A Statistical Model-Based Study of the Coupled Relationship between Labor Force Skill Complementarity and Economic Growth
Pages 382 - 393
Abstract
Economic growth is one of the key indicators of whether a region is developing and the level of development. The degree of complementarity of labor force skills directly reflects the rationality of the labor force structure in a region. The degree of complementarity between labor force skills and economic growth in a region can be reflected by their coupling degree. To identify the relationship between the degree of labor force skill complementarity and economic growth in Shandong Province and the issues therein, this study utilizes relevant data from the Shandong Statistical Yearbooks from 2006 to 2020 to mainly analyze the synergistic relationship between the degree of labor force skill complementarity and economic growth. The results show that the level of economic growth and the degree of labor force skill complementarity in various cities in Shandong Province have generally steadily increased, and the coupling degree has also shown an increasing trend, indicating an improvement in the synergy between the degree of labor force skill complementarity and economic growth. However, there is significant regional imbalance in the economic growth index and the labor force skill complementarity index in Shandong Province, with substantial disparities between regions. Therefore, recommendations are made based on the results: economically underdeveloped regions should cooperate with economically developed regions, identify positioning accurately, introduce industries, and improve the economic growth level of underdeveloped regions. Developed regions should relax policies, attract low-skilled labor, optimize the labor force structure of developed regions, promote mutual development, and further enhance the synergy between labor force skill complementarity and economic growth.
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Published In
November 2024
419 pages
ISBN:9798400718076
DOI:10.1145/3696952
Copyright © 2024 Copyright held by the owner/author(s).
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).
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Association for Computing Machinery
New York, NY, United States
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Published: 21 November 2024
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ICIIP 2024
ICIIP 2024: 2024 9th International Conference on Intelligent Information Processing
November 21 - 23, 2024
Bucharest, Romania
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