The impact of IFRS complexity on analyst forecast properties: The moderating role of high quality audit
研究了IFRS复杂性对分析师预测误差、分散度和修正的影响，发现高质量审计能缓解复杂性对预测误差的不利影响，但对分散度和修正无显著调节作用。
Abstract This paper examines the impact of International Financial Reporting Standards (hereafter IFRS) complexity on analyst forecast properties including forecast errors, forecast dispersion and forecast revision. Because high‐quality audit is likely to moderate the effect of complexity on analyst forecast properties, Industry Specialization (ISP) as a proxy for high quality audit is introduced as a moderating variable in this paper. The complexity of individual IFRS standards is measured based on IFRS reconciliation statements capturing the adjustments on accounts affected by the changes in accounting standards. We analyze 322 companies listed on the Australian Securities Exchange (ASX). Our results suggest that all IFRS standards are not equally complex. A few standards are relatively more complex. These standards have a positive effect on analyst forecast errors, forecast dispersion and forecast revision. In addition, we find that high quality audit (proxied by city‐level industry specialist auditors) can mitigate the adverse impact of IFRS complexity on analyst forecast errors but not on forecast dispersion and revision. More interestingly, the mitigating effect of high quality audit is restricted to only a group of companies exposed to a higher level of aggregate IFRS complexity. The findings of our study contribute to the IFRS literature by identifying the most complex accounting standards. Secondly, this study provides an ex‐ante experiment in IFRS adoption, which can be used by adopting countries to understand the impact of IFRS on the analyst forecasts. Finally, our study helps regulators to understand the effects of the complexity of accounting standards on users of financial statements.