Enhancing crop insurance analysis with agricultural zoning data
Melhoria da análise de seguro agrícola com dados de zoneamento agrícola
Gilson Martins; Guilherme Signorini
Abstract
Keywords
Resumo
Palavras-chave
Referências
Abbaspour, K. C. (1994). Bayesian risk methodology for crop insurance decisions.
Akerlof, G. A. (1970). The Market for “Lemons”: Quality Uncertainty and the Market Mechanism.
Aparecido, L. E. O., Batista, R. M., Moraes, J. R. S. C., Costa, C. T. S., & Moraes-Oliveira, A. F. (2019). Agricultural zoning of climate risk for Physalis peruviana cultivation in Southeastern Brazil.
Bonatto, M. I., Bosco, L. C., Pandolfo, C., Ricce, W. da S., Stanck, L. T., de Souza, A. G., Rossato, O. B., & Streck, N. A. (2021). Agricultural climate risk zoning for gladiolus in santa catarina.
Brisolara, C. S., & Ozaki, V. A. (2022). Uma proposição metodológica para a precificação de seguro de receita agrícola no Brasil.
Brito, J. E. D., Santos, M. A., Lyra, G. B., Ferreira Júnior, R. A., & Souza, J. L. (2022). Maize sowing dates in the hinterland region of Northeast Brazil.
Caldana, N. F. S., Nitsche, P. R., Martelocio, A. C., Rudke, A. P., Zaro, G. C., Ferreira, L. G. B., Zaccheo, P. V. C., Carvalho, S. L. C., & Martins, J. A. (2019). Agroclimatic Risk Zoning of Avocado (Persea americana) in the Hydrographic Basin of Paraná River III, Brazil.
Campbell, C. A., Selles, F., Zentner, R. P., & McConkey, B. G. (1993). Available water and nitrogen effects on yield components and grain nitrogen of zero-till spring wheat.
Casella, G., & Berger, R. L. (1990).
Cox, M. S., Gerard, P. D., Wardlaw, M. C., & Abshire, M. J. (2003). Variability of selected soil properties and their relationships with soybean yield.
Cunha, G. R., Barni, N. A., Haas, J. C., Maluf, J. R. T., Matzenauer, R., Pasinato, A., Pimentel, M. B. M., & Pires, J. L. F. (2001a). Zoneamento agrícola e época de semeadura para soja no Rio Grande do Sul.
Cunha, G. R., Haas, J. C., Maluf, J. R. T., Caramori, P. H., Assad, E. D., Braga, H. J., Zullo Junior, J., Lazzarotto, C., Gonçalves, S., Wrege, M., Druneta, D., Dotto, S. R., Pinto, H. S., Brunini, O., Thomé, V. M. R., Zampieri, S. L., Pasinato, A., Pimentel, M. B. M., & Pandolfo, C. (2001b). Zoneamento agrícola e época de semeadura para trigo no Brasil.
Dalhaus, T., Barnett, B. J., & Finger, R. (2020). Behavioral weather insurance: Applying cumulative prospect theory to agricultural insurance design under narrow framing.
Dominoni, A. P. F., Caldana, N. F. S., Rodrigues, L., Negrão, B. W., Favoretto, V. R., Bodnar, V. R., & Silva, M. A. A. (2021). Agricultural zoning and recommendations for the seeding of wheat (Triticum species) in the Central-Southern Mesoregion of Paraná State in Brazil.
Food and Agriculture Organization of the United Nations – FAO. (2021).
Gonçalves, S. L., & Wrege, M. S. (2018). Considerações sobre metodologias para zoneamento agrícola em escala regionalizada.
Grimm, A. M. (2004). How do La Niña events disturb the summer monsoon system in Brazil?
Heinemann, A. B., Ramirez-Villegas, J., Stone, L. F., Silva, A. P. G. A., da Matta, D. H., & Diaz, M. E. P. (2021). The impact of El Niño Southern Oscillation on cropping season rainfall variability across Central Brazil.
Hoff, P. D. (2009).
Judge, G. G., Hill, R. C., Griffiths, W. E., Lütkepohl, H., & Lee, T. C. (1988).
