基于增长核算模型的广西林业科技进步贡献率测算
Calculation of Contribution Rate of Forestry Science and Technology Progress in Guangxi Based on Growth Accounting Model
韦立权 1沈伟航 2韩锋 3宁攸凉 2刘亚 1胡冬冬1
作者信息
- 1. 广西壮族自治区林业勘测设计院,广西南宁 530011
- 2. 中国林业科学研究院林业科技信息研究所,北京 100091
- 3. 中国林业科学研究院,北京 100091
- 折叠
摘要
为科学测算广西林业科技进步贡献率,在分析和借鉴既有研究成果的基础上,提出基于经验法的增长核算模型和基于要素份额法的增长核算模型,并对2006-2020年广西林业科技进步贡献率进行测算与分析.结果表明,广西林业经济增速明显回落,已由超高速增长转向较高速增长;基于要素份额法的增长核算模型更适用于广西林业科技进步贡献率测算;"十一五""十二五"和"十三五"期间,广西林业科技进步贡献率分别为34.19%、46.94%和55.97%,总体呈增长态势;"十三五"期间,广西林业经济增长超过一半的贡献来自林业科技进步,广西林业经济发展模式已由要素驱动转变为创新驱动.
Abstract
To scientifically calculate contribution rate of forestry science and technology progress in Guangxi,growth accounting models based on empirical method and factor share method were proposed which were based on analysis and reference of existing research results,and contribution rates of forestry science and technology progress in Guangxi from 2006 to 2020 were calculated and analyzed.Results showed that growth rate of forest-ry economy in Guangxi significantly declined,shifting from ultra high growth to relatively high growth.Growth accounting model based on factor share method was suitable for calculating contribution rate of forestry science and technology progress in Guangxi.Contribution rates of forestry science and technology progress in Guangxi showed growth trends,which were 34.19%,46.94%and 55.97%during the 11th Five-Year Plan period,12th Five-Year Plan period and 13th Five-Year Plan period respectively.During the 13th Five-Year Plan period,over half of contribution for forestry economic growth in Guangxi came from forestry science and technology progress,which meant development model of forestry economy in Guangxi had shifted from factor-driven to in-novation-driven.
关键词
科技评价/科技进步贡献率/增长核算模型/林业/广西Key words
evaluation of science and technology/contribution rate of science and technology progress/growth accounting model/forestry/Guangxi引用本文复制引用
基金项目
广西林业"十四五"科学研究项目(桂林科研[2022ZC]第55号)
广西林业科技推广示范项目(桂林科研[2022]第8号)
国家林业和草原局软科学项目(2022131002)
出版年
2024
国家科技期刊平台
NSTL
万方数据