Abstract：
Based on the theories of welfare economics, this paper analyzed the mechanism of agricultural insurance (AI) affecting agricultural economic growth (AEG), theoretically, and carried out an empirical analysis by using the random effects model and thirteen years of panel data, which included the annual data of 11 cities in Zhejiang Province, China, from 2007 to 2019. The gross output value of agriculture, forestry, animal husbandry, and fishery (GOVA) of 11 cities in Zhejiang Province is selected as the explained variable, agricultural insurance premium income (AIPI) as an explanatory variable. We selected area of waterlogging removal (AWR), rural electricity consumption (REC), total power of agricultural machinery (TPAM), and crop-sown area (CSA) as control variables. The study shows that: (1) the AIPI has a significant positive impact on the growth of GOVA. When other conditions remain unchanged, a 1% increase in AIPI increases the GOVA by 0.166%, accordingly; (2) The control variables of REC, TPAM, and CSA are statistically significant for the growth of the GOVA. The elasticity coefficient of REC is 0.325, the elastic coefficient of the TPAM is 0.287, and the elasticity coefficient of CSA is -0.281.
摘要：
基于福利经济学的理论,本文分析了农业保险(AI)对农业经济增长(AEG)的影响机制,理论上,并利用随机效应模型和十三年的面板数据进行了实证分析,其中包括浙江省11个城市的年度数据，中国,从2007年到2019年。农业总产值，林业,畜牧业,选取浙江省11个市的渔业(GOVA)作为被解释变量，农业保险保费收入(AIPI)作为解释变量。我们选择了除涝区(AWR)，农村用电量（REC），农业机械总功率(TPAM)，和作物播种面积(CSA)作为控制变量。研讨注解：(1)AIPI对GOVA的成长有显著的正向影响。当其他条件不变时，AIPI增加1%，GOVA增加0.166%，相应地；(2)REC的控制变量，TPAM,和CSA对GOVA的生长具有统计学意义。REC的弹性系数为0.325,TPAM的弹性系数为0.287,CSA的弹性系数为-0.281。
