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Creative accounting for pensions. Why discretion may not be good for financial reporting.

Mark Billings, Christopher O’Brien, Margaret Woods

CRIS Discussion Paper Series – 2009.II

Creative accounting for pensions. Why discretion may not be good for financial reporting.

MARK BILLINGS* CHRISTOPHER O‟BRIEN MARGARET WOODS Nottingham University Business School, Jubilee Campus, Wollaton Road, Nottingham, NG8 1BB

* Corresponding author. Contact details: [email protected]

We would like to thank Gemma Cooney, Lynsey Jefferies and James McKay for their assistance in compiling the data used in this paper. We would also like to acknowledge helpful contributions from Gareth Thomas and participants at the 2008 Financial Reporting and Business Communication Conference in Cardiff.

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Creative accounting for pensions. Why discretion may not be good for financial reporting.

ABSTRACT

Accounting standard setters worldwide are reviewing the financial reporting rules on pensions. The IASB, FASB and ASB require the funded status of a defined benefit pension plan to be reflected on the sponsoring company‟s balance sheet. Funded status equals the fair value of the fund‟s assets less its associated liabilities. Valuation of the assets presents few problems, but valuation of pension liabilities is less straightforward and requires a number of assumptions. Using data on 239 UK listed companies, this paper analyses the assumptions used to value pension fund liabilities under FRS 17 and IAS 19. We analyse the relationships between these assumptions and factors such as pension scheme funding position, company status, and audit firm. We contribute to the academic literature by standardising the liability valuations to eliminate bias arising from the underlying assumptions. We find evidence of selective “management” of two core assumptions which underpin the liability value. We conclude that companies exercise discretion to manage liability values downwards, thereby reducing the representational faithfulness of the reported pension figures. We suggest that discretion could be constrained by introducing tighter parameters on both salary growth rates and the definition of the high grade bond used to establish the discount rate. KEYWORDS: Pensions, IAS 19, liability valuation, actuarial assumptions, UK

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1. Introduction In recent years, accounting standard setting bodies around the world have been reviewing the rules on the financial reporting of pensions. The desire for reform arose from an acknowledgement that reporting practice failed to „communicate the funded status of … plans in a complete and understandable way‟ (FASB, 2006: 4). Indeed it has even been suggested that global concerns about present accounting standards for pensions are sufficiently significant that „some consider their deficiencies are so great as to pose a risk to confidence in financial reporting‟ (EFRAG, 2008: 19). The International Accounting Standards Board (IASB) and the US Financial Accounting Standards Board (FASB) have been working together since 2006 on a fundamental review of the pension accounting rules, aimed at the publication of a single common accounting standard by 2011. At the same time, the Accounting Standards Board (ASB) in the UK has led a project within the European Financial Reporting Advisory Group (EFRAG) on the issue of how to account for pensions. The IASB, FASB and ASB all now agree that it should be mandatory for the sponsoring company‟s balance sheet to recognise the funded status of a defined benefit pension scheme (DBPS). Funded status is measured as the difference between the fair value of the fund‟s assets and the related pension obligations. The current view contrasts with that of previous standards such as the UK‟s SSAP 24 (ASC, 1988) which simply required the sponsoring employer to record the cost of the pension scheme in the income statement, with no corresponding requirement to recognise a funding deficit in the balance sheet. The compression of the funded status of a DBPS into a single balance sheet figure is, however, fraught with difficulties because of the assumptions that underpin the fund valuation process. Indeed Blake et al (2008: 5) suggest that such compression creates an „illusion of certainty‟. They argue that the funded status figure is uncertain because accounting for defined benefit pension funds is complex and set within a context of long time horizons. Pension fund assets are valued using arm‟s length market values but the valuation of liabilities, which is the focus of this paper, is more problematic. The value (as currently reported) is dependent upon four key assumptions about rates of future price inflation, salary inflation, mortality rates/life expectancy and the discount rate used to convert future pension obligations to a present value. Changes in any, or all, of these assumptions will result in a change in the resulting funded status. The challenges in valuing DBPS liabilities are deemed by Blake et al (2008: 37) to be so severe that “uncertainty is the distinguishing characteristic…. uncertainty as to how much pay is deferred; uncertainty as to the amounts and timing of the future pension payments; uncertainty as to the discount rate to be used to calculate their present value; and uncertainty as to the future cash flows of the plan assets that will be used to settle those liabilities.” It is this uncertainty, and the potential resulting motivation that it provides for manipulation of the funded status, that stimulated the research reported in this paper. Senior accounting practitioners have expressed concerns over the problems of interpretation and the associated scope for the exercise of managerial discretion in the selection of the core assumptions that underpin the pension liability valuation. Collier (2004: 18, para. 7.4) suggested that „... the subjective judgements required under ...

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FRS 17 ... were widely cited as providing scope for earnings management ...‟ This was reinforced by an observation attributed to the Chief Executive of the UK‟s Financial Reporting Council that the scope for discretion in the selection of assumptions used in pension fund valuations facilitates the use of „the magic telescope ... to make very big things appear very small‟ (Williams, 2005: 18). This paper outlines the accounting theories which explain why managers may be motivated to apply a magic telescope approach to DBPS liability valuation, and, using a large sample of FTSE 350 companies, we investigate the level of variation in the financial assumptions used in arriving at the DBPS liability valuations. Investigation of mortality assumptions is outside the scope of this paper as over the period of the study their disclosure was discretionary and not compulsory. We standardise the data by developing a common measure of liabilities which is then used to generate a measure for a fund‟s common financial strength. Our research highlights the potential impact of variations in assumptions upon a pension fund‟s reported financial status. We also find that firms with pension funds that have low common financial strength tend to use assumptions that result in a lower liability valuation, and we therefore conclude that there is preliminary evidence of liability values being actively managed downwards by some firms. This has important implications for regulators who wish to eliminate earnings management and encourage more transparent and comparable reporting practices. The research findings are important because, as Zeff (1978) observed, accounting practice can have economic consequences. In the case of pension funds, the consequences may impact upon the sponsoring companies, their employees and investors and also the general population. Such widespread economic consequences warrant academic comment on current practice in accounting for pensions. In extremis, reporting companies may face bankruptcy as a result of pension fund obligations. For example, in the USA, Bethlehem Steel filed for Chapter 11 bankruptcy and cited its $1.9 billion pension fund deficit as a major cause of its demise (The Actuary, 2002). At the very least, there is evidence that the associated financial obligations affect credit ratings. In 2003 Standard and Poor‟s placed ten companies on CreditWatch based on their pension liabilities (Mercer.com, 2005). More recently, there has been further comment from experts in the technical and financial press that large DBPS deficits can create a potential “poison pill” in both merger and acquisition (Kumar, 2006) and restructuring transactions (Financial Times, 2008a). Amidst the continuing turmoil in financial markets, and a collapse in the fair value of many DBPS assets, there is a further risk that the scheme deficits will grow relative to the market capitalisation of the sponsoring companies, and threaten their going concern status. Auditors therefore need to be conscious of the potentially greater temptation for preparers to “manage” the assumptions that determine liability values. A pension deficit can lead to the closure of a DBPS, with potentially costly economic consequences for scheme members. Lane Clark and Peacock (2006) reported that almost half of the UK‟s FTSE 100 companies had closed their DBPS to new members. For those companies still operating DBPS schemes, the falling stock markets of 2007 and 2008 have raised the extent of pension scheme under funding to a point where the Pensions Regulator estimates that 86% of all UK final salary plans

