longitudinal value relevance of earnings and intangible assets: evidence from australian firms

Journal of International Accounting, Auditing and Taxation15 (2006) 72–91

Longitudinal value relevance of earnings andintangible assets: Evidence from Australian firms

John Goodwin a, Kamran Ahmed b,∗a School of Accounting and Law, RMIT University, Melbourne, Australia

b School of Business, La Trobe University, Melbourne, Australia

Abstract

Recent U.S. studies report that earnings value relevance has declined over time. Some authors suggest non-recognition of intangible assets in the U.S. is a major reason for declining earnings value relevance. However,the evidence is mixed on the effect of non-recognition of intangible assets. To examine this conjecture, thispaper examines earnings value relevance for Australian firms since Australian GAAP has not prohibitedintangible asset recognition. Using a variety of established models and specifications, our results indicatethat for the average firm, there is weak evidence of decline in earnings value relevance. However, firms thatcapitalize intangibles have increasing earnings value relevance. Further, the magnitude of the difference inearnings value relevance between capitalizing firms and non-capitalizing firms is most pronounced in thelatter part of the 1990s and this difference is increasing.© 2006 Elsevier Inc. All rights reserved.

Keywords: Longitudinal earnings value relevance; Intangible assets; Australian GAAP

1. Introduction

Studies in the U.S. have documented that the value relevance of earnings has declined overthe last few decades as measured by the extent of association between either share price orshare returns and accounting earnings (see for example, Brown, Lo, & Lys, 1999; Chang, 1998;Collins, Maydew, & Weiss, 1997; Ely & Waymire, 1999; Francis & Schipper, 1999; Lev &Zarowin, 1999).1 Lev and Zarowin (1999) attribute this decline to the lack of proper recognitionof intangibles in the financial statements by U.S. companies. Recent studies have documented

∗ Corresponding author. Tel.: +61 3 9479 1125; fax: +61 3 9479 3278.E-mail address: [email protected] (K. Ahmed).

1 This is the conclusion when returns regressions are estimated. The evidence is mixed when price ‘levels’ regressionsare estimated. For example, overall Francis and Schipper (1999) report mixed evidence about changing value relevanceof earnings and book value. However, they report that earnings value relevance has declined significantly using a returns

1061-9518/$ – see front matter © 2006 Elsevier Inc. All rights reserved.doi:10.1016/j.intaccaudtax.2006.01.005

J. Goodwin, K. Ahmed / Journal of International Accounting, Auditing and Taxation 15 (2006) 72–91 73

that the capital market values capitalization of intangibles positively and significantly comparedwith immediate expensing in the income statement (Aboody & Lev, 1998; Abrahams & Sidhu,1998; Ahmed & Falk, 2003; Lev & Sougiannis, 1996).

Whether intangible accounting affects longitudinal earnings value relevance is an importantquestion and is best investigated in an environment in which accounting for intangibles is differentthan in the U.S. and where economic trends are similar to the U.S. Omitting intangibles from bal-ance sheets may reduce earnings value relevance, possibly because the omission of the associatedamortization from the income statement hinders matching. Assuming the relative importance ofintangibles has increased with time vis-a-vis tangible assets, some authors assert that immediateexpensing of certain intangibles is the primary cause of declining earnings value relevance (seeLev & Zarowin, 1999; Stewart, 1997). Others contend that immediate expensing of intangibles isnot as important as other causes, such as the increase in percentage of losses and one-time items(Collins et al., 1997) or the increase in returns volatility (Francis & Schipper, 1999) in explainingdeclining earnings value relevance. These studies use proxy variables to examine the policy ofimmediately expensing intangible assets since such assets are generally not recognized under U.S.GAAP.

The purpose of this study is to examine whether the value relevance of earnings has declinedover time in Australia using a large sample of about 13,000 firm-year observations spanning 25years beginning in 1975. In particular, this study seeks to investigate whether or not capitalizationof intangibles such as research and development expenditure, deferred costs and other intangi-bles has an effect on longitudinal value relevance. Australia has six standards that deal directlywith intangible assets: AASB 1008 Leases, AASB 1009, Construction Contracts, AASB 1013Accounting for Goodwill, AASB 1022 Accounting for the Extractive Industries, AASB 1036 Bor-rowing Costs and AASB 1011 Accounting for Research and Development Costs. Except for R&D,these assets are excluded from this study since the literature focuses on intangibles for which thereis no standard (e.g. brands, licences, trademarks), inadequate accounting (e.g. R&D) or proposalsto change standards (e.g. internally-developed software). Therefore, this study focuses on assetsthat are immediately expensed under U.S. GAAP and have been capitalized under AustralianGAAP.

Yearly cross-sectional regressions are estimated for each year from 1975 to 1999 followingFrancis and Schipper (1999) and Lev and Zarowin (1999). There is evidence of a decline inearnings value relevance as measured by the explanatory power of ordinary least squares (OLS)regression model (adjusted R2, hereafter R2) and by earnings coefficients over this 25-year period,consistent with U.S. studies (Lev & Zarowin, 1999). However, only losses explain much ofthe decline, which is inconsistent with U.S. studies. Consistent with U.S. studies, the resultsshow increasing value relevance of earnings and book value combined (Francis & Schipper,1999). Further, the results show that earnings value relevance has declined for firms which do notrecognize intangible assets (hereafter “non-capitalizers”), and there is weak evidence of decline forfirms which recognize intangible assets (hereafter “capitalizers”). The increasing value relevanceof earnings and book value is due to the capitalizers. Results are robust to various alternativeexplanations and different model specifications.

design. In longitudinal studies, levels regressions may result in spurious inferences being made due to changes in thecoefficient of variation over time (Brown et al., 1999). Brown et al. (1999) formally show the problem with scale effects.After controlling for scale effects there is evidence of declining earnings and book-value relevance using a levels design(see for example, Brown et al., 1999 and Chang, 1998).

74 J. Goodwin, K. Ahmed / Journal of International Accounting, Auditing and Taxation 15 (2006) 72–91

The important finding is the over-time widening of the value relevance ‘gap’ between capital-izers and non-capitalizers, which occurs in Australia’s relatively unregulated reporting regime forintangibles. For capitalizers in the 1990s, the period when this gap is widest, firms that amortizegenerally have stronger earnings value relevance than non-amortizers. Tests for the value rele-vance of amortization for the most recent 8 sample years reveal amortization level and its changeare significant for different types of intangibles. The results have implications for value relevanceof earnings for firms that capitalize intangibles assets, particularly research and development(R&D) expenditure, given that Australia, like many other countries including those comprisingthe European Union, have adopted the International Financial Reporting Standards (IFRS) fromJanuary 2005. The new accounting standard AASB 138 Intangible Assets (outside the period ofthe present study), requires the immediate expensing of all expenditure of the research compo-nent of R&D and development expenditure may be capitalized provided that certain conditions fordeferral are satisfied.2 This standard is less restrictive in terms of meeting the beyond reasonabledoubt criteria required by the former standard on R&D and allows more managerial discre-tion on the capitalization of the development component of R&D expenditure (Deegan, 2005,Chapter 7).

