乡村非农就业水平的时空格局及动态演进——以青海省为例

doi:10.12118/j.issn.1000-6060.2023.123

Abstract

Abstract:

This study aims to comprehensively understand the spatiotemporal patterns and dynamic evolution of rural nonfarm employment in Qinghai Province of China at the county level, contributing to the realization of “common prosperity”. Leveraging panel data spanning 2010 to 2020 from 43 county-level units in Qinghai Province, China, we employ global trend analysis, standard deviation ellipse, and Moran’s I index to unveil the spatiotemporal evolution characteristics of rural nonfarm employment from both static and dynamic perspectives. In addition, we use kernel density estimation and Markov chain to explore the dynamic evolution characteristics. Our findings indicate the following key insights: (1) The overall level of rural nonfarm employment exhibits a fluctuating upward trend, marked by distinct stages of rapid and slow growth driven by robust economic development and effective employment policies. (2) Spatially, the distribution pattern is characterized by a “high in the eastern and western, low in the middle” trend, with a noticeable shift from “due east-due west” to “northeast-southwest”. (3) Spatial correlation analysis reveals that neighboring counties, sharing similar resource endowments, nonfarm industry development concepts, and interactive effects in employment policy formulation, exhibit significant positive spatial autocorrelation. Notably, “high-high” and “low-low” agglomerations are prominent. (4) Dynamic evolution, as evidenced by kernel density estimation, indicates a narrowing of regional differences in rural nonfarm employment across Qinghai Province. Despite stable “club convergence” phenomena due to terrain conditions, resource distribution, and economic development disparities among the 43 counties, spatial factors play a crucial role that cannot be overlooked in enhancing rural nonfarm employment. The development process also reflects a noteworthy “spatial spillover” phenomenon in Qinghai Province.

Key words: rural non-farm employment, common prosperity, spatiotemporal pattern, dynamic evolution, Qinghai Province

GAO Fuxin, ZHAO Ling, WEI Qiong. Spatiotemporal pattern and dynamic evolution of rural non-farm employment: A case of Qinghai Province[J].Arid Land Geography, 2023, 46(12): 2111-2119.

