Recognition versus Disclosure:
The Case of Employers’ Pension Cost Accounting

Yong Li
Lecturer in Accounting and Financial Management
Department of Management
Kings College London
LondonSE1 9NH
Tel: +44 (0) 02078483113
Fax: +44 (0) 78484254
e-mail: Yong.li@kcl.ac.uk

Preliminary Draft – Please do not quote
8 November 2013

Abstract

This paper addresses the fundamental question of whether, and the extent to which, capital
markets impound the information contained in disclosed and recognised amounts in thecontext of employers’ pension cost accounting. Using a sample of non-financial UK firms thathave only disclosed net pension liabilities (assets) prior to IAS 19, which are subsequently
recognised after IAS 19 adoption, we find that while valuation coefficients on disclosed net
pension liabilities (assets) are not significant, the valuation coefficients on recognised net
pension liabilities (assets) are significant. We find model-sensitive evidence that recognisedbalance sheet pension components receive more weight than the equivalent disclosed
information in market value association tests. In addition, our results suggest that recognitionand disclosure have a differential impact on the complementarities of balance sheet andincome statement pension measures. Overall the results from our study are consistent with the‘rational difference’ view that recognition and disclosure are not substitutes.
Keywords: recognition; disclosure; IAS 19, FRS 17, net pension liabilities (assets)
Data Availability: Data are available from public sources as indicated in the text.
JEL Classifications: M41

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1. INTRODUCTION
The equivalency of recognition and disclosures1 has been an issue of significant debate amongstandard setters, academics and practitioners. The ‘efficient market’ hypothesis implies an‘equivalency’ view, which suggests that the location of accounting amounts reported infinancial statements has no direct capital market implication. This is because users inaggregate are knowledgeable and efficient information processors who fully appreciate themeaning of accounting information regardless of where it is presented. Under this view, thestandard setters’ decision to recognise a previously disclosed amount conveys no new
information (Aboody, Barth, and Kasznik, 2004). By contrast, the competing‘rational

differences’ view posits that information location (disclosure versus recognition) reveals
differential characteristics of accounting information in terms of decision usefulness(Schipper, 2007). Schipper argues that this view is consistent with rational investors inaggregate who assess financial reporting requirements to uncover pertinent informational
properties of disclosed versus recognised items (e.g. reliability).
The relevant theory by which to analyze and discriminate between recognition anddisclosure is very limited, and the mixed evidence from prior empirical research sheds limited
light on this debate. Some studies provide evidence that disclosed items are evaluated bycapital market participants (e.g. Ely, 1995; Imhoff, Lipe, and Wright, 1993), but are unable todetermine whether disclosed information is processed by capital markets ‘correctly’ or
equivalently to recognised information. Other studies provide some evidence suggesting thatrecognised information receives stronger market response than disclosed items (e.g. DavisFriday et al., 1999; Davis-Friday, Liu and Mittelstaedt, 2004; Ahmed, Kilic and Lobo, 2006;
Al Jifri and Citron, 2009).
This study exploits the unique UK financial reporting setting in which accounting for
employers’ pension costs moved from notes disclosure to balance sheet recognition regime.
Mandatory pension disclosure and accounting practice prior to IFRS adoption in the UK withsubsequent recognition of the net pension liability/asset on balance sheet under IAS 19 provide

1

Recognition is defined as the depictions in numbers with captions on the face of the financial statements, anddisclosures as the displays in the notes and supporting schedules that accompany financial statements (Schipper,
2007).
3

a good experiemental setting to test the valuation implication of recognised versus disclosed
items. This setting mitigates some of the research design problems in prior recognition anddisclosure studies. Bernard and Schipper (1994) noted that cross-sectional comparisons are
difficult because if accounting standards allow a choice between recognition and disclosure forthe same economic situation, then firms self-select themselves into either recognition or
disclosure regime. The use of the mandatorily disclosed liability amounts prior to IAS 19
adoption and the subsequently recognised liability amounts upon IAS19 mandatory adoption
allows a unique within-firm design, thereby avoiding self-selection bias. In addition, Bernard
and Schipper (1994) also suggest that recognition and disclosure could result in different stock
price effects if the investors inappropriately undervalue disclosed amounts or recognition orthat they perceive recognition implies greater relevance or reliability. In our setting, the FRS
17 disclosure of the pension liability was provided in anticipation that recognition would be
required by the mandated adoption of IAS 19. As a result, it is less likely that investors would
perceive the recognised number as more reliable, since UK firms faced broadly similar
economic conditions before and after adoption of IAS 19. Therefore, the UK setting greatly
reduces the endogeneity issue related to changing investor perceptions of reliability.
Using a sample of non-financial UK firms that have only disclosed their pension balance
sheet pension liability and asset amounts under FRS 17, which is subsequently recognised
after IAS 19 adoption, we perform price association tests for evaluating the value relevance ofrecognised and disclosed pension liability/asset information (on a ‘net’ and a ‘disaggregated’basis). There are three key results from our value relevance tests. First, we find that while
valuation coefficients on disclosed net pension liabilities (assets) are not significant, thevaluation coefficients on recognised net pension liabilities (assets) are significant. Second,
recognition seems to make a difference. The incremental benefit from recognising the net
pension liability (asset) information on balance sheet is significantly greater than merely place
it as footnote disclosures. Third, our tests on incremental value relevance of pension asset andliability versus pension cost component provide evidence that recognition and disclosure havea differential impact on the complementarities of balance sheet and income statement pension

