Long-Run Evolution and Industry Divergence of Real Activities Earnings Management in Chinese A-Share Listed Firms: Evidence From 58,661 Firm-Year Observations, 1998-2025
DOI:
https://doi.org/10.65150/EP-jefrr/V2E7/2026-02Keywords:
real activities earnings management, earnings quality, listed firms, industry heterogeneity, firm fixed effects, Chinese A-sharesAbstract
Real activities earnings management affects reported earnings through operating decisions such as sales policies, production scheduling and discretionary expenditure. Compared with purely accrual-based adjustments, it is less visible in accounting entries and more likely to alter future cash flows, inventory risk and long-term investment. Using a real earnings management dataset for Chinese A-share listed firms from 1998 to 2025, this study examines the long-run evolution, industry divergence and firm-level persistence of REM based on 58,661 firm-year observations, 5,288 listed firms and 74 detailed industries. The evidence shows that Abs_REM reached its highest level in 2007-2012 and subsequently declined, whereas the median of REM_Total and the share of positive REM continued to rise in recent years. Real activity deviations are stronger in internet services, retail, pharmaceuticals, real estate, wholesale and software services. The explanatory power of firm-level grouping is much higher than that of year or industry grouping, and REM_Total, Abs_REM, REM1 and REM2 all display significant first-order persistence. The contribution of this paper is threefold. First, it provides a long-window measurement of REM in the A-share market over nearly three decades, complementing short-horizon event studies. Second, under a unified measurement design, it distinguishes REM direction, absolute intensity, industry divergence and firm persistence, thereby reducing the interpretive bias created by a single composite indicator. Third, it offers replicable evidence for regulatory enquiries, audit risk assessment and investor screening of earnings-quality risk embedded in operating activities.
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Copyright (c) 2026 Dr. Gan Weixiang, Shashi Kant Gupta, Dr. Xiao Mengfei, Liu Jialin (Author)
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