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have shortfalls (Financial Times, 2008b). The shortfalls are growing so rapidly that closures of schemes in deficit could threaten to swamp the Pension Protection Fund (PPF) set up by the government to guarantee the retirement funds of millions of workers (Financial Times, 2008b). Investors are another stakeholder group affected by deficits because of their impact on the value of equity. Aisbitt (2006) found that the transfer to IFRS rules on retirement benefit obligations reduced the value of equity by an average of 15.5%. Similarly, in a US context, Grant et al (2007) estimated that the average equity value for S & P 100 companies would decline by $2.2 billion when FAS 158 became effective, and the information on the funded status of the pension scheme moved from the footnotes onto the balance sheet. Our paper contributes to the academic literature in a number of ways. Firstly, our study is novel in providing evidence on UK reporting practice, and thus addresses the literature gap identified by Glaum (2008: 3) that „almost all existing studies on pensions accounting are based on US accounting and capital-market data ...‟ Secondly, we add to the literature by adjusting the reported figures for scheme liabilities to derive a standardised measure of common financial strength, which improves cross-company comparability and thus increases the reliability of the findings. Using this measure, we find that firms with weak pension schemes select actuarial assumptions which lower the liability valuation. Our paper is therefore consistent with US evidence which indicates that managers exercise discretion over actuarial assumptions in an opportunistic way (Glaum, 2008). Lastly, the paper updates the existing literature by analysing reporting practice under both FRS 17 and IAS 19. The remainder of the paper is structured as follows. Section 2 outlines the theoretical case for subjective selection of core actuarial assumptions and academic evidence on the manipulation of liability values. Section 3 provides the regulatory background on accounting for pensions, paying particular attention to the extent of discretion available under current accounting regulations. Section 4 sets out the hypotheses we derive and test, based on the existing literature. Section 5 describes the data set, and explains how we derive our common measure of DBPS financial strength, and section 6 discusses the results. The paper concludes with a consideration of the implications of our findings for accounting regulators, and a number of recommendations for future research. 2. The Manipulation of Pension Accounting Numbers – Accounting theory and academic evidence 2.1 Accounting Theory As already indicated, the calculation of a present value for the future pension liabilities of a company operating a DBPS requires assumptions to be made regarding future price inflation, salary inflation, mortality rates (or life expectancy) and the discount rate. Variations in any or all of these assumptions will have an impact upon the liability valuation that is recognised in the balance sheet.

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The management compensation hypothesis within Positive Accounting Theory (Watts and Zimmermann, 1990) assumes that management remuneration schemes linked to financial performance create incentives to manage the relevant accounting numbers. In the context of pensions accounting, managers may therefore have an incentive to exercise bias in the selection of the actuarial assumptions if they believe that higher pension liabilities (or funding deficits) will be negatively received by the capital markets and subsequently affect them personally, via reduced remuneration. A large DBPS deficit may require additional contributions from the sponsoring company, reducing future cash flows as well as potentially lowering income, management remuneration and also share prices. In principle, therefore, managers may have an incentive to select actuarial assumptions which reduce reported pension liabilities. The incentive for such opportunistic behaviour is further increased if management compensation is linked to the market value of the company, and managers believe that market value is directly affected by the reported funding position. Positive Accounting Theory also suggests that debt contracts may influence management‟s choice of accounting policies. Watts and Zimmermann (1990) use the debt: equity hypothesis to argue that as the debt: equity ratio increases, managers are likely to use accounting methods that will minimise the risk of breaching debt covenants and incurring default costs. Debt covenants which set minimum total asset to total liability ratios are increasingly common in the loan contracts issued by banks. Additionally, analysts and rating agencies are now treating pension liabilities as long term corporate debt. This approach is consistent with the financial management literature, which integrates surplus pension assets or unfunded liabilities with the sponsoring company‟s assets and liabilities (Carroll and Niehaus,1998). Consequently, pension liabilities may lead to a company being in breach of a debt covenant and concerns about such a risk may therefore affect the selection of actuarial assumptions and the resulting pension liability valuation. Remuneration systems, stock market reaction to pension deficits and the desire to avoid debt covenant default costs therefore all serve as possible motivations for managers to reduce the reported size of the pension deficit. In the UK, these incentives are further reinforced by the levy system introduced in 2006-7 for the Pension Protection Fund (PPF). The PPF imposes a risk based levy on companies operating pension schemes, the receipts from which are used to finance compensation payments to scheme members in the case of corporate collapse. Companies with large DBPS deficits and low credit ratings incur higher levies than those with lower deficits and higher credit ratings, and therefore have a financial incentive to manage pension liabilities downwards. The attraction to managers of carefully selecting the actuarial assumptions in order to manipulate the accounting figures is further confirmed by the apparent emergence of a market for advice in this area. For example, Standard and Poor‟s currently offer an “assessment service” and Blacket Research say that „our quarterly IAS 19/FRS 17 report helps finance directors set assumptions that optimise the reporting of defined benefit pension schemes and gain external auditor approval‟ (Blacket Research website). The financial press provides some empirical evidence in support of the theoretical case for opportunistic behaviour that is presented above. For example, The Times

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(2006) drew attention to the impact of the use of over-optimistic assumptions in the valuation of the pension schemes of companies subject to private equity bids. The optimism appears to be recognition of market sensitivity to pension information. A number of take-over deals, such as Marks and Spencer, Rentokil and W.H. Smith, have been aborted because bidders withdrew partly in response to information about the expected future costs of pension liabilities. For example, in the Summer of 2004 the £940 million take-over bid by the private equity group Permira for the high street retailer W.H. Smith collapsed after the company‟s pension fund trustees failed to persuade the bidder to make a substantial cash contribution to the pension fund which had a deficit of £190 million. In similar vein, there is evidence that pension liabilities are directly impacting upon credit ratings. Downgradings of the credit ratings of General Motors, Ford and Boeing were attributed to the very large scale pension deficits reported by these industrial giants and additional evidence from the US shows that there was „a notable positive relationship between higher pension deficits and lower credit ratings amongst the Fortune 1000 companies over the three years 20022004‟ (Watson Wyatt, 2005). We therefore conclude that both Positive Accounting Theory and comment in the financial media suggest that the managers of firms with pension deficits have incentives to select assumptions which flatter the pension fund status. This hypothesis is tested later in the paper

