemas creados por la reforma agraria de México.” El Trimestre Económico 13 (51): 463–494.
   Google Scholar
• Frahm, G., M. Junker, and A. Szimayer. 2003. “Elliptical Copulas: Applicability and Limitations.” Statistics & Probability Letters 63 (3): 275–286. doi:10.1016/S0167-7152(03)00092-0.
   Web of Science ®Google Scholar
• Genius, M., and E. Strazzera. 2008. “Applying the Copula Approach to Sample Selection Modelling.” Applied Economics 40 (11): 1443–1455. doi:10.1080/00036840600794348.
   Web of Science ®Google Scholar
• González Amador, R. 1998. “La Jornada.” [On line]. Accessed 26 January 2019 Available at: https://www.jornada.com.mx/1998/11/07/paraestatal.html
   Google Scholar
• Grolemund, G., and H. Wickham. 2011. “Dates and Times Made Easy with Lubridate.” Journal of Statistical Software 40 (3): 1–25. doi:10.18637/jss.v040.i03.
   Web of Science ®Google Scholar
• Groll, A., B. López-Cabrera, and T. Meyer-Brandis. 2016. “A Consistent Two-factor Model for Pricing Temperature Derivatives.” Energy Economics 55 (1): 112–126. doi:10.1016/j.eneco.2015.12.020.
   Google Scholar
• Hasselmann, K. 1993. “Optimal Fingerprints for the Detection of Time-dependent Climate Change.” Journal of Climate 6 (10): 1957–1971. doi:10.1175/1520-0442(1993)006<1957:OFFTDO>2.0.CO;2.
   Web of Science ®Google Scholar
• Hernández Trujillo, J. M., and E. Salinas Callejas. 2009. “Visión retrospectiva del campo mexicano.” El Cotidiano 156 (1): 63–75.
   Google Scholar
• Hess, M. 2016. “Modeling and Pricing Precipitation Derivatives under Weather Forecasts.” International Journal of Theoretical and Applied Finance 19 (7): 650051. doi:10.1142/S0219024916500515.
   Web of Science ®Google Scholar
• Hess, U., K. Richter, and A. Stoppa. 2002. “Weather Risk Management for Agriculture and Agri-business in Developing Countries.” In Climate Risk and the Weather Market, Financial Risk Management with Weather Hedges, edited by R. Gorvett. London: Risk Books, p. 16.
   Google Scholar
• Huang, J., M. Korolkiewicz, M. Agrawal, and J. Boland. 2013. “Forecasting Solar Radiation on an Hourly Time Scale Using a Coupled AutoRegressive and Dynamical System (CARDS) Model.” Solar Energy 87 (1): 136–149. doi:10.1016/j.solener.2012.10.012.
   Google Scholar
• Huang, J., S. S. Yang, and C. Chang. 2018. “Modeling Temperature Behaviors: Application to Weather Derivative Valuation.” Journal of Futures Markets 38 (9): 1152–1175. doi:10.1002/fut.21923.
   Web of Science ®Google Scholar
• Huang, J.-K., and Y. J. Wang. 2014. “Financing Sustainable Agriculture under Climate Change.” Journal of Integrative Agriculture 13 (4): 698–712. doi:10.1016/S2095-3119(13)60698-X.
   Web of Science ®Google Scholar
• Isakson, S. R. 2015. “Derivatives for Development? Small‐farmer Vulnerability and the Financialization of Climate Risk Management.” Journal of Agrarian Change 15 (4): 569–580. doi:10.1111/joac.12124.
   Web of Science ®Google Scholar
• Joe, H., and J. Xu. 1996. “The Estimation Method of Inference Functions for Margins for Multivariate Models, Technical Report 166, Department of Statistics, University of British Columbia.” Accessed 16th February 2019. https://open.library.ubc.ca/cIRcle/collections/facultyresearchandpublications/52383/items/1.0225985
   Google Scholar
• Juárez-Torres, M., and L. Sánchez-Aragon (2012). Effectiveness of Weather Derivatives as a Cross-Hedging Instrument against Climate Change: The Cases of Reservoir Water Allocation Management in Guanajuato, Mexico and Lambayeque, Peru, IDB Working Paper Series, No. IDB-WP-328, Inter-American Development Bank (IDB), Washington, DC.
