The efficiency of new soybean producers is of great importance to the agricultural development of China. Based on the survey data of some counties (cities) in Heilongjiang, Jilin, Liaoning, and Inner Mongolia Autonomous Region, the efficiency of new soybean producers in these regions is calculated by means of the data envelopment analysis (DEA) model. Then, the Tobit model is used to select relevant explanatory variables to study the factors affecting the production efficiency, and relevant conclusions and suggestions are put forward. The results show that (1) in 2017, the new soybean producers’ average technical efficiency of soybean production in the research samples was 0.618, of which the average pure technical efficiency was 0.680 and the average scale efficiency was 0.872; (2) factors such as the degree of education, the soybean planting area, the degree of mechanization, and the soybean sales channel have positive impacts on the efficiency of new soybean producers, while the ones such as the stability of the soybean price, the difficulty in obtaining soybean market information, and the implementation of the soybean subsidy policy have negative impacts.
A measurements of China’s mariculture carbon sink efficiency (MCSE) and its driving factors analysis are conducted in this paper. First, based on the Super-SBM model, the panel data from 9 Chinese coastal provinces (autonomous regions) during 2015–2019 are used to measure the MCSE in China. Second, the STRIPAT method and ridge regression method are used to explore the driving factors of China’s MCSE. Third, a blueprint for China to achieve carbon neutrality is constructed, and the advantages of mariculture carbon sink are summarized. The results show that the mariculture carbon sink has a high carbon store and carbon flux, and it has a dual value of ecology and economy. Meanwhile, mariculture carbon sink has the less negative impacts on eco-environment. Further, the MCSE, on the whole, of the 9 coastal regions in China presents an upward trend in 2015–2019, and this trend is more significant in the Pan-Pearl River Delta (PPRD) and Circum-Bohai Sea (CBS) Economic Zone. In 2019, 66.67% of the regions in the sample is the SBM-efficient DMUs on technical efficiency (TE), and 88.89% of the regions in the sample is the BSM-efficient DMUs on pure technical efficiency (PTE). Finally, driving factors analysis shows that the affluence and service industry of a region may have a positive impact on the MCSE, while the population, urbanization and international trade may have a negative impact on the MCSE to a certain extent.
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