Figures/Tables 8

Fig. 1

Fig. 2

Tab. 1

Tab. 2

Tab. 3

Fig. 3

Tab. 4

Tab. 5

References 24

[1]	贺雪峰. 关于实施乡村振兴战略的几个问题[J]. 南京农业大学学报(社会科学版), 2018, 18(3): 19-26, 152.
	[He Xuefeng. Some issues in rural thriving strategy implementation[J]. Journal of Nanjing Agricultural University (Social Sciences Edition), 2018, 18(3): 19-26, 152.]
[2]	陈琛, 石颜露, 邱珊珊, 等. 首轮退耕补贴到期对农户非农就业的影响[J]. 干旱区资源与环境, 2022, 36(12): 15-21.
	[Chen Chen, Shi Yanlu, Qiu Shanshan, et al. Impact of the expiration of subsidies for the first round of the SLCP on farm households’ off-farm employment[J]. Journal of Arid Land Resources and Environment, 2022, 36(12): 15-21.]
[3]	罗美娟, 申小亮. 人情支出对农村劳动力非农就业的影响研究——基于CFPS微观数据的实证分析[J]. 西北人口, 2021, 42(6): 47-60.
	[Luo Meijuan, Shen Xiaoliang. A study on the impact of gift expenditure on non-farm employment of rural labor: Empirical analysis based on CFPS microdata[J]. Northwest Population Journal, 2021, 42(6): 47-60.]
[4]	张青, 况志华, 王焰辉. 数字普惠金融对农村青年非农就业的影响研究[J]. 金融与经济, 2021(11): 34-45.
	[Zhang Qing, Kuang Zhihua, Wang Yanhui. A study on the impact of digital inclusive finance on off-farm employment of rural youth[J]. Finance and Economy, 2021(11): 34-45.]
[5]	蔡洁, 刘斐, 夏显力. 农村产业融合、非农就业与农户增收——基于六盘山的微观实证[J]. 干旱区资源与环境, 2020, 34(2): 73-79.
	[Cai Jie, Liu Fei, Xia Xianli. Rural industry convergence, non-agricultural employment and rural households’ income: Microscopic evidence based on Liupanshan area[J]. Journal of Arid Land Resources and Environment, 2020, 34(2): 73-79.]
[6]	骆永民, 骆熙, 汪卢俊. 农村基础设施、工农业劳动生产率差距与非农就业[J]. 管理世界, 2020, 36(12): 91-121.
	[Luo Yongmin, Luo Xi, Wang Lujun. Rural infrastructure, industrial and agricultural labor productivity gap and non-agricultural employment[J]. Journal of Management World, 2020, 36(12): 91-121.]
[7]	程名望, 潘烜. 个人特征、家庭特征对农村非农就业影响的实证[J]. 中国人口·资源与环境, 2012, 22(2): 94-99.
	[Cheng Mingwang, Pan Xuan. Empirical analysis on the effects of individual features and family traits to non-farm employment[J]. China Population, Resources and Environment, 2012, 22(2): 94-99.]
[8]	魏滨辉, 苏柯雨, 柳松. 中国农村非农就业对农户融资的影响与机制——基于CFPS面板数据的研究[J]. 农村经济, 2020(5): 105-112.
	[Wei Binhui, Su Keyu, Liu Song. The impact and mechanism of rural non-agricultural employment on rural households’ financing in China: A study based on CFPS panel data[J]. Rural Economy, 2020(5): 105-112.]
[9]	严飞, 侯远潮. 中国农村劳动力非农就业对经济增长的贡献[J]. 统计与决策, 2006(17): 91-92.
	[Yan Fei, Hou Yuanchao. The contribution of non-agricultural employment of rural labor to economic growth in China[J]. Statistics & Decision, 2006(17): 91-92.]
[10]	柳建平, 刘咪咪, 王璇旖. 农村劳动力非农就业的微观效应分析——基于甘肃14个贫困村的调查资料[J]. 干旱区资源与环境, 2018, 32(6): 50-56.
	[Liu Jianping, Liu Mimi, Wang Xuanyi. Analysis on the micro-effect of rural labor’s non-agricultural employment for poverty villages, Gansu Province[J]. Journal of Arid Land Resources and Environment, 2018, 32(6): 50-56.]
[11]	马卫, 吉婷婷, 伯娜, 等. 江苏省乡村非农就业水平时空格局及其驱动因素[J]. 江苏师范大学学报(自然科学版), 2023, 41(1): 66-72.
	[Ma Wei, Ji Tingting, Bo Na, et al. Spatio-temporal pattern of rural non-farm employment level in Jiangsu Province and its driving factors[J]. Journal of Jiangsu Normal University (Natural Science Edition), 2023, 41(1): 66-72.]
[12]	杨洋, 乔家君, 王伟, 等. 扶贫资源配置对低收入农户收入影响——以青海省18村为例[J]. 干旱区地理, 2023, 46(2): 325-336.
	[Yang Yang, Qiao Jiajun, Wang Wei, et al. Impact of poverty alleviation resource allocation on income of rural low-income farmer households: A case of 18 villages in Qinghai Province[J]. Arid Land Geography, 2023, 46(2): 325-336.]
[13]	方方, 何仁伟, 李立娜. 京津冀地区乡村振兴地域模式研究——基于乡村非农就业与农民增收的空间效应[J]. 地理研究, 2019, 38(3): 699-712. doi: 10.11821/dlyj020181151
	[Fang Fang, He Renwei, Li Lina. Research of the regional mode of rural revitalization in Beijing-Tianjin-Hebei Region: Based on the spatial effect between rural off-farm employment and farmers’ income growth[J]. Geographical Research, 2019, 38(3): 699-712.] doi: 10.11821/dlyj020181151
[14]	周春山, 罗利佳, 史晨怡, 等. 粤港澳大湾区经济发展时空演变特征及其影响因素[J]. 热带地理, 2017, 37(6): 802-813. doi: 10.13284/j.cnki.rddl.003011
	[Zhou Chunshan, Luo Lijia, Shi Chenyi, et al. Spatio-temporal evolutionary characteristics of the economic development in the Guangdong-Hong Kong-Macao Greater Bay Area and its influencing factors[J]. Tropical Geography, 2017, 37(6): 802-813.] doi: 10.13284/j.cnki.rddl.003011
[15]	麻学锋, 杨雪. 大湘西高级别景区时空分布特征及影响因素的空间异质性[J]. 自然资源学报, 2019, 34(9): 1902-1916. doi: 10.31497/zrzyxb.20190908
	[Ma Xuefeng, Yang Xue. Spatio-temporal distribution of high-level tourist attractions and spatial heterogeneity of its influencing factors in western Hunan[J]. Journal of Natural Resources, 2019, 34(9): 1902-1916.] doi: 10.31497/zrzyxb.20190908
[16]	殷颂葵. 西北地区城乡收入差距的时空分异及影响因素[J]. 中国农业资源与区划, 2022, 43(1): 197-205.
	[Yin Songkui. A view on the changing characteristics and influencing factors of the urban-rural residents’ income gap in northwestern China[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2022, 43(1): 197-205.]
[17]	高新才, 殷颂葵. 西北地区城市水资源利用效率时空演变及俱乐部趋同分析[J]. 经济经纬, 2021, 38(2): 5-13.
	[Gao Xincai, Yin Songkui. Analysis of spatial-temporal evolution of urban water resources utilization efficiency and its club convergence in northwest China[J]. Economic Survey, 2021, 38(2): 5-13.]
[18]	郭凤玉, 孟静怡, 徐磊, 等. 冀北山区农业生态效率时空演变特征及预测分析[J]. 中国农机化学报, 2021, 42(10): 146-156. doi: 10.13733/j.jcam.issn.2095-5553.2021.10.21
	[Guo Fengyu, Meng Jingyi, Xu Lei, et al. Spatio-temporal evolution characteristics and prediction analysis of agricultural ecological efficiency in northern Hebei Mountains[J]. Journal of Chinese Agricultural Mechanization, 2021, 42(10): 146-156.] doi: 10.13733/j.jcam.issn.2095-5553.2021.10.21
[19]	周丽, 谢舒蕾. 基于空间马尔科夫链的农村经济发展水平分析——以四川省为例[J]. 中国农业资源与区划, 2016, 37(12): 186-191, 208.
	[Zhou Li, ZXie Shulei. Analysis of evolvement level of rural economy based on spatial Markov chains: Taking Sichuan Province for example[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2016, 37(12): 186-191, 208.]
[20]	刘华军, 乔列成, 孙淑惠. 黄河流域用水效率的空间格局及动态演进[J]. 资源科学, 2020, 42(1): 57-68. doi: 10.18402/resci.2020.01.06
	[Liu Huajun, Qiao Liecheng, Sun Shuhui. Spatial distribution and dynamic change of water use efficiency in the Yellow River Basin[J]. Resource Science, 2020, 42(1): 57-68.] doi: 10.18402/resci.2020.01.06
[21]	王少剑, 黄永源. 中国城市碳排放强度的空间溢出效应及驱动因素[J]. 地理学报, 2019, 74(6): 1131-1148. doi: 10.11821/dlxb201906005
	[Wang Shaojian, Huang Yongyuan. Spatial spillover effect and driving forces of carbon emission intensity at city level in China[J]. Acta Geographica Sinica, 2019, 74(6): 1131-1148.] doi: 10.11821/dlxb201906005
[22]	杨玉珍, 闫佳笑. 黄河流域高质量发展时空动态演变及溢出效应——基于9省域61个地市的数据分析[J]. 河南师范大学学报(自然科学版), 2022, 50(1): 23-35, 2.
	[Yang Yuzhen, Yan Jiaxiao. Spatio-temporal dynamic evolution and spillover effects of high-quality development in the Yellow River Basin: Based on data analysis of 61 cities in 9 provinces[J]. Journal of Henan Normal University (Natural Science Edition), 2022, 50(1): 23-35, 2.]
[23]	王少剑, 王洋, 赵亚博. 1990年来广东区域发展的空间溢出效应及驱动因素[J]. 地理学报, 2015, 70(6): 965-979. doi: 10.11821/dlxb201506010
	[Wang Shaojian, Wang Yang, Zhao Yabo. Spatial spillover effects and multi-mechanism for regional development in Guangdong Province since 1990s[J]. Acta Geographica Sinica, 2015, 70(6): 965-979.] doi: 10.11821/dlxb201506010
[24]	杨智. 地方户籍制度改革的现状分析——以青海省为视角[J]. 改革与开放, 2014(8): 35-36.
	[Yang Zhi. Analysis of the current situation of local reform of the household registration system: From the perspective of Qinghai Province[J]. Reform & Opening, 2014(8): 35-36.]