2. Accounting for intangibles

Under Australian GAAP, disclosure of intangible amortization, write-offs and the total ofintangible assets are mandatory.3 Disclosure of intangible expenditures is not required exceptfor R&D expenditure. There are, however, no specific standards for most intangibles meaningrecognition and measurement of intangibles are subject only to general provisions. For example,the Corporations Act requires the accounts to show a true and fair view4 (Sections 292 and 293 ofthe Corporations Act). Since 1992, SAC 4 Definition and Recognition of the Elements of FinancialStatements, which is non-legally binding, permits recognition of assets when it is probable thefuture economic benefits will eventuate and the asset has a cost or other value that can be measuredreliably (para 38 SAC 4). Australian firms can choose to capitalize or immediately expense mostintangibles.

Two standards deal with the measurement of capitalized intangibles: AASB 1021 Depreciationand AASB 1010 Accounting for the Revaluation of Non-Current Assets. AASB 1021 requires adepreciable non-current asset to be depreciated on a systematic basis over its useful life. AASB1010 imposes a loose impairment test on non-current assets, and requires them to be written downto recoverable amount when that amount exceeds net book value. AASB 1010 also allows suchassets to be written up to recoverable amount, with the increment credited to the asset revaluationreserve.5

Apart from goodwill, AASB 1011 Accounting for Research and Development Costs dealsdirectly with an intangible. AASB 1011 was issued in 1987 and requires R&D costs to pass a

2 AASB 138 Intangible Assets permits an intangible asset to be recognized if: (a) it is probable that the future economicbenefits that are attributable to the asset will flow to the enterprise and (b) the cost of the asset can be measured reliably.

3 These provisions are in AASB 1018 Statement of Financial Performance and AASB 1040 Statement of FinancialPosition, having previously been contained in AASB 1034 Financial Report Presentation and Disclosures and prior tothat the Corporations Law and its predecessors. That these disclosures are mandatory is a sometimes overlooked fact.

4 There is, however, no definition of ‘true and fair view.’5 This is the general rule. A revaluation increment can be revenue when an asset(s) from that class was previously

revalued down and the decrement expensed. In this case the revenue is limited to the amount of the previous expense(s)with any excess credited to the revaluation reserve (para 6.2(a) AASB 1010).


“beyond reasonable doubt” test in order to be capitalized (Cl. 30 AASB 1011). Once capitalizedthe deferred R&D is to be amortized over the life of expected benefits (Cl. 32 AASB 1011) startingwhen commercial productions starts (Cl. 32 AASB 1011). In short, the standard permits R&Dcapitalization under a tougher recognition test than for other intangibles.

3. Prior research and motivation

Recent studies report a decline in the value relevance of U.S. firms’ earnings over the past fewdecades, but they offer different reasons for this decline. Motivated by claims from members of theaccounting profession and analysts that accounting has lost relevance, Collins et al. (1997) reportthat the value relevance of earnings has decreased over the 1953–1994 period, and this decline hasbeen more than compensated by an increase in value relevance of book value. They state muchof this switch from earnings to book value is explained by the increase in relative magnitude ofone-time items, loss-making firms and smaller firms. Francis and Schipper (1999) report “mixedevidence” that earnings and book value have lost relevance over the period 1952–1994. However,they find a decline in earnings value relevance using a returns design, which they attribute toincreased variability of share returns. They also report only marginal evidence that earnings valuerelevance has declined more for high technology than for low technology stocks, leading them toconclude: “We do not believe evidence of a decline in the value relevance of financial informationcan be attributed solely, or even primarily, to the increasing number and importance of high-techfirms in the economy” (Francis & Schipper, 1999, p. 347). To control for scale effects, Chang(1998) uses several alternative measures to Collins et al. (1997) and Francis and Schipper (1999)and concludes that both earnings and book value have declined over the period 1953–1996. Chang(1998) reports a decline in value relevance of accruals for U.S. firms from the mid 1970s, which isattributed to the introduction of immediate expensing for R&D. Declines in both R2 and earningsresponse coefficient (ERC) are also reported by Lev and Zarowin (1999) over a more recentperiod 1977–1996, which they contend capture a period of significant economic change. Theyargue that relative increases in losses and one-time items, offered by Collins et al. (1997) as twoof the causes of the shift from earnings to book value over time, are symptoms of inadequaciesof the U.S. accounting model rather than causes of the decline. They provide evidence that thedecline is driven by the increase in business change coupled with the failure of U.S. GAAP toadequately record change drivers, namely R&D assets. Specifically, immediate expensing of R&Dunder U.S. GAAP results in a poor matching of benefits with the costs to generate those benefits,especially when the R&D investment rate increases. They suggest that as the relative importanceof intangibles has increased over the past 20 years, U.S. GAAP earnings reflects less value relevantinformation today than it did in the past. Lundholm and Myers (2000) report declines in R2s aredue primarily to increases in voluntary disclosures that enable investors to better forecast earnings.Thus information in earnings is ‘brought’ forward in the sense that over time it is impounded inprice earlier. A decline in R2 is also reported by Brown et al. (1999) although they provide noreason for the decline. It is fair to say that the value relevance of U.S. earnings has declined overthe past few decades and that the specific causes of this decline are not clear.6

6 Another reason may be increasing conservatism, reported by Basu (1997), Givoly and Hayn (2000) and Holthausenand Watts (2001). Givoly and Hayn (2000) report the temporal increase in conservatism in the U.S. contributes to the risein market-to-book ratios and this increase is additional to the non-recognition of intangible assets as an explanator of themarket-to-book rise.


One potential cause of the decline, intangible accounting, is examined in these studies morethan any other for two main reasons. First, there is U.S. and international evidence that investorsview intangibles to be an ‘asset’ yet U.S. firms rarely recognise such assets (see for exam-ple, Abrahams & Sidhu, 1998 and Lev & Sougiannis, 1996 for R&D, Aboody & Lev, 1998for software costs, and Barth & Clinch, 1998 for upward revaluations of intangibles). Sec-ond, it has been argued by some (for example, Lev, 2001) that there has been a considerable‘shift’ in the relative importance of intangible assets over time. Lev (2001) states that the twoforces that have caused the shift toward intangibles, are an increase in global competition andchanges in information technology (Lev, 2001, p. 16). These forces are not unique to the U.S.7

For example, a recent Productivity Commission8 report highlighted the importance for Aus-tralia’s automotive industry to “evolve further if it is to be competitive in a global context”(Productivity Commission, report no. 25, 9). Australia’s uptake of information technology has,in large part, driven its economic growth throughout the 1990s, in a similar vein to the U.S.and some other high-income countries (Productivity Commission, 2004, Commission researchpaper).

