Uma Aplicação do Lasso Quantílico Geograficamente Ponderado ao Seguro de Índice Climático



Artigo principal Conteúdo

Daniel Lima Miquelluti
Vitor Augusto Ozaki
David José Miquelluti

Resumo

Objetivo: este artigo estuda a eficiência de uma nova abordagem de regressão, o Lasso quantílico geograficamente ponderado (GWQlasso), na modelagem da relação índice-rendimento para produtos de seguro de índice climático. O GWQlasso permite que os coeficientes de regressão variem espacialmente, enquanto usa as informações de locais vizinhos para gerar estimativas robustas. O componente Lasso do modelo facilita a seleção de variáveis explicativas relevantes. Metodologia: um produto de seguro de índice climático (WII) é desenvolvido com base no standardized precipitation index (SPI) de um mês derivado de um conjunto de dados de precipitação diária para 41 estações meteorológicas no estado do Paraná (Brasil) para o período de 1979 a 2015. Os dados de produção de soja também são usados para os 41 municípios de 1980 a 2015. A eficácia do seguro modelado utilizando-se GWQlasso é avaliada em comparação com uma abordagem de regressão quantílica clássica e um produto de seguro de produtividade tradicional usando a medida de risco espectral (SRM) e o semidesvio médio. Resultado: embora o GWQlasso tenha se mostrado tão eficaz quanto a regressão quantílica, ele superou o produto de seguro de produtividade. Conclusão: o GWQlasso mostra-se como alternativa para o mercado de seguro agrícola no Brasil e em outros locais com limitação de dados.



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Miquelluti, D. L., Ozaki, V. A., & Miquelluti, D. J. (2021). Uma Aplicação do Lasso Quantílico Geograficamente Ponderado ao Seguro de Índice Climático. Revista De Administração Contemporânea, e200387. https://doi.org/10.1590/1982-7849rac2022200387.en
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