年份	转角/(°)	平均形状指数	重心坐标
2010	85.53°	0.42	100.98°E，36.40°N
2015	82.97°	0.36	100.79°E，36.35°N
2020	73.59°	0.37	100.71°E，36.14°N

年份	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
Moran’s I	0.671	0.722	0.675	0.661	0.669	0.700	0.706	0.704	0.705	0.704	0.627
P值	0.001	0.001	0.001	0.001	0.001	0.001	0.001	0.001	0.001	0.001	0.001
Z值	7.472	7.971	7.457	7.239	7.311	7.636	7.780	7.649	7.635	7.674	7.021

年份	高-高	低-高	低-低	高-低
2010	平安区、互助土族自治县、化隆回族自治县、城东区、城中区、城西区、城北区、湟中区	-	玛沁县、班玛县、甘德县、达日县、久治县、玛多县、同德县、兴海县、玉树市、囊谦县、曲麻莱县、杂多县	格尔木市
2015	平安区、互助土族自治县、化隆回族自治县、城东区、城中区、城西区、城北区、大通回族土族自治县、湟中区	-	玛沁县、班玛县、甘德县、达日县、久治县、玛多县、同德县、兴海县、玉树市、曲麻莱县、河南蒙古族自治县	-
2020	平安区、互助土族自治县、化隆回族自治县、城东区、城中区、城西区、城北区、大通回族土族自治县、湟中区	-	玛沁县、班玛县、甘德县、达日县、久治县、玛多县、同德县、兴海县、都兰县、称多县、曲麻莱县	杂多县

