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Reform of state-owned capital authorised operation system and expense stickiness: evidence from state-owned listed companies

Jinkang Zhang & Xiaofeng Quan

China Journal of Accounting Studies2025https://doi.org/10.1080/21697213.2025.2487550article
AJG 1ABDC B
Weight
0.50

Abstract

This study examines how state-owned capital investment and operation companies (SCIOCs), a key reform of China’s state-owned capital authorised operation system with a foucs on managing capital, influence firms’ expense stickiness. Using a staggered difference-in-differences approach with data from Chinese state-owned listed companies, we find that SCIOCs significantly reduce expense stickiness. Mechanism analysis reveals that SCIOCs enhance shareholder supervision and strengthen executive incentives, while simultaneously reducing employee redundancy and overinvestment, indicating that decreased agency costs and government intervention are the key underlying channels. Additional analyses show that the mitigating effect of SCIOCs on expense stickiness is stronger in local and commercial state-owned enterprises, and in firms with weaker supervisory governance. This study contributes novel insights into how SCIOCs reshape firms’ cost behavior, offering empirical support and important policy implications for deepening reform of the state-owned capital authorised operation system and improving the operational efficiency of state-owned enterprises.

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https://doi.org/https://doi.org/10.1080/21697213.2025.2487550

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@article{jinkang2025,
  title        = {{Reform of state-owned capital authorised operation system and expense stickiness: evidence from state-owned listed companies}},
  author       = {Jinkang Zhang & Xiaofeng Quan},
  journal      = {China Journal of Accounting Studies},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1080/21697213.2025.2487550},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.