4

measures. More specifically, recognition of pension balance sheet components appears to have
reduced the explanatory power of pension costs in price association tests.
The study contributes to recognition versus disclosure debate and related academic
literature in a number of ways. First, it contributes significantly to the recognition versus
disclosure debate against a unique UK setting of an extended IAS 19 adoption period. We
present evidence consistent with the ‘rational difference’ view that recognition and disclosure
are not substitutes. Such view is supportive of the beliefs of accounting standard setters forfinancial statement elements that meet recognition criteria (e.g. Barth, Clinch and Shibano,
2003; Al Jifri and Citron, 2009). Second, it contributes to the prior pension value relevanceresearch on complementarities of pension balance sheet and pension cost component
information. We present evidence suggesting that recognition and disclosure have differential
impact on incremental value relevance of pension asset and liability versus pension cost
components. Third, the evidence on value relevance of ‘disaggregated’ pension liability andasset information under both disclosure and recognition regimes lends some support to recent
accounting standard setters’ proposal recommending the full recognition of companies’
pension assets and liabilities on a ‘disaggregated’ basis rather than on a ‘net’ basis.
The remainder of this paper proceeds as follows. Section 2 describes the institutional
background required for this study. Section 3 reviews prior recognition and disclosure
research, and the literature on value relevance of pension accounting information. Section 4
overviews the research design. Section 5 describes the sampling procedure, data, anddescriptive statistics. Section 6 reports the results of empirical analysis, while Section 7
concludes.
2. PENSION ACCOUNTING: FROM FRS 17 TO IAS 19
Prior to the 1980s, pension accounting in the UK was based on the cash contributions made byemployer sponsors during the accounting period. Statement of Standard Accounting Practice
24 (hereafter SSAP 24) “Accounting for Pension Costs” was issued in 1988 by the UK
Accounting Standards Committee (ASC), the predecessor body to the UK AccountingStandards Board (ASB). SSAP24 introduced the fundamental principle of accruals to pension
accounting but was mainly income statement focused, with the primary objective of5maintaining a regular pension cost each year that was a substantially level percentage of thepension payroll. Any variations from the regular costs were recognised gradually over theremaining service life of employees. However, SSAP 24 did not address the issue of theappropriate treatment of the pension asset and liability on an employer sponsor’s balance
sheet, which is central to the pension accounting debate.
On 30 November 2000, the ASB issued Financial Reporting Standard 17 (‘Retirement
Benefits’, FRS 17) which represented a significant pension accounting regime change in the
UK. The ASB’s major objectives were to ensure that the ‘fair value’ approach is used inmeasuring pension assets and liabilities and to achieve transparency and comparability inaccounting for pension costs (FRS 17, para 1). One of the most significant and controversialchanges required the recognition of the pension surplus or deficit as a net pension
liability/asset on balance sheet (FRS17, para.37). The surplus or deficit is required to bevalued annually, using market prices for pension investments and the AA corporate bond rate
to discount pension obligations (FRS17, para14). The recognition of this “pension balance” ina firm’s financial statement is consistent with the corporate finance perspective which would
treat the pension fund as part of the employer firm’s net worth, requiring full consolidation on
its balance sheet.
From 1 Jan 2005, all listed companies across Europe are required to adopt IAS 19‘Employee Benefits’ in their consolidated accounts, as part of EU-endorsed International
Financial Reporting Standards (‘IFRS’). As a result, ASB extended the full adoption of the
UK standard (FRS 17) over the reporting period from 2001 to 2004. This extended adoption
has resulted in a unique experimental setting for testing value relevance of recognition versus
disclosure. Prior to IAS 19, UK companies have the choice under the transitional regime of
FRS 17 to recognise the net pension liabilities (assets) on balance sheet; or continue to reportunder SSAP 24, and provide comprehensive mandatory disclosures in pension footnotes theeffects on the main financial statements as if FRS 17 had been fully implemented. From 1 Jan
2006 all firms adopting IAS 19 had to recognise the pension assets and liabilities on balance
sheets, however, again firms could choose how to report the actuarial gains and losses. In June
2011, the IASB issued an amended version of IAS 19 (Employee Benefits), which required the6full and immediate recognition of actuarial gains and losses in ‘other comprehensive income’.
The US pension accounting rules are consistent with IAS 19 approach in mandating balance
sheet recognition of the net pension liability/asset. In September 2006, the US FASB adopted
SFAS 158 (Employers' Accounting for Defined Benefit Pension and Other Postretirement
Plans, an Amendment of FASB Statements Nos. 87, 88, 106, and 132(R)), which requires
balance-sheet recognition of the funding status of defined benefit pension and OPEB plans.2
3. REVIEW OF PRIOR RESEARCH
3.1. Recognition versus disclosure
Prior academic research into the effects of recognition versus disclosure has advanced ourunderstanding of whether users interpret accounting information differently when it ispresented in different locations (e.g., see Ely 1995; Imhoff, Lipe, and Wright, 1993; Barth,
Clinch and Shibano, 2003; Aboody, Barth and Kasznik, 2004; Nelson and Tayler, 2007). Twoelements of this strand of literature are relevant to our study. The first investigates whether thecapital market processes accounting information disclosed in financial statement notes in theirfinancial decision making. A large volume of empirical research provides evidence that
disclosed items appear to be taken into account by capital market participants (e.g., see Ely
1995; Imhoff, Lipe, and Wright, 1993; Barth, Clinch and Shibano, 2003; Aboody, Barth andKasznik, 2004; Nelson and Tayler, 2007). For example, Aboody, Barth and Kasznik (2004)
show that disclosed stock-based compensation expense has a negative relation to share price.
Imhoff, Lipe and Wright (1993) and Ely (1995) provide evidence that disclosed future
minimum operating-lease payments are related to market assessment of equity risk. One UKbased study investigates whether the UK market incorporates footnote operating lease
disclosures in its assessment of equity risk (Beattie, Goodacre and Thomson 2000). Using an
improved measure of operating lease liabilities, they find a significantly positive relation
between equity risk and their estimate of operating lease liabilities. They conclude that
operating leases disclosures are incorporated in UK market participants’ assessments of equity
risk, thus corroborating prior US-based research findings.
2

Crucially, for the purpose of the paper, the mandatory disclosure and recognition requirements of FRS 17 and
IAS 19 are almost identical.
7

