Abstract:

Developing actuarially fair premium rates is essential for the sustainable and efficient advancement of area yield insurance. Incorporating climate forecast information is one of the important means to enhance the accuracy of premium calculation in area yield insurance pricing. This study introduced the Standardized Precipitation Evapotranspiration Index (SPEI) into the pure premium rate making method of the U.S. Department of Agriculture's Risk Management Agency (RMA) to construct an SPEI−RMA model. The model was applied to calculate pure premium rates for corn area yield insurance in Heilongjiang, Jilin, and Liaoning provinces of Northeast China. An out-of-sample game framework was employed to compare the performance of the SPEI−RMA method with the traditional RMA method in insurance pricing, aiming to provide a scientific basis for designing more precise area yield insurance products. Results indicated that when fitting the trend of crop yield, compared to the RMA method, the SPEI−RMA method increased the coefficient of determination (R²) by 0.044, 0.088, and 0.153 and reduced the mean squared error (MSE) by 0.068, 0.067, and 0.213 for Heilongjiang, Jilin, and Liaoning, respectively, thereby enhancing model estimation accuracy. The median absolute differences in pure premiums between the two methods are 0.105, 0.114, and 0.087 for the three provinces. Out-of-sample game result revealed that at coverage levels of 70%, 80%, and 90%, the SPEI−RMA method more accurately determines pure premium rates, yielding significant economic and statistical benefits. 

Key words: Agricultural insurance, Area yield insurance, Rate making, RMA, SPEI-RMA