2.2 Academic evidence of manipulation in accounting for pensions

US evidence supports the notion that managers exercise opportunistic discretion in their selection of the assumptions that underpin pension fund valuations. Blankley and Swanson (1995) studied US schemes over the period 1987-93 and found evidence that discount rate changes lagged changes in bond yields, leading to underestimation of the value of future liabilities. In similar vein Godwin (1999), found that firms with poorly-funded schemes also manipulated discount rates. Asthana (1999), in a study based on a large sample of US schemes in the period 1990-92, found that well-funded schemes applied conservative actuarial assumptions, whereas underfunded schemes used liberal or less prudent assumptions. More recently Eaton and Nofsinger (2004) observed that US public sector pension plans vary the assumptions in order to manage pension costs. These specific observations are reinforced at a more general level. A survey of the pensions accounting literature by Klumpes (2001) concluded that the adoption of SFAS 87 served to increase accounting manipulation. SFAS 87 imposed restrictions on assumptions about discount rates and the expected rates of return on plan assets, but allowed for the exercise of choice over other assumptions, including mortality, length of working life of scheme members and projected rates of salary growth. Similarly, in an overview of research in the area of pension accounting, Glaum (2008: 43) concluded that the evidence to date indicates that „managers have scope for discretion, in particular, when setting assumptions. Findings from research suggest that managers exercise this discretion in opportunistic ways.‟ Equivalent academic

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research evidence on pension reporting practice in the UK is, however, lacking and this paper seeks to fill this gap in the literature. Before reporting our findings on UK reporting practice, it is necessary to review the regulations on the selection of actuarial assumptions under the relevant UK accounting standards, FRS 17 and IAS 19. This review summarises the scope for directors to exercise discretion in their selection of values for the relevant assumptions.

3. Regulatory Background 3.1 From FRS 17 to IAS 19 The introduction of FRS 17 (ASB, 2000) began the shift towards the now internationally common requirement to recognise the net funding position of a company‟s DBPS on the balance sheet. Extended transitional arrangements meant, however, that many companies were slow to implement the new standard, and by mid-2005 only 25% of FTSE 100 companies and 19% of FTSE Mid 250 companies had adopted it in full (Company Reporting, 2005). Nonetheless, the rules required that from June 2003 onwards companies had to make FRS 17 disclosures in notes to their accounts as if the standard had been adopted in full (ASB, 2000, para. 94). From January 2005, pension reporting by listed groups in the EU was regulated by IAS 19 instead of FRS 17, and from that date on the UK‟s non-adopters of FRS 17 were forced to recognise the funding status of the company‟s pension fund on the balance sheet.

3.2. Assumptions under FRS 17 and IAS 19 The liability value is determined by four key assumptions which are selected by management on the basis of expert actuarial advice. The assumptions are described in IAS 19 (IASB, 2004, para.73) as „an entity‟s best estimates of the variables that will determine the ultimate cost of providing post-employment benefits.‟ The significance of each of the assumptions and the rules on disclosure under both FRS 17 and IAS 19 are summarised in Table 1. INSERT TABLE 1 HERE Each of the assumptions shown in Table 1 affects the reported size of the DBPS liability, but the rules on disclosure and the degree of specific guidance on the selection of assumptions varies between the two accounting standards. We therefore examine in more detail the regulations relating to each assumption. The absence of specific guidance may create the opportunity for the exercise of discretion in the selection of the relevant assumption(s). Mortality rates The disclosure of mortality assumptions is not explicitly mandatory under either IAS 19 or FRS 17, but both standards may be interpreted as requiring their disclosure on

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the grounds that they have a material impact on the valuation of liabilities. Mortality rate predictions are essential for estimating future pension payments - the longer pensioners live, the greater such liabilities will be. It is estimated that (ceteris paribus) a one year increase in employees‟ life expectancy will increase pension liabilities by three to four per cent (Blake et al, 2008). Companies rely on actuarial advisers in determining appropriate mortality rates, and commonly use a standard set of tables. Changes in life expectancy over time, however, have resulted in some companies using out-dated mortality tables which have the effect of creating a sudden increase in liability values when the mortality figures are revised. In 2005, ICI reported a pension deficit of £470 million, but added a note that this could be up to £250 million higher if mortality assumptions were adjusted to take account of known increases in longevity (Life and Pensions, 2005). There is clearly some temptation for managers to continue to use, and possibly not disclose, out of date tables if updating can result in such significant increases in liabilities. Concern that companies were not using up-to-date assumptions was expressed by the Pensions Regulator (2006), but the problem seems to be ongoing. The Accounting Standards Board (2007) recommended that firms should disclose both the mortality assumptions and the corresponding expectations of life for current and future retirees. Nonetheless, The Financial Times (2008c) reported that the Pension Regulator still estimates that 99.5 per cent of schemes are using a longevity table incompatible with scientific evidence about life expectancy at older ages. The interpretation of mortality assumptions is further complicated by the fact that mortality rates are not standard. It is known that there are important differences between the mortality of manual and non-manual workers (Donkin et al., 2002), between different geographical regions (Office for National Statistics, 2005), and also by birth cohort (Willetts, 2004). Some, but not all, firms therefore make adjustments to standard tables to reflect such factors. Consequently, variations in mortality assumptions may provide extensive scope for management of the valuation of DBPS liabilities. In summary, mortality assumptions are affected by constantly evolving predictions on longevity, combined with the unique demographic characteristics of a DBPS‟s membership. Consequently, the interpretation and comparison of mortality disclosures is extremely difficult, and it is currently impossible to assess the extent to which discretion in the selection of mortality rates is used as a tool for liability management. We therefore exclude this assumption from the empirical analysis reported in Section 6

Price inflation rate As Table 1 shows, the assumption about future price inflation is important for two reasons. Firstly, pension payments are commonly inflation-linked, although inflation adjustment may be capped under scheme rules. Secondly, it is reasonable to assume that the rate of price inflation will influence the company‟s assumed rate of salary inflation. Inflation therefore increases the cost of both current and future pension obligations.

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Both FRS 17 and IAS 19 suggest that the financial assumptions (price and salary inflation) should be based on market expectations, but the criteria for disclosure are subtly different between the two standards. FRS 17 explicitly requires disclosure, but IAS 19 requires it only if it forms the basis for future benefit increases. FRS 17 also suggests that the difference between the yields on long dated inflation-linked bonds and fixed interest bonds of a similar credit rating can be used to derive the market‟s expectation of future price inflation. If all firms adopt the FRS 17 guidance, and the yield difference is reasonably consistent, then the scope for variation in this assumption will be extremely limited. Under IAS 19, however, the variability may be greater.

