Abstract: Scientific and reasonable rate determination could effectively promote the enthusiasm of both supply and demand sides in the forest fire insurance market, which is an important basis for the fine development of forest fire insurance products. In order to achieve the fine-grained determination of the forest fire insurance rate in China, based on the equilibrium theory and the related data of forest fire insurance from 1993 to 2018, 29 provinces (cities, districts) in China were selected as the research areas, starting from the expected utility of insured forest farmers and the risk of forest disasters, the principle of determining forest fire insurance rate that could meet the balance between supply and demand was discussed. Based on this, the Holecy model was improved to solve the problem that the distribution parameter model in the original model is limited to Weibull distribution and the variables don’t conform to the reality. The improved Holecy model was used to calculate and partition the forest fire insurance rate, and the results were compared with the actual average annual compensation ratio. The results showed that, firstly, there was a big difference in the expected pure rate of forest fire insurance among different regions based on the improved Holecy model, Tibet had the lowest expected pure rate of 0.0093‰, while Heilongjiang had the highest expected pure rate of 51.7641‰. Meanwhile, the risk pure rate of forest fire insurance varied greatly from region to region, under the condition of 100% participation rate, the risk pure rate of Heilongjiang was the highest, at 4.107‰, while that of Anhui was less than 0.001‰. And the risk pure rate of forest fire insurance was higher on the whole, which indicated that it’s necessary to reflect the annual risk and disaster loss difference among different regions through the pure risk premium rate. Moreover, the pure rate of forest fire insurance calculated by the sum of the expected pure rate and the risk pure rate of each region also had great differences. Under the 100% participation rate, the pure rate of forest fire insurance in Heilongjiang was the highest, 52.955‰, while that in Gansu was the lowest, 0.164‰. It could be seen that there were significant differences in forest fire risks in different regions of China, and it was urgent to refine and differentiate forest fire insurance rates and risk zoning. Secondly, the risk pure rate and the pure rate of forest fire insurance in different regions were subject to the insured rate, the rate level of forest fire insurance decreased with the increase of the insured rate, and the decline range varied with the different rate values. Therefore, encouraging farmers to participate in forest insurance to improve the insurance rate would be a crucial way to achieve risk dispersion and reduce the insurance premiums. Thirdly, according to >5‰, 1.0‰−5.0‰, 0.5‰−1.0‰ and <0.5‰, the pure rate of forest fire insurance was divided into high risk area, general risk area, lower risk area and low risk area. By comparing the actual occurrence and disaster situation of forest fires in different regions, the calculated pure rate of forest fire insurance and the zoning results were in line with the actual risk levels in different regions. Fourthly, the simple compensation ratio of national forest insurance was relatively low, with an average of about 30%, and the compensation ratio was highly differentiated in different regions, which further reflected the necessity of implementing fine rate determination and zoning of forest insurance, and also verified that forest insurance could be divided into risk zones. What’s more, the results of forest fire insurance pure rate partition were basically consistent with the forest insurance compensation ratio grouping results.

Key words: Forest fire insurance, Holecy model, Pure rate, Rate determination, Rate partition