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Sustainable Development of the Rural Labor Market in China from the Perspective of Occupation Structure Transformation

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  • Zhiyuan Ma

    (Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    United Nations Environment Programme-International Ecosystem Management Partnership (UNEP-IEMP), Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Yunli Bai

    (Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    United Nations Environment Programme-International Ecosystem Management Partnership (UNEP-IEMP), Beijing 100101, China)

  • Linxiu Zhang

    (Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    United Nations Environment Programme-International Ecosystem Management Partnership (UNEP-IEMP), Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

This study analyzes the structural transformations of the occupations of all off-farm rural laborers in China over the period 2007–2022. The changes in the rural labor market are mainly reflected in the decrease in the share of routine manual laborers from 66.59 percent to 52.77 percent, and the increases in the shares of non-routine cognitive and non-working laborers by 4.48 and 10.73 percentage points from 2007 to 2022, respectively. By adopting decomposition analysis, which improves the definition of occupational classification based on information on sub-sectors in industries and job contents using a dataset with a nationally representative sample covering 2000 rural households, the results show that both composition effect and propensity effect play important roles in the decrease in routine manual occupations; the composition effect dominates the changes in the non-routine cognitive occupation category, while the propensity effect is the main driver of the increasing trend in the non-working group. The economic model further illustrates the results of decomposition analysis. These findings imply that the government should further improve education in rural areas and pay greater attention to female and low-education-attainment groups among rural laborers. This study provides a reference for policies aimed at promoting the sustainable development of the rural labor market.

Suggested Citation

  • Zhiyuan Ma & Yunli Bai & Linxiu Zhang, 2024. "Sustainable Development of the Rural Labor Market in China from the Perspective of Occupation Structure Transformation," Sustainability, MDPI, vol. 16(7), pages 1-22, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:7:p:2938-:d:1368624
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    References listed on IDEAS

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    1. Linxiu Zhang & Yongqing Dong & Chengfang Liu & Yunli Bai, 2018. "Off-farm employment over the past four decades in rural China," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 10(2), pages 190-214, May.
    2. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    3. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    4. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    5. Jaison R. Abel & Richard Deitz, 2012. "Job polarization and rising inequality in the nation and the New York-northern New Jersey region," Current Issues in Economics and Finance, Federal Reserve Bank of New York, vol. 18(Oct).
    6. Fana, Marta & Giangregorio, Luca, 2024. "The role of tasks, contractual arrangements, and job composition in explaining the dynamics of wage inequality: Evidence from France," Labour Economics, Elsevier, vol. 87(C).
    7. Linxiu Zhang & Yongqing Dong & Chengfang Liu & Yunli Bai, 2018. "Off-farm employment over the past four decades in rural China," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 10(2), pages 190-214, May.
    8. Fang Cai, 2010. "Demographic transition, demographic dividend, and Lewis turning point in China," China Economic Journal, Taylor & Francis Journals, vol. 3(2), pages 107-119.
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