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    Audit Quality and Analyst Forecast Accuracy: The Impact of...
    research summary posted July 18, 2016 by Jennifer M Mueller-Phillips, tagged 11.0 Audit Quality and Quality Control, 11.04 Industry Experience, 14.0 Corporate Matters, 14.01 Earnings Management 
    Audit Quality and Analyst Forecast Accuracy: The Impact of Forecast Horizon and Other Modeling Choices
    Practical Implications:

    This paper contributes to research examining the determinants and impacts of audit quality by identifying the limitations of aspects of metrics employed in recent research that could have been utilized by practitioners and suggesting useful alternate metrics for investigating the impact of audit quality on the properties of analysts’ forecasts, including the usefulness of audited financial information and the prediction of future performance. 


    Wu, Y. and Wilson, M. 2016. Audit Quality and Analyst Forecast Accuracy: The Impact of Forecast Horizon and Other Modeling Choices. Auditing: A Journal of Practice and Theory 35 (2): 167-185. 

    audit quality, auditor industry specialization and analyst forecast accuracy
    Purpose of the Study:

    Many studies examine the influence of auditor characteristics on the properties of analyst forecasts of client firms’ earnings. A common argument is that audit quality affects the accuracy of analyst forecasts or closely associated metrics. However, there is considerable divergence in the posited theoretical association between audit quality and forecast accuracy and in the empirical associations reported. The majority of these studies rely exclusively on measures of forecast accuracy based on analysts’ end-of-year forecasts. The authors argue that metrics drawn from these forecasts are noisy indicators of the impact of audit quality because there are convincing reasons why superior audit quality may affect the accuracy of the metrics in either direction. Financial reports of clients of higher quality auditors may be more useful for forecasting future earnings which in turn may increase forecast accuracy; however, higher quality auditors may be more effective in disallowing client attempts to manage earnings. Thus, if an auditor provides superior quality services to their client, then it is conceivable that these competing effects will offset each other, resulting in no net impact on forecast accuracy. As a result, the authors argue that the properties of analysts’ beginning-of-year forecasts provide superior measures of any of the impacts of auditor characteristics because these forecasts are less likely to induce benchmark-beating incentives for earnings manipulation and because audited financial information has a greater relative impact on analysts’ information set at the beginning-of-year than at the end-of-year. 

    Design/Method/ Approach:

    Focusing on measures of audit firm industry specialization common to papers with competing predictions and results, the authors demonstrate the noisiness and sensitivity to model specification of test based on end-of-year forecast accuracy and show that similar tests based on beginning-of-year forecast accuracy generate predicted results that are consistent over a range of modeling approaches. 

    • The authors find that analysts’ beginning-of-year forecasts are a potentially superior proxy for auditors’ impact on the properties of analyst forecasts because the “decision usefulness” impact of an audit is at its strongest soon after those reports are released and is likely to dominate any effect on audit quality on client benchmark-beating behavior.
    • The authors also identify the importance of other modeling choices facing researchers, such as the deflation of forecast errors and controls for the endogenous selection of industry specialist auditors. 
    Audit Quality & Quality Control, Corporate Matters
    Earnings Management, Industry Expertise – Firm and Individual