There are other similarities between the Australian and U.S. economic environments. Forexample, it has been well documented that the U.S. and Australia’s business cycles are highlycorrelated and this relation is long term (see for example, de Roos & Russell, 1996; McTaggart &Hall, 1993). Further, de Brouwer and Romalis (1996) show that despite the difference in size, theindustrial structures of the two countries are similar over the period 1977–1993. For instance, themining sector, often cited as a major underpinning of the Australian economy, comprises about5% of gross domestic output in Australia and about 3% in the U.S. over the period 1977–1993(de Brouwer & Romalis, 1996). Other industry sectors have similar relations with the exceptionof finance, where the U.S. is relatively larger. These similarities are important for this study sincewe test for changing value relevance for the average firm and changes in the industry mix canaffect this longitudinal relation (Collins et al., 1997).

In this paper longitudinal value relevance is studied under a relatively unregulated reportingregime for intangibles. Under this reporting regime, firms have recognized intangible assets,both acquired and internally generated, at cost or value, and employed different accountingpractices after initial recognition.9 In so doing, this study is related to the above studies examin-ing over-time value relevance but measures intangibles by the amount in the balance sheet andthe reported amortization. Prior U.S. studies did not use such measures. Rather, they proxy forunrecorded intangibles using an industry classification or they use R&D expenses in the incomestatement.

Using reported amounts gives some control for inter-industry differences, both accounting andeconomic. For example, banks and insurance companies, typically classified as non-intangible-intense firms, often use market value accounting, which increases (lowers) the earnings level(change) coefficient and increases R2 compared to historic cost. Banks and insurance companies

7 Lev argues that intangibles can provide firms with a competitive edge because such assets are usually not traded, theirbenefits vest in the firm and they can provide investors with abnormal rates of return. Plant, equipment and other fixedassets’ rates of return have been driven down to normal rates of return by the exhaustion of economies of scale over time(Lev, 2001, p. 16).

8 The Productivity Commission is the Australian Government’s Principal Review and Advisory Body on MicroeconomicPolicy and Regulation.

9 Internally generated intangibles initially recognized at value are rare however. 3408 accounts were examined in theperiod 1984–1999 for firms with capitalized intangibles (excluding goodwill), and there were 47 (about 1.3%) instancesof initial recognition of an intangible asset by crediting the asset revaluation reserve account.


also tend to be big and size and risk are negatively related (Banz, 1981).10 Second, a broadcoverage of intangibles is achieved, thereby capturing assets (licences, mastheads, patents, etc.),that may drive future earnings. This coverage could bias against consistent finding, strong resultsas different intangibles are likely to have different economic lives, and those lives vary by industryfor the same type of intangible (Lev & Sougiannis, 1996).

About 30% of Australian firms capitalize intangibles, so higher earnings value relevance mightbe expected for the average firm in Australia than the U.S., ceteris paribus. This qualified expec-tation is subject to at least two caveats. First, the relatively unregulated reporting environment forintangibles in Australia means all firms do not adopt uniform measurement and amortize policies.Inspection of 3408 accounts (about 90% of capitalizers) over the period 1984–1999 reveals about70% of intangible assets are amortized and of the remainder, about 10%, are recorded at valueabove cost and about 20% are at cost.11 Firms use different policies for different intangibles.Second, intangible assets comprise assets with different risk profiles (R&D versus advertising)and economic lives (deferred expenses versus licences).

Regarding earnings value relevance between capitalizers and non-capitalizers, there are rea-sons to expect higher earnings value relevance for capitalizers. Capitalizers are bigger thannon-capitalizers (see Table 1). Big firms provide more informative disclosures than small firms(Lang & Lundholm, 1993). More informative disclosure and the cost of equity capital are neg-atively related (Botosan, 1997) and one expects earnings persistence to be decreasing with thecost of equity capital. Additionally, big firms are likely more successful and report more goodnews (Lang & Lundholm, 1993) and good news and the ERC are positively related (Basu, 1997).However, there are also reasons to expect that capitalizers’ earnings value relevance will be lowerthan non-capitalizers. Freeman (1987) and Collins and Kothari (1989) report value relevant infor-mation in big firms’ earnings is impounded earlier than for small firms, leading to lower R2s andERCs for big firms. Kerstein and Kim (1995) extend this finding to non-earnings information,capital expenditures. Additionally, the contemporaneous returns–earnings relation is weaker forhigher disclosure level firms (Lang & Lundholm, 1993).

For the above reasons, size (among other variables) is controlled for by including size as anadditional explanatory variable in specification checks conducted below in Section 6. Whetherintangible capitalization and the associated ‘mix’ of accounting policies affects earnings valuerelevance for the average Australian capitalizer firm is an untested empirical question and thefocus of this study.

4. Research method and data collection

The earnings and earnings change model estimated for each year, is used to examine earningsvalue relevance:

rit = α0 + α1Eit + α2�Eit + εit (1)

where rit are the raw returns for firm i measured from the first month of the financial year throughto the end of the last month of the financial year, Eit the annual net result (net profit or net loss)

10 Although not prevalent, there are capitalizers in these two industries (89 firm years over the sample period). The meanmarket capitalization (at financial year end) for firms in these industries is in the top 25% in every year except 1980 andthey have become relatively larger than the average firm over time.11 These figures include deferred costs and R&D which inflate the amortize group. Excluding deferred costs and R&D

the percentages are about: 52% (amortized), 19% (value above cost) and 29% (cost).

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Table 1Descriptive statistics

Period Non-capitalizers Capitalizers

N Size BM Lev ROE Intangibleindustry (%)

N Size BM Lev ROE Intangibleindustry (%)

Intangible intensitymean

(Panel A) Descriptive statistics for the non-capitalizer and capitalizer samples1975–1976 444 28.74 1.97 0.48 0.13 0.33 138 44.47 1.92 0.49 0.11 0.33 0.011977–1979 1091 36.10 1.82 0.44 0.12 0.29 289 39.06 1.77 0.48 0.14 0.33 0.011980–1982 1197 75.64 1.77 0.38 0.01 0.22 306 85.94 1.34 0.45 0.06 0.28 0.021983–1985 1204 93.05 1.48 0.35 0.01 0.20 364 128.36 1.45 0.45 0.06 0.36 0.041986–1988 696 162.91 1.05 0.38 0.06 0.21 395 293.08 0.95 0.53 0.07 0.45 0.091989–1991 848 200.90 1.63 0.37 −0.17 0.14 521 426.50 1.91 0.53 −0.12 0.38 0.121992–1994 1036 285.87 1.12 0.30 −0.11 0.12 514 634.67 1.27 0.50 −0.01 0.50 0.131995–1997 1542 307.04 0.96 0.29 −0.05 0.14 847 622.80 0.92 0.52 −0.00 0.46 0.131998–1999 993 420.12 1.14 0.35 −0.15 0.16 493 738.71 0.84 0.60 0.01 0.52 0.13

