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干旱区地理 ›› 2023, Vol. 46 ›› Issue (12): 2111-2119.doi: 10.12118/j.issn.1000-6060.2023.123

• 区域发展 • 上一篇    

乡村非农就业水平的时空格局及动态演进——以青海省为例

高福鑫(),赵玲(),魏琼   

  1. 青海大学财经学院,青海 西宁 810016
  • 收稿日期:2023-03-20 修回日期:2023-05-18 出版日期:2023-12-25 发布日期:2024-01-05
  • 通讯作者: 赵玲(1978-),女,博士,教授,主要从事区域经济发展研究. E-mail: 14720838@qq.com
  • 作者简介:高福鑫(1998-),男,硕士研究生,主要从事区域经济发展、农业经济发展研究. E-mail: 15776872807@163.com
  • 基金资助:
    国家社会科学基金项目(18XMZ059);国家社会科学基金项目(20BMZ149)

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

GAO Fuxin(),ZHAO Ling(),WEI Qiong   

  1. School of Finance and Economics, Qinghai University, Xining 810016, Qinghai, China
  • Received:2023-03-20 Revised:2023-05-18 Online:2023-12-25 Published:2024-01-05

摘要:

为了准确把握县域尺度下青海省乡村非农就业水平的时空格局及动态演进趋势,促进共同富裕的实现,基于2010—2020年青海省43个县域单元的面板数据,借助全局趋势分析、标准差椭圆、Moran’s I指数等方法揭示青海省乡村非农就业水平的时空演变特征,并进一步采用Kernel密度估计、马尔科夫链考察其动态演进趋势。结果表明:(1) 青海省乡村非农就业水平总体呈现出波动上升趋势,根据增长速度划分为快速增长阶段和缓慢增长阶段。(2) 在空间分布格局上,空间分布整体表现为“东、西部高中部低”“北高南低”,空间格局呈现出由“正东—正西”分布向“偏东北—偏西南”方向偏移趋势。(3) 在空间相关性上,乡村非农就业水平存在显著的空间正自相关性,“高-高”集聚和“低-低”集聚的板块特征显著。(4) 在分布动态演进上,乡村非农就业水平存在稳定的俱乐部趋同现象,乡村非农就业水平在发展过程中存在“空间溢出”效应。

关键词: 乡村非农就业水平, 共同富裕, 时空格局, 动态演进, 青海省

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