Revista de Economia e Sociologia Rural
https://app.periodikos.com.br/journal/resr/article/doi/10.1590/1806-9479.2025.284274
Revista de Economia e Sociologia Rural
ORIGINAL ARTICLE

Enhancing crop insurance analysis with agricultural zoning data

Melhoria da análise de seguro agrícola com dados de zoneamento agrícola

Gilson Martins; Guilherme Signorini

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Abstract

This article proposes a framework for integrating agricultural zoning data into insurance risk analysis. It is based on combining official public information from the Brazilian zoning program, ZARC, with open insurance data provided by the Brazilian Ministry of Agriculture and Livestock. The methodology presented in this article transforms ZARC information into distributional data and integrates it into a Bayesian model alongside insurance indemnities data, allowing for comprehensive risk analysis. It uses information on soil types from ZARC to develop basic best- and worst-case scenarios and calculate posterior distributions using insurance data. The resulting framework enables the comparison of municipalities, crop types, and overall risk classification. The study applies the framework to analyze the risk of soybeans, corn, wheat, and corn double-crop in Paraná State, resulting in consistent risk classifications across all crops and municipalities. The proposed framework has the potential to enhance agricultural risk management analysis for reinsurers, insurers, government agencies, and private companies. Future research could explore the use of this methodology to compare insurers, analyze risk in structured operations of credit and insurance, and evaluate risks at the farm level. This article presents a potential tool for improving risk analysis and decision-making in the agricultural sector.

Keywords

crop risk-management, Bayesian Analysis, agricultural risk classification, adverse selection, beta distribution

Resumo

Resumo: Este artigo propõe uma estrutura para integrar dados de zoneamento agrícola na análise de riscos de seguros. Baseia-se na combinação de informações públicas do programa brasileiro de zoneamento, o ZARC, com dados abertos de seguros fornecidos pelo Ministério da Agricultura e Pecuária. A metodologia apresentada transforma as informações do ZARC em dados de distribuição e as integra em um modelo Bayesiano juntamente com dados de indenizações de seguros, permitindo uma análise de risco abrangente. Utiliza informações sobre tipos de solo do ZARC para desenvolver cenários e calcular distribuições posteriores. A estrutura resultante possibilita a comparação entre municípios, tipos de culturas e classificação geral de risco. O estudo aplica a estrutura para analisar o risco de soja, milho, trigo e milho safrinha no Paraná, resultando em classificações de risco consistentes em todas as culturas e municípios. A estrutura proposta aprimora a análise de gestão de risco agrícola para resseguradoras, seguradoras, agências governamentais e empresas privadas. Pesquisas futuras poderiam explorar a metodologia para comparar seguradoras, analisar riscos em operações estruturadas de crédito e seguro, e avaliar riscos no nível das fazendas. O artigo apresenta uma ferramenta para melhorar a análise de risco e a tomada de decisões no setor agrícola.

Palavras-chave

gestão de riscos rurais, Análise Bayesiana, classificação de risco agrícola, seleção adversa, distribuição beta

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Submitted date:
03/07/2024

Accepted date:
09/21/2024

674a03d1a953955567590c02 resr Articles
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