All 9055 194.7 1.40 0.36 −0.02 0.19 3864 443.6 1.28 0.51 0.02 0.42 0.09

Size BM Lev ROE

(Panel B) Comparison of means between non-capitalizer and capitalizer samples1975–1976 Difference (t-statistics) 15.7 (1.39) −0.05 (−0.38) 0.01 (0.45) −0.02 (−1.60)1977–1979 Difference (t-statistics) −2.96 (−0.54) −0.05 (−0.54) 0.04 (3.30)† 0.02 (0.26)1980–1982 Difference (t-statistics) 10.28 (0.83) −0.43 (−0.87) 0.07 (5.08)† 0.05 (0.68)1983–1985 Difference (t-statistics) 35.31 (2.14)† −0.03 (−0.36) 0.10 (7.33)† 0.05 (1.51)1986–1988 Difference (t-statistics) 130.17 (5.20)† −0.10 (−1.42) 0.15 (9.34)† 0.01 (0.12)1989–1991 Difference (t-statistics) 225.60 (3.24)† 0.28 (2.34)† 0.16 (3.20)† 0.05 (1.46)1992–1994 Difference (t-statistics) 348.78 (3.12)† 0.15 (1.71)† 0.20 (9.39)† 0.09 (1.31)1995–1997 Difference (t-statistics) 315.76 (3.24)† −0.04 (−0.52) 0.23 (18.00)† 0.04 (0.72)1998–1999 Difference (t-statistics) 318.59 (2.11)† −0.30 (−2.85)† 0.25 (6.65)† 0.16 (3.38)†

All Difference (t-statistics) 248.80 (7.38)† −0.12 (−1.67)‡ 0.15 (18.41)† 0.03 (1.72)‡

N is the number of firms. Size is market value of the firm at the end of the financial year expressed in million AUS$. BM is book value of equity (net assets to parent members)divided by market value of equity both at the start of the financial year. Leverage is total liabilities divided by total assets less intangible assets all at the end of the financialyear. ROE is net result plus all amortization divided by the average of book value less intangible assets at the start and book value less intangible assets at the end of thatfinancial year. Intangible industry (%) is the number of firms that are in intangible-intensive industries divided by the total number of firms in that group that period, whereintangible-intensive industry is defined to comprise the following industries (group codes): alcohol and tobacco (8), chemicals (10), media (15), telecommunications (18),healthcare and biotechnology (21), miscellaneous industrials and services (22), diversified industrials (23) and tourism and leisure (24). Intensity is the ratio of intangible assetsdivided by financial year-end total assets. Intangible intensity ratio is calculated as the book value of intangible assets at year end divided by total assets at year end.† Significant at the 0.05 level (two-tailed).‡ Significant at the 0.10 level (two-tailed).


for firm i scaled by beginning-of-financial year market value, �Eit the change in annual net result(net profit or net loss) for firm i scaled by beginning-of-financial year market value, and εit is theerror term.

The earnings and earnings change model is used for several reasons. First, prior researchsuggests inclusion of earnings change improves informativeness of earnings (see Ohlson, 1995for theory and Easton & Harris, 1991 for evidence). Second, earnings change can indicate thedegree of earnings persistence (see Ali & Zarowin, 1992; Ohlson, 1995). And third, the modelis commonly used which improves comparability. Following prior research (Ely & Waymire,1999; Lev & Zarowin, 1999; Nwaeze, 1998), R2 and the earnings response coefficient are used asmeasures of earnings value relevance. The R2 indicates the relative ability of earnings numbers toexplain returns and the ERC indicates the average change in returns associated with a one-dollarchange in earnings. The ERC is defined as the sum of the coefficients for earnings level and changeand when earnings are more persistent, earnings change provides complimentary information toearnings level about future earnings (Ali & Zarowin, 1992; Ohlson, 1995).

We also estimate a levels regression to examine the value relevance of financial statementinformation:

Pit = α0 + α1ESit + α2BVit + εit (2)

where Pit is the share price for firm i measured at the end of the financial year, ESit the annual netresult (net profit or net loss) for firm i scaled by the number of shares at the end of the financialyear, BVit the book value (net assets to parent members) for firm i scaled by the number of sharesat the end of the financial year, and εit is the error term.

Ordinary share price data for 1974–1999 are hand collected from the Australian GraduateSchool of Management (AGSM) prices and price relatives database and annual (raw) returnscalculated for all firms that have usable data for each month. Earnings and other accounting dataare obtained from the: (1) AGSM’s CRIF database for 1974–1985, (2) AGSM Annual Report Filefor 1986 and 1987 and (3) Australian Stock Exchange (ASX) Findata database for 1988–1999.Observations with negative book values at the start of the financial year (139 observations) weredeleted to reduce the influence of these outliers following prior studies. The final sample comprises12,918 firm-year observations over 25 years from 1975 to 1999.

In the tests conducted below, firms are classified as capitalizers if they recognize intangibleassets (excluding goodwill). On the assumption that it is only intangible amortization that improvesearnings value relevance, classifying firms in this way likely biases toward accepting the nullhypothesis of no difference in earnings value relevance between capitalizers and non-capitalizers,since about 30% of capitalizers do not amortize.

5. Descriptive statistics and results

5.1. Descriptive statistics

Panel A of Table 1 reports descriptive statistics for the capitalizer and non-capitalizer samples.It is evident that capitalizers are, on average, larger than non-capitalizers and the relative size,measured by market value of the firm at the end of financial year, of capitalizers has increased.This can be seen from the comparison of means shown in Panel B, where the size differencesare significant at the 0.05 level only after 1980–1982. Book-to-market is measured by book valuedivided by market value both at the start of the financial year. Book value is unadjusted for


Table 2Descriptive statistics for regression variables

Variable All firms Non-capitalizers Capitalizers

Mean (median) S.D. Mean (median) S.D. Mean (median) S.D.

Returns 0.29 (0.12) 1.33 0.30 (0.12) 1.42 0.26 (0.11) 1.07Price 1.80 (0.97) 3.03 1.72 (0.90) 3.06 2.00 (1.13) 2.94E −0.04 (0.07) 0.93 −0.04 (0.07) 0.90 −0.03 (0.08) 0.98�E 0.01 (0.01) 2.00 −0.001 (0.01) 2.17 0.02 (0.01) 1.49ES 0.13 (0.07) 0.41 0.13 (0.06) 0.42 0.14 (0.09) 0.37BV 1.58 (1.02) 2.67 1.54 (0.98) 2.81 1.67 (1.12) 2.32

Returns = raw return measured from the first month of the financial year through to the end of the last month of the financialyear, price = price per share at year end, E = annual net result (net profit or net loss) scaled by beginning-of-financial yearmarket value, �E = change in annual net result scaled by beginning-of-financial year market value, ES = annual net resultdivided by the number of shares at year end and BV = book value (net assets to parent members) divided by the numberof shares at year end.

intangible assets since the price effect of recognizing intangible assets is unknown (see Ronen,2001). Capitalizers have a lower book-to-market ratio in seven of the nine time periods, possiblyreflecting more growth opportunities than non-capitalizers. However, of these seven differences,only the difference for 1998–1999 is significant (difference = −0.30, t = −2.85). The other twodifferences, which occur for the 1989–1991 and 1992–1994 periods, are both significant at the0.05 level. Leverage is measured as total liabilities divided by total assets less intangible assets atthe end of the financial year, and shows captializers are more highly levered.