However, this element of the literature does not assess whether investors process disclosed
information ‘appropriately’ or equivalently to recognised information. The second element of
the literature addresses this issue. A few empirical studies document evidence suggesting thatrecognised information receives stronger market response than disclosed items (e.g. DavisFriday et al., 1999; Davis-Friday, Liu and Mittelstaedt, 2004; Ahmed, Kilic and Lobo, 2006;
Bratten, Choudhary and Schipper, 2013). Most relevant to the present study, David-Friday etal. (1999) investigate whether the market priced firms’ obligations for postretirement benefit
other than pensions (PRB) measured under SFAS 106 (FASB, 1990) equivalently before andafter formal recognition. Their results suggest that both disclosed PRB liabilities prior to
SFAS 106 and those recognised subsequent to the adoption of SFAS 106 significantly
contribute to explaining stock prices. They also find some evidence that the market priced the
PRB liability differently before and after it was recognised under SFAS 106. In a follow-up
study, Davis-Friday, Liu and Mittelstaedt (2004) presents evidence consistent with the market
treating disclosed PRB liabilities as less reliable than recognised PRB liabilities. In a different
context, for a sample of banks, Ahmed, Kilic and Lobo (2006) find that information onderivatives recognised in financial statements pursuant to SFAS 133 is significantly positively
valued by the market, whereas the equivalent derivatives information disclosed in footnotes
does not appear to be valued. By contrast, Al Jifri and Citron (2009) found that both
recognised and disclosed good-will (in the UK) are significantly associated with share price.
Bratten, Choudhary and Schipper (2013) examine whether and why capital market participants
treat recognized and disclosed lease amounts differently in setting the costs of debt and equity.
Using a sample of US firms reporting both capital and operating leases, they present evidence
that recognized information and disclosed information is processed similarly when thedisclosed information is salient, reliable and easily processed. Bratten et al. (2013) suggest thatequivalence of recognized versus disclosed amounts are attributable to the setting in which thedisclosed amounts are reliable and the disclosed information is readily identifiable and easily
processed. They provide further evidence showing that the associations between costs of debt
and equity, and recognized amounts versus as-if recognized amounts are statisticallydistinguishable only when the as-if recognized values are imputed from less-reliable8disclosures. Their findings however are not consistent with prior studies (e.g. Ahmed et al.
2006; Davis-Friday et al. 1999) which find valuation differences between recognized anddisclosed values for derivatives and post-retirement benefits. They attribute the difference to a
combination of reliability and ease-of-use effects; that is, investors and creditors appear to use
recognized and disclosed information similarly when there are few or no difficulties in
identifying and processing the information and the information itself is reliable.
Experimental and analytical research of individual users provide converging evidence,
supporting that argument that recognition or disclosure of information affects the extent ofsome financial statement users’ response. A recent experimental study by Nelson and Tayler(2007) examines how financial statement users’ judgements are influenced by the process oftransforming financial statements from disclosed information to on balance sheet recognition.
The authors provide evidence suggesting that disclosed information acquired via reconciled
information displays and effortful processing influences financial decision making to a greater
extent than if it had been recognised. Analytical research typically models disclosure
separately from recognition by characterising disclosures as freely available information, butless used by some investors. For example, Barth, Clinch and Shibano (2003) find that becauseof costs associated with understanding footnote disclosures, recognition can affect the extent
to which information is reflected in share prices. Disclosures receive a lower valuation weightbecause some investors do not understand these items.
Overall, empirical research on recognition versus disclosure suggests that the market reacts
to disclosed information, but possibly to a lesser degree than to recognised information. This
may reflect a perception that recognised amounts are more reliable than merely disclosed
amounts. However, empirical evidence to date is mixed given a number of difficulties in
research designs including the choice of model specification (for a detailed discussion see
Schipper, 2007). Typically, earlier research studies rely upon an equity valuation frameworkwith over-simplifying assumptions. For example, Davis-Friday et al. (1999) model the market
value of equity as the sum of market values of assets and liabilities, where book values ofassets and liabilities are used as proxies for market values, under the premise that market value
captures earnings and other factors. Such regression specification fails to capture9‘unrecognised goodwill’, i.e. the omitted expected future ‘rents’ that are also priced byinvestors.
3.2. Market valuation of pension liabilities
The second strand of research concerns the value relevance of pension liabilities or pension
cost components (e.g. Landsman, 1986; Feldstein and Morck, 1983; Daley, 1984; Barth, 1991;
Barth, Beaver and Landsman, 1992; Picconi, 2006; Hann, Lu and Subramanyam, 2007). An
implicit assumption in these studies is that recognition or disclosure does not affect value
relevance. A majority of these studies relies on some form of pricing model to structure theirtests. Typically, they use equity market value as the benchmark to assess how well disclosed
and/or recognised pension accounting amounts reflect information used by investors.
However, evidence from this strand of US-based empirical accounting literature is also
somewhat mixed.
Some studies find evidence that disclosed pension amounts are incorporated in firms’
equity valuation. For example, Barth (1991) investigates disclosures of pension assets andliabilities information under SFAS 87 to determine which information investors appear to use
in their valuation of firm equity. She finds that footnote disclosures are closer to those
assessed in market valuation than the measures recognised in the balance sheet at that time.
This suggests that the market pays some attention to the pension information reported in thefinancial statement notes, but that it may have trouble properly weighting this information.
Barth, Beaver and Landsman (1992) test whether the market assigns different coefficients tothe various components of reported pension cost based on their perceived permanence. Theyfind that, in general, the market weights the various components differently, although notnecessarily with the magnitude or sign predicted. Hann, Lu and Subramanyam (2007) examine
the value relevance of disclosed projected pension obligation (PBO) under SFAS 87. The
authors separate the discretionary component of PBO, attributable to flexibility allowed in
actuarial assumption choices, from the non-discretionary PBO component. They find that thediscretionary component is incrementally priced by the market in a similar manner to thenondiscretionary component.

10A number of studies have also suggested that pension and postretirement benefits
information is not fully impounded in share prices. Landsman and Ohlson (1990) examined
whether the market fully values net pension assets (liabilities) disclosed in the notes under
SFAS No. 36 from 1979 to 1982. Contrary to Barth’s (1991) findings, Landsman and Ohlsonsuggest that the market under-reacts to the pension disclosures. Amir and Gordon (1996)
examine the association between firm value and other post employment benefits (OPEB)
liabilities. They conclude that equity values are consistent with the stock market taking
reported OPEB liabilities at face value without adjusting for differences in assumptions.
Analytical research by Gold (2005) postulates that SFAS 87 overstates and smoothes
earnings leading to upwardly biased equity valuation. Gold develops a model in whichinvestors fail to adjust for plan asset risk and rely on recognised pension costs rather than thedisclosed plan assets and liabilities. Consistent with Gold (2005), Coronado and Sharpe (2003)
find supportive evidence that US capital market participants failed to interpret the pension
expense correctly throughout the late 1990s leading to the over-valuation of firms.
Picconi (2006) investigates whether analysts and investors fully incorporate theinformation contained in pension footnote disclosures. His results indicate that analysts do not
explicitly incorporate the information from changes in pension plan parameters into theirinitial forecasts so that these changes predict future earning surprises. In addition, Picconi
finds that the off-balance-sheet portion of the pension plan’s funded status and the projected
benefit obligations (PBO) are predictive of future returns while the on-balance-sheet portion of
the funded status is not. This implies that investors do not accurately assess the long-run cash
flow and earnings implications of these off-balance-sheet pension disclosures.
Overall, prior research suggests that disclosed information (including pension-related) isvalue relevant. Some studies find that recognised information is more value relevant thandisclosed information, but others find little difference in relevance. One experimental study
provides a possible explanation for such conflicting results: the need for additional processingof disclosed information may actually enhance its value (Nelson and Tayler, 2007). Whiledisclosed discretionary components of pension liabilities may be particularly helpful to users(Hann et al, 2007), there is other US evidence that disclosed pension information is not

11accurately impounded in firm share price. The present study seeks to investigate such issues
further, within the UK context, taking advantage of the within-firm design possibility enabledby the mandatory change from disclosure to recognition.
4. RESEARCH DESIGN AND METHOD
4.1. Development of hypotheses
The first research question we investigate is whether there is a differential market valuation
impact between recognised and disclosed pension liability/asset values. Prior pension research
has implicitly assumed that recognition or disclosure does not have a differential impact onvalue relevance. Indeed the empirical evidence from the US suggests that pension accounting
information (recognised or disclosed) is significantly associated with share prices (e.g. Barth,1991; Hann, Lu and Subramanyam, 2007). However, the somewhat opaque pension
accounting practices permit UK firm management to engage in smoothing and spreading
pension cost over time. Consequently, the UK capital market may not be able to weight thepension accounting information (disclosed or recognised) properly.
The ASB chairman explained that the premise underlying FRS 17 is that the “pension
surplus or deficit should be shown in the balance sheet for investors and employees to see”
(Tweedie, 2003: p. 722). Absent a theoretical framework underlying recognition versus
disclosure in financial reporting, we expect that value relevance of pension accounting
information depend on whether the change from the pre-IAS 19 disclosure regime to post-IAS
19 recognition regime conveys new information to investors who might perceive
recognised/disclosed amounts to have different informational properties (e.g. greater decisionusefulness). This prediction is consistent with the ‘rational differences’ view that the disclosed
net pension liability/asset amounts may be viewed by investors as less value-relevant or lessreliable (Schipper, 2007; Davis-Friday et al., 1999) because of their locations on the financial
statements. This discussion leads the following hypotheses:
Hypothesis 1 (H1)
H1: Capital market assigns greater valuation weight to a recognised net pension
liability/asset than a disclosed net pension liability/asset.