Discount rate DBPS liabilities represent future cash flows and a discount rate is therefore required to derive their present value. Additionally, the extended time horizon means that even small variations in the assumed discount rate can lead to substantive changes in the present value of the liabilities. Glaum (2008) reports that researchers indicate that a 1% change in the discount rate will change the value of the liability by 15% (May et al, 2005: 1229; Gohdes & Baach, 2004: 2571). Other evidence from Bozewicz (2004) suggests that the sensitivity of the liability to a discount rate change may be even higher. Whilst recognising that the level of sensitivity is dependent upon the duration of the liability, she reports that actuaries approximate the effect by applying a formula by which a 0.5% drop in the discount rate results in an increase in the liability value of 12.36%. Conversely, a rise in the discount rate may be used to reduce the DBPS liability and variation in the rate becomes a potentially useful tool for directors wishing to manage the size of the reported liability. Perhaps in recognition of the potential significance of such sensitivity, both FRS 17 and IAS 19 require disclosure of the discount rate and offer some guidance on its selection. FRS 17 suggests that the discount rate used should match a AA corporate bond yield, whereas IAS 19 is rather less precise in requiring the rate used to equal the yield on „high quality‟ corporate bonds. In principle, these guidelines should constrain variability in assumptions, although the Pension Adviser Review found that in the fourth quarter of 2004 the assumed discount rate across all companies varied between 4.85% and 5.09% (Williams, 2005). Evidence from the USA indicates slightly greater levels of variation in reported discount rates. Grant et al (2007) found that a sample of 81 S & P 100 companies used discount rates ranging from 5.5% to 6.3% in 2004. Applying the Bozewicz (2004) evidence discussed above, these differences are sufficient to ensure material variations in the size of the associated pension liabilities. We therefore take the view that, despite guidance on external reference points, the existing accounting regulations facilitate the exercise of discretion in the selection of the discount rate and therefore provide scope for the manipulation of the liability valuation. Salary inflation rate Pension obligations increase in line with the rate of future salary growth, and so the salary inflation assumption is an important element in the liability valuation. Not surprisingly, therefore, both FRS 17 and IAS 19 require this disclosure. There

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remains, however, a general lack of guidance in accounting standards on what, if any, salary growth assumption is appropriate (ASB, 2006). Under FRS 17 the rate is expected to reflect the rate of general price inflation, but leaves scope for interpretation. Record (2006) suggests that, based on historic data, a suitable assumption would be that earnings growth exceeds price inflation by around two percentage points per year but the precise differential may be expected to vary across different sectors of the economy. Variations in assumptions may therefore not necessarily imply opportunistic selection of favourable growth rates by managements. Table 1 shows that in IAS 19 the regulations require that the assumption explicitly reflects the management‟s expectations of supply and demand in the employment market. As in FRS17, therefore, the scope for variation in reported assumptions is potentially wide. The ongoing regulatory reviews on the financial reporting of pensions have incorporated debate on whether or not salary increases should be included at all in the valuation of pension liabilities (see for example EFRAG, 2008: 39-52 for a detailed discussion of alternative viewpoints on this issue). The details of the debate are outside the scope of this paper, but it would seem that current regulatory guidance on establishing an assumption of future salary growth is very limited. The resulting flexibility in reporting practice creates scope for liability management and suggests that directors of firms in a weak financial position may have the incentive, and be tempted, to make an assumption on salary inflation which flatters the accounting figures. Summary The four assumptions discussed above interact to determine the present value of a company‟s future pension obligations, but we have noted differences in the scope for discretion in their selection. This analysis complements the accounting theory and academic evidence discussed in Section 2 and provides the framework for the following hypotheses.

4. Hypotheses Hypothesis 1: Firms’ assumptions regarding the rate of price inflation, rate of salary inflation and discount rate are positively correlated. The rationale is that these factors are inter-linked and influenced by economic conditions. If price inflation is high, then we would expect salary inflation and the discount rate also to be high. This interpretation is reflected in the accounting standards, which require these assumptions to be compatible. Hypothesis 2: Salary inflation assumptions vary more widely between companies than assumptions about price inflation or the discount rate.

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As argued in Section 3, the accounting regulations give external reference points for assumptions of both the price inflation rate and the discount rate, whereas the rate of salary inflation assumption offers greater scope for flexibility .

Hypothesis 3: The variability in assumptions is greater for firms in the FTSE 250 compared with the FTSE 100. The rationale for this is the political cost hypothesis. The larger firms in the FTSE 100 are higher-profile than those in the FTSE 250 and their results will be given greater attention. To avoid additional scrutiny the larger firms will not use financial assumptions substantially different from the peer average. Hypothesis 4: The assumptions are influenced by the financial strength of the pension scheme, and by the auditor. This hypothesis tests for whether financial weakness of the DBPS leads to increased management of the liability value through variations in the underlying financial assumptions. It also tests for possible auditor bias. As pensions accounting under FRS 17/IAS 19 is still relatively new, individual firms of auditors may hold different views on appropriate values for any/all of the financial assumptions.

5. Data and the common financial strength measure 5.1 Data set The data set comprises for the UK DBPS liabilities of companies in the FTSE 350 at 28 February 2006 (FTSE, 2006). A total of 111 firms were excluded from the sample because of their specific characteristics, namely: investment or property trusts; those not reporting a UKDBPS; firms for which the relevant data are not provided due to restructuring, and four firms that do not report the assumed rate of salary inflation and discount rate. The final sample therefore totalled 239 firms, of which 90 were in the FTSE 100 and 149 in the FTSE 250. Using the 2005 financial statements we analyse the IAS 19 or FRS 17 disclosures for 2005 and 2004, focusing on the assumptions for price inflation, salary inflation and discount rates. The 2005 financial statements are selected because they are the first which definitely contain these disclosures. Where a range of figures for an assumption are reported, we have taken the mid-point. This approach mirrors that used by a leading firm of consulting actuaries (Lane Clark and Peacock, 2006). The deficit is reported in relation to funded liabilities only and calculated as the excess of liabilities over assets. Firm auditors are as shown in the 2005 accounts. The Big Four auditors involved are: PWC (92 firms), KPMG (55), Deloitte (51) and Ernst & Young (40). In only one case was a non-Big Four audit firm involved (RSM Robson Rhodes).