Panel B shows that the differences in leverage are significant in every period except for the1975–1976 period. Medians (unreported) are also higher in every period for capitalizers. Returnon equity (ROE) is measured by net profit plus all amortizations divided by average book valueadjusted for intangible assets. Capitalizers have become relatively more profitable, evidenced bythe larger positive differences in the ROE ratios in later years, shown in Panel B. These statisticssuggest that over the sample period, firm risk may be correlated with intangible capitalization, anissue addressed in Sections 5 and 6.

The intangible industry percentage variable is the percentage of firms that are in intangible-intensive industries. Intangible-intensive industry is defined as an industry in which we expectintangibles to be of highest relative importance to future profitability and growth. The selectionis arbitrary as in Collins et al. (1997). The following industries (group codes) are classified asintangible intensive: alcohol and tobacco (8), chemicals (10), media (15), telecommunications(18), healthcare and biotechnology (21), miscellaneous industrials and services (22), diversi-fied industrials (23) and tourism and leisure (24). About 85% of the non-capitalizer sampleis made up of firms from intangible non-intensive industries in the last half of the sampleperiod.

The last right-hand column of Table 1 presents mean value for the intangible intensity ratio,measured by intangible assets divided by total assets at financial year end. The mean shows arise from about 0.01 for the 1975–1976 period to about 0.13 for the 1998–1999 period. Medians(unreported) also rose from about 0.001 to about 0.05. The jump in the 1986–1988 period is likelydue to the introduction of mandatory amortization of goodwill in 1986. Around the introductionof that requirement, some firms reacted by adopting the practice of recognizing other intangibles(e.g. brands, trademarks) at acquisition to reduce the effect on earnings of goodwill amortization.These firms did not amortize these assets (Wines & Ferguson, 1993).


Table 2 presents descriptive statistics for the regression variables in models 1 and 2 over theperiod from 1975 to 1999. The variables E, �E and ES are measured using net profit or lossthat includes extraordinary items. Extraordinary items were not removed because the definitionchanged from 1990 making over-time comparisons problematic. The table shows mean (median)returns of 0.29 (0.12) for all firms, with mean (median) returns of 0.30 (0.12) for non-capitalizersand 0.26 (0.11) for capitalizers. Capitalizers have a higher price per share. With respect to theearnings variables (E and ES), the table shows no distinct difference between non-capitalizersand capitalizers. However, capitalizers show a positive change in earnings, while the changes arenegative, on average, for non-capitalizers.

5.2. Results

Panel A of Table 3 presents results from estimating models 1 and 2 for each of the 25 years1975–1999. The results from model 1 (earnings relation) for all firms indicate a declining trendin R2s and ERCs. To test these apparent declines formally, R2s and ERCs are regressed on Time,where Time equals the year. Results, reported in Panel B of Table 3 show Time coefficients arenegative and significant for both the R2 and the ERC and both equations are significant at the 0.05level (F-test). We conclude that, consistent with most U.S. research, there is evidence of decliningearnings value relevance.

Collins et al. (1997) report the declining U.S. earnings value relevance is, in part, due to theover-time increase in percentage of loss-making firms. The earnings value relevance declines forthe full sample may be due only to increases in the percentage of losses. Alternatively, earningsvalue relevance may have declined at a faster rate and the decline is masked by a decreasingpercentage of losses over time.

To examine the patterns of losses over time, the number and magnitude of losses scaled by mar-ket value are calculated for each year. Unreported results show an increase in both frequency andmagnitude of losses over time, consistent with U.S. studies (Collins et al., 1997; Ely & Waymire,1999; Hayn, 1995). Yearly percentage frequencies and magnitudes are slightly higher than forU.S. firms, possibly because of different earnings measures and sample periods.12 Regressing thepercentage of losses on Time gives a statistically significant positive coefficient (0.02, t = 7.52),indicating increasing frequency of losses over 1975–1999. This suggests the significant decline inearnings value relevance for all firms, reported in Panel B of Table 3, may be due to the increasein the percentage of losses (Collins et al., 1997). To investigate this possibility, the model isre-estimated excluding losses.

Results for firms excluding losses are presented in Panel A of Table 3(columns 5–7). Removinglosses resulted in higher model significance than for the full sample, as Hayn (1995) has shown.R2s and ERCs are again regressed on Time. Results in Panel B of Table 3, show that the R2

equation is significant at the 0.05 level but is less significant than for the full sample. As expected,the Time coefficient has a negative sign, suggesting declining earnings value relevance. Since thissample excludes loss firms, it is not surprising that the coefficient on ERCs is positive and higherthan the full sample. Based on the evidence from both the full and no-loss samples, we find thatmuch of the decline in earnings value relevance measured by the ERC is explained by changingloss frequency over time. When value relevance is measured by R2 there is evidence that earningsvalue relevance has declined after controlling for losses.

12 Collins et al. (1997), for example, use “core income” instead of net result which is used in this study and their samplecovers 42 years to 1994.


Table 3Regression results for annual returns on earnings and earnings change and price on earnings and book value

Year Earnings relation Earnings and book value relation

All firms Excluding losses All firms

N R2 ERC N R2 ERC R2 E BV

(Panel A) Sample sizes, R2, ERCs (earnings relation) and earningsand book value coefficients

1975 269 0.15 0.90 252 0.21 1.54 0.61 2.29 0.331976 313 0.31 0.80 299 0.49 1.29 0.57 1.92 0.351977 323 0.34 0.83 314 0.34 0.90 0.59 1.34 0.311978 517 0.05 0.39 444 0.09 1.14 0.46 2.22 0.241979 540 0.001 0.05 455 0.07 0.33 0.12 1.39 0.071980 471 0.002 0.14 398 0.08 0.87 0.19 2.24 0.061981 530 0.003 0.11 404 0.03 0.46 0.35 −0.09 0.631982 502 0.23 0.48 326 0.20 0.71 0.80 1.16 0.911983 493 0.08 −0.65 329 0.05 1.40 0.84 3.32 0.761984 551 0.06 0.37 373 0.09 0.47 0.60 0.22 0.741985 524 0.03 0.35 376 0.24 1.98 0.64 2.19 0.631986 382 0.03 0.39 303 0.03 0.36 0.63 3.21 0.711987 375 0.002 0.11 306 0.06 1.13 0.39 1.48 0.461988 334 0.04 0.01 232 0.10 0.84 0.63 1.09 0.741989 537 0.04 0.14 253 0.08 0.62 0.73 2.20 0.741990 472 0.22 0.02 241 0.18 0.93 0.74 3.68 0.491991 360 −0.002 −0.04 187 0.07 0.18 0.58 1.29 0.891992 431 0.02 −0.07 213 0.13 2.43 0.76 1.60 1.141993 503 0.02 0.12 283 0.18 1.98 0.76 5.46 0.781994 616 0.01 0.23 376 0.17 2.24 0.75 0.53 1.221995 718 0.05 0.40 411 0.09 0.76 0.57 3.39 0.731996 801 0.02 0.03 481 0.09 0.70 0.34 7.94 −0.351997 870 0.05 0.48 489 0.09 0.89 0.74 3.34 1.561998 787 0.04 0.08 430 0.02 −0.02 0.73 1.98 1.351999 699 0.03 0.13 392 0.12 1.73 0.67 6.98 0.66

