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供给侧中国非农就业变动及驱动因素分析
引用本文:田开兰,孔亦舒,高翔,杨翠红.供给侧中国非农就业变动及驱动因素分析[J].系统工程理论与实践,2018,38(5):1132-1140.
作者姓名:田开兰  孔亦舒  高翔  杨翠红
作者单位:1. 中国科学院 数学与系统科学研究院, 北京 100190;2. 中国科学院大学, 北京 100049;3. 中国科学院 管理、决策与信息系统重点实验室, 北京 100190;4. 中国科学院 国家数学与交叉科学中心, 北京 100190
基金项目:国家自然科学基金(71673269);中国科协高端科技创新智库青年项目(DXB-ZKQN-2017-046)
摘    要:在我国产能过剩和结构性供给短缺并存的背景下,我国正积极推进供给侧结构改革,以稳定就业和推动经济长期增长.利用反映加工贸易生产的非竞争型投入产出Ghosh模型,本文从供给侧对2002-2007年和2007-2012年两阶段的非农就业变化进行了结构分解分析,以探讨非农就业变动的驱动因素.整体而言,经济增速的放缓将对非农就业增长造成不小的压力,技术进步使得劳动生产率得以提高,加大了各部门的失业风险.结果还显示,不同生产方式对应的就业变化驱动因素贡献有所不同,对于加工贸易生产比重高的技术密集型部门,进口投入是就业变化的重要影响因素.与此同时,分配结构的调整和部门结构的变化都对就业变化产生重要影响.

关 键 词:供给侧改革  就业  DPN模型  Ghosh模型  结构分解分析  
收稿时间:2016-11-25

Structural decomposition analyses of non-agricultural employment changes from the supply side
TIAN Kailan,KONG Yishu,GAO Xiang,YANG Cuihong.Structural decomposition analyses of non-agricultural employment changes from the supply side[J].Systems Engineering —Theory & Practice,2018,38(5):1132-1140.
Authors:TIAN Kailan  KONG Yishu  GAO Xiang  YANG Cuihong
Institution:1. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China;2. University of Chinese Academy of Sciences, Beijing 100049, China;3. Key Laboratory of Management, Decision and Information Systems, Chinese Academy of Sciences, Beijing 100190, China;4. National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences, Beijing 100190, China
Abstract:Since China has been promoting supply-side structural reform determinedly, it is particularly important for us to explore the relationship between employment changes and supply-side reform. This paper, from the supply side, decomposes the determinants of employment into technological development factor, economic structure factor, imported inputs changes and economic growth factor, using structural decomposition techniques and non-competitive input-occupancy-output tables which capture processing trade. The results suggest that the decline in economic growth will depress employment growth and imported inputs had positive effects on employment growth. The technological development improved labor productivity, but also increased the risk of unemployment. Meanwhile, technological development has accelerated the adjustment of economic structure. In 2002-2007, the adjustment of economic structure had positive impacts on the employment of secondary industries, while these positive impacts transferred to the tertiary industries in 2007-2012. It implies that the demand for employment in China has gradually transferred to service industries with economic transition.
Keywords:supply side  employment changes  DPN model  Ghosh model  structural decomposition techniques  
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