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5.2 Standardising data for financial strength The creation of a measure of „common financial strength‟ (CFS) is a significant addition to the existing literature in which comparisons of assumptions are based simply on the information reported in firms‟ accounts on the assets and liabilities of their pension schemes. The reported financial strength (RFS) of a firm‟s pension obligations is the ratio of its DBPS assets to its DBPS liabilities. The use of fair value ensures that pension assets are measured on a common basis. As already indicated, however, the RFS reflects the inflation, salary inflation and discount rate assumptions that the firms have made in valuing their pension liabilities, and so RFS is “distorted” by this self- selection process. The CFS adjustment is important because it eradicates the impact of variations in assumptions from the liability measure. This then allows us to test whether firms with a relatively low CFS choose different assumptions from firms with a high CFS. The reported liability figure for each firm is adjusted to a common measure of liabilities in two steps. The first step involves consideration of the effect on a scheme‟s calculated liabilities of using different discount rates. As indicated in Section 3, Glaum (2008) suggests that a 1% change in the discount rate results in a 15% change in the liability value, and Bozewicz (2004) provides a rule of thumb that translates into a change of 24.72% per 1% move in the discount rate. Both of these estimates are, however, based on non-UK data, where life expectancies, workforce composition and market rates of return may lead to different results. Record (2006) examined data for UK public sector schemes and found that liabilities change by an average of 18% for each percentage point change in the discount rate. This is almost mid-way between Glaum (2008) and Bozewicz (2004) and we use this adjustment in our analysis by correcting the liability by 18% for each percentage point difference between the reported discount rate and the average for all firms with the same balance sheet date. Pension liabilities also need adjusting for differences in assumed rates of salary inflation. To establish the adjustment that needs to be made, we construct a simplified model of an occupational pension scheme. Assume a scheme where employees begin pensionable service at age 25, and receive a cash sum at age 65 equal to 1/60th of their final salary for each year of pensionable service. We assume that there is one employee at each age from 25 to 55, 0.95 at age 56, decreasing linearly to 0.50 at age 65. We assume that the pensionable service for the 25-year-olds is 0, increasing by 0.4 years for each year of age, so that 65-year-olds have pensionable service of 16 years. We assume that the 25-year-old has a salary of £15,000 and the average salary increases by 2% year on year, so that the 65-year-old has a salary of £33,121. The firm‟s total pension liability is calculated as the sum of the discounted value of expected cash sums: Σ e. S. (1 + s)^(65-x)/(1 + i)^(65-x) x

where e = no. of employees at age x S = current salary

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s = assumed future salary growth i = discount rate Table 2 shows the calculated pension liability on various bases.

INSERT TABLE 2 HERE

For any given discount rate, Table 2 shows that that the benefits increase in value by approximately 12% for every one percentage point rise in the assumed rate of salary growth. This adjustment requires further refinement, however, to accommodate for the ratio of active to non-active members of a scheme, as only the former accrue salary-related benefit increases. There is evidence that in public sector schemes the liabilities in respect of active members are about 50% of the total, although this proportion would be increased if alternative future assumptions were made (Record, 2006). If we were to assume that 50% of scheme liabilities were in respect of active members, this would imply that the 12% sensitivity factor should reduce to 6%. There may also be differences in the ratio of active to non-active members in private sector, as opposed to public sector schemes. In recognition of the fact that many private sector schemes have now been closed to new entrants and also shifted towards average salary rather than final salary based benefits we have therefore made a further (ad hoc) adjustment by reducing the sensitivity factor to 4%. We therefore adjust the reported liabilities by 4% for each percentage point difference in the assumed rate of salary inflation relative to the average. Most of the inflation effect is incorporated in the salary increase assumption. There is a separate effect from pension increases resulting from links between payments and price inflation, but as we do not know what scheme rules say about such increases we cannot adjust for this.

6. Results and discussion 6.1 Summary of assumptions Table 3 provides descriptive data on the price inflation, salary inflation and discount rate assumptions observed across the sample. INSERT TABLE 3 HERE The data show that there are ranges of values for all three assumptions, with the greatest spread relating to the assumed rates of salary increase. The extent of variation in each assumption is discussed in more depth later in this section, but these statistics indicate a lack of uniformity and hence the possibility of some selectivity on the part of managers. The data are consistent with the descriptive statistics on the range of discount rates and salary growth rates reported by Byrne et al (2007), who did not report price inflation statistics, and the even greater variation in salary growth assumptions in the USA reported by Grant et al (2007).

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There is evidence of a marked reduction in the discount rate from 5.43% to 5.02% between 2004 and 2005 and the difference between the two years is significant (p = 0.0000). Simultaneously, the discount rate net of salary increases fell from an average of 1.27% to 0.91% p.a. and this shift is also significant (p = 0.0000). In contrast, the differences from 2004 to 2005 in price inflation and salary inflation are not significant at the 10% level.

6.2 Results Hypothesis 1: Firms’ assumptions regarding the rate of price inflation, rate of salary inflation and discount rate are positively correlated. Table 4 shows the correlation coefficients, together with the p-value and number of observations. A p-value of under 0.05 indicates a significant correlation at the 5% level. INSERT TABLE 4 HERE

In both 2004 and 2005 there is clearly a significant correlation between the assumptions for price inflation and salary inflation and also between price inflation and the discount rate. This is consistent with the hypothesis. We do not, however, find a significant correlation between salary inflation and the discount rate. This suggests that whilst each of these is linked to price inflation, those links are sufficiently different to result in no significant correlation between the salary inflation assumption and the discount rate. Hypothesis 2: Hypothesis 2: Salary inflation assumptions vary more widely between companies than assumptions about price inflation or the discount rate. Table shows the means, and standard deviation values for price inflation, salary inflation and discount rate assumptions for all 239 firms for each of 2004 and 2005.

INSERT TABLE 5 HERE

We use the F-test for differences in the standard deviations (SDs) between the variables, with a hypothesis that the ratio of the SDs is less than one. The p-values are 0.0000, at both December 2004 and 2005, for differences between price inflation and salary inflation and between salary inflation and the discount rate. However, comparing the SDs of price inflation and discount rate, p = 0.6776 (December 2004) and 0.5184 (December 2005). The findings are consistent with the hypothesis, confirming greater variation in the salary inflation assumptions than the other variables.

16

Hypothesis 3: The variability in assumptions is greater for firms in the FTSE 250 compared with the FTSE 100. Table 6 sets out data on the variables for the FTSE 100 and FTSE 250 firms separately. Since the discount rate changes markedly over the period, we examine differences in the discount rate using data for December 2004 and 2005 year-ends. The p-values derive from a t-test that examines differences in means, and we find no significant differences. Further, the SDs shown do not support the hypothesis that the assumptions are more variable in the FTSE 250 than in FTSE 100 firms. We therefore find no evidence to support the hypothesis that the variations are greater in the FTSE 250 than in the FTSE 100 companies.

INSERT TABLE 6 HERE

Hypothesis 4: The actuarial assumptions are influenced by the financial strength of the pension scheme, and by the auditor. A number of regression equations are estimated. The dependent variables are:     

price inflation; salary inflation; discount rate minus the average discount rate used by firms with a balance sheet date in the same month; real salary inflation; i.e. salary inflation minus price inflation; and discount rate net of salary inflation, minus the average rate used by firms with a balance sheet date in the same month.

When analysing the discount rate, and the discount rate net of salary inflation, we have to recognise that the discount rate decreased over the two-year period of the analysis. The dependent variable is therefore the discount rate (and discount rate net of salary inflation) less the average of the relevant assumption for firms with a balance sheet date in the same month. We regress each of the dependent variables against the following explanatory variables:   

whether the firm is in the FTSE-100 at 28 February 2006. the CFS of the firms‟ pension schemes i.e. the ratio of assets to the common value of funded liabilities the firm of auditors.