Mean 0.07 0.23 0.13 1.03 0.59 2.49 0.65

Intercept Time R2 F-statistics

Regressions results for R2 and ERC on Time for all sample firms and forfirms excluding losses (t-values in parentheses)All firms

Earnings relationR2 12.19 (2.48) −0.006 (−2.46) 0.17 6.06†

ERC 34.92 (2.06) −0.02 (−2.05) 0.12 4.19†

Earnings and book value relationR2 −18.12 (−1.85) 0.009 (1.90) 0.09 3.63‡

Excluding lossesEarnings relation

R2 11.21 (2.06) −0.006 (−2.03) 0.11 4.13‡

ERC −12.14 (−0.33) 0.007 (0.36) −0.04 0.13

N = number of firms. ERC = sum of the coefficients on net profit or loss and the change in net result.† Significant at the 0.05 level (two-tailed).‡ Significant at the 0.10 level (two-tailed).


Columns 8–10 of Table 3 show the results of the levels model 2. In contrast to the earnings inmodel 1, the R2 values appear not to be declining. R2 values range from 12 to 61% in the first7 years and from 34 to 76% in the most recent 7 years of the sample. The regression of R2 onTime shows a positive coefficient of 0.009 (t-statistics = 1.90), but the trend does not show strongevidence of increasing value relevance since the coefficient is significant only at the 0.10 level.The evidence is, however, inconsistent with the earnings model 1 but consistent with Francis andSchipper (1999), who also report conflicting trends in value relevance from estimating these twomodels. Further, this evidence is inconsistent with Lev and Zarowin (1999), who report decliningvalue relevance from estimating these two models over a more recent period than Francis andSchipper (1999). The inconsistency between results from the returns and levels models may be dueto scale effects in the levels model. For example, Brown et al. (1999) show that the levels modelgives conflicting results about longitudinal changes in U.S. firms’ value relevance, dependingupon whether scale is controlled for.

Since the above evidence is not wholly consistent with U.S. evidence, subsequent analysesfocus on intangibles, often singled out as a candidate for causing declining value relevance.

6. Intangibles and longitudinal earnings value relevance

In this section, evidence is provided on the impact of intangibles on longitudinal value relevancein a reporting environment that allows their capitalization. Ideally, this issue should be examinedusing reported data and policies over the whole sample period. This is not possible due to datalimitations, so the problem is tackled by estimating the earnings model for two groups: non-capitalizers and capitalizers.

6.1. Earnings and earnings change results

Panel A of Table 4 presents results from estimating model 1 for each group for all firms and foreach group excluding losses. Looking first at the results for the full sample, capitalizers generallyhave higher R2s and ERCs than non-capitalizers in recent years. The top half of Panel B of Table 4shows the Time coefficients are significantly (p < 0.05) negative for the non-capitalizer sample,and both the R2 and ERC equations for non-capitalizers are more significant than the capitalizers.This suggests that the evidence of declining earnings value relevance for the sample of all firms(reported in Panel B of Table 3), is driven by the non-capitalizers within our sample.

To investigate the possibility that one group has relatively more losses thereby weakeningearnings value relevance more for that group than the other, the model was re-estimated excludinglosses. Results, presented in the right half of Table 4, Panel A, generally show higher R2s andERCs for capitalizers in the most recent 12-year period, perhaps indicating a shift in investors’assessment of the value of recognized intangible assets.13 The bottom half of Panel B of Table 4shows declining earnings value relevance except for the profitable capitalizers that show increasingvalue relevance. The time coefficient for the ERC regression is the only instance of significance(coefficient = 0.07, t = 2.90).

13 A shift toward intangibles has been suggested by Lev (2001) to have occurred in the mid 1980s as a result of advances ininformation technology coupled with increased business competition (Lev, 2001, p. 16). Chang (1998) provides evidencethat a decline in value relevance of U.S. GAAP accruals occurred in the mid 1970s, which is about the same time as theFASB’s decision to move to immediate expensing of R&D. Alternatively, this apparent shift may be due to changes inthe type of intangibles recognized over time.


Table 4Regression results of annual returns on earnings and earnings change for each year for all firms and for firms excludinglosses classified by intangible capitalization and time regressions

Year All firms Excluding losses

Non-capitalizers Capitalizers Non-capitalizers Capitalizers

N R2 ERC N R2 ERC N R2 ERC N R2 ERC

(Panel A) Sample sizes, R2 and ERCs for non-capitalizers andcapitalizers for all firms and for firms excluding losses

1975 199 0.15 0.85 70 0.19 1.41 186 0.21 1.56 66 0.17 1.501976 245 0.31 0.79 68 0.30 0.84 234 0.54 1.34 65 0.22 0.891977 249 0.38 0.93 74 0.16 0.48 242 0.38 0.99 72 0.15 0.471978 410 0.05 0.36 107 0.04 0.51 350 0.09 0.87 94 0.17 2.051979 432 0.003 0.07 108 0.07 −0.04 357 0.02 0.10 98 0.04 −0.041980 378 0.003 0.33 93 0.17 0.56 315 0.03 0.93 83 0.10 0.651981 422 0.002 0.03 108 0.07 0.34 313 0.03 0.42 91 0.21 1.211982 397 0.22 0.54 105 0.26 0.51 254 0.19 0.71 72 0.32 0.881983 390 0.11 −1.04 103 0.02 0.32 259 0.06 1.78 70 0.19 0.251984 430 0.05 0.32 121 0.16 0.95 284 0.09 0.43 89 0.24 2.141985 384 0.006 0.17 140 0.15 0.73 265 0.24 1.35 111 0.21 1.261986 275 0.03 0.49 107 0.02 0.32 213 0.20 2.18 90 0.06 0.171987 233 0.003 −0.20 142 0.16 1.07 185 0.01 0.91 121 0.17 1.101988 188 0.22 0.60 146 0.004 0.01 134 0.10 0.61 98 0.12 1.491989 305 0.02 0.18 232 0.10 0.11 145 0.05 0.59 108 0.10 0.691990 296 0.29 −0.05 176 0.02 0.03 141 0.21 1.15 100 0.21 1.221991 247 0.003 −0.06 113 0.05 0.05 123 0.002 0.16 64 0.13 0.201992 294 0.01 −0.19 137 0.19 0.29 134 0.04 3.13 79 0.73 3.091993 334 0.01 −0.26 169 0.12 0.42 168 0.05 2.04 115 0.27 1.871994 408 0.01 0.16 208 0.02 0.58 219 0.18 1.92 157 0.16 3.091995 464 0.04 0.37 254 0.08 0.49 233 0.06 0.51 178 0.20 1.391996 516 0.01 −0.03 285 0.04 0.35 286 0.06 0.48 195 0.29 2.371997 562 0.03 0.45 308 0.09 0.56 279 0.06 0.66 210 0.19 2.081998 528 0.04 0.06 259 0.08 0.41 253 0.04 −0.02 177 0.09 1.071999 465 −0.001 0.03 234 0.16 1.20 232 0.04 0.41 160 0.25 4.13

