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Digital economy, aging of the labor force, and employment transformation of migrant workers: Evidence from China

Author

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  • Guo, Lu
  • Xiao, Fang

Abstract

Migrant workers are the key group of employment work. Promoting the employment transformation of migrant workers under the background of the booming digital economy and the deepening aging degree is related to the overall stability of employment, but also to rural revitalization and common prosperity. This paper uses five waves of data from the China Family Panel Studies (CFPS) from 2012 to 2020 to explore the impact of the aging of the labor force on the employment transformation of migrant workers using multiple Logit regression models, and systematically and deeply explores the role of the digital economy in this process and its mechanism. The main findings of this study are as follows: firstly, the aging of the labor force significantly inhibits the employment transformation of migrant workers, which is mainly reflected in the inhibition of their transformation from traditional industries to new economy industries. Secondly, the digital economy significantly promotes the employment transformation of migrant workers and effectively alleviates the inhibitory effect of the aging of the labor force on the employment transformation of migrant workers. And it mainly plays its role by promoting the industrial structure upgrading, and the social capital and human capital accumulation of migrant workers. Thirdly, the mitigation effect of the digital economy is more effective among high-skilled migrant workers, young and middle-aged migrant workers, rural migrant workers, as well as migrant workers in eastern cities, large-sized cities, and cities with high digital development levels. Based on the above research conclusions, this article proposes relevant policy recommendations for actively responding to the aging of the labor force and fully leveraging the mitigating effects of the digital economy.

Suggested Citation

  • Guo, Lu & Xiao, Fang, 2024. "Digital economy, aging of the labor force, and employment transformation of migrant workers: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 787-807.
    • Handle: RePEc:eee:ecanpo:v:84:y:2024:i:c:p:787-807
    DOI: 10.1016/j.eap.2024.09.032
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    References listed on IDEAS

