Can big data inhibit earnings management in corporations? — An analysis based on national big data comprehensive pilot zones

Yiran Chen, Jiaye Li, Yan Tong and Laiqun Jin

Research in International Business and Finance, 2025, vol. 78, issue C

Abstract: The issue of financial information distortion caused by earnings management may mislead investors and reduce the decision-making efficiency of the capital market. This study, based on the data of Chinese A-share listed companies from 2010 to 2022, examines the impact and mechanism of the "National Big Data Comprehensive Pilot Zone" policy on corporate earnings management. The findings reveal that the establishment of big data pilot zones significantly reduced corporate earnings management behavior, and this conclusion remains robust after a series of robustness tests. Further mechanism analysis indicates that big data inhibits earnings management by alleviating information asymmetry, enhancing the transparency of corporate financial information, and strengthening the level of internal control. Heterogeneity analysis shows that the inhibitory effect of big data policy on earnings management is more pronounced in labor-intensive industries and growth-stage corporations, while relatively weaker in technology-intensive industries and mature corporations. Additionally, the big data pilot zone has also enhanced the risk-taking ability of corporations. This study provides empirical insights for assessing the effectiveness of policy implementation and its role in the governance of earnings management.

Keywords: Big data pilot zones; Information asymmetry; Earnings management (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:riibaf:v:78:y:2025:i:c:s0275531925002764

DOI: 10.1016/j.ribaf.2025.103020

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