In carrying out the regressions, we include dummy variables for the Big 4 auditors apart from PWC, which was the auditor to the largest number of firms. The results shown therefore indicate the coefficients for KPMG, Deloitte and Ernst & Young (effectively in comparison with PwC). Formally, the standard form of regression equation can be expressed as:

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Yi = ά +β1CFSi + β2Si + β3Ki + β4Di + β5Ei + εi Where Yi = the assumption (alternately the five assumptions set out above) for firm i CFSi = common financial strength of firm i Si = 1 if firm is in the FTSE 100, 0 otherwise Ki, Di, Ei are dummy variables which are 1 if the firm i‟s auditors are KPMG, Deloitte and Ernst & Young respectively, 0 otherwise εi is an error term We calculate t-statistics using robust standard errors (White, 1980). The results for price inflation, salary inflation, discount rate, real salary inflation and discount rate net of salary inflation are shown in Tables 7 to 11 respectively. INSERT TABLES 7, 8, 9, 10 AND 11 HERE The results show that the audit firm appears to have little or no significance in terms of creating bias in respect of any of the assumptions. This suggests that the Big Four auditors are using common points of reference in advising their clients on the appropriateness of the selected of assumptions. An alternative explanation, which we could not test due to lack of the relevant publicly available information, is that the sample firms employ the same firms of advising actuaries and it is the actuarial advice, rather than the audit advice, which is the common feature. Our results nonetheless confirm those of Byrne et al (2007) that the assumptions presented in the financial accounts cannot be attributed to the audit firm. We also find, with a high level of significance, that firms with low CFS tend to assume lower rates of salary inflation. This confirms our perception that the scope for discretion in the selection of salary growth rates provides an opportunity to reduce the reported pension liability. Simultaneously, despite the fact that the regulations appear to limit the scope for variation in the selection of the discount rate, we find that firms with low CFS tend to assume higher discount rates, which also serve to reduce the pension liability value. This again hints at a degree of opportunistic liability management. In order to explore the exercise of managerial discretion more deeply, we express our results in a different form, by categorising those firms reporting to a December 2005 balance sheet date as either high (above average) or low (below average) CFS. We then use t-tests to establish whether the means of each of the price inflation, salary inflation, discount rate, real salary growth inflation and the discount rate net of the salary inflation assumptions differ between the high and low CFS groups. The results, including the average CFS and RFS, are shown in Table 12. INSERT TABLE 12 HERE As already indicated, the use of either a low salary growth rate assumption or a high discount rate will have the effect of lowering the value of the pension liabilities. It therefore follows that use of favourable figures for both assumptions in combination will generate a “double benefit.” The exercise of such discretion can be analysed by

18

comparing the discount rate net of salary inflation for low versus high CFS firms, and in the presence of liability management, we would expect to find a significant difference between the two groups.

Table 12 shows that the mean discount rate net of salary inflation that is used by low CFS firms is 0.79% compared with 0.60% for the high CFS group of firms. The t-test result is significant at the 5% level. In other words, firms with weak pension schemes clearly select assumptions that give a relatively low valuation of liabilities. As might be expected given the regulatory guidance on selection of the discount rate, most of the differential between the low and high CFS firms is explained by variation in the salary growth rate (0.15%) compared with a 0.04% difference in the average discount rate used by the two groups. It seems somewhat unlikely that firms with weaker pension schemes are routinely finding themselves subject to higher rates of salary growth. The more obvious interpretation is that there is some opportunistic selection of assumptions to take advantage of the scope for discretion in the application of the accounting regulations. This finding affirms but also extends the work of Byrne et al (2007).

7. Conclusions The research findings contribute to the literature on pensions accounting by providing new insights into UK reporting practice under both FRS 17 and IAS 19. We confirm the results of US based research (Blankley and Swanson, 1995; Godwin, 1999; Asthana, 1999; and Eaton and Nofsinger, 2004) that there is evidence of accounting manipulation in the selection of the actuarial assumptions, but we also add to that literature by refining the measure of funding status via the application of a standardised measure of common financial strength. Whilst the sample size and limited time frame of the analysis both limit the extent to which the findings can be generalised, we would argue that the use of assumptions to manipulate the reporting of pensions suggests the need for tighter regulation of disclosures or additional guidance in the setting of “acceptable” parameters for relevant assumptions. More specifically, the establishment of tighter parameters in respect of both salary growth rates and the definition of the high grade bond used to establish the discount rate under IAS 19 may reduce the scope for manipulation. In the absence of tighter parameters, our results suggest that investors, regulators and pension fund members should pay close attention to the actuarial assumptions used in the reporting of DBPS funded status. The scope for their manipulation limits the representational faithfulness of the data, and as economic conditions around the world continue to deteriorate, the temptation to manage downwards the DBPS liabilities might be expected to increase. A number of companies are facing triennial pension scheme reviews in 2009, but the current low asset prices are resulting in huge deteriorations in the funding status of many schemes, implying potentially huge increases in future contributions. The recent interim results from the UK listed company Smiths Group reveal the potential scale of the problem. The company‟s pension fund deficit widened from £11 million

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to half a billion pounds in the six months to January 2009 (Financial Times, 2009), and was followed by an announcement that a forthcoming triennial review could cause pension contributions to increase. As a result, the company‟s share price fell by 14% in one day. Faced with the risk of such consequences, it is not difficult to see why directors may be tempted to select actuarial assumptions that limit the size of the reported pension fund deficit. In December 2008, Deloitte‟s Audit and Enterprise Risk Services arm in the USA issued a financial reporting alert on pensions accounting (Deloitte, 2008). The report (Deloitte 2008: 1) recommended that „in measuring the pension obligation … Financial statement preparers should understand, evaluate and conclude on the reasonableness of the underlying assumptions.‟ The question remains, however, as to whether or not the term “reasonable” from the preparers perspective is also “reasonable” from the perspective of other stakeholders.

