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Earnings management using classification shifting of revenues: evidence from Chinese-listed firms

Author

Listed:
  • Ajid Ur Rehman
  • Asad Yaqub
  • Tanveer Ahsan

    (ESC [Rennes] - ESC Rennes School of Business)

  • Zia-Ur-Rehman Rao

Abstract

Purpose This study aims to investigate earnings management practice of classification shifting of revenues in Chinese-listed firms. Design/methodology/approach The study employs a dataset of 2,920 A-listed firms from Chinese stock exchanges of Shanghai and Shenzhen for the period of 2003–2019. We apply both univariate and panel regression analysis by using fixed effect estimation with robust standard errors. Findings Our findings reveal that firms misclassify revenues by taking advantage of the flexibility provided by applicable financial reporting standards. The empirical evidence obtained through regression analysis suggest that managers reclassify non-operating revenues as operating revenue to alter the economic reality while seeking the advantage of financial reports users' vulnerability for valuing the upper half of income statement items more as compared to lower part. The results further indicate that international financial reporting standards adoption inhibits the earnings management practices using classification shifting of revenues. It is also concluded that firms, which are suffering losses or having low growth, are more persistently involved in misclassification of revenues. Originality/value The study is unique from the point of view that it investigates earnings management from the prospective of revenue's classification in an emerging market characterized by various market imperfections such as lower investor protection and higher information asymmetry.

Suggested Citation

  • Ajid Ur Rehman & Asad Yaqub & Tanveer Ahsan & Zia-Ur-Rehman Rao, 2024. "Earnings management using classification shifting of revenues: evidence from Chinese-listed firms," Post-Print hal-04727629, HAL.
  • Handle: RePEc:hal:journl:hal-04727629
    DOI: 10.1108/JAEE-04-2022-0118
    as

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