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The second related research question we address is whether balance sheet pension
liability/asset information (on a ‘net’ or ‘disaggregated’ basis), upon IAS 19 adoption isincrementally more value relevant than pension cost component. Glaum (2009:283) points outthat examining whether the complementarities of balance sheet and income data underlying
the Ohlson (1994) equity valuation model applies to pension accounting measures is at thevery heart of the current pension accounting debate. Recent research finds that for the US
market firm valuations continue to be unduly influenced by the recognised pension expenses
in the income statement, with less weight attached to the incremental information in the net
pension position disclosed in the financial statement footnotes (Coronado et al, 2008); thisleads to significant market valuation errors in the price of companies with defined benefit
pensions. Franzoni and Marin (2006) find that US firms sponsoring underfunded defined
benefit pension plans appear to be undervalued relative to those sponsoring overfundedpension plans. By contrast, an earlier US-based study by Barth et al. (1993) finds that pension
cost component information is largely redundant in explaining share price, once disclosed
pension balance sheet information are incorporated into the valuation model. Fasshauer and
Glaum (2009) find evidence consistent with Barth et al. (1993) in a German setting.
In the UK, under the traditional pension accounting rules (SSAP 24), any pension surplus
or deficit arising from a UK firm’s past funding practices was not recognised on its balance
sheet. Consequently, investors may have valued the firm on the basis of the (recognised)
impact of pensions on reported earnings than on the (disclosed) underlying true economic
measure of the firms’ pension exposure prior to IAS 19 adoption. Compliance with FRS
17/IAS 19 facilitated a shift away from the smoothing of pension expenses to the impact on
the fair value of the firm’s pension exposure on the balance sheets. This discussion leads to thefollowing hypotheses:
Hypothesis 2 (H2)
H2 (a): Net pension liabilities (assets) components are incrementally more value
relevant than pension cost components upon IAS 19 adoption.
H2 (b): Pension assets and liabilities components on a “disaggregated” basis are morevalue relevant than pension cost components upon IAS19 adoption.

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4.2. Empirical models
In earlier recognition versus disclosure studies, which have adopted the value relevanceapproach (e.g. Davis-Friday et al., 1999; Davis-Friday, Liu and Mittelstaedt, 2004), the choiceof valuation model sometimes relies upon an equity valuation framework with potentiallyover-simplifying assumptions. Consistent with recent pension research (e.g. Coronado andSharpe, 2003; Hann, Lu and Subramanyam, 2007), we use the Ohlson (1995) model to test thevalue-relevance of FRS17 pension footnote disclosures (H1). Market value of equity isregressed on the specific balance sheet accounting items under investigation (e.g., fair value ofpension assets, projected benefit pension obligations), non-pension assets and liabilities, net
income and a vector of control variables. Ohlson (1995) shows that firm value can be
expressed as a linear function of equity book value, net income, dividends and otherinformation with additional assumptions of linear information dynamics. When income isneither perfectly persistent nor transitory, the correct specification of the equity valuation
model is the one includes both the book value of equity and income (Ohlson, 1995). The
baseline regression models are specified as follows:
MVE it   0   1 BVE it   2* NPL it   5 NI it   6 PC
  7 SALEGRW it   8 R & D it   9 EMP it   it

MVE it   0   1 BVE it   3* FVPA it   4* PBO it   5 NI it   6 PC
  7 SALEGRW it   8 R & D it   9 EMP it   it

(1)

(2)

where MVEit is the market value of equity of firm i at time t (closing price 3 months following
the firm’s fiscal year end); BVE it is the book value of equity; NPLit is the recognised ordisclosed net pension liability (asset); FVPAit is the fair value of pension assets; PBOit is the
projected pension benefit obligations; NIit is the net income before extraordinary items, PCit is
the net periodic pension expenses, R&D and pension expenses; SALEGRWit is the averagesales growth over the previous three years; R&Dit is the research and development expense;
EMPit is the number of employees in thousands.
We include sales growth (SALEGRW) as a control variable for growth opportunities thatare not reflected in the financial statements. Research and development expenditure (R&D)

14

and number of employees (EMP) are also included to control for unrecognised intangibles andvalues created by human capital.3
Eq. (1) only includes the net pension liability measured as the difference between thepension liability and the fair value of the plan assets. This approach effectively assumes thatpension assets and liabilities are measured with equal precision and that the market capitalises
both at the same rate. By contrast, Eq. (2) allows the pension plan assets and obligations toenter the regression individually. This approach takes into account prior research whichsuggests that pension assets and liabilities are priced differently and that both disaggregatedpension assets and pension liabilities are individually important in explaining cross-sectionalvariation in equity values (Landsman, 1986; Barth, 1991). The advantage of Eq. (2) is thatvaluation coefficients of pension asset and liability component are allowed to vary; thedisadvantage is that pension asset (FVPA) and pension liability (PBO) are typically highly
correlated.
To detect possible differences in the relation between market prices and recognised net
pension liabilities versus pre-IAS 19 disclosed pension liabilities, we modify the above
baseline valuation models to allow for different coefficients in pre-IAS 19 and post-IAS 19
periods. Our research design focuses on those UK firms that complied with the immediate
recognition of actuarial gains and losses (AG&L) in full in Statement of Recognised Income
and Expenses (SORIE) under IAS 19, and which made a disclosure of the pension assets andliabilities amounts in the prior year. Given the great similarity between FRS 17 and IAS 19,
pension disclosures made under FRS 17 can be considered an estimate of the pension
liability/asset to be subsequently recognised under IAS 19. Both the disclosed and recognised
items were measured by using the same valuation method, and were often similar inmagnitude. We mitigate the potential effects of measurement error in the disclosed items byfocusing on the difference between the coefficients of the disclosed and recognised items as
opposed to their deviations from some theoretical value.
We refine the baseline models by introducing a dummy variable (D) to capture thetransition from the disclosure to recognition regime (D is coded 1 indicating the post-IAS 19
3

Inclusion of R&D and EMP also helps to mitigate the service cost anomaly. More detailed discussion on thiscan be found in Hann, Lu and Subramanyam (2007).
15

mandatory recognition period; D is coded 0 indicating the pre-IAS 19 mandatory disclosure
period) as follows:
MVE it   0   02 D   1 BVE it   2* NPL it   5 NI it   6 PC   7 SALEGRW it   8 R & D it
  9 EMPit   10 D * BVE it  11* D * NPL it   12 D * NI it   13 D * PC   14 D * SALEGRW it  15 D * R & D   16 D * EMPit   it(3)
MVE it   0   02 D   1 BVE it   3* FVPA it   4* PBO it   5 NI it   6 PC   7 SALEGRW it  8 R & D it   9 EMP it   10 D * BVE it   11* D * FVPA it   12 * D * PBO it  13 D * NI it   14 D * PC it   15 D * SALEGRW it   16 D * R & D it   17 D * EMP it   it(4)
We again have two equations: Eq. (3) includes the net pension plan liability/assets (NPL),
whereas Eq. (4) allows the pension plan assets (FVPA) and obligations (PBO) to enter the
regression individually. In Eq. (3), the coefficients corresponding to the disclosure regime are
the intercept coefficient α0, together with the slope coefficients α1 through to α9. The
valuation coefficient for the recognition period equals the valuation coefficient corresponding
to the disclosure period plus the corresponding interaction term coefficient. For example in Eq.
(3), the recognition valuation coefficient for NPL is α2* + α11*. In Eq. (4), the recognition
valuation coefficient for FVPA is α3* + α11*, and for PBO is α4* + α12*.
Our first test in Eq. (3) focuses on whether the coefficient on the net pension liability/asset(α11*) differs significantly from zero; if so, this suggests a differential market valuation
impact between a disclosed and a recognised net pension liability/asset. A significant positive
sign for the interaction valuation coefficient (α11*) would indicate that recognised amounts
are weighted greater than disclosed amounts. This would be consistent with the ‘rational
differences’ view that the disclosed net pension liability/asset amounts may be viewed byinvestors as less value-relevant (Schipper, 2007; Davis-Friday et al., 1999). Our second test in
Eq. (3) focuses on whether valuation coefficient (α2* + α11*) of recognised net pension
liability (NPL) is significantly different from zero, while the coefficient on pension cost (α6+α13) is not. In Eq. (4), our test focuses on whether valuation coefficients of FVPA (α3* +α11*) and PBO (α4* + α12*) are significant, while the coefficient on pension cost component(α6+ α14) is not.

