\"When theres no November rain\": developing a parametric insurance for hydroelectric energy generators in Brazil

• Ano de defesa: 2023
• Autor(a) principal: Fonseca, Nathalia Costa
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Copulas; Econometria espacial; Energy generators; Geradores de energia; Hydrological risk; Parametric insurance; Risco hidrológico; Seguro paramétrico; Spatial econometrics
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/12/12136/tde-13032024-184740/

The nonlife insurance industry plays a crucial role in safeguarding societal members against a myriad of perils. However, there are some insurance protection gaps (IPGs), especially for fundamental risks. Parametric insurance offers a solution for IPGs while improving the insurance markets efficiency. One possible application is towards climate change issues. The increasing frequency and intensity of droughts in Brazil, exacerbated by climate change, have caused economical and energetic crises. This study addresses this pressing issue by introducing a parametric insurance product tailored to Brazilian hydroelectric companies, aiming to improve the resilience of energy generation during drought crises and mitigating hydrological systemic risks. The primary objective of this study was to design and evaluate the feasibility of this innovative insurance product. The initial proposal was to link the insurance solely on precipitation indexes, however, the results point out to a combined index of precipitation and rivers water flow or reservoirs volume, depending on hydroelectric powerplants characteristics. Regarding to methodological procedures, this research lies in its pioneering use of spatial econometrics and copulas to model energy generation of Brazilian hydroelectric powerplants, an approach not commonly explored in the existing literature. Our main findings emphasize the utility of spatial econometrics, particularly the fixed-effects SARAR model, in effectively modeling energy generation for both hydroelectric powerplants types. This model takes into account the influence of neighboring powerplants, which is vital in the context of Brazils interconnected electrical system. Moreover, the study sheds light on the potential of parametric insurance in mitigating hydrological risks during drought crises, but it underscores the need for differentiated insurance designs for run-of-river and water store powerplants, due to their diverse characteristics. A crucial and pioneering aspect of this study was to use vine copulas models as a robustness check mechanism, to ensure the non- endogeneity of the spatial model. The primary design does not show immediate viability for insurance companies, due to a high loss ratio, but improvements can be made, especially by introducing a dynamic component in the models, as they were all estimated in a static way. Ultimately, by introducing innovative methodologies and providing valuable insights into energy generation modeling, this study offers a promising avenue to enhance the sustainability and resilience of Brazils energy supply given the growing threat of climate change-induced droughts.