Mean 0.08 0.20 0.11 0.50 0.12 1.01 0.20 1.41

Non-capitalizers Capitalizers

Intercept Time R2 F-statistics Intercept Time R2 F-statistics

(Panel B) Regression results for R2 and ERC on time for, non-capitalizerand capitalizer firms, full sample and firms excluding losses (t-values inparentheses)

All firmsR2 13.48 (2.36) −0.007 (−2.35) 0.16 5.52† 7.81 (1.88) −0.004 (−1.85) 0.09 3.44‡

ERC 42.18 (1.94) −0.02 (−1.93) 0.10 3.72‡ 14.83 (0.72) −0.007 (−0.69) −0.02 0.48

Excluding lossesR2 16.46 (2.61) −0.008 (−2.59) 0.19 6.69† −7.07 (−0.98) 0.004 (1.00) 0.000 1.01ERC 17.74 (0.42) −0.008 (−0.39) −0.04 0.16 −14.04 (−2.87) 0.07 (2.90) 0.24 8.43†

† Significant at the 0.05 level (two-tailed).‡ Significant at the 0.10 level (two-tailed).


6.2. Levels regression results

Panel A of Table 5 presents the results from estimating model 2 for non-capitalizers andcapitalizers. The table shows a mean R2 of 0.62 for non-capitalizers and 0.59 for capitalizersamples. Results from regressing the R2s on Time presented in Panel B, show coefficients arepositive but only the coefficient on R2 for the capitalizers sample is significant (t-statistics = 5.33,p < 0.01). These results indicate that the value relevance of earnings and book value of equity forcapitalizers has increased over the sample period compared with non-capitalizers. Since the focusof the present paper is earnings value relevance, subsequent tests use model 1 and its variation.

Table 5Regression results for price on earnings and book value for each year for all sample firms and for capitalizers andnon-capitalizers

Year Non-capitalizers Capitalizers

R2 E BV R2 E BV

(Panel A) R2 and estimated coefficients for earnings and book value1975 0.63 2.03 0.37 0.59 4.08 0.071976 0.64 2.00 0.39 0.38 2.75 0.061977 0.66 1.77 0.31 0.39 0.89 0.251978 0.48 2.45 0.27 0.45 1.51 0.151979 0.12 1.37 0.13 0.15 0.83 0.011980 0.25 2.54 0.25 0.17 0.46 0.111981 0.43 −1.01 0.89 0.18 2.04 0.091982 0.82 1.33 0.94 0.54 0.92 0.521983 0.88 4.02 0.72 0.49 1.49 0.331984 0.59 0.03 0.78 0.69 1.66 0.591985 0.63 2.39 0.61 0.67 1.25 0.781986 0.64 2.79 0.73 0.60 5.53 0.531987 0.32 2.01 0.45 0.60 0.97 0.531988 0.68 0.99 0.83 0.53 1.23 0.641989 0.79 2.82 0.85 0.69 1.49 0.561990 0.83 2.45 0.89 0.73 4.35 0.331991 0.78 0.19 1.49 0.71 5.97 0.561992 0.77 1.36 1.45 0.79 1.50 0.981993 0.68 5.95 0.66 0.89 4.79 0.961994 0.73 −0.18 1.29 0.80 4.66 0.821995 0.65 6.71 0.56 0.59 −2.42 1.191996 0.32 6.89 −0.32 0.85 2.70 1.521997 0.69 3.48 1.56 0.82 3.06 1.571998 0.76 2.11 1.44 0.66 1.71 1.101999 0.64 6.54 0.60 0.76 6.41 1.03

Mean 0.62 2.52 0.73 0.59 2.39 0.61

Intercept Time R2 F-statistics

(Panel B) Regression results for R2 on Time for all firms and fornon-capitalizer and capitalizer firms

Non-capitalizers −14.41 (−1.38) 0.008 (1.44) 0.04 2.07Capitalizers −41.34 (−5.25) 0.02 (5.33) 0.53 28.43†

R2 = α0 + α1 Time + ε (t-statistics in parentheses). †Significant at the 0.05 level (two-tailed).


6.3. Additional specification checks and alternative explanations

We also regressed returns on earnings, earnings change, book-to-market, size, profitabilityand leverage for each year and measured value relevance using only the earnings coefficientmagnitudes. Book-to-market and size are included in an attempt to control for changing bias incoefficient estimates over the sample period since Pearson and Spearman correlations (unreported)show the direction and strength of the correlation between these variables and the earnings variableis not the same in all years. Profitability and leverage reduce the possibility that capitalization iscorrelated with other attributes that affect changing earnings value relevance. Time regressionsgave very similar inferences to those for the full sample (results in Panel B of Table 3) and forthe two groups (Panel B of Table 4).

Givoly and Hayn (2000) show that over-time increases in conservatism reduce book-to-marketratios and authors such as Lev and Zarowin (1999) suggest declining book-to-market ratios aresymptomatic of non-recognition of intangible assets. The earnings value relevance trends forcapitalizers and non-capitalizers may be due only to different over-time changes in conservatism.Following Basu (1997), the sample is split into positive and negative returns sub-samples and‘reverse’ regressions (earnings are regressed on returns) are estimated for each of these sub-samples for each year post 1982, first for all firms, then for non-capitalizers and capitalizers. WhenR2s and ERCs are regressed on Time (1983–1999), results (unreported) provide weak evidence ofa conservatism increase. For both the negative and positive returns samples, the Time coefficientfor R2 is 0.003 (t = 1.81) and 0.019 (t = 1.45), respectively. None of the four equations is significantfor non-capitalizers, suggesting no change in conservatism. For capitalizers, both negative andpositive returns R2 equations are significant (p < 0.05) and indicate increasing conservatism. TheERC equations for the capitalizer sample support the above results since one model indicatescapitalizers have reduced conservatism. Overall, the evidence suggests conservatism has increasedfor capitalizers and there is no change for non-capitalizers, which is probably due to more financeindustry firms in the non-capitalizer sample. Differences in conservatism between the two groupsdo not appear to explain the reported difference in their earnings value relevance.

