4.3.1 Test of hypothesis 1
Table 3 presents results consistent with our prediction that analyst coverage is negatively associated with the propensity for firms to receive MAOs from their auditors. First we use Report (the number of analyst reports issued for firm i in year t-1) as a proxy for analyst coverage and regress MAO in year t on Report and the control variables. The coefficient of Report is negative and significant (-0.0793, t= -2.62), suggesting that firms are less likely to receive MAOs when more analyst reports were issued in the previous year. When we compute the marginal effect, a one standard deviation increase in Report (12.218) leads to 3.15% decrease in the incidence of MAO, implying the economic significance of our finding. Next we replace Report with Analyst (number of analyst following firm i in year t-1) and repeat the analysis. The negative and significant coefficient of Analyst (-0.1527, t= -3.76) indicates that firms are less likely to experience MAOs if they are followed by more analysts in the previous year. Finally we substitute Analyst with Broker (number of brokerage house that issue report for firm i in year t-1) and repeat the regression. We find the coefficient of Broker is negative and significant (-0.1765, t= -4.12), confirming that more brokerage houses
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following a firm reduces the propensity that MAOs would be issued.
Among the control variables, the coefficient of ST is positive and significant across the models, consistent with the conjecture that firms reporting consecutive losses are more likely to manipulate earnings to avoid being delisted, which results in the issuance of a MAO. The coefficient of size is negative and significant, suggesting that large firms are less likely to receive MAOs. The coefficient of SEOF is significantly negative, indicating that firms proposing seasonal offerings are less likely to receive MAOs. The coefficients of Fund and OwnCon are negative and significant across the models, indicating that firms with high ownership by mutual funds and high ownership concentration are less likely to receive MAO.
It is worth noting that the IFRS dummy variable is positively significant, which suggests more MAOs after accounting standards in China converge toward IFRS. This may be attributed to the increase of managerial discretionary influence in financial reporting under principles-based accounting standards such as IFRS (Agoglia et al., 2011; Ahmed et al., 2013). Regarding the governance variables, the coefficients of Indr are negative (although
marginally significant) across the models, which implies that an independent board is more effective in constraining earnings management and therefore contributes to high financial reporting quality. The findings are consistent with the view that independent directors have incentives to be effective monitors to maintain their reputation (Fama and Jensen, 1983). Overall we find supporting evidence for hypothesis 1.
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4.3.2 Test of hypothesis 2
To test hypothesis 2 we first regress MAO on NSOE and other control variables (excluding analyst coverage) in regression I. Then we add Coverage and interaction between Coverage and NSOE. We use Report, Analyst and Broker as proxies for analyst coverage in regression
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II, III and IV. The results are presented in Table 4. In regression I the positive and significant coefficient of NSOE (0.36, t= 3.95) indicates that NSOEs are more likely to receive MAOs. This is consistent with the findings documented in Wang et al. (2008) that state-controlled firms are economically protected by central or local government, so auditors are less likely to issue MAOs for these firms. In regression II the coefficient of the interaction term between NSOE and analyst coverage is negative and significant (-0.1225, t= -1.93), which suggests that analyst monitoring of NSOEs (in terms of number of analyst reports issued) plays a more significant effect in decreasing the propensity that these firm would receive MAO.13 When we compute the marginal effect, a one standard deviation increase in Report (12.218) reduces the incidence of MAOs among NSOEs by 4.73%, confirming the economic significance of our results. It is plausible that NSOEs are more susceptible to the external monitoring of analysts, because they have to maintain their good reputations to access the capital market at a lower cost. Consequently they are more likely to react to the issues raised in the analyst reports, leading to improved financial reporting quality and reduced propensity of receiving a MAO. In contrast, SOEs are under less pressure from analyst monitoring because they can enjoy the preferential treatment from the central and local government. The results in
regression III are consistent with those in regression II, as the coefficient of the interaction is negative and significant (-0.1837, t= -2.22). In regression IV we use Broker as the proxy for analyst coverage and repeat the analysis. In line with results based on Report and Analyst, we find that the coefficient of NSOE (interaction) is significant and positive (negative). Our results thus support hypothesis 2.
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4.3.3 Results on the test of hypothesis 3
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To test hypothesis 3 we first regress MAO on ST and other control variables (excluding analyst coverage) in regression I. The positive and significant coefficient of ST is consistent with the conjecture that firms with consecutive losses are more likely to engage in earnings management to avoid compulsory delisting, which in turn results in high propensity of receiving MAOs. Next we include analyst coverage and an interaction term between ST and analyst coverage in the regression. In regression II we use Report as the first proxy for analyst coverage. The coefficients of Report and interaction are negative and significant (- 0.08, t=-2.70; -0.3674, t=-2.18), suggesting that analyst coverage reduces the propensity that firms would receive MAO, and the effect is more pronounced for firms experiencing consecutive losses. The result of the marginal effect shows that a one standard deviation increase in Report (12.218) reduces the incidence of MAOs among ST firms by 14.46%, indicating the economic significance of our result. It is plausible that due to their sensitive
and rather urgent status on the market ST firms attract more intense attention from analysts, who are able to utilize their expertise to identify and disclose the earnings management practice of ST firms. Consequently, ST firms have to take corrective action, which results in improved reporting quality and reduced propensity of receiving MAOs. Consistent with prior findings that analysts are more effective in detecting corporate fraud (Dyck et al., 2010), our results suggest that analysts play a disciplinary role in monitoring the financial reporting practice of ST firms. Next, we replace Report with Analyst (Broker) in regression III (IV), and get qualitatively consistent results. Taken together, our empirical evidence support hypothesis 3 that analyst coverage plays a more significant role in reducing the propensity that ST firms would receive MAOs from their auditors.
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5 Robustness checks
We perform a battery of sensitivity tests to check the robustness of our main findings.