摘要
作为发展中大国,中国不同地区间农业科技进步水平和农业碳排放量的差异非常明显;要全面研究农业科技进步对农业碳排放的影响,需要选择恰当的研究视角;基于多方面原因的限制,从省级行政单位视角来研究农业科技进步对农业碳排放影响的成果极为少见。为此,在剖析农业科技进步影响农业碳排放的理论基础上,本文设定动态面板数据模型,运用我国30个省级单位2000-2010年的数据,实证农业科技进步对农业碳排放的影响。结果发现,在控制其他变量的前提下,农业科技进步与农业碳排放之间存在负相关关系,农业科技水平越高,农业碳排放越少;农业科技进步水平越低,农业碳排放越多。文章最后就减少农业碳排放提出了相应的对策建议。
As a big developing country, the differences of progress level of agricultural science and technology and carbon emissions among different areas are very obvious in China. To comprehensively study the impact of progress of agricultural science and technology to agricultural carbon emissions, we need to select appropriate research perspective. Based on many reasons limited, research findings about the impact of progress of agricultural science and technology to agricultural carbon emissions from the perspective of provincial administrative are extremely rare. To this end, this paper analyzed theories about the impact of progress of agricultural science and technology to agricultural carbon emissions and constructed a dynamic panel data model. Based on these, the paper made an empirical study about the impact of progress of agricultural science and technology to agricultural carbon emissions using the data of the 30 provincial units from 2000 to 2010. The results show that under the premise of controlling for other variables, there was a negative correlation between progress of agricultural science and technology and agricultural carbon emission. The higher progress level of agricultural science and technology, the less agricultural emission, and the lower progress level of agricultural science and technology, the more agricultural emissions. Finally, the paper put forward the corresponding countermeasures and suggestions aiming at reducing agricultural e- missions.
出处
《科学学研究》
CSSCI
北大核心
2013年第5期674-683,共10页
Studies in Science of Science
基金
国家社科基金重大项目(11&ZD141)
国家社科基金项目(10XJY0024)
教育部人文社科项目(12XJC790009)
关键词
农业科技进步
农业碳排放
区域差异
动态面板数据模型
agricultural science and technology progress
agricultural carbon emission
regional differences
dynamic panel data model