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References Aisbitt, S. (2006) „Assessing the Effect of the Transition to IFRS on Equity: The Case of the FTSE 100‟, Accounting in Europe, 3, pp. 117-133. ASB (2000) FRS 17, Retirement Benefits London: Accounting Standards Board. ASB (2006) „Project update: accounting for pensions, Discussion Summary 30 June 2006‟ London: Accounting Standards Board. ASB (2007) Reporting statement: retirement benefits - disclosures. London: Accounting Standards Board. ASC (1988) SSAP 24, Accounting for Pensions Costs London: Accounting Standards Committee. Asthana, S. (1999) „Determinants of Funding Strategies and Actuarial Choices for Defined-Benefit Pension Plans‟, Contemporary Accounting Research, 16 (1), pp. 3974. Blake, D., Khoranasee, Z., Pickles, J. and Tyrrall, D. (2008) An Unreal Number. How Company Pension Accounting Fosters an Illusion of Uncertainty. Institute of Chartered Accountants in England and Wales, London. Blacket Research (http://www.blacketresearch.co.uk/products_frs.asp). Blankley, A.I., and E.P. Swanson (1995) „A Longitudinal Study of Accounting Assumptions‟, Accounting Horizons, 9 (4), pp. 1-21. Bozewicz, J. (2004) „Changes Ahead: Pension Liabilities and New Discount Rate Assumptions‟, AFP Exchange, 24 (.2) , pp. 36-8. Byrne, A., Clacher, I., Hillier, D. and Hodgson, A. (2007) „Fair Value Accounting and Managerial Discretion‟, Leeds University Business School Working Paper,.2(2). Carroll, T.J. and Niehaus, G. (1998), ‘Pension plan funding and corporate debt‟, Journal of Risk and Insurance, 65(3), pp. 427-41. Collier, J. (2004) Aggressive Earnings Management: Is It Still a Significant threat? London: The Institute of Chartered Accountants in England and Wales: Audit and Assurance Faculty. Company Reporting (2005) Retirement Benefits: IAS 19 versus FRS 17, Edinburgh, June. Deloitte (2008) „Pension and other Postretirement Benefits affected by Turmoil in the Credit Markets‟, Financial Reporting Alert 08-19, December 4 2008.

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Donkin, A., Goldstatt, P. and Lynch, K. (2002), „Inequalities in life expectancy by social class, 1972-1999‟, Health Statistics Quarterly, 15, pp. 5-15. Eaton, T.V. and J.R. Nofsinger (2004) „The Effect of Financial Constraints and Political Pressure on the Management of Public Pension Plans‟, Journal of Accounting and Public Policy, 23, pp. 161-89. EFRAG (2008) Discussion Paper: The Financial Reporting of Pensions. Brussels: European Financial Reporting Advisory Group FASB (2006), FAS 158, Employers’ Accounting for Defined Benefit Pension and Other Post-retirement Plans. Norwalk, CT: Financial Accounting Standards Board. The Financial Times (2008a) Pensions deficits may be poison pill in corporate debt restructuring, November 20 2008, p. 4 The Financial Times (2008b) Pensions lifeboat risks being swamped, December 9 2008, p. 1. The Financial Times (2008c) Pension sell-offs signal the start of something big for business, 25 February 2008, p. 12 The Financial Times (2009) Time to heed warnings over rising pension fund deficits, 28/29 March, p.27. FTSE (2006), FT-SE All Share Index Series Weightings Book at 28 February 2006, http://www.ftse.com/Research_and_Publications/2006Downloads/ASWB_0206.pdf Glaum, M. (2008) Pension Accounting and Research: An Overview. Paper presented at the Institute of Chartered Accountants in England and Wales, 2008, Information for Better Markets Conference. Godwin, N.H. (1999) „An Examination of Pension Actuarial Assumptions over the Decade Following the Issuance of FAS 87‟, Journal of Pension Planning and Compliance, 25 (1), pp. 62-75. Gohdes, A.E. & Baach, E. (2004) „Rechnungszins und Inflationsrate fűr die betriebliche Alterversorgung‟, Betriebs-Berater, 59(47), pp. 2571-73. Grant, T., Grant, G.H. & Ortega, W. (2007) „Quick Fix for Pension Accounting is only First Step‟, Financial Analysts Journal, 63 (2), pp. 21-35. IASB (2004), IAS 19, Employee Benefits, London: International Accounting Standards Board. Klumpes, P.J.M. (2001) „Implications of Four Theoretical Perspectives for Pension Accounting Research‟, Journal of Accounting Literature, 20, pp. 30-61.

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Kumar, J. (2006) „Impact of Pension Plan Funding Status on M&A Activity‟, Watson Wyatt Technical Paper No. 2006-TR-05. Available at: http://ssrn.com/abstract=929647 Lane Clark & Peacock (2006) Accounting for Pensions: UK and Europe Annual Survey 2006 London: Lane Clark & Peacock LLP. Life and Pensions (2005) ICI discloses large rise in pension deficit. Available at: http://www.life-pensions.com/public/showPage.html?page=290484 May, G., Querner, I. & Schmitz, U. (2005) „Entwicklung von Zinskurven fűr Zwecke der Bilanzierung nach IFRS/US-GAAP‟, Der Betrieb, 58(23), pp.1229-37. Mercer.com (2005) A fresh look at pensions risk. Available format: http://www.mercer.com/referencecontent.jhtml?idContent=1181540 Office for National Statistics (2005) „Life expectancy at birth and at age 65 by local areas in the United Kingdom, 2004–06‟, Health Statistics Quarterly, 36, 73-83. Pensions Regulator (2006) „Underestimate Life Expectancy at Your Peril, Warns Pensions Regulator‟ Press Notice/06/32, 25 September 2006. Record, N. (2006), Sir Humphrey‟s Legacy: facing up to the cost of public sector pensions, London: Institute of Economic Affairs. Available at: http://www.iea.org.uk/files/upld-publication332pdf?.pdf The Actuary (2002), Ralfe, J., „Why move to bonds?‟ March, pp. 28-9. The Times (2006) Companies Hide Truth About Pension Deficits, 28 September 2006, p. 49. Watson Wyatt (2005) „Cashing in: Do aggressive funding policies lead to higher credit ratings?‟ Insider, October. Available at: http://www.watsonwyatt.com/us/pubs/insider/showarticle.asp?ArticleID=15305 Watts, R.L. and J.L. Zimmerman (1990) „Positive Accounting Theory: A Ten Year Perspective‟, The Accounting Review, 65, January, pp. 131-56. White, H. (1980) „A heteroskedasticity-constant covariance matrix estimator and a direct test for heteroskedasticity‟, Econometrica, 48, pp. 817-38. Willetts, R.C. (2004) „The cohort effect: insights and explanations‟, British Actuarial Journal, 10, 833-98. Williams, P. (2005) „Transparency in Pensions‟, Accounting and Business, October, pp. 18-20. Zeff, S. A. (1978) ‟The rise of economic consequences‟, The Journal of Accountancy, December, pp.56-63

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Table 1: Significance of assumptions and their treatment in accounting standards Assumption Mortality rate

Price inflation rate

Discount rate

Salary inflation rate

Significance of this assumption Future obligations of schemes depend on the longevity of scheme members - which can only be predicted and can be expected to change in the future Future payments to current and deferred pensioners may be linked to price inflation (dependent on scheme rules) Expected to influence the salary inflation assumption This rate is used to discount the value of future obligations thus, other things being equal, a higher rate will result in a lower value attributed to future obligations Higher salary inflation will increase future obligations to current employees

Treatment in IAS 19 (IASB, 2004) Disclosure not explicitly required but may be implied on materiality grounds (para. 120A (n) )

Treatment in FRS 17 (ASB, 2000) Disclosure not explicitly required but may be implied on materiality grounds for periods ending on or after 31 December 2006 (ASB, 2006b, para. 5)

