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中国连片特困地区非农就业增长的时空特征与驱动因素
引用本文:殷江滨,李尚谦,姜磊,程哲,黄晓燕,路改改.中国连片特困地区非农就业增长的时空特征与驱动因素[J].地理学报,2021,76(6):1471-1488.
作者姓名:殷江滨  李尚谦  姜磊  程哲  黄晓燕  路改改
作者单位:1. 陕西师范大学西北国土资源研究中心,西安 7101192. 陕西师范大学全球区域与城市研究院,西安7101193. 浙江财经大学经济学院,杭州 3100184. 西安建筑科技大学公共管理学院,西安 710055
基金项目:国家自然科学基金项目(42071213);国家自然科学基金项目(41871168);国家自然科学基金项目(41831284);陕西省自然科学基础研究计划(2018JM4022);陕西省自然科学基础研究计划(2018JM4006);陕西省社科界重大理论与现实问题研究项目(2020Z088);中央高校基本科研业务费专项资金(2019CSLY031)
摘    要:中国的贫困治理已从消除绝对贫困转向解决相对贫困的新阶段。增加贫困地区的非农就业机会,保障贫困人口充分有效就业是解决相对贫困问题,促进贫困地区转型发展的根本举措。基于2013—2017年全国14个连片特困地区县域数据,采用空间计量模型方法,解析精准扶贫战略实施以来贫困地区非农就业的空间增长趋势及其驱动因素,并区分了不同人口规模条件下非农就业增长机制的差异性。结果表明:① 中国连片特困地区非农就业在空间上表现出较强的非均衡性;② 连片特困地区非农就业的增长趋势快于全国平均水平,存在明显的空间分异,并呈现出收敛趋势;③ 连片特困地区县域间非农就业增长存在较强的空间依赖性,地方性因素和地理结构因素共同影响了连片特困地区的非农就业增长。初始就业水平对非农就业增长具有抑制作用,而地区经济总量、金融资本可获得性、产业结构、基础教育水平、邻近省会或特大城市的市场区位条件、平坦湿润的地理环境等因素显著促进了就业增长;④ 不同规模县域非农就业增长的决定因素存在显著差异。研究可以为促进贫困地区非农就业增长,推动新时期贫困治理与地区转型发展提供科学参考。

关 键 词:贫困地区  非农就业  空间增长  空间计量模型  中国  
收稿时间:2020-06-17
修稿时间:2020-12-22

The spatio-temporal variations and driving factors of non-farm employment growth in contiguous destitute areas of China
YIN Jiangbin,LI Shangqian,JIANG Lei,CHENG Zhe,HUANG Xiaoyan,LU Gaigai.The spatio-temporal variations and driving factors of non-farm employment growth in contiguous destitute areas of China[J].Acta Geographica Sinica,2021,76(6):1471-1488.
Authors:YIN Jiangbin  LI Shangqian  JIANG Lei  CHENG Zhe  HUANG Xiaoyan  LU Gaigai
Institution:1. Northwest Land and Resource Research Center, Shaanxi Normal University, Xi'an 710119, China2. Global Regional and Urban Research Institute, Shaanxi Normal University, Xi'an 710119, China3. School of Economics, Zhejiang University of Finance and Economics, Hangzhou 310018, China4. School of Public Management, Xi'an University of Architecture and Technology, Xi'an 710055, China
Abstract:The focus of China's battle against poverty will shift from relative poverty to absolute poverty. The fundamental measure in the new stage of poverty governance is to promote transformation of destitute areas by increasing their non-farm employment opportunities and ensuring fully effective employment for the poor. Based on county data from 2013 to 2017 covering 14 contiguous destitute areas of China, the spatial econometric model method was adopted to analyze the spatial growth trend of non-farm employment in these areas and its driving factors since the implementation of the poverty alleviation strategy, and the differences in the drivers of non-farm employment under different population sizes were distinguished. The results were obtained as follows: (1) Non-farm employment exhibits a strong spatial non-equilibrium. (2) The growth of non-farm employment is faster than the national average, with apparent characteristics of spatial heterogeneity and clear tendencies of convergence. (3) There is substantial spatial dependence on the growth of non-farm employment among counties in the study areas. Place-based factors and geo-structural factors have jointly affected the growth of non-farm employment in these areas. The level of initial employment has a restraining effect on non-farm employment growth. However, the regional economic scales, the availability of financial capital, the industrial structure, the level of basic education, the proximity of market to provincial capitals or megacities, and the flat or humid geographical environments have significantly contributed to the growth of non-farm employment in destitute areas. (4) The determinants of non-farm employment growth in counties at different scales have significant differences. This research provides support to further research on the growth of non-farm employment in poor areas as well as poverty governance and regional transformation and development in the new period.
Keywords:destitute areas  non-farm employment  spatial growth  spatial econometric model  China  
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