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Asymmetric fiscal policies and digital economy development: An empirical analysis based on the global digital value chain perspective

Author

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  • Wang, Zhan
  • Ma, Dan
  • Tang, Jiaqi

Abstract

The indicator system for evaluating the development level of the digital economy is multidimensional and dynamic. Accurate and scientific evaluation of the digital economy's development level is crucial. This study, based on the characteristics of the digital economy's development stages, evaluates the value creation dimension of the digital economy from the perspective of the global digital value chain. Additionally, it considers the access and usage dimensions to construct a comprehensive indicator system for evaluating the global digital economy development level. The results reveal significant disparities in digital economy development between countries, but also show that some developing countries have experienced rapid improvements in their digital economy development levels. In theoretical and empirical research, this paper utilizes the Barro Rule and the Cobb-Douglas production function, employing mathematical derivations combined with empirical regression analysis to explore the relationship and mechanisms between asymmetric fiscal policies and digital economy development during economic downturns. It finds that in the new era of the digital economy, governments often implement proactive asymmetric fiscal expenditure policies during downturns. Continuously promoting the development levels of national digital economies is an important mechanism for forming these characteristics of fiscal expenditures. Finally, this study proposes relevant policy recommendations, enriching academic research and policy discussions in the fields of financial fiscal policy and digital economy development.

Suggested Citation

  • Wang, Zhan & Ma, Dan & Tang, Jiaqi, 2024. "Asymmetric fiscal policies and digital economy development: An empirical analysis based on the global digital value chain perspective," International Review of Financial Analysis, Elsevier, vol. 96(PA).
  • Handle: RePEc:eee:finana:v:96:y:2024:i:pa:s1057521924004885
    DOI: 10.1016/j.irfa.2024.103556
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