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.
Does clean energy development (CED) have a spatial spillover effect on economic growth (EG)? Using the panel data of 30 provincial administrative units from 2000 to 2019 in China, this study empirically investigates the spatial spillover effect of CED on EG. From the perspective of the supply side rather than the consumption side, using the spatial Durbin model (SDM), the study finds that CED does not have a significant impact on EG, while there is an apparent positive spillover effect of CED on EG in China, meaning that CED in one province can boost EG in the surrounding provinces. Theoretically, this paper provides a new perspective for studying the relationship between CED and EG. In practice, it provides a reference for further improving the government’s future energy policy.
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