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Centre for Risk & Insurance Studies
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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
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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.
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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 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
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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
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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
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
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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