Over-time increases in returns volatility can indicate declining earnings value relevance (bylower R2s) even if price relevant information captured by earnings is constant or even increasing. Toinvestigate the effect of changing returns volatility on the R2 trends for the two groups, the standarddeviation of annual returns for each year for each group is regressed on Time. Results show thatthe change in standard deviation of returns is increasing for capitalizers more than for the non-capitalizers (capitalizers—R2: Time coefficient = 0.018, t = 1.36 and non-capitalizers—R2: Timecoefficient = 0.011, t = 0.744). The analysis was repeated for the profit samples. None of the timeregressions was significant at the conventional level of 5%. Overall, one interprets this evidencethat over-time changes in returns volatility do not explain the widening gap in R2s between thetwo groups.

We conclude from the above results that firms which capitalize intangibles also measure earn-ings in a manner which reflects investors’ expectations about future cash flows better than firmsthat do not capitalize intangibles ceteris paribus. We also conclude that the gap in earnings valuerelevance between the two groups has increased in recent years.

7. A further look at capitalizers

Lev and Zarowin (1999) suggest that amortization is a likely candidate for explaining thehigher value relevance of capitalizers. To examine this issue further, we investigate the role


Table 6Descriptive statistics for the intangible amortizing sample 1992–1999 for three groups of amortized intangible assets,R&D, deferred costs and other

Year N Number of assets Amortization ratio Amortization period Amortization extent

R&D Def Other R&D Def Other R&D Def Other R&D Def Other

1992 83 19 45 53 0.12 0.03 0.02 10.3 6.4 14.5 0.83 0.84 0.571993 114 20 64 68 0.09 0.02 0.02 5.4 5.8 13.0 0.62 0.88 0.551994 133 32 69 81 0.16 0.03 0.02 6.1 7.8 13.8 0.75 0.84 0.531995 164 32 82 97 0.06 0.03 0.02 6.3 5.7 14.6 0.58 0.85 0.521996 187 42 96 112 0.08 0.03 0.02 7.4 6.2 13.1 0.70 0.88 0.511997 197 42 90 124 0.09 0.03 0.02 7.5 5.5 13.4 0.70 0.87 0.531998 162 38 54 121 0.09 0.03 0.02 8.7 6.0 15.3 0.78 0.86 0.541999 160 29 43 132 0.06 0.02 0.02 11.4 7.1 15.4 0.75 0.86 0.59

Median 32 67 105 0.09 0.03 0.02 7.5 6.1 14.2 0.73 0.86 0.54

All numbers are medians except number of firms (N) and number of assets. Median in the bottom row is the median ofthe medians. Amortization ratio is measured by amortization expense divided by the absolute value of net result (profit orloss). Amortization period is the inverse of the ratio amortization expense for a financial year divided by the gross assetamount at that financial year-end. For other intangibles, this ratio is separately calculated for each firm for each amortizedasset, and the reported median is the median of all the ratios so calculated. Amortization extent is the number of amortizedassets divided by the total number of intangible assets.

of amortization by hand collecting data for 1726 firm years (476 firms) from 1992 to 1999,representing about 94% of the original capitalizing firms for that period. Amortization is reportedin 1200 (about 70%) of these firm years. Table 6 reports descriptive statistics for the intangible-amortizing sample.

The number of assets columns report frequencies for the research and development, deferredcosts and other intangibles asset groups. These data reveal that other intangibles are most frequentand that asset group has become relatively more frequent over the sample period. Amortizationratio is the reported amortization expense divided by the absolute value of net result for that year.The wide range in the R&D amortization ratio from about 16 to about 6% is likely due to smallsample sizes. Deferred costs and other intangibles are fairly stable at about 3 and 2%, respectively.

Amortization period is estimated for each amortized asset by the inverse of the ratio amortiza-tion expense divided by the gross amount of the asset at that year-end. Clearly, such a measure hasits problems, not the least of which is the grouping of a variety of assets for other intangibles thatlikely have different lives (brands with patents for example).14 For this reason the medians arereported rather than the means. Despite the estimate’s shortcomings, the periods are quite closeto expectations. The deferred costs’ periods are generally the shortest and range from 5.5 to 7.8years.

Amortization extent is the number of amortized assets divided by the total number of intangibleassets. The data reveal a decline in amortization extent for other intangibles over the first 5 yearsconsistent with some prior Australian studies (see for example, Wines & Ferguson, 1993, who

14 Three other potential problems are the implicit assumption of straight-line amortization, the practice of some firmsrestating the gross amount and accumulated balance each year and the inclusion of the first year of amortization when theasset began to be amortized after the start of a financial year. The straight-line assumption should not be too much of aproblem as most firms use straight line. The restating practice will downwardly bias the estimation period and so will theinclusion of the first year of amortization meaning the real periods are probably higher. These estimates should be viewedwith some scepticism.


report a decrease in amortization frequency of these types of asset over the period 1985–1989),and an increase over the last 3 years, which is probably due to recent pronouncements requiringamortization.15

Using disclosed amortization expense as the discriminator, the sample was split into firms thatamortized at least one asset (hereafter amortizers) and firms that amortize none. The model wasestimated for each sample and for a sample matched on size and book-to-market.16 Unreportedresults show that amortizers have consistently higher R2s and ERCs for the full sample and for 6 ofthe 8 years for the sample excluding losses. For the full sample, the matched results show higherand positive ERCs compared with lower and in some years negative ERCs for non-amortizers.R2s are higher for amortizers in 5 of the 8 years.

To test this directly, model 1 is adapted following Aboody and Lev (1998) to include amortiza-tion level and amortization change and is estimated on a pooled sample, controlling for industryand year effects using dummy variables. The model is:

rtt = α0 + α1Eit + α2�Eit + α3Amortit + α4�Amortit +24∑

j=1

α5jDIijt

+1999∑

t=1992

α6tDYit + ett (3)

where Eit is the annual net result (net profit or net loss) adjusted for all amortization for firm i forperiod t scaled by beginning-of-financial year market value, �Eit, the change in annual net result(net profit or net loss) adjusted for all amortization for firm i for period t scaled by beginning-of-financial year market value, Amortit the amortization expense for firm i for period t scaledby beginning-of-financial year market value, �Amortit the change in amortization expense forfirm i, for period t scaled by beginning-of-financial year market value, DIijt the dummy variablethat equals the industry number 1–24 as categorized by the Australian Stock Exchange and zerootherwise, DYit the dummy variable that equals the year 1992–1999 and zero otherwise, and eit

is the error term.Earnings and earnings change are measured before all intangibles amortization, including

goodwill, since amortization of intangibles is positively correlