Abstract：With the process of economic development and industrial structure transformation, China's employment spatial pattern is undergoing a huge transformation. This article is based on the data from the fifth to seventh population censuses by county, revealing the spatiotemporal pattern of the employed population at the city and county levels in China since the new century. It identifies the regional types and industrial characteristics of the contraction of the employed population, and uses the ordinal logistic regression model to explore the influencing factors of the contraction of the employed population. The main conclusions are as follows: 1) Since 2000, the employed population in China has shown a trend of first increasing and then decreasing, The number of counties maintaining the employment growth has significantly decreased; 2) Among the three types of contraction areas, the episodic shrinkage area accounts for about half of the country, mostly transitioning from growth cessation to contraction, mainly distributed in the central and western regions. The continuous shrinkage area accounts for about 1/3, mainly distributed at the junction of the three major economic belts. The non-shrinking area accounts for about 15%, mainly distributed in the northwest region and the three major urban agglomerations; 3) The intensity of industrial reduction in areas with reduced employment shows a decreasing trend in the primary, secondary, and tertiary industries; 4) A high wage level, the age structure with a high proportion of working-age population, and the development of the secondary and tertiary industries can help suppress the contraction of the employed population, while an increase in the minimum wage standard can promote the occurrence of employment population shrinkage.
李浩天, 薛德升, 黄耿志, 张沈圆. 2000—2020年中国就业人口时空格局及影响因素研究[J]. 人文地理, 2024, 39(5): 96-108.
LI Hao-tian, XUE De-sheng, HUANG Geng-zhi, ZHANG Shen-yuan. STUDY ON THE SPATIO-TEMPORAL PATTERN AND INFLUENCING FACTORS OF CHINESE EMPLOYED POPULATION FROM 2000 TO 2020. HUMAN GEOGRAPHY, 2024, 39(5): 96-108.
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