Summary:
In 2001, the China Securities Regulatory Commission (CSRC) officially cancelled the Particular Transfer (PT) of stocks and announced that listed companies reporting losses for three consecutive years will have their listings suspended within 10 days of the announcement of the third annual report.In the same year, the CSRC required listed companies that want to issue new stocks to meet the requirement that the average of the weighted average return on equity (ROE) of the previous three fiscal years must not be less than 6%.Given these regulations, listed firms are likely to attempt to manage their earnings to avoid delisting or to satisfy secondary public offering (SPO) conditions.In this paper, we use a bunching design method to estimate the earnings management frequency (how many companies manage their earnings) and the earnings management magnitude (how many companies' earnings are manipulated) from the distribution of weighted average ROE of listed companies for the 2002-2017 period using two thresholds: 0% (delisting policy) and 6% (SPO conditions).The results shed light on whether the scale of earnings management is economically significant. Although many papers focus on the estimation of earnings management, they do not solve the problems associated with estimations in the case of multiple thresholds.Furthermore, the estimation models used have too many assumptions.Domestic research on the estimation of the earnings management of listed companies has stagnated over the last 10 years.However, many policy changes have taken place during this period, such as allowing listed companies to conduct non-public secondary issuance and the strengthening of financial supervision.Therefore, we use a new methodology—bunching design￣￣—to determine whether the previous findings still hold after such policy changes and to simultaneously estimate the frequency of earnings management at two thresholds. In contrast to existing studies, which assume the specific form of the ROE density function, we use a polynomial function and other control variables to approximate the ROE density function beyond the threshold intervals.Estimated parameters in the approximation are used to estimate counterfactual ROE density within the threshold intervals.The difference between the counterfactual ROE density and the real ROE density yields an estimation of earnings management that represents how many firms manipulate their ROE from the left side of the threshold to the right side. Using a bunching design, our estimations of the frequency and magnitude of earnings management show that about 3.184% of listed companies managed their earnings to avoid reporting losses, accounting for 59.25% of firms with losses if no earnings management was conducted.The counterfactual estimations suggest that about 93% of firms with an ROE within-1.5-0% engaged in earnings management.The firms that conducted earnings management increased their ROE by 2.115 percentage points on average.Although only 0.28% of listed companies managed their earnings to satisfy SPO conditions, these firms account for 58.13% of all successful SPOs.The counterfactual estimations suggest that firms with an ROE within 5￣-6% were most likely to engage in earnings management. We also analyze the heterogeneity of earnings management.First, we estimate the frequency and magnitude of earnings management year-by-year.During the 2002-2015 period, the earnings management incentives for listed companies to avoid delisting were relatively stable, but our estimations are not significant after 2016 as the CSRC strengthened its financial supervision.The proportion of companies that managed their earnings to satisfy SPO conditions was the highest in the 2002-2004 period and has fallen sharply since then, which may be attributable to the deregulation of non-public secondary issuance.Furthermore, the frequency of earnings management for special treated (ST) companies is 3.62 times that of non-ST companies.High-leverage companies have stronger earnings management incentives to avoid delisting and satisfy SPO conditions.Finally, industry analysis suggests that the manufacturing industry has a high incidence of earnings management to avoid delisting, and that the agriculture industry has the largest magnitude of earnings management at the 0% threshold. The conclusions of this paper have practical implications.From the macro perspective, the intention of using accounting indicators as a hard constraint to supervise listed companies is to eliminate poor-performing firms from the stock market and enable strong-performing companies to refinance.However, this policy has unintentionally strengthened firms' incentives to manage earnings to avoid delisting or having to issue additional shares.If the regulatory agency requires accounting indicators as a hard constraint of supervision, strict earnings management supervision should be supplemented to achieve the desired effect.From the micro perspective, we estimate the aspect of earnings that is most likely to be falsely reported.Regulators should focus their review and supervision efforts on these listed companies.
张红, 汪小圈. 避免亏损与公开增发盈余管理的识别与估计:来自聚束设计的实证证据[J]. 金融研究, 2021, 490(4): 187-206.
ZHANG Hong, WANG Xiaoquan. Identification and Estimation of Earnings Management to Avoid Delisting and Satisfy SPO Conditions: Evidence from a Bunching Design Study. Journal of Financial Research, 2021, 490(4): 187-206.
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