This investigation reveals sectoral differences in real earnings management among industries, suggesting that market competition influences manipulation practices.
This paper investigates real earnings management (REM) practices in public non-financial companies listed on the Warsaw Stock Exchange (WSE) from 2014 to 2023, focusing on sectoral differences and the influence of market competition. REM, defined as deviations from normal business operations aimed at manipulating reported earnings, can distort financial information and harm long-term firm value. This study contributes to the existing literature in two key ways. First, it examines variations in abnormal levels of production costs, sales, and discretionary expenditures – REM proxies based on Roychowdhury’s methodology – across sectors classified according to the WSE’s industry framework. This sectoral classification, reflecting economic activities and client types, allows for identifying industries with distinct REM patterns and uncovering hidden relationships in earnings manipulation across sectors. Second, the research evaluates the impact of industry-specific characteristics on REM using concentration measures such as the Herfindahl-Hirschman Index (HHI) and the entropy ratio (E). Our sample of 218 companies shows significant sectoral variation in REM, with consumer goods firms exhibiting the highest level of earnings manipulation and finance sector firms the lowest. We find significant negative associations between market competition and certain REM proxies – specifically, abnormal production costs and discretionary expenditures – while aggregate REM measures do not show similar relationships. These findings challenge prior studies that suggest greater REM activity in less competitive industries. Limitations include sample restrictions to firms with consistent reporting and at least ten years of trading on the WSE, covering approximately half of the market. Future research incorporating variables such as ownership structure and corporate governance could enhance model fit. Overall, this study offers valuable insights for investors, regulators, academics, and financial statement users who rely on high-quality earnings information to distinguish economically efficient firms.
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Michał Comporek (2025) studied this question.
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