16

5. SAMPLE AND DATA
Our sample selection began with the 350 UK companies listed on the London Stock
Exchange, which were constituents of the FTSE 350 index in the year 2006. A significant
number (142) of these firms did not sponsor defined benefit pension schemes. Exclusion ofthese firms, financial firms, firms following US GAAP, firms adopting the ‘corridor
approach’, and early adopters of FRS 17 yields a sample of 132 companies. Table 1
summarises the sample selection process. In our regression analysis, we use firm-year
observations with available data and delete the firm-year observations with negative bookvalue of equity.
[INSERT TABLE 1 ABOUT HERE]
The 2004 to 2006 sample period is chosen because this period witnessed the transition
from a disclosure to a recognition regime for pension accounting in the UK. First, the former
UK pension GAAP (SSAP 24, ‘Accounting for Pension Costs’) was superseded by FRS 17(‘Retirement Benefits’) issued on 30 November 2000. However, the full adoption of FRS 17
was phased in over an extended period from 2001 to 2004. During the transition to FRS 17,
UK companies had a choice between voluntarily recognising the net pension liability/asset onbalance sheet and disclosing the equivalent information in the notes to the financial
statements. Second, the EU regulations required listed companies to prepare accounts inaccordance with international financial reporting standards (IFRS) (including IAS 19 forpension accounting) for accounting periods beginning on or after 1st January 2005. Crucially,
for the purpose of the proposed project, the recognition and disclosure requirements of FRS 17
and IAS 19 under investigation are more or less identical.
The area in which IAS 19 differs from FRS 17 is the treatment of actuarial gains and losses(AG&L). IAS 19 allows the ‘corridor’ option in addition to the FRS 17 approach which
requires AG&L to be recognised in full in the Statement of Recognised Income and Expenses(SORIE) immediately they arise. Under the ‘corridor’ approach, gains and losses are permitted
to remain unrecognised (i.e. kept off the balance sheet) until they breach the corridor, and eventhen recognition on the balance sheet is spread over a number of years. The five companies

17which elected to adopt the IAS 19 ‘corridor’ approach are not comparable to the rest of thesample so had to be excluded, as indicated in Table 1.
All the accounting data pertinent to the project were manually extracted from the firms’
annual reports filed during the period from December 2004 to November 2006. The
mandatory FRS 17 disclosure regime covers accounting year ending from 1 December 2004 to
30 November 2005, and the mandatory IAS 19 recognition regime covers accounting year
ending from 1 December 2005 to 30 November 2006.
6. EMPIRICAL RESULTS
6.1. Descriptive Statistics
Table 2 presents descriptive statistics for sample firms, with Panels A and B reporting
separately for the disclosure year and the recognition year, respectively. Liabilities appear as
negative values in the table. In the year of disclosure, the mean (median) total market value ofequity (MVE) is £3,667m (£914m) or £5.08 (£3.24) per share. The mean (median) values aremuch higher in the following recognition year at £5,013m (£1,334 million), part of which canbe explained by the general rise in the stock market over the period. The mean (median) total
net pension liability (NPL) in the disclosure year is £226m (£54m) falling to £216m (£46m)
million in the recognition year. The negative amounts represent net liabilities and confirm thatthe sponsored pension schemes, on average, were underfunded during the period 2004–2006.
This contrasts with the overfunded US pension plans in the earlier 1991-1993 period in theDavis-Friday et al. (1999) study. The decline in underfunding in the year of recognitionreflects the overall net effect of typical increases in pension fund assets (FVPA), reflecting thestock market rise, and liabilities (PBO). Paired t-tests and Wilcoxon signed rank tests indicatethat disclosed pension assets (FVPA) and pension liabilities (PBO) are not significantly
different than the post-IAS 19 recognised amounts.
[INSERT TABLE 2 ABOUT HERE]
Table 3 provides Pearson and Spearman correlations for the full sample using per sharedata over the full sample period (2004-06). The correlations calculated separately for the yearsof disclosure and recognition are very similar to those reported. As expected, MVE is strongly
positively correlated with BVE and NI. The SALEGRW, R&D and EMP are all positively
18

correlated with MVE. The correlations between pension fund assets (FVPA) and liabilities(PBO) are also extremely high, with Pearson (Spearman) correlation coefficients of -0.993(-0.994).
[INSERT TABLE 3 ABOUT HERE]
6.2. Regression Results
Table 4 presents results from estimating baseline valuation equations (1) and (2) on priceassociation of pension liability/asset values for the full sample over the entire sample period.
The explanatory power of the models is relatively high, with adjusted-R squares of 56% and60%, which is slightly higher but similar to prior U.S. studies (e.g. Hann et al. 2007). The
coefficients for BVE are highly significant and approximately 1.0 across both equations,which is in line with Davis-Friday et al. (1999). Panel A shows that the combined recognised
and disclosed net pension liability NPL coefficient (α2*) is positive and significantly negativeat the 0.03 level, suggesting that net pension liability/asset amounts (disclosed and recognised)
contribute to explaining share price. Eq. (2) (Panel B) assesses the value relevance of thedisaggregated measures of pension fund assets and liabilities. The coefficients of both
disclosed pension fund assets FVPA (α3*) and liabilities PBO (α4*) are positive, arestatistically significant at less than 0.01 level.
The pension cost coefficients are negative and significant at 0.01 levels in both models,
which is consistent with theoretical considerations. It is interesting to note that the significanceof the coefficients on pension costs (PC) is reduced when pension assets and liabilities areallowed to enter the regression separately. The magnitude of the coefficient of PBO (2.720) is
smaller than that of FVPA (3.454) during the pre- and post-IAS 19 period, and the F-testsuggests that the two coefficients are statistically different at less than 0.01 level ofsignificance. This evidence suggests that the capital market assigns valuation weights topension assets and liabilities (on a “disaggregated” basis) individually and differently.
However, the evidence on the disaggregated assets and liabilities needs to be interpreted withcaution, given the high collinearity between FVPA and PBO. Overall, these results show both19

