Designing and evaluating a composite climatic index to risk management in livestock insurance

The livestock sector in Iran, which has a significant nomadic population, is highly vulnerable to climate change and drought. This high vulnerability increases the need for modern support tools such as insurance, as traditional insurance has proven inefficient due to its complex processes and high costs. In response to this challenge, Index-Based Livestock Insurance (IBLI) has emerged as an effective solution. However, the most significant challenge of IBLI is “basis risk”, which refers to the imperfect correlation between the index and actual losses. This study examines the design and evaluation of a composite climatic index to reduce basis risk in livestock insurance for nomads in Kerman Province. To achieve the goal of basis risk reduction, this study used Principal Component Analysis (PCA) to develop a composite climatic index that includes the Normalized Difference Vegetation Index (NDVI), Standardized Precipitation Index (SPI), daily maximum temperature (DMT), and monthly sunshine hours (MSH). The PCA results showed that the Standardized Precipitation Index (SPI) should be considered separately in the model due to its weak correlation with the other variables, while the other indices (NDVI, DMT, and MSH) were well combined into a single component. These analyses confirm that using a composite index (CI) alongside an independent index (SPI) in a dual model significantly reduces basis risk. The composite index acts as a comprehensive measure for rangeland conditions and an early warning system, while the SPI captures the direct and independent effects of rainfall, especially in critical conditions. To investigate the relationship between the composite index and livestock mortality rates, a threshold regression model was used, which confirmed the existence of a critical point with a value of 1.65. This critical point has been considered the basis for activating indemnity payments. The model results showed that vaccination plays a crucial role in reducing losses during critical conditions. Furthermore, a financial comparison revealed that the index-based model is superior to traditional insurance by offering dynamic and flexible premiums and indemnities. Finally, the research suggests that policymakers pilot the proposed model and, in parallel, monitor potential long-term environmental consequences, such as rangeland degradation. • This study examines the design and evaluation of a composite climatic index to reduce basis risk in livestock insurance. • Principal Component Analysis (PCA) has used to develop a composite climatic index. • Index-based model is superior to traditional insurance by offering dynamic and flexible premiums and indemnities.