县域类型	Ⅰ	Ⅱ	Ⅲ	Ⅳ
Ⅰ	0.867	0.115	0.018	0.000
Ⅱ	0.057	0.838	0.086	0.019
Ⅲ	0.000	0.065	0.841	0.093
Ⅳ	0.000	0.010	0.038	0.952

邻域类型	县域类型	Ⅰ	Ⅱ	Ⅲ	Ⅳ
Ⅰ	Ⅰ	0.900	0.083	0.017	0.000
	Ⅱ	0.000	1.000	0.000	0.000
	Ⅲ	0.000	0.000	0.000	0.000
	Ⅳ	0.000	0.000	0.000	0.000
Ⅱ	Ⅰ	0.809	0.170	0.021	0.000
	Ⅱ	0.080	0.853	0.040	0.027
	Ⅲ	0.000	0.108	0.865	0.027
	Ⅳ	0.000	0.500	0.000	0.500
Ⅲ	Ⅰ	1.000	0.000	0.000	0.000
	Ⅱ	0.000	0.778	0.222	0.000
	Ⅲ	0.000	0.052	0.828	0.121
	Ⅳ	0.000	0.000	0.067	0.933
Ⅳ	Ⅰ	0.000	0.000	0.000	0.000
	Ⅱ	0.000	0.000	0.000	0.000
	Ⅲ	0.000	0.000	0.833	0.167
	Ⅳ	0.000	0.000	0.017	0.983

Spatiotemporal pattern and dynamic evolution of rural non-farm employment: A case of Qinghai Province

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 24

Related Articles 9

Metrics

Comments

Recommended 0

[1]	ZHANG Jing, BAO Guangyu, LIU Wei, YANG Chunhua, YAN Zhenning, DAI Qingcuo, FU Yongchao. Characteristics and model of rainstorm and flood disaster risk index along Qinghai Highway [J]. Arid Land Geography, 2024, 47(1): 28-37.
[2]	JIANG Yuekun, SHI Pengjuan. Spatiotemporal evolution and its affecting factors of urban-rural income gap at the city-level scale in China [J]. Arid Land Geography, 2024, 47(1): 147-157.
[3]	MA Wenjiang, BAI Miaoqin, Adili AIHEMAITI, ZHANG Deping, YANG Zhongna. Spatial-temporal differentiation and driving factors analysis of green total factor productivity of Xinjiang grain under the carbon peaking and carbon neutrality goals [J]. Arid Land Geography, 2023, 46(12): 2029-2041.
[4]	LI Lingwei,BAI Yongping,YANG Xuedi,ZHANG Chunyue,LIANG Jianshe,WANG Qian. Dynamic evolution and regional differences of sustainable development in Jiziwan of the Yellow River [J]. Arid Land Geography, 2022, 45(2): 639-649.
[5]	TAO Zefu,WANG Shiqing,SUN Piling,LI Kaidi,TIAN Wen,HAN Xiaoxiao. Spatio-temporal differentiation and driving factors of cropland in the agro-pastoral ecotone of northern China [J]. Arid Land Geography, 2022, 45(1): 153-163.
[6]	ZHANG Jian-hai, ZHANG Qi, XU De-he, DING Yan. Application of a combined ARIMA-LSTM model based on SPI for the forecast of drought：A case study in Qinghai Province [J]. Arid Land Geography, 2020, 43(4): 1004-1013.
[7]	HUANG Xin, LIU Jian-hong, SHEN Ke-jian, LIU Yong-mei, WANG Lei. Grassland yield change in Qinghai Province based on MODIS data [J]. Arid Land Geography, 2020, 43(3): 715-725.
[8]	YANG Xiao-min, LI Ling-qin, FU Jian-xin, CAO Guang-chao, TANG Zhong-xia, LI Ya-ling, WANG Hao-wen, WANG Rui-qing, LIU Ai-jia. Pattern variation of accessibility and economic linkage at county scale in Qinghai Province from 1986 to 2016 [J]. 干旱区地理, 2018, 41(6): 1376-1387.
[9]	HAN Bing-hong, ZHOU Bing-rong, WU Rang, ZHAO Min, NIE Guo-yan, NIU De-cao, FU Hua. Grid-based estimation of drought disaster in Qinghai Province [J]. 干旱区地理, 2018, 41(6): 1194-1203.