balance sheet pension asset/liability information and pension costs contribute to explaining
share prices when research design does not control for disclosed and recognised items.
[INSERT TABLE 4 ABOUT HERE]
Table 5 presents the results from the tests of value relevance of recognised versus disclosed
pension liability/asset values on a ‘net’ basis for the pre- versus post- IAS 19 periods fromestimating Eq. (3). The intercept and slope adjustment variables, indicated with a D prefix, areincluded to detect differences in the market pricing of disclosed versus recognised net pension
liabilities (assets). Dummy variable D is coded 1 for the post-IAS 19 recognition period.
Estimating Eq. (3) yields the recognition valuation coefficient (α2*+α11*) of 1.553, which is
positive and statistically significant at the 0.01 level. The magnitude of this recognition
coefficient is significantly greater than the disclosed coefficient (α2* = 0.358). Consistent
with H1 (a), the coefficient on D*NPL, α11*, is positive and statistically highly significant at
less than 0.01 level (t-statistic =2.84). This evidence suggests that the market places
significantly greater weight on the recognised net pension liability/asset information over theequivalent disclosed information.
Comparing the estimation result for Eq. (1) for the full sample to those for Eq. (3) showsthat the coefficient on pension costs (α6+α13) during post-IAS 19 recognition period lost its
significance (t-statistic=0.66). This is consistent with our H2 (a), indicating that balance sheet
net pension liability information is incrementally more value relevant when recognised thanpension cost information. This finding is in line with the results of Fasshauer and Glaum(2009) in a German setting, suggesting pension balance sheet components when recognised
appear to be more important for stock market valuation than pension costs. Another interestingfinding is that the result from estimating Eq. (3) also shows that coefficient on disclosed net
pension liability (α2*) is not statistically significant at conventional level (t-statistics=0.72),
but the coefficient on pension cost component is negative and significant at 0.10 level (tstatistics = -1.79). This evidence suggests those pension cost components are more closely
associated with share price than pension balance sheet components (on a ‘net’ basis) under the
pre-IAS 19 disclosure regime.

20

[INSERT TABLE 5 ABOUT HERE]
Table 6 reports the results from estimating Eq. (4), which allows pension assets andliabilities to have different coefficients in the valuation equation. The results show significant
recognition valuation coefficients for pension assets FVPA (α3* + α11*) and for pension
liabilities PBO (α4* + α12*), both highly significant at less than 0.01 level. The incremental
difference between recognition and disclosure valuation coefficients of pension assets, thecoefficient on D*FVPA (α11* = 0.411) are not statistically significant, though of expected
positive sign. The coefficient on D*PBO (indicated by α12*=0.750), the incremental
difference between recognition and disclosure valuation coefficients of pension liabilities, is of
expected positive sign, and is only very weakly significant at the 0.10 level based on a one-tailtest (t-statistic = 1.544). Furthermore, the disclosure valuation coefficients for pension assets
FVPA (α3*) and pension liabilities PBO (α4*) are positive and highly significant at 0.01 level.
Overall this evidence suggests that the incremental value relevance between disclosed andrecognised disaggregated pension assets and liability information is relatively small, and suchincrease is insufficient for the market to assign greater weights to this disaggregatedinformation when recognised on balance sheet. Table 6 also shows that the coefficient on
pension costs (α6+α14) under recognition regime is not statistically significant (tstatistics=0.66), comparing with the estimation result for Eq. (2) for the full sample whichallows pension assets and liabilities to have different coefficients. This is consistent with ourH2 (b), suggesting “disaggregated” pension balance sheet components when recognised
appear to be more important for stock market valuation than pension costs. This finding is also
in line with the results obtained in Table 5.
Taken together, the results from estimating Eq. (3) to Eq. (4) show that while the valuation
coefficients on the disclosed net pension liability/asset are not significant, the valuation
coefficient on recognised net pension liability/asset are significant. There is model-sensitive
evidence suggesting that recognised balance sheet pension components receive more weight
than the equivalent disclosed information in market value association tests. This evidence isconsistent with prior research findings on recognised versus disclosed post-retirement benefit
liabilities and derivative financial instruments (e.g. Davis-Friday et al. 1999; Ahmed et al.,21

2006). In addition, we present evidence that disaggregated amounts for pension liabilities andassets are separately value relevant, under both disclosure and recognition regimes. Thisevidence further supports the notion that the market views pension fund property rights(ownership of pension assets and liabilities) as lying fully with the firm, consistent with
Landsman (1986). Finally, our tests on incremental value relevance of pension asset andliability versus pension cost component provide evidence that recognition and disclosure havea differential impact on the complementarities of balance sheet and income statement pension
measures. More specifically, recognition of pension balance sheet components appears to have
reduced the explanatory power of pension costs in explaining share prices.
[INSERT TABLE 6 ABOUT HERE]
6.3. Robustness checks
We perform a number of sensitivity analyses. First, it is possible that our results are driven byfactors other than the differences in recognition and disclosure per se. In order to mitigate theomitted variables problems, we follow Amhed et al. (2006) to employ change specifications ofequations (3) and (4). The un-tabulated estimation results for the changes models are
qualitatively consistent with the results for the level models. Second, we repeat our tests using
annual year-by-year regressions; again we find consistent results as in our fixed effect panel
regressions. Third, we examine the sensitivity of our results to the choice of deflators by
repeating levels estimations using variables scaled by beginning sales as in Hann et al. (2007).
We obtain similar results. Overall, these additional tests confirm the primary finding
concerning the value relevance of recognised net pension liability (asset) information.
7. SUMMARY AND CONCLUSION
The question of whether the capital market considers that a firm’s pension asset and liability
information (on a ‘net’ or ‘disaggregated’ basis) conveys incremental information is of criticalimportance for accounting standard setters, investors and auditors. This study contributes tothe recognition versus disclosure debate by estimating cross-sectional equity valuation
regressions to assess whether investors value pension liability/asset information differently
depending on whether reported items are disclosed or recognised. We examine this issue in the22context of employers’ pension cost accounting, exploiting a financial reporting setting inwhich UK firms disclosed pension asset and liability amounts under mandatory requirement of
FRS 17, which then were subsequently required to be recognised on balance sheet upon
mandatory adoption of IAS 19. This unique experimental setting enables the avoidance of selfselection bias issues by using a within-firm research design. It also helps to mitigate thepotential problem of differences in reliability between recognised and disclosed amounts,
since both FRS 17 and IAS 19 adopt identical valuation methods for the measurement ofpension assets and liabilities.
The primary objective of the study is to examine whether capital markets implicitly
assign different valuation coefficients to disclosed and recognised pension assets and liability
amounts. We find that that while valuation coefficients on disclosed net pension liabilities(assets) are not significant, the valuation coefficients on recognised net pension liabilities(assets) are significant. We also find model-sensitive evidence that recognised balance sheet
pension components receive more weight than the equivalent disclosed information in market
value association tests. Our findings thereby lend support to the ‘rational differences’ view of
the non-substitutability of recognition versus disclosure held by accounting regulators. Our
results are also of interest to accounting standard setters who are seeking to enhance thetransparency and improve the decision usefulness of employers’ pension cost accounting.
Recently the Accounting Standards Board (IASB) in conjunction with the European Financial
Reporting Advisory Group (EFRAG) issued a discussion paper as part of its long-term review
of pension accounting. The discussion paper recommended that normal consolidation
principles be applied such that pension assets and liabilities should be included in thesponsoring firm’s balance sheet on a ‘disaggregated’ rather than on a ‘net’ basis. We present
evidence that investors appear to price disaggregated pension liability and assets information
under the pre-IAS 19 recognition regime, but did not price the net pension liability (asset)
information over the same period. Thus, our findings could be interpreted as providing support
for the full recognition of companies’ pension assets and liabilities on a disaggregated basis.
An interesting avenue for future research would be to investigate whether the market treats

23

recognised pension accounting information as if it is more reliable than the equivalent
disclosed information.