   Google Scholar
• Juárez-Torres, M., L. Sánchez-Aragón, and D. Dmitry Vedenov. 2017. “Weather Derivatives and Water Management in Developing Countries.” Journal of Agricultural and Resource Economics 42 (2): 146–163.
   Web of Science ®Google Scholar
• Kaplan, J. O., and M. New. 2006. “Arctic Climate Change with a 2∘ C Global Warming: Timing, Climate Patterns and Vegetation Change.” Climatic Change 79 (3–4): 213–241. doi:10.1007/s10584-006-9113-7.
   Web of Science ®Google Scholar
• Kojadinovic, I., and J. Yan. 2010. “Modeling Multivariate Distributions with Continuous Margins Using the Copula R Package.” Journal of Statistical Software 34 (9): 1–20. doi:10.18637/jss.v034.i09.
   Web of Science ®Google Scholar
• Konstantinidi, E., G. Papazian, and G. Skiadopoulos. 2016. “Modeling the Dynamics of Temperature with a View to Weather Derivatives. En: A. G. Malliaris and W. T. Ziemba, Edits.” The World Scientific Handbook of Futures Markets 5: 511–544.
   Google Scholar
• Lau, K. M., and P. H. Chan. 1986. “The 40–50 Day Oscillation and the El Niño/Southern Oscillation: A New Perspective.” Bulletin of the American Meteorological Society 67 (5): 533–534. doi:10.1175/1520-0477(1986)067<0533:TDOATE>2.0.CO;2.
   Web of Science ®Google Scholar
• Lau, W. K., and K. M. Kim. 2002. The MJO-ENSO Relationship: A Re-assessment. Maryland, 88–91. USA, NASA: Technical Report Series on Global Modeling and Data Assimilation.
   Google Scholar
• Leiva, A. J., and J. R. Skees. 2008. “Using Irrigation Insurance to Improve Water Usage of the Rio Mayo Irrigation System in Northwestern Mexico.” World Development 36 (12): 2663–2678. doi:10.1016/j.worlddev.2007.12.004.
   Web of Science ®Google Scholar
• Li, P. 2018. “Pricing Weather Derivatives with Partial Differential Equations of the Ornstein–Uhlenbeck Process.” Computers & Mathematics with Applications 75 (3): 1044–1059. doi:10.1016/j.camwa.2017.10.030.
   Web of Science ®Google Scholar
• Lipper, L., et al. 2014. “Climate-smart Agriculture for Food Security.” Nature Climate Change 4 (12): 1068–1072. doi:10.1038/nclimate2437.
   Web of Science ®Google Scholar
• Lokare, S. M. 2007. “Commodity Derivatives and Price Risk Management: An Empirical Anecdote from India.” Reserve Bank of India Occasional Papers 28 (2): 27–77.
   Google Scholar
• Lustig, N., and R. Pérez Espejo. 1982. “Sistema alimentario mexicano: Antecedentes, características, estrategias y efectos.” Problemas del Desarrollo 13 (51): 247–286.
   Google Scholar
• Maity, R., M. Suman, P. Laux, and H. Kunstmann. 2019. “Bias Correction of Zero-inflated RCM Precipitation Fields: A Copula-based Scheme for Both Mean and Extreme Conditions.” Journal of Hydrometeorology 20 (4): 595–611. doi:10.1175/JHM-D-18-0126.1.
   Web of Science ®Google Scholar
• Makkeasorn, A., N.-B. Chang, and X. Zhou. 2008. “Short-term Streamflow Forecasting with Global Climate Change implications–A Comparative Study between Genetic Programming and Neural Network Models.” Journal of Hydrology 352 (3–4): 336–354. doi:10.1016/j.jhydrol.2008.01.023.
   Web of Science ®Google Scholar
• Manner, H., and O. Reznikova. 2012. “A Survey on Time-varying Copulas: Specification, Simulations, and Application.” Econometric Reviews 31 (6): 654–687. doi:10.1080/07474938.2011.608042.
   Web of Science ®Google Scholar
• Martínez-Carrasco Pleite, F., J. B. Colino Sueiras, and M. Á. Gómez Cruz. 2014. “Pobreza y políticas de desarrollo rural en México.” Estudios Sociales 22 (43): 9–35.