Disclosure required, if basis for future benefit increases (para. 120A (n) )

Disclosure required (para. 78) Rate to reflect market expectations (para. 23) and may be based on the difference between yields on fixed-interest and index-linked government bonds (para. 26)

Disclosure required (para. 120A (n) )

Disclosure required (para. 78)

Rate to equate to rate of return on high quality corporate bonds and to be consistent with currency and term of benefit obligations (para. 78)

Rate to reflect rate of general inflation (para. 26), to equate to rate of return on high quality corporate bonds, defined as bonds rated at AA or equivalent, and to be consistent with currency and term of benefit obligations (paras. 32 and 33) Disclosure required (para. 78)

Disclosure required (para. 120A (n) ) Rate to reflect „inflation, seniority, promotion and other relevant factors, such as supply and demand in the employment market‟ (para. 84)

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Rate to reflect rate of general inflation (para. 26)

Table 2: Pension liabilities under alternative assumptions Discount rate (%) Salary growth 4 5 6 (%) 3 100,449 90,000 81,229 4 113,004 100,559 90,184 5 127,901 113,004 100,667

Table 3: Summary of assumptions SD Minimum Maximum

2004

Mean

Rate of price inflation Rate of salary increases Discount rate Real salary increases Discount rate net of salary increases

0.0280

0.0015

0.0230

0.0330

Number of observations 232

0.0417

0.0054

0.0200

0.0600

239

0.0543 0.0138

0.0018 0.0052

0.0463 -0.0090

0.0600 0.0300

239 232

0.0127

0.0056

-0.0031

0.0375

239

2005

Mean

SD

Minimum

Maximum

Rate of price inflation Rate of salary increases Discount rate Real salary increases Discount rate net of salary increases

0.0279

0.0013

0.0230

0.0300

Number of observations 222

0.0412

0.0054

0.0200

0.0570

239

0.0502 0.0134

0.0030 0.0051

0.0400 -0.0070

0.0560 0.0300

239 222

0.0091

0.0062

-0.0081

0.0350

239

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2004 Price inflation Salary inflation p-value observations Discount rate p-value observations

2005 Price inflation Salary inflation p-value observations Discount rate p-value observations

Table 4: Pearson Correlation Coefficients Price inflation Salary inflation 1.000 0.3224 1.000 0.0000 232 0.2394 0.0252 0.0002 0.6987 232 239

Price inflation 1.000 0.2799 0.0000 222 0.1982 0.0030 222

Salary inflation

Discount rate

1.000

Discount rate

1.000

0.0114 0.8612 239

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1.000

Company yearend Price inflation: Mean SD Observations

Table 5: Variability of Assumptions December Deecember2005 2004

All of 2004 & 2005

.0276 .001374 120

.0278 .00125 110

.0279 .00141 454

Salary inflation: Mean SD Observations

.0414 .00502 127

.0410 .00510 127

.0414 .00540 478

Discount rate: Mean SD Observations

.0533 .00132 127

.0479 .00125 127

.0523 .00323 478

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Table 6: Assumptions of FTSE 100 and FTSE 250 Firms FTSE 100 FTSE 250 Mean S.D. Mean S.D. Price inflation .0277 .00142 .0280 .00140 (163) (291)

p-value 0.5824

Salary inflation

.0418 (180)

.00517

.00412 (298)

.00554

0.1517

Discount rate (Dec 2004)

.0531 (52)

.00139

.0534 (75)

.00126

0.7944

Discount rate (Dec 2005)

.0477 (52)

.00128

.0481 (75)

.00120

0.8925

Discount rate less salary inflation (Dec 2004)

.0112 (52)

.00533

.0125 (75)

.00521

0.9585

Discount rate less salary inflation (Dec 2005)

.00595 (52)

.00488

.00767 (75)

.00547

0.7953

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ftse100 CFS KPMG Deloitte E&Y constant

Table 7: Price inflation assumption Coefficient Robust t Std. Err. -.000248 .000139 -1.78 -.001375 .000477 -2.88 .000060 .000184 0.33 -.000131 .000172 -0.76 -.000069 .000193 -0.36 .029131 .000387 75.25

Number of observations = 454

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P>|t| 0.075 0.004 0.743 0.448 0.720 0.000

Table 8: Salary inflation assumption Coefficient ftse100 CFS KPMG Deloitte E&Y constant

.000063 .006118 -.000547 -.000652 .000122 .036746

Robust Std. Err. .000512 .001972 .000635 .000755 .000608 .001620

Number of observations = 478

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T

P>|t|

0.12 3.10 -0.86 -0.86 0.20 22.68

0.902 0.002 0.390 0.388 0.841 0.000

Table 9: Difference in assumed discount rate from average for firms with balance sheet date on the same month Coef. Robust t P>|t| Std. Err. ftse100 -.000234 .000117 -2.00 0.046 CFS -.001257 .000402 -3.13 0.002 KPMG .000284 .000144 1.97 0.049 Deloitte .000026 .000150 0.17 0.862 E&Y .-.000013 .000179 -0.07 0.943 constant .001030 .000342 3.01 0.003 Number of observations =

478

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ftse100 CFS KPMG Deloitte E&Y constant

Table 10: Real salary assumptions Coefficient Robust t Std. Err. .000276 .000489 0.56 .007308 .001908 3.83 -.000611 .000604 -101 -.000403 .000729 -0.55 -.000242 .000571 -0.42 .007901 .001571 5.03

Number of observations =

454

33

P>|t| 0.573 0.000 0.312 0.580 0671 0.000

Table 11: Discount rate net of the salary inflation assumption (difference from the average discount rate for firms with a balance sheet date in the same month) Coefficient Robust t P>|t| Std. Err. ftse100 -.000293 .000503 -0.58 0.560 CFS -.006475 .001941 -3.34 0.001 KPMG .000951 .000626 1.52 0.130 Deloitte .000514 .000718 0.72 0.475 E&Y -.000171 .000620 -0.28 0.782 constant .005018 .001611 3.11 0.002 Number of observations =

478

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Price inflation

Table 12: Firms with low and high common financial strength CFS observations Mean (%) S.E. (%) t Low 60 2.79 0.0167 0.78 High

50

2.77

0.0170

Low

66

4.03

0.0628

High

61

4.18

0.0644

Low

66

4.81

0.0135

High

61

4.77

0.0176

Real salary low inflation high

60

1.28

0.0524

50

1.42

0.0676

Discount low rate net of salary inflation high

66

0.79

0.0631

61

0.60

0.0654

CFS

low high

66 61

72.25 90.91

RFS

low high

66 61

72.16 91.40

Salary inflation

Discount rate

35

p 0.219

-1.62

0.0544

1.73

0.0432

-1.62

0.0540

2.05

0.0212

0.908 1.017

-13.43

0.0000

0.840 1.006

-14.76

0.0000