24

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27

Table 1: Sample Selection
Panel A: Selection of sample of firms
No. of firms
London Stock Exchange FTSE 350 Index Constituentsas of December 31, 2006:350- not sponsoring defined benefit pension plans-142- financial service sector firms-31- US GAAP-1- adopting ‘corridor approach’ to account for actuarial gains/losses-5- early adopters of FRS 17 in 2004

-39

Sample firms as per Dec. 31, 2006:

132

Panel B: Selection of firm-year observations
Year
2004
2005
2006
Total
Number of sample firms
132
132
132
396
Missing values for firmand pension related data

14

14

13

41

Book value of equity <0

1

0

1

2

117

118

118

353

Firm-years

28Table 2:

Descriptive Statistics
Panel A: Period of Disclosure

Variables
MVE

N
195

Mean
3666.61

MVE/NOSH

195

BE

193

5.08
(0.00)a2393.72

BVE/NOSH

193

NPL

193

NPL/NOSH

193

FVPA

194

FVPA/NOSH

194

PBO

193

PBO/NOSH

193

NI

194

NI/NOSH

194

PC

197

PC/NOSH

196

SALEGRW

192

R&D

195

R&D/NOSH

195

EMP

195

EMP/NOSH

195

2.75(0.11)-225.82-0.34(0.19)
1079.77
1.65(0.20)-1308.34-2.02(0.15)
169.610.43(0.00)
169.610.05(0.03)
0.08(0.63)
42.84
0.03(0.65)
27.72
0.06(0.93)

Std.
Dev.
10858.80
4.6310800.00

Median914.00N
195

Mean5013.16

Std.
Dev.
11558.88

Median1334.44

3.24(0.00)b
410.00

195

7.28

7.22

4.49

192

2006.816550.72

573.941.65(0.26)-54.00

192

2.84

2.98

1.77

192

-216.05

572.02-46.16-0.20(0.35)
227.92

192

-0.30

0.41

-0.17

193

1387.68

3509.26368.800.78(0.05)-288.40

193

1.95

2.50

1.03

192

-1601.963963.74-444.20-1.09(0.36)
62.85

192

-2.26

2.83

-1.27

195

357.211968.69

96.57

0.28
(0.01)
8.50

195

0.63

0.79

0.35

198

25.20

56.02

6.00

0.03
(0.06)
0.06(0.29)
0.00

195

0.04

0.06

0.02

192

0.09

0.13

0.07

195

81.09

408.240.00

0.00(0.48)
8.68

195

0.04

0.15

0.00

195

28.49

60.64

11.65

0.03
(0.78)

195

0.07

0.17

0.03

2.82
639.120.443300.982.21
3916.64

Panel B: Period of Recognition

2.63
1039.57
0.47
62.53
0.08
0.14
265.22
0.12
58.84
0.13

Notes:
This table presents the summary descriptive statistics for the sub-samples during the period of disclosure (Panel A)
and for the sub-sample during the period of recognition (Panel B). N indicates the number of firm-year observations.
MVE is the market value of equity (closing price 3 months following the firm’s fiscal year end). BVE is the bookvalue of equity (excluding the net pension liability/asset). NPL is the net pension liability/asset. FVPA is the fairvalue of pension assets. PBO is the projected pension benefit obligations. NI is the net income before extraordinary
items, R&D and pension expenses. PC is the net periodic pension expenses. SALEGRW is the average sales growthover the previous three years. R&D is the research and development expense. EMP is the number of employees (inthousands). Variable amounts are £million totals and negative values represent liabilities or net liabilities. NOSH isthe number of shares issued at the accounting year end. All variables with deflator NOSH are measured on a per-sharebasis. a,b Values reported in parentheses below the means (medians) for disclosure sub-sample are p-values from twotailed paired t-tests (Wilcoxon sign rank tests) of the null hypothesis that the mean (median) for that sample equals themean (median) of the recognition sub-sample.

29

TABLE 3
Pearson and Spearman Correlations of Full Sample
Variable

MVE

NPL

FVPA

PBO

NI

PC

-0.1619*0.2430*-0.2357*

0.8210*0.2422*0.2453*-0.0770.2254*0.7384*-0.4306*

0.4647*-0.4805*

0.7141*0.4207*0.057-0.016

0.3793*-0.6969*

0.7562*-0.2656*-0.7783*0.1342*-0.1545*-0.5005*

1-0.9937*0.3126*

0.7217*-0.1388*0.2401*0.5592*-0.9930*

1-0.3128*-0.7571*0.1343*-0.2384*-0.5823*

0.3268*0.1322*0.026

0.2141*1-0.0810.128

0.5294*-0.130-0.3077*

FVPA

0.2537*0.3696*-0.6793*-0.2437*-0.3737*0.7579*NI

0.8033*0.7299*-0.1496*0.2524*-0.2461*1PC

0.2111*0.3167*-0.7020*0.7305*-0.7633*

0.2503*

R&D
EMP

EMP

1

1

SALEGRW

R&D

0.7370*NPL

PBO

SALEGRW

1

MVE
BVE

BVE

0.1752*

0.128

0.093

-0.069

0.077

0.112

1

-0.0550.2343*0.049-0.1290.052-0.0640.3336*0.040-0.0460.5420*0.4821*-0.2564*0.3725*-0.3759*

0.3458*0.3799*0.003-0.0620.022
1-0.046-0.0901

Notes:
Upper (Lower) Diagonal: Pearson (Spearman) Correlation Coefficients. All correlations are based on variables scaled by the number of shares outstanding at the end of the accounting
year (NOSH). MVE is the market value of equity (closing price 3 months following the firm’s fiscal year end). BVE is the book value of equity (excluding the net pension liability/asset).
NPL is the disclosed (recognised) net pension liability/asset. FVPA is the fair value of pension assets. PBO is the projected pension benefit obligations. NI is the net income before
extraordinary items, R&D and pension expenses. PC is the net periodic pension expense. SALEGRW is the average sales growth over the previous three years. R&D is the research anddevelopment expense. EMP is the number of employees (in thousands). * represents significant at the 1% level (2-tail).

30

TABLE 4
Tests of Value Relevance of Pension Liability/Asset Valuesof the Full Sample

Panel A: Equation 1

Coeff.
α0

Predicted
Sign+

Coefficient
Estimates
2.429

t-statistic
3.20

p-value
0.002

BVE

α1

+

1.351

4.53

0.000

NPL

α2*

+

2.081

2.22

0.029

NI

α5

+

3.389

3.59

0.000

PC

α6

-

-7.054

-2.80

0.006

SALEGRW

α7

+

3.363

1.68

0.095

R&D

α8

?

-13.064

-1.94

0.054

EMP

α9

?

