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Has inspection supervision effectively reduced the risk of local government debt? Evidence from China

Author

Listed:
  • Zhang, Jinjin
  • Liu, Jin
  • Zhou, Gang
  • Pan, Di
  • Liao, Fang-nan

Abstract

This paper employs a difference-in-differences (DID) model to analyze data from 289 Chinese prefecture-level cities from 2009 to 2016 and comes to the following conclusion: patrol supervision can reduce the risk of local government debt. After conducting a series of robustness tests, including propensity score matching (PSM) tests, transformation study design, and replacement of explained variables, this conclusion remains robust. Further investigation reveals that the effectiveness of inspection and supervision in reducing local government debt risk is more pronounced in regions with a poorer financial ecological environment and a greater soft budget constraint, indicating a substitute function. By examining the impact of patrol supervision on local government debt risk, this paper provides valuable insights for preventing and resolving major risks and offers up recommendations for future efforts in this domain.

Suggested Citation

  • Zhang, Jinjin & Liu, Jin & Zhou, Gang & Pan, Di & Liao, Fang-nan, 2024. "Has inspection supervision effectively reduced the risk of local government debt? Evidence from China," Finance Research Letters, Elsevier, vol. 60(C).
  • Handle: RePEc:eee:finlet:v:60:y:2024:i:c:s1544612323012412
    DOI: 10.1016/j.frl.2023.104869
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    References listed on IDEAS

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    1. Niclas Berggren & Christian Bjørnskov, 2019. "Regulation and government debt," Public Choice, Springer, vol. 178(1), pages 153-178, January.
    2. Attahir Babaji Abubakar, 2020. "Does fiscal tightening (loosening) reduce public debt?," African Development Review, African Development Bank, vol. 32(4), pages 528-539, December.
    3. Alessandro Dovis & Rishabh Kirpalani, 2020. "Fiscal Rules, Bailouts, and Reputation in Federal Governments," American Economic Review, American Economic Association, vol. 110(3), pages 860-888, March.
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