   Google Scholar
• Mazabel, D., V. Tamayo Ricárdez, and T. Carmen Patiño. 2014. “Estructura agraria, evolución del sector agrícola y crisis en el campo mexicano.” Observatorio de la Economía Latinoamericana 201.
   Google Scholar
• Mendelsohn, R. 2014. “The Impact of Climate Change on Agriculture in Asia.” Journal of Integrative Agriculture 13 (4): 660–665. doi:10.1016/S2095-3119(13)60701-7.
   Web of Science ®Google Scholar
• Musshoff, O., M. Odening, and W. Xu. 2011. “Management of Climate Risks in Agriculture–will Weather Derivatives Permeate?” Applied Economics 43 (9): 1076–1077. doi:10.1080/00036840802600210.
   Web of Science ®Google Scholar
• Nelsen, R. 1998. An Introduction to Copulas, Lectures Notes in Statistics. 1 st ed. New York, USA: Springer Verlag.
   Google Scholar
• Oh, D. H., and A. J. Patton. 2018. “Time-varying Systemic Risk: Evidence from a Dynamic Copula Model of CDS Spreads.” Journal of Business and Economic Statistics 36 (2): 181–195. doi:10.1080/07350015.2016.1177535.
   Web of Science ®Google Scholar
• Ortiz-Álvarez, M. I., and R. Y Vidal-zepeda. 2006. “Población expuesta a inviernos fríos en México.” Investigaciones Geográficas 59: 93–112.
   Google Scholar
• Ortmann, G. F., and R. P. King. 2007a. “Agricultural Cooperatives I: History, Theory and Problems.” Agrekon 46 (1): 18–46. doi:10.1080/03031853.2007.9523760.
   Google Scholar
• Ortmann, G. F., and R. P. King. 2007b. “Agricultural Cooperatives II: Can They Facilitate Access of Small-scale Farmers in South Africa to Input and Product Markets?” Agrekon 46 (2): 219–244. doi:10.1080/03031853.2007.9523769.
   Google Scholar
• Otsuka, K., Y. Nakano, and K. Takahashi. 2016. “Contract Farming in Developed and Developing Countries.” Annual Review of Resource Economics 8 (1): 353–376. doi:10.1146/annurev-resource-100815-095459.
   Google Scholar
• Patton, A. J. 2009. “Copula–based Models for Financial Time Series.” In Handbook of Financial Time Series, edited by T. Mikosch, J. Kreiß, R. A. Davis, and T. G. Andersen, 767–785. Berlin: Springer.
   Google Scholar
• Pirrong, C., and M. Jermakyan. 2008. “The Price of Power: The Valuation of Power and Weather Derivatives.” Journal of Banking and Finance 32 (12): 2520–2529. doi:10.1016/j.jbankfin.2008.04.007.
   Web of Science ®Google Scholar
• Poulton, C., A. Dorward, and J. Kydd. 2010. “The Future of Small Farms: New Directions for Services, Institutions, and Intermediation.” World Development 38 (10): 1413–1428. doi:10.1016/j.worlddev.2009.06.009.
   Web of Science ®Google Scholar
• Ramírez-Vázquez, J., J. A. Santa Rosa, H. E. Villaseñor-Mir, E. López-Herrera, y Martínez-Cruz, and E. Espitia Rangel. 2016. “Evaluación De Variedades Y Líneas Uniformes De Trigo Harinero De Temporal En Valles Altos.” Revista Mexicana de Ciencias Agrícolas 7 (3): 655–667. doi:10.29312/remexca.v7i3.325.
   Google Scholar
• Randrianarisoa, J. C., and B. Minten. 2001. “Agricultural Production, Agricultural Land and Rural Poverty in Madagascar. Cornell Food and Nutrition Policy Program.” Working Paper No. 112. Accessed 15 January 2019. https://ssrn.com/abstract=439101;http://doi.org/10.2139/ssrn.439101
   Google Scholar
• Ray, P. 2016. “Weather Derivatives - A Need for Indian Farmers?” International Journal of Banking, Risk and Insurance 4 (1): 19–25. doi:10.21863/ijbri/2016.4.1.014.
