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The impact of China’s value-added tax credit refunds on enterprise labor demand: Ex-ante analysis and ex-post test

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  • Yang Yang
  • Xin Yu
  • Jian Du

Abstract

This paper aims to explore the impact of China’s value-added tax (VAT) credit refunds policy on the enterprises’ labor demand through a paradigm combining ex-ante analysis and ex-post test. By introducing the VAT credit refunds into the production-decision model of the enterprise, calibrating the parameters and conducting the dynamic effects tests using the data of Chinese A-share listed enterprises, this paper finds that the labor employment of the pilot enterprises exhibits a V-shaped fluctuation trend. In the initial implementation of the policy, due to the existence of layoff costs, iso-cost line of the enterprise bends, which results in that the enterprise with a capital-labor substitution elasticity greater than 1 will not reduce labor hiring, as it has already deployed labor force before the implementation of the policy. When the enterprise enter the next production cycle where the labor force can be freely allocated, the labor employment of the enterprise with a capital-labor elasticity of substitution greater than 1 will decline compared to that without the policy. In the long run, as output increases, the labor demand will recover. The results of ex-post test are consistent with that of the ex-ante analysis. Additionally, heterogeneity test reveals that the greater the elasticity of capital-labor substitution of the sub-industry is, the more severe the degree of the V-shaped fluctuation is. Following the implementation of the policy, the continuous increase in enterprise output and capital stock verifies the relevant transmission mechanism. This study provides a more detailed perspective for comprehensively understanding the impact of VAT credit refunds policy on employment.

Suggested Citation

  • Yang Yang & Xin Yu & Jian Du, 2024. "The impact of China’s value-added tax credit refunds on enterprise labor demand: Ex-ante analysis and ex-post test," PLOS ONE, Public Library of Science, vol. 19(6), pages 1-32, June.
  • Handle: RePEc:plo:pone00:0305249
    DOI: 10.1371/journal.pone.0305249
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