Kravchenko, A. N., & Bullock, D. G. (2000). Correlation of corn and soybean grain yield with topography and soil properties.
Liu, Y., & Ker, A. P. (2020). Rating Crop Insurance Contracts with Nonparametric Bayesian Model Averaging.
Liu, Y., & Ramsey, A. F. (2023). Incorporating historical weather information in crop insurance rating.
Miranda, M. J., & Glauber, J. W. (1997). Systemic risk, reinsurance, and the failure of crop insurance markets.
National Oceanic and Atmospheric Administration – NOAA. (2023).
Nyiraneza, J., Cambouris, A. N., Ziadi, N., Tremblay, N., & Nolin, M. C. (2012). Spring wheat yield and quality related to soil texture and nitrogen fertilization.
Ozaki, V. A. (2009). Pricing farm-level agricultural insurance: a Bayesian approach.
Ozaki, V. A., & Silva, R. S. (2009). Bayesian ratemaking procedure of crop insurance contracts with skewed distribution.
Ozaki, V. A., Goodwin, B. K., & Shirota, R. (2011). Parametric and nonparametric statistical modelling of crop yield: implications for pricing crop insurance contracts.
Ozaki, V. A., Olinda, R., Faria, P. N., & Campos, R. C. (2014). Estimation of the agricultural probability of loss: evidence for soybean in Paraná state.
Ozaki, V. A., Olinda, R., Faria, P. N., & Campos, R.C. (2014). Estimating the probability of loss in agricultural insurance: An application of extreme value theory.
Pandolfo, C., Da Silva, B. E., & Werner, S. S. (2021). Publicações sobre o zoneamento agrícola em revistas científicas no Brasil de 1995 a 2018. Agrometeoros.
Park, E., Brorsen, B. W., & Harri, A. (2019). Using bayesian kriging for spatial smoothing in crop insurance rating.
Ray, D. K., Gerber, J. S., MacDonald, G. K., & West, P. C. (2015). Climate variation explains a third of global yield variability.
Rejesus, R. M., Coble, K. H., Miller, M. F., Boyles, R., Goodwin, B. K., & Knight, T. O. (2015). Accounting for weather probabilities in crop insurance rating.
Secretaria Estadual de Agricultura e Abastecimento – SEAB. (2022).
Sene, M., Vepraskas, M. J., Naderman, G. C., & Denton, H. P. (1985). Relationships of soil texture and structure to corn yield response to subsoiling.
Shi, W., & Irwin, S. H. (2005). Optimal hedging with a subjective view: An empirical Bayesian Approach.
Tack, J. B., & Ubilava, D. (2015). Climate and agricultural risk: Measuring the effect of Enso on US crop insurance.
Tsiboe, F., & Tack, J. (2021). Utilizing Topographic and Soil Features to Improve Rating for Farm-Level Insurance Products.
Uhlmann, L. O., Ramos, P. C. S., Cunha, G. R., Parfitt, J. M. B., Galvani, D. B., & Buriol, G. A. (2020). Climate risk zoning for gladiolus in the state of Rio Grande do Sul, Brazil.
Wilson, A., Avila-Diaz, A., Oliveira, L. F., Zuluaga, C. F., & Mark, B. (2022). Climate extremes and their impacts on agriculture across the Eastern corn belt region of the U.S.
Woodard, J. D., & Verteramo-Chiu, L. J. (2017). Efficiency impacts of utilizing soil data in the pricing of the federal crop insurance program.
Yamada, E. S. M., & Sentelhas, P. C. (2014). Agro-climatic zoning of Jatropha curcas as a subside for crop planning and implementation in Brazil.
Yi, F., Zhou, M., & Zhang, Y. Y. (2020). Value of incorporating Enso forecast in crop insurance programs.
Zhu, W., Porth, L., & Tan, K. S. (2019). A credibility-based yield forecasting model for crop reinsurance pricing and weather risk management.
Submetido em:
07/03/2024
Aceito em:
21/09/2024
Facebook
Google+
Twitter
LinkedIn
Mendeley
Email