Financial estimates against investors’ preferences:anchoring, denial and spillover effects

This experimental study investigates how the characteristics of an estimate in a sensitivity disclosure and the level of threat it presents to investors' preferences interact to influence investors’ risk judgments. Firstly, I predict and find that variation in an estimate affects not only investors’ judgment on a related issue but also their future judgments on an unrelated issue. Secondly, I predict and find that investors are more sensitive to variations in an estimate when information contained in the estimate presents less threat to their preferred conclusions than when it presents greater threat. Finally, I predict and find that investors perceive more uncertainty regarding the association between the disclosed risk factor and the estimated financial reporting item in the estimate when the information presents greater threat

Discretion in accounting for pensions under IAS 19: using the ‘magic telescope’?

We use a panel data set of UK-listed companies over the period 2005 to 2009 to analyse the actuarial assumptions used to value pension plan liabilities under IAS 19. The valuation process requires companies to make assumptions about financial and demographic variables, notably discount rate, price inflation, salary inflation, and mortality/life expectancy of plan members/beneficiaries. We use regression analysis to analyse the relationships between these key assumptions (except mortality, where disclosures are limited) and company-specific factors such as the pension plan funding position and duration of pension liabilities. We find evidence of selective ‘management’ of the three assumptions investigated, although the nature of this appears to differ from the findings of US authors. We conclude that IAS 19 does not prevent the use of managerial discretion, particularly by companies whose pension plan funding positions are weak, thereby reducing the representational faithfulness of the reported pension figures. We also highlight that the degree of discretion used reflects the extent to which IAS 19 defines how the assumptions are to be determined. We therefore suggest that companies should be encouraged to justify more explicitly their choice of assumptions