Centre for Risk & Insurance Studies

enhancing the understanding of risk and insurance

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

2

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: mark.billings@nottingham.ac.uk

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.

3

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

4

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 ...

5

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

6

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.

7

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

8

(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 2002-

2004‟ (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

9

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

10

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.

11

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

12

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.

13

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).

14

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

15

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).

16

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.

17

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:

18

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

19

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

20

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.

21

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. 39-

74.

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.

22

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.

23

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

24

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

Assumption Significance of this assumption Treatment in IAS 19 (IASB, 2004) Treatment in FRS 17 (ASB, 2000)

Mortality

rate

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

Disclosure not explicitly required but

may be implied on materiality grounds

(para. 120A (n) )

Disclosure not explicitly required but may be

implied on materiality grounds for periods ending

on or after 31 December 2006 (ASB, 2006b, para.

5)

Price

inflation rate

Future payments to current and

deferred pensioners may be

linked to price inflation

(dependent on scheme rules)

Expected to influence the salary

inflation assumption

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)

Discount rate 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

Disclosure required (para. 120A (n) )

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)

Disclosure required (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)

Salary

inflation rate

Higher salary inflation will

increase future obligations to

current employees

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)

Disclosure required (para. 78)

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

26

Table 3: Summary of assumptions

2004 Mean SD Minimum Maximum Number of

observations

Rate of price

inflation

0.0280 0.0015 0.0230 0.0330 232

Rate of

salary

increases

0.0417 0.0054 0.0200 0.0600 239

Discount rate 0.0543 0.0018 0.0463 0.0600 239

Real salary

increases

0.0138 0.0052 -0.0090 0.0300 232

Discount rate

net of salary

increases

0.0127 0.0056 -0.0031 0.0375 239

2005 Mean SD Minimum Maximum Number of

observations

Rate of price

inflation

0.0279 0.0013 0.0230 0.0300 222

Rate of

salary

increases

0.0412 0.0054 0.0200 0.0570 239

Discount rate 0.0502 0.0030 0.0400 0.0560 239

Real salary

increases

0.0134 0.0051 -0.0070 0.0300 222

Discount rate

net of salary

increases

0.0091 0.0062 -0.0081 0.0350 239

27

Table 4: Pearson Correlation Coefficients

2004 Price inflation Salary inflation Discount rate

Price inflation 1.000

Salary inflation

p-value

observations

0.3224

0.0000

232

1.000

Discount rate

p-value

observations

0.2394

0.0002

232

0.0252

0.6987

239

1.000

2005 Price inflation Salary inflation Discount rate

Price inflation 1.000

Salary inflation

p-value

observations

0.2799

0.0000

222

1.000

Discount rate

p-value

observations

0.1982

0.0030

222

0.0114

0.8612

239

1.000

28

Table 5: Variability of Assumptions

Company year-

end

December

2004

Deecember2005 All of 2004 &

2005

Price inflation:

Mean .0276 .0278 .0279

SD .001374 .00125 .00141

Observations 120 110 454

Salary inflation:

Mean .0414 .0410 .0414

SD .00502 .00510 .00540

Observations 127 127 478

Discount rate:

Mean .0533 .0479 .0523

SD .00132 .00125 .00323

Observations 127 127 478

29

Table 6: Assumptions of FTSE 100 and FTSE 250 Firms

FTSE 100 FTSE 250 p-value

Mean S.D. Mean S.D.

Price inflation .0277

(163)

.00142 .0280

(291)

.00140 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

30

Table 7: Price inflation assumption

Coefficient Robust

Std. Err.

t P>|t|

ftse100 -.000248 .000139 -1.78 0.075

CFS -.001375 .000477 -2.88 0.004

KPMG .000060 .000184 0.33 0.743

Deloitte -.000131 .000172 -0.76 0.448

E&Y -.000069 .000193 -0.36 0.720

constant .029131 .000387 75.25 0.000

Number of observations = 454

31

Table 8: Salary inflation assumption

Coefficient Robust

Std. Err.

T P>|t|

ftse100 .000063 .000512 0.12 0.902

CFS .006118 .001972 3.10 0.002

KPMG -.000547 .000635 -0.86 0.390

Deloitte -.000652 .000755 -0.86 0.388

E&Y .000122 .000608 0.20 0.841

constant .036746 .001620 22.68 0.000

Number of observations = 478

32

Table 9: Difference in assumed discount rate from average for

firms with balance sheet date on the same month

Coef. Robust

Std. Err.

t P>|t|

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

33

Table 10: Real salary assumptions

Coefficient Robust

Std. Err.

t P>|t|

ftse100 .000276 .000489 0.56 0.573

CFS .007308 .001908 3.83 0.000

KPMG -.000611 .000604 -101 0.312

Deloitte -.000403 .000729 -0.55 0.580

E&Y -.000242 .000571 -0.42 0671

constant .007901 .001571 5.03 0.000

Number of observations = 454

34

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

Std. Err.

t P>|t|

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

35

Table 12: Firms with low and high common financial strength

CFS observations Mean (%) S.E. (%) t p

Price

inflation

Low 60 2.79 0.0167 0.78 0.219

High 50 2.77 0.0170

Salary

inflation

Low 66 4.03 0.0628 -1.62 0.0544

High 61 4.18 0.0644

Discount

rate

Low 66 4.81 0.0135 1.73 0.0432

High 61 4.77 0.0176

Real salary

inflation

low 60 1.28 0.0524 -1.62 0.0540

high 50 1.42 0.0676

Discount

rate net of

salary

inflation

low 66 0.79 0.0631 2.05 0.0212

high 61 0.60 0.0654

CFS low 66 72.25 0.908 -13.43 0.0000

high 61 90.91 1.017

RFS low 66 72.16 0.840 -14.76 0.0000

high 61 91.40 1.006