摘要
本文根据偏向性技术进步理论,构建基于标准化供给面系统的资本、劳动、能源三要素固定替代弹性生产函数,测算1990-2017年我国八大区域偏向性技术进步水平,并实证分析各区域偏向性技术进步的收入分配效应。结果表明,我国各区域技术进步总体表现为资本偏向性,少数年份由于经济形势、产业结构调整、政策等因素影响,使技术进步的收入分配效应在部分区域偏向能源和劳动,劳动收入份额呈震荡下降趋势,即偏向性技术进步对劳动收入存在显著的抑制作用。其中,大西北地区、西南地区等欠发达地区偏向性技术进步对劳动收入的抑制作用明显高于发达的东南沿海地区,这在一定程度上说明随着我国经济发展水平的提高,偏向性技术进步有利于实现劳动收入份额的增加。为优化我国收入分配格局,应着力培养技术型人才,多措并举鼓励技术创新。
Based on the theory of biased technological change,this paper constructs the production function of fixed substitution elasticity of capital,labor and energy based on the standardized supply side system,calculates the index of biased technological change in eight regions of China from 1990 to 2017,and empirically analyzes the income distribution effect of biased technological change in each region. Results show that the regional technology change in China is generally capital-biased. In a few years,due to the economic situation,industrial structure adjustment,policy and other factors,the income distribution effect of technological change has been biased towards energy and labor in some regions,and the labor income share has shown a declining trend. That is,biased technological change has a significant inhibitory effect on labor income. Among them,the inhibitory effect of biased technological change on labor income in less developed areas such as northwest China and southwest China is obviously higher than that in developed coastal areas of southeast China,which to some extent indicates that biased technological change is conducive to the increase of labor income share with the improvement of China’s economic development level. Based on this,in order to optimize the income distribution pattern of our country,we should focus on training technical talents and take multiple measures to encourage technological innovation.
作者
廉晓梅
王科惠
Lian Xiao-mei;Wang Ke-hui(Northeast Asia Studies College,Jilin University,Changchun Jilin 130012)
出处
《经济纵横》
CSSCI
北大核心
2020年第4期96-103,共8页
Economic Review Journal
关键词
偏向性技术进步
四方程标准化系统
要素收入分配
Biased Technological Change
Four-equation Standardized System
Factor Income Distribution