This paper considers the level of bias observed in management disclosures of earnings forecasts and historic earnings data in Australian prospectuses. Management forecasts and naïve forecasts derived from managements’ normalised historic data are analysed. A key focus is upon the possible association between such forecast bias and differential audit services performed upon the data. Audit firm size and level of engagement are modelled against bias. The full sample revealed no overestimation bias for any of the forecast models, but underestimation was observed for elements of the management and random walk naïve forecasts. Cross-sectionally, a significant association was observed between forecast bias and audit firm size across all three forecast models. Specifically, the audit firm size variable (Non Big-5/Big-5) was inversely associated with the extent to which forecasted and normalised historic earnings data were upwardly biased. On the other hand, the level of engagement was not a significant discriminator for forecast bias. These outcomes are contrasted against others reported elsewhere in the literature and suggest a risk in generalising across contexts. The findings imply a level of ‘disclosure management’ regarding company IPO forecasts and normalised historic accounting data, with forecast overestimation and error size more extreme when the monitoring expertise and/or reputation of auditors is lower (JEL D80, G14, M41, N27).
Review of Quantitative Finance and Accounting – Springer Journals
Published: Jan 1, 2006
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