我国农业保险财政补贴最优比例研究——基于三阶段DEA模型的分析

Research on the Optimal Proportion of Financial Subsidies for Agricultural Insurance in China——Analysis based on three-stage DEA model

2021年中央一号文件提出:支持有条件的省份降低产粮大县三大粮食作物农业保险保费县级补贴比例。基于2017-2019年数据,运用传统DEA模型进行实证研究发现:在现行农业保险财政补贴比例下,农业保险补贴效率强有效的省份数量在逐年减少,2019年全国各省中仅北京、天津、上海、宁夏的农业保险财政补贴强有效。进一步运用SFA模型探究农村人均可支配收入、粮食总产量以及受灾面积三个环境变量对农业保险补贴效率的影响,发现财政补贴效率与农村人均可支配收入、受灾面积成正向关系,而与粮食总产量成反向关系。最后,根据各环境变量影响结果,提出调整农业保险中央和省级财政投入额度,重新测算各省农业保险补贴最优比例,旨在为进一步完善我国农业保险财政补贴政策提供理论依据。

The 2021 Central No. 1 document proposes to support qualified provinces to reduce the county-level subsidy ratio of agricultural insurance premiums for the three major grain-producing counties. Based on the data from 2017 to 2019, this paper uses the traditional DEA model to conduct empirical research. It finds that under the current proportion of agricultural insurance financial subsidies, the number of provinces with strong and effective agricultural insurance subsidies is decreasing year by year. In 2019, only Beijing, Tianjin, Shanghai, and Ningxia had substantial and effective agricultural insurance financial subsidies in all provinces in the country. This paper further uses the SFA model to explore the impact of three environmental variables of rural per capita disposable income, total grain output, and disaster-affected areas on the efficiency of agricultural insurance subsidies. The results show that the efficiency of financial subsidy has a positive relationship with rural per capita disposable income and disaster-affected areas but has an inverse relationship with total grain output. Finally, according to the impact results of various environmental variables, it is proposed to adjust the agricultural insurance central and provincial financial input quotas and recalculate the optimal proportion of agricultural insurance subsidies in each province. The purpose is to provide a theoretical basis for further improving China’s agricultural insurance financial subsidy policy.