   Google Scholar
• Redacción, R. P. 1988. “Proceso.” [On line].Accessed 25 January 2019. Available at: https://www.proceso.com.mx/179498/con-la-desaparicion-de-conasupo-quedarian-sepultadas-las-pruebas-de-corrupcion-de-tres-sexenios
   Google Scholar
• Redacción, R. P. 2002. “Proceso.” [On line]. Accessed 26 January 2019. Available at: https://www.proceso.com.mx/246003/acusan-a-banrural-de-fraude
   Google Scholar
• Rheinwalt, A., N. Boers, N. Marwan, J. Kurths, P. Hoffmann, F. Gerstengarbe, and P. Werner. 2016. “Non-linear Time Series Analysis of Precipitation Events Using Regional Climate Networks for Germany.” Climate Dynamics 46 (3–4): 1065–1074. doi:10.1007/s00382-015-2632-z.
   Web of Science ®Google Scholar
• Ritter, M., O. Musshoff, and M. Odening. 2014. “Minimizing Geographical Basis Risk of Weather Derivatives Using a Multi-site Rainfall Model.” Computational Economics 44 (1): 67–86. doi:10.1007/s10614-013-9410-y.
   Web of Science ®Google Scholar
• Rodríguez Chaurnet, D. 1980. “El Sistema Alimentario Mexicano.” Problemas del Desarrollo 11 (41): 161–172.
   Google Scholar
• Rodríguez-Puebla, C., S. M. Ayuso, M. D. Frias, and L. A. Garcia-Casado. 2007. “Effects of Climate Variation on Winter Cereal Production in Spain.” Climate Research 34 (3): 223–232. doi:10.3354/cr00700.
   Web of Science ®Google Scholar
• Salvadori, G., and C. C. De Michele. 2007. “On the Use of Copulas in Hydrology: Theory and Practice.” Journal of Hydrologic Engineering 12 (4): 369–380. doi:10.1061/(ASCE)1084-0699(2007)12:4(369).
   Web of Science ®Google Scholar
• Salvadori, G., and C. C. De Michele. 2011. “Estimating Strategies for Multiparameter Multivariate Extreme Value Copulas.” Hydrology and Earth System Sciences 15 (1): 141–150. doi:10.5194/hess-15-141-2011.
   Web of Science ®Google Scholar
• Schneider, S. H. 2004. “Abrupt Non-linear Climate Change, Irreversibility and Surprise.” Global Environmental Change 1 4 (3): 245–258. doi:10.1016/j.gloenvcha.2004.04.008.
   Google Scholar
• Schoelzel, C., and P. Friederichs. 2008. “Multivariate Non-normally Distributed Random Variables in Climate Research–introduction to the Copula Approach.” Non-linear Processes in Geophysics 15 (5): 761–772. doi:10.5194/npg-15-761-2008.
   Web of Science ®Google Scholar
• Secretaría de Hacienda y Crédito, P., and P. E. Federal. 2018. Accessed 19 January 2019. https://www.ppef.hacienda.gob.mx/es/PPEF2019.https://www.ppef.hacienda.gob.mx/work/models/PPEF2019/paquete/egresos/Proyecto_Decreto.pdf
   Google Scholar
• Servicio de Información Agroalimentaria y Pesquera, Gobierno de México. 2017. “Producción Agrícola.” Accessed 5th February 2019. https://www.gob.mx/siap/acciones-y-programas/produccion-agricola-33119
   Google Scholar
• Sexton, R. J. 2012. “Market Power, Misconceptions, and Modern Agricultural Markets.” American Journal of Agricultural Economics 95 (2): 209–219. doi:10.1093/ajae/aas102.
   Web of Science ®Google Scholar
• Shih, J. H., and T. A. Louis. 1995. “Inferences on the Association Parameter in Copula Models for Bivariate Survival Data.” Biometrics 51 (4): 1384–1399. doi:10.2307/2533269.
   PubMed Web of Science ®Google Scholar
• Shukla, J. 1992. “Short Term Climate Variability and Predictions.” AIP Conference Proceedings, 274( 1),113–128.
