We examine equation 6 where we include extent timing

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Unformatted text preview: essarily errors in the financial statements. The auditor collected all the differences identified during the audit regardless of magnitude to consider the potential aggregate effect of all identified differences.15 These were the actual differences the auditor discussed with client management. When DIFF is a dependent variable, we expect the MI coefficient to be negative, suggesting that a weak MI assessment is associated with more audit differences. Equation (5) examines the impact of MI on the probability of discovering current period errors without consideration of EXTENT, TIMING, or PERSUASIVENESS. To better assess the incremental impact of MI on discovering error, we control for MI’s influence on audit planning. We examine Equation (6) where we include EXTENT, TIMING, or PERSUASIVENESS in the model. RESULTS Descriptive Statistics Table 1 provides descriptive statistics on our dependent and independent variables. Mean MI is 1.40 and only 9 (18) of the 60 firms have MI scores of 0 (1). Hence, the median firm in the sample has high management integrity and, on average, auditors assessed client integrity as moderate. This result is consistent with findings from the client acceptance literature that suggests auditors screen out very high-risk clients (Johnstone and Bedard 2003). The mean RMM of 1.50 suggests that auditors on average assessed the risk of material misstatement as low. The mean of PERSUASIVENESS (1.62) suggests that on average auditors sought information from a mix of internal and external sources, but relied more heavily on internal sources. The mean of TIMING (79.67) suggests on average a majority of the procedures were performed at year-end. Auditors identified an average of $180,973 in audit differences, but over two-thirds of the clients (69 percent) did not have any audit differences. The frequency of differences is consistent with prior research (for a summary see Eilifsen and Messier [2000]). Table 2 presents the correlation between all the variab...
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