摘要
本文基于Battese and Coelli(1995)提出的随机前沿生产函数模型,构建了农业FDI影响下的面板数据随机前沿函数模型,根据1994-2010年的省际面板数据,实证分析了农业FDI对中国农业全要素生产率的影响。研究表明,农业FDI对中国农业技术效率和农业技术进步均具有显著的正向影响,从而在总体上促进了中国农业全要素生产率的增长;农业资源利用、农业劳动力投入质量、农业资本投入和政府对农业的支持对中国农业技术效率均具有显著的正向影响,农业劳动力投入数量和自然灾害则对中国农业技术效率均具有显著的负向影响;中国农业在总体上出现了技术进步与技术效率下降并存的局面。最后,根据研究结论提出了相应的政策启示。
Based on the research of Battese and Coelli (1995), this study constructs a stochastic frontier function model for panel data under the impact of agricultural FDI, and then draws on China's provincial panel data from 1994 to 2010 to empirically analyze the impact of agricultural FDI on the total factor productivity (TFP) of China's agriculture. The results indicate that agricultural FDI can significantly promote the TFP of China's agriculture by improving China's agricultural technical efficiency. Such factors as utilization of agricultural resources, quality of agricultural labor input, agricultural capital input and government support for agriculture all have a significant positive effect on China's agricultural technical efficiency, and quantity of agricultural labor input and natural disasters have significant negative effect on it. Technical progress and technical efficiency decline coexist under the impact of agricultural FDI. To conclude, this paper suggests corresponding policies based on the research results.
基金
农业部农业国际交流与合作项目"负责任农业投资准则谈判与全球粮食安全形势跟踪"(农科[2013]922)
关键词
农业FDI
全要素生产率
面板数据
随机前沿函数模型
Agricultural FDI
Total factor productivity (TFP)
Panel data
Stochastic frontier function model