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Driving total factor productivity: Capital and labor with tax allocation

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  • Xu, Bing
  • Sendra-García, Javier
  • Gao, Yanxia
  • Chen, Xiaohui

Abstract

In small and micro enterprises, the capital and labor input change frequently with time, which is difficult to observe directly. Therefore, it is a challenging problem to measure total factor productivity, the source of sustainable economic growth. This paper establishes a new time-varying production function model to measure the Total Factor Productivity for small and micro enterprises, as well as its corresponding technological progress and efficiency improvement. Based on the data of 7158 small and micro enterprises in Yuhuan China Auto Parts City. The results of this paper find that Total factor productivity is mainly attributed to technological progress, which is mainly driven by labor force. Efficiency improvement is also changing in the same direction as labor-driven efficiency improvement Human resource management may be the main reason for low efficiency. As a policy implication of our results, this paper designs a policy allocation using delaying tax payment and proper tax policy allocation. The economic and social benefits of enterprises can be balanced and total factor productivity can be promoted.

Suggested Citation

  • Xu, Bing & Sendra-García, Javier & Gao, Yanxia & Chen, Xiaohui, 2020. "Driving total factor productivity: Capital and labor with tax allocation," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    • Handle: RePEc:eee:tefoso:v:150:y:2020:i:c:s004016251931073x
    DOI: 10.1016/j.techfore.2019.119782
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    References listed on IDEAS

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    4. Xin Jin & Shuhao Liu & Xue Lei, 2026. "ICT investment and carbon emission efficiency in regional port groups: evidence from Chinese coastal provinces," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 13(1), pages 1-18, December.
    5. Shen Zhong & Yu’an Fang, 2025. "The Impact of Electricity Consumption on Green Total Factor Productivity: Evidence from Chinese Provinces," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(1), pages 3921-3947, March.
    6. Fan, Hongwei & Yin, Junming & Usman, Muhammad & Li, Zhengguang, 2024. "Intellectual property protection and total factor productivity of enterprises: A quasi-natural experiment of intellectual property courts," Finance Research Letters, Elsevier, vol. 70(C).
    7. Rongwu Zhang & Lan Luo & Jianjun Du, 2023. "The influence of fiscal policy uncertainty on corporate total factor productivity: Evidence from Chinese public companies," Contemporary Economic Policy, Western Economic Association International, vol. 41(3), pages 532-554, July.
    8. Yan, Jiajia & Zhang, Chenyan, 2024. "Financial institution agglomeration and corporate labor allocation efficiency—Based on the context of government debt expansion," Finance Research Letters, Elsevier, vol. 63(C).
    9. Musa Abdu & Adamu Jibir & Salihu Abdullahi & Aisha Adamu Hassan, 2021. "Drivers of manufacturing firms’ productivity: a micro-perspective to industrialization in Nigeria," SN Business & Economics, Springer, vol. 1(2), pages 1-17, February.
    10. Zhang, Sheng-Hao & Yang, Jun & Cheng, Jixin & Li, Xiaoming, 2025. "Exploring the carbon rebound effect of digitalization and policy responses: A CDEEEA/CGE based analysis," Energy Economics, Elsevier, vol. 141(C).

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