Development of index insurance under the dynamics of multi-hazard risk in the context of climate change - Benso, Marcos Roberto (2023)
The increase in losses and damage caused by climatic extremes, such as droughts, excessive rainfall, and temperature variability associated with climate change, represents a major challenge for risk management. In this way, new methodologies aimed at insurance development, which consider the dynamics of multiple hazards, that is, how their frequencies and magnitudes vary over time, play an important role in increasing society\'s financial resilience in the face of climate change. Based on this challenge, this thesis aims to develop a dynamic multi-hazards indexed insurance model as an effective climate risk management tool. This work focuses on the development of insurance aimed at protecting food production, with generalizable results and methods for different sectors susceptible to losses and damages related to climate extremes. With this, the main challenges and trends, in addition to approaches traditionally used in insurance development, were explored in a systematic literature review, through which a conceptual model of indexed insurance is proposed based on the identification of hazards, the assessment of vulnerability, in financial methods, and risk pricing. Climatic impact-drivers are defined as climate means, events, and extremes that affect society and ecology. The threat these drivers pose to food production is increasing, and further research is needed to understand their relationship and how climate change influences them in Brazil to design better risk mitigation strategies. Despite the multi-hazard nature of climate threats to food production, research in index insurance has mostly focused on single index insurance. This paper presents a multi-hazard risk approach for index insurance design for food production and climate change adaptation. We used municipal-level crop yield data for soybean (1980-2022) in 452 municipalities and for maize (2003-2022) in 216 municipalities and climate data (1980-2022). We employ a multi-hazard insurance model to evaluate the effectiveness of risk transfer strategies to improve resilience and increase food production under current climate conditions and also to simulate the impacts of projected climate change (1980-2100) under moderate (SSP 5 8.5) and high emission (SSP 5 8.5) scenarios. The results showed that the inclusion of climate extreme indices improves the risk reduction potential of soybeans and maize, and these improvements were statistically significant (p ≤ 0.01) under current conditions for soybeans and maize. The projected climate changes in both scenarios suggest that the monthly mean temperatures could rise to 5 °C at the end of the century, while there is no evidence of any trend in the monthly precipitation averages. Droughts (SPEI less than -1.5) are projected to increase 2 to 5 times the probability; however, they are located in the northwest of Paraná and in the states of São Paulo, Mato Grosso do Sul, Minas Gerais and Goias. Climate change projections also indicate an increase in high-temperature indices and an increase in heavy rainfall, especially in South Brazil. The dynamics of risk represents a potential increased pressure for the insurance market; on average, projected climate extremes represent an increase in 26.5 % risk premiums for soybeans, and temperature means an increase of 24.6 % for maize. Our study highlights the importance of considering climate extremes to reduce the risk of financial losses for farmers and provides an overview of how the 5 risk dynamic caused by climate change is projected to affect risk premium prices and insurance design.