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Forecast of Advanced Human Capital Gap Based on PSO-BP Neural Network and Coordination Pathway: Example of Beijing–Tianjin–Hebei Region

Author

Listed:
  • Miao He

    (School of Economics, Hebei University, Baoding 071002, China
    Research Center of Resource Utilization and Environmental Protection, Hebei University, Baoding 071002, China
    These authors contributed equally to this work.)

  • Junli Huang

    (School of Marxism, Peking University, Beijing 100092, China
    These authors contributed equally to this work.)

  • Ruyi Sun

    (School of Economics, Hebei University, Baoding 071002, China)

Abstract

The upgrading of human capital caused by education is significant to regional development. Reasonable predictions of the degree of advanced human capital in different regions are effective for formulating reasonable talent policies and accelerating regional coordinated development. The BP neural network is a widely used prediction technology. PSO-BP neural network has good global search ability, which can accelerate the convergence speed of traditional BP neural network, which is suitable for forecasting larger data. The study takes the provincial data of China from 2005 to 2019 as an example, using PSO-BP neural network algorithm to predict the advanced level of human capital through the influencing factors filtered by OLS regression. The results show that: (1) Innovation ability and urbanization can play a decisive role in advanced human capital filtered by OLS regression; (2) The results of predicting the development trend of advanced human capital in the Beijing–Tianjin–Hebei region in 2020–2025 through the PSO-BP neural network have showed that there is still a large gap between the senior human capital stock in Hebei-Beijing-Tianjin in terms of total and per capita in 2020–2025 compared with other regions in east of China; (3) Giving full attention to elaborate the positive role of economic quality and quantity development are suitable for narrowing the difference of advanced human capital in this region. Through the method of OLS-BP-neural network, this study explores the gap and influencing factors of the Beijing–Tianjin–Hebei region, excavates the reasons for the huge gradient difference in the development of this region, and extends the machine learning prediction method to the analysis of the advanced level of human capital and the research of narrowing the regional development gap.

Suggested Citation

  • Miao He & Junli Huang & Ruyi Sun, 2023. "Forecast of Advanced Human Capital Gap Based on PSO-BP Neural Network and Coordination Pathway: Example of Beijing–Tianjin–Hebei Region," Sustainability, MDPI, vol. 15(5), pages 1-18, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4671-:d:1089020
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    as
    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Alain Desdoigts & Fernando Jaramillo, 2020. "Bounded Learning by Doing, Inequality, and Multi-Sector Growth: A Middle-Class Perspective," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 36, pages 198-219, April.
    3. Haixiao Wu, 2023. "The contribution of interregional and inter-field knowledge spillovers to regional Smart Specialisation," Regional Studies, Taylor & Francis Journals, vol. 57(2), pages 356-369, February.
    4. Ahmed, Zahoor & Asghar, Muhammad Mansoor & Malik, Muhammad Nasir & Nawaz, Kishwar, 2020. "Moving towards a sustainable environment: The dynamic linkage between natural resources, human capital, urbanization, economic growth, and ecological footprint in China," Resources Policy, Elsevier, vol. 67(C).
    5. Maha Mohamed Alsebai Mohamed & Pingfeng Liu & Guihua Nie, 2022. "Causality between Technological Innovation and Economic Growth: Evidence from the Economies of Developing Countries," Sustainability, MDPI, vol. 14(6), pages 1-39, March.
    6. Zahoor Ahmed & Muhammad Mansoor Asghar & Muhammad Nasir Malik & Kishwar Nawaz, 2020. "Moving towards a sustainable environment: The dynamic linkage between natural resources, human capital, urbanization, economic growth, and ecological footprint in China," Post-Print hal-03557938, HAL.
    7. Zhiwei Liu & Yonglei Fang & Lei Ma, 2022. "A Study on the Impact of Population Age Structure Change on Economic Growth in China," Sustainability, MDPI, vol. 14(7), pages 1-15, March.
    8. Liping Fu & Yuhui Wang & Lanping He, 2020. "Age composition change and inter-provincial labor productivity: a study from the perspective of population dividend and population urbanization," Journal of Applied Economics, Taylor & Francis Journals, vol. 23(1), pages 183-198, January.
    9. Peng Liang & Shuangyi Xie & Fengyu Qi & Yu Huang & Xiuwen Wu, 2023. "Environmental Regulation and Green Technology Innovation under the Carbon Neutrality Goal: Dual Regulation of Human Capital and Industrial Structure," Sustainability, MDPI, vol. 15(3), pages 1-18, January.
    10. Kumar, Alok & Kober, Brianne, 2012. "Urbanization, human capital, and cross-country productivity differences," Economics Letters, Elsevier, vol. 117(1), pages 14-17.
    11. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    12. Enrico Moretti, 2004. "Workers' Education, Spillovers, and Productivity: Evidence from Plant-Level Production Functions," American Economic Review, American Economic Association, vol. 94(3), pages 656-690, June.
    13. Alain Desdoigts & Fernando Jaramillo, 2020. "Bounded Learning by Doing, Inequality, and Multi-Sector Growth: A Middle-Class Perspective," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 36, pages 198-219, April.
    14. Kamalika Chakraborty & Bidisha Chakraborty, 2018. "Publisher Correction: Low level equilibrium trap, unemployment, efficiency of education system, child labour and human capital formation," Journal of Economics, Springer, vol. 125(1), pages 105-105, September.
    15. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    16. Na Li & Meng Li & Miaochao Chen, 2022. "Forecast of Chemical Export Trade Based on PSO-BP Neural Network Model," Journal of Mathematics, Hindawi, vol. 2022, pages 1-10, March.
    17. Francesco Cinnirella & Jochen Streb, 2017. "The role of human capital and innovation in economic development: evidence from post-Malthusian Prussia," Journal of Economic Growth, Springer, vol. 22(2), pages 193-227, June.
    18. Cecilia Casalegno & Michela Pellicelli & Chiara Civera, 2017. "CSR and human capital as levers for enhancing shareholder value creation. An early investigation of the largest European companies," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 19(4), pages 448-467.
    19. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
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