    as
    1. Jay Dixon & Bryan Hong & Lynn Wu, 2021. "The Robot Revolution: Managerial and Employment Consequences for Firms," Management Science, INFORMS, vol. 67(9), pages 5586-5605, September.
    2. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    3. Davis, Donald R. & Dingel, Jonathan I., 2020. "The comparative advantage of cities," Journal of International Economics, Elsevier, vol. 123(C).
    4. Su, Chi-Wei & Yuan, Xi & Umar, Muhammad & Lobonţ, Oana-Ramona, 2022. "Does technological innovation bring destruction or creation to the labor market?," Technology in Society, Elsevier, vol. 68(C).
    5. Eric J. Bartelsman & Pieter A. Gautier & Joris Wind, 2016. "Employment Protection, Technology Choice, And Worker Allocation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57, pages 787-826, August.
    6. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    7. Scarpetta, Stefano & Tressel, Thierry, 2004. "Boosting productivity via innovation and adoption of new technologies : any role for labor market institutions?," Policy Research Working Paper Series 3273, The World Bank.
    8. Zhang, Zhuo, 2023. "The impact of the artificial intelligence industry on the number and structure of employments in the digital economy environment," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    9. Zhou, Qiuyang, 2024. "Does the digital economy promote the consumption structure upgrading of urban residents? Evidence from Chinese cities," Structural Change and Economic Dynamics, Elsevier, vol. 69(C), pages 543-551.
    10. Paula Prenzel, 2021. "Are old regions less attractive? Interregional labour migration in a context of population ageing," Papers in Regional Science, Wiley Blackwell, vol. 100(6), pages 1429-1447, December.
    11. Alexandra Spitz-Oener, 2006. "Technical Change, Job Tasks, and Rising Educational Demands: Looking outside the Wage Structure," Journal of Labor Economics, University of Chicago Press, vol. 24(2), pages 235-270, April.
    12. Georg Duernecker & Berthold Herrendorf, 2022. "Structural Transformation of Occupation Employment," Economica, London School of Economics and Political Science, vol. 89(356), pages 789-814, October.
    13. Mao, Rui & Xu, Jianwei & Zou, Jingxian, 2018. "The labor force age structure and employment structure of the modern sector," China Economic Review, Elsevier, vol. 52(C), pages 1-15.
    14. Luo, Kang & Liu, Yaobin & Chen, Pei-Fen & Zeng, Mingli, 2022. "Assessing the impact of digital economy on green development efficiency in the Yangtze River Economic Belt," Energy Economics, Elsevier, vol. 112(C).
    15. Gideon Bornstein, 2019. "Entry and Profits in an Aging Economy: The Role of Consumer Inertia," 2019 Meeting Papers 309, Society for Economic Dynamics.
    16. Ling Li, 2020. "Education supply chain in the era of Industry 4.0," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(4), pages 579-592, July.
    17. Sotiris Blanas & Gino Gancia & Sang Yoon (Tim) Lee, 2019. "Who is afraid of machines?," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 34(100), pages 627-690.
    18. David Roodman, 2011. "Fitting fully observed recursive mixed-process models with cmp," Stata Journal, StataCorp LLC, vol. 11(2), pages 159-206, June.
    19. Li, Wencong & Yang, Xingquan & Yin, Xingqiang, 2024. "Digital transformation and labor upgrading," Pacific-Basin Finance Journal, Elsevier, vol. 83(C).
    20. Peter Kuhn & Hani Mansour, 2014. "Is Internet Job Search Still Ineffective?," Economic Journal, Royal Economic Society, vol. 124(581), pages 1213-1233, December.
    21. Siliverstovs, Boriss & Kholodilin, Konstantin A. & Thiessen, Ulrich, 2011. "Does aging influence structural change? Evidence from panel data," Economic Systems, Elsevier, vol. 35(2), pages 244-260, June.
    22. Tommaso Porzio & Federico Rossi & Gabriella Santangelo, 2022. "The Human Side of Structural Transformation," American Economic Review, American Economic Association, vol. 112(8), pages 2774-2814, August.
    23. Eric J. Bartelsman & Pieter A. Gautier & Joris De Wind, 2016. "Employment Protection, Technology Choice, And Worker Allocation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(3), pages 787-826, August.
    24. Guo, Bingnan & Wang, Yu & Zhang, Hao & Liang, Chunyan & Feng, Yu & Hu, Feng, 2023. "Impact of the digital economy on high-quality urban economic development: Evidence from Chinese cities," Economic Modelling, Elsevier, vol. 120(C).
    25. repec:bla:ecpoli:v:24:y:2009:i::p:349-402 is not listed on IDEAS
    26. Benjamin David, 2017. "Computer technology and probable job destructions in Japan: An evaluation," Post-Print hal-01549790, HAL.
    27. Arntz, Melanie & Gregory, Terry & Zierahn, Ulrich, 2017. "Revisiting the risk of automation," Economics Letters, Elsevier, vol. 159(C), pages 157-160.
    28. Robert J. Gordon, 2016. "Perspectives on The Rise and Fall of American Growth," American Economic Review, American Economic Association, vol. 106(5), pages 72-76, May.
    29. Zhang, Huafeng, 2010. "The Hukou system's constraints on migrant workers' job mobility in Chinese cities," China Economic Review, Elsevier, vol. 21(1), pages 51-64, March.
    30. Daron Acemoglu & Pascual Restrepo, 2022. "Demographics and Automation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(1), pages 1-44.
    31. Andrea Bassanini & Luca Nunziata & Danielle Venn, 2009. "Job protection legislation and productivity growth in OECD countries [Appropriate growth policy: a unifying framework]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 24(58), pages 349-402.
    32. Zhu, Yuke & Lan, Mudan, 2023. "Digital economy and carbon rebound effect: Evidence from Chinese cities," Energy Economics, Elsevier, vol. 126(C).
    33. Qiang Li & Jikun Huang & Renfu Luo & Chengfang Liu, 2013. "China's Labor Transition and the Future of China's Rural Wages and Employment," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 21(3), pages 4-24, May.
    34. David, Benjamin, 2017. "Computer technology and probable job destructions in Japan: An evaluation," Journal of the Japanese and International Economies, Elsevier, vol. 43(C), pages 77-87.
    35. Lisi Tan & Zhuodong Yang & Muhammad Irfan & Chante Jian Ding & Mingjun Hu & Jin Hu, 2024. "Toward low‐carbon sustainable development: Exploring the impact of digital economy development and industrial restructuring," Business Strategy and the Environment, Wiley Blackwell, vol. 33(3), pages 2159-2172, March.
    36. Moreno-Galbis, Eva & Sopraseuth, Thepthida, 2014. "Job polarization in aging economies," Labour Economics, Elsevier, vol. 27(C), pages 44-55.
    37. Pan, Wenrong & Xie, Tao & Wang, Zhuwang & Ma, Lisha, 2022. "Digital economy: An innovation driver for total factor productivity," Journal of Business Research, Elsevier, vol. 139(C), pages 303-311.
    38. de Brauw, Alan & Huang, Jikun & Rozelle, Scott & Zhang, Linxiu & Zhang, Yigang, 2002. "The Evolution of China's Rural Labor Markets During the Reforms," Journal of Comparative Economics, Elsevier, vol. 30(2), pages 329-353, June.
    39. Liu, Yi & Zhao, Xuan & Liu, Yi & Kong, Fanjun, 2023. "The dynamic impact of digital economy on the green development of traditional manufacturing industry: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 143-160.
    40. Andreas Irmen, 2017. "Capital‐ And Labor‐Saving Technical Change In An Aging Economy," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 58(1), pages 261-285, February.
    41. Nicole Maestas & Kathleen J. Mullen & David Powell, 2023. "The Effect of Population Aging on Economic Growth, the Labor Force, and Productivity," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(2), pages 306-332, April.
    42. Cheng, Shihui & Ma, Wenjing & Luo, Lai & Li, Yunlong, 2023. "Can the development of digital economy improve the quality of regional investment? — Empirical evidence from Chinese cities," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 214-221.
    43. Fossen, Frank M. & Sorgner, Alina, 2022. "New digital technologies and heterogeneous wage and employment dynamics in the United States: Evidence from individual-level data," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
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    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J61 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Geographic Labor Mobility; Immigrant Workers
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • J14 - Labor and Demographic Economics - - Demographic Economics - - - Economics of the Elderly; Economics of the Handicapped; Non-Labor Market Discrimination

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