   Google Scholar
• Sistema Meteorológico Nacional. 2020. “Comunicado publicado el 14 de abril de 2020”. Retrieved from: https://www.gob.mx/smn/prensa/se-pronostican-temperaturas-superiores-a-35-grados-celsius-en-21-entidades-de-mexico-debido-a-onda-de-calor-240242
   Google Scholar
• Sklar, A. 1959. “Fonctions de répartition à n dimensions et leurs marges.” Publications De l’Institut De Statistique De l’Université De Paris 8 (1): 229–231.
   Google Scholar
• Slafer, G. A., and H. M. Rawson. 1994. “Sensitivity of Wheat Phasic Development to Major Environmental Factors: A Re-examination of Some Assumptions Made by Physiologists and Modellers.” Functional Plant Biology 21 (4): 393–426. doi:10.1071/PP9940393.
   Google Scholar
• Spalding, R. J. 1985. “El Sistema Alimentario Mexicano (SAM): Ascenso y decadencia.” Estudios Sociológicos 3 (8): 315–349.
   Google Scholar
• Stöber, J., H. Joe, and C. Czado. 2013. “Simplified Pair Copula Constructions - Limitations and Extensions.” Journal of Multivariate Analysis 119: 101–118. doi:10.1016/j.jmva.2013.04.014.
   Web of Science ®Google Scholar
• Swinnen, J. F. M. M. 2007. “Globalization, Privatization, and Vertical Coordination in Food Value Chains in Developing and Transition Countries.” Agricultural Economics 37 (1): 89–102. doi:10.1111/j.1574-0862.2007.00237.x.
   Web of Science ®Google Scholar
• Trivedi, P. K., and D. M. Zimmer. 2007. Copula Modeling: An Introduction for Practitioners. 1st Ed. ed. Hanover, MA, USA: Now Publishers .
   Google Scholar
• Turvey, C. G. 2001. “Weather Derivatives for Specific Event Risks in Agriculture.” Review of Agricultural Economics 23 (2): 333–351. doi:10.1111/1467-9353.00065.
   Google Scholar
• Valentinov, V. 2007. “Why are Cooperatives Important in Agriculture? An Organizational Economics Perspective.” Journal of Institutional Economics 3 (1): 55–69. doi:10.1017/S1744137406000555.
   Google Scholar
• Vedenov, D. V., and B. J. Barnett. 2004. “Efficiency of Weather Derivatives as Primary Crop Insurance Instruments.” Journal of Agricultural and Resource Economics 29 (3): 387–403.
   Web of Science ®Google Scholar
• Venegas-Martínez, F. 2008. Riesgos Financieros Y Económicos: Productos Derivados Y Decisiones Económicas Bajo Incertidumbre. Segunda Edición ed. Cengage Learning Méxi.
   Google Scholar
• Vermeulen, S. J., P. K. Aggarwal, A. Ainslie, C. Angelone, Campbell, B. Morgan, A. J. Challinor, et al. 2012. “Options for Support to Agriculture and Food Security under Climate Change.” Environmental Science & Policy 15 (1): 136–144. doi:10.1016/j.envsci.2011.09.003.
   Web of Science ®Google Scholar
• Villafuerte-Solís, D. 2015. “Crisis rural, pobreza y hambre en Chiapas.” LiminaR 13 (1): 13–28. doi:10.29043/liminar.v13i1.363.
   Google Scholar
• Weeks, J. E. 2016. Structural Adjustment and the Agricultural Sector in Latin America and the Caribbean. London: Springer.
   Google Scholar
• Woodard, J. D., and P. Garcia. 2008. “Basis Risk and Weather Hedging Effectiveness.” Agricultural Finance Review 68 (1): 99–117. doi:10.1108/00214660880001221.
   Google Scholar
• Yan, J. 2007. “Enjoy the Joy of Copulas: With a Package Copula.” Journal of Statistical Software 21 (4): 1–21. doi:10.18637/jss.v021.i04.
   Web of Science ®Google Scholar
• Yang, C. C., P. L. Brockett, and M. M. Wen. 2009. “Basis Risk and Hedging Efficiency of Weather Derivatives.” The Journal of Risk Finance 10 (5): 517–536. doi:10.1108/15265940911001411.
   Google Scholar
• Zara, C. 2010. “Weather Derivatives in the Wine Industry.” International Journal of Wine Business Research 22 (3): 222–237. doi:10.1108/17511061011075365.
   Google Scholar