-13.604

-1.12

0.263

VariableIntercept

Adj. R2

0.557

No. of firm-year Obs.

353

Panel B: Equation 2

Coeff.
α0

Predicted
Sign+

Coefficient
Estimates
2.453

t-statistic
4.04

p-value
0.000

BVE

α1

+

1.231

4.24

0.000

FVPA

α3*

+

3.454

4.43

0.000

PBO

α4*

+

2.720

3.45

0.001

NI

α5

+

2.846

3.12

0.002

PC

α6

-

-6.181

-2.33

0.022

SALEGRW

α7

+

3.660

1.78

0.078

R&D

α8

?

-12.488

-1.96

0.053

EMP

α9

-2.09

0.039

α3* = α4*0.000

VariableIntercept?

Adj. R2

0.602

No. of firm-year Obs.

353

-22.212
F-testNotes:
This table presents results from estimating equations (1) and (2) on value relevance of pension liability/asset values during theentire sample period. MVE is the market value of equity (closing price 3 months following the firm’s fiscal year end); BVE is thebook value of equity (excluding the net pension liability/asset); NPL is the disclosed net pension liability/asset. FVPA is the fairvalue of pension assets. PBO is the projected pension benefit obligations. PC is periodic pension expense. NI is the net income
before extraordinary items, R&D and pension expenses; SALEGRW is the average sales growth over the previous three years;
R&D is the research and development expense; EMP is the number of employees in thousands. All regression variables are scaledby the number of shares outstanding at the end of the accounting year. Coefficients on NPL (α2*) and PBO (α4*) are expected to bepositive as liabilities are measured as negative amounts. Huber-White heteroskedasticity robust t-statistics are reported inparentheses next to the coefficient estimates. All p-values are based on two-tailed t-tests.

31

TABLE 5
Tests of Value Relevance of Recognised versus Disclosed Net Pension Liability/Asset Values
For the Pre- versus Post- IAS 19 periods
Equation 3

VariableIntercept(n=353)

Coeff.
α0

Predicted
Sign+

Coefficient
Estimates
2.360

t-statistic
4.96

p-value
0.000

D

α02

?

-0.007-0.037

0.970

BVE

α1

+

1.102

4.76

0.000

D*BVE

α10

?

0.196

2.11

0.037

NPL

α2*

+

0.358

0.72

0.474

D*NPL

α11*

+

1.195

2.84

0.005

NI

α5

+

0.722

0.87

0.387

D*NI

α13

?

1.548

2.29

0.024

PC

α6

-

-3.122

-1.79

0.075

D*PC

α13

+

5.418

1.59

0.114

SALEGRW

α7

+

2.072

1.43

0.154

D*SALEGRW

α14

?

0.835

0.71

0.477

R&D

α8

?

-5.445

-0.83

0.408

D*R&D

α15

?

1.137

0.73

0.467

EMP

α9

?

-7.545

-1.36

0.175

D*EMP

α16

?

0.884

0.82

0.412

Adj. R2

0.735
α2*+ α11*

+

1.553

2.72

0.008

α6+ α13

+

2.296

0.66

0.509

32

TABLE 5 (Cont’d)Notes:
This table presents results from the tests of value relevance of recognised versus disclosed pension liability/asset values on a‘net’ basis for the pre- and post-IAS 19 periods by estimating equations (3). The dummy variable D is coded 1 for the period ofrecognition (post-IAS 19), and 0 for the period of disclosure (pre-IAS 19). MVE is the market value of equity (closing price 3
months following the firm’s fiscal year end); BVE is the book value of equity (excluding the net pension liability/asset); NPL is
the disclosed net pension liability/asset. FVPA is the fair value of pension assets. PBO is the projected pension benefit
obligations. PC is periodic pension expense. NI is the net income before extraordinary items, R&D and pension expenses;
SALEGRW is the average sales growth over the previous three years; R&D is the research and development expense; EMP is
the number of employees in thousands. All regression variables are scaled by the number of shares outstanding at the end of theaccounting year.
b
Coefficients on NPL (α2*) and PBO (α4*) are expected to be positive as liabilities are measured as negative amounts.
c
Variables with prefix D* are interaction variables with the dummy variable (D) which capture the transition from thedisclosure to the recognition pension accounting regime.
d
Huber-White heteroskedasticity robust t-statistics are reported in parentheses next to the coefficient estimates. All regressions
control for fixed year and industry effect.
e
All p-values are based on two-tailed t-tests.
a33TABLE 6
Tests of Value Relevance of Recognised versus Disclosed Pension Liability and Pension Asset Values
over the Pre- and Post- IAS 19 periods
Equation 4
VariableIntercept(n=349)Coeff.
α0

Predicted
Sign+

Coefficient
Estimates
2.376

t-statistic
6.10

p-value
0.000

D

α02

?

0.074

0.41

0.684

BVE

α1

+

1.012

5.25

0.000

D*BVE

α10

?

0.173

1.81

0.073

FVPA

α3*

+

2.514

3.28

0.001

D*FVPA

α11*

+

0.411

0.80

0.424

PBO

α4*

+

1.533

2.63

0.010

D*PBO

α12*

+

0.750

1.54

0.125

NI

α5

?

0.216

0.30

0.765

D*NI

α13

?

1.875

3.08

0.003

PC

α6

-

-2.362

-1.29

0.201

D*PC

α14

?

4.548

0.96

0.338

SALEGRW

α7

+

2.415

1.75

0.082

D*SALEGRW

α15

?

1.347

1.16

0.248

R&D

α8

?

-5.515

-0.84

0.404

D*R&D

α16

?

0.709

0.48

0.630

EMP

α9

?

-19.039

-2.95

0.004

D*EMP

α17

?

1.187

1.32

0.190

2

0.755

F-testα3* = α4*0.010

α3*+ α11*

+

2.925

3.84

0.000

α4*+ α12*

+

2.283

3.47

0.001

Adj. R

34

TABLE 6 (cont’d)Notes:
This table presents results from the tests of value relevance of recognised versus disclosed pension liability/asset values on an‘aggregate’ basis for the pre- and post-IAS 19 periods by estimating equations (4). The dummy variable D is coded 1 for theperiod of recognition (post-IAS 19), and 0 for the period of disclosure (pre-IAS 19). MVE is the market value of equity (closing
price 3 months following the firm’s fiscal year end); BVE is the book value of equity (excluding the net pension liability/asset);
NPL is the disclosed net pension liability/asset. FVPA is the fair value of pension assets. PBO is the projected pension benefit
obligations. PC is periodic pension expense. NI is the net income before extraordinary items, R&D and pension expenses;
SALEGRW is the average sales growth over the previous three years; R&D is the research and development expense; EMP is thenumber of employees in thousands. All regression variables are scaled by the number of shares outstanding at the end of theaccounting year.
b
Coefficients on NPL (α2*) and PBO (α4*) are expected to be positive as liabilities are measured as negative amounts.
c
Variables with prefix D* are interaction variables with the dummy variable (D) which capture the transition from the disclosure
to the recognition pension accounting regime.
d
Huber-White heteroskedasticity robust t-statistics are reported in parentheses next to the coefficient estimates. All regressions
control for fixed year and industry effect.
e
All p-values are based on two-tailed t-tests.
a35