摘要
基于我国1996—2005年的科技投入和产业发展的经济统计数据,分析了我国科技投入情况,构建灰关联度模型,对我国科技投入与产业经济增长的关联性进行实证分析,用图形模拟方法予以佐证。采取关联度模型对我国几个有代表性的省市进行比较分析,得出结论:科技经费投入、科技活动人员投入对产业经济增长有显著作用;科技经费投入,尤其是 R&D 经费对高端制造业、服务业的投入效率更高,在我国这些产业集中的发达地区加大科技经费的投入更有效率,而科技活动人员的投入对以农业为主的第一产业的效率更高。提出我国不仅要加大科技投入,同时要以集约型方式来引导科技投入科学流向,提高科技投入效率。
Based on statistical data of S＆T input and industry development in China since 1996 to 2005, this paper ana- lyzed the conditions of S＆T input, constructs gray correlation degree model to do an empirical study about the correlation of S＆T input and industry economic growth, and gives a test by graphics simulation. Next the paper uses gray correlation degree model to analyze several representative regions and get some conclusions： S＆T outlay input and national S＆T active population make prominent effect to industry economy development; S＆T outlay, especially R＆D outlay makes more efficiency for high - level manufacturing and service, and playsmore prominent roles in the developed regions, so it should be strengthened more; and national S＆T active population makes more efficiency for the primary industry domina- ted with agriculture. At last the paper puts forward that the government should push the finance and tax policy to guide the flow direction of S＆T input for improve its efficiency by intensivism.
出处
《中国软科学》
CSSCI
北大核心
2007年第11期57-63,共7页
China Soft Science
关键词
科技投入
产业增长
灰关联度
对策
S＆T input
industry economic growth
gray relational degree
countermeasures
