Crop Insurance Premium Ratemaking Based on Survey Data: A Case Study from Dingxing County, China

Abstract

Premium ratemaking is an important issue to guarantee insurance balance of payments. Most ratemaking methods require large samples of long-term loss data or farm-level yield data, which are often unavailable in developing countries. This study develops a crop insurance ratemaking method with survey data. The method involves a questionnaire survey on characteristic yield information (average yield, high yield, and low yield) of farming households' cropland. After compensating for random error, the probability distributions of farm-level yields are simulated with characteristic yields based on the linear additive model. The premium rate is calculated based on Monte Carlo yield simulation results. This method was applied to Dingxing County, North China to arrive at the insurance loss cost ratio and calculate the necessary premium rate. The method proposed in this study could serve as a feasible technique for crop insurance ratemaking in regions that lack sufficient long-term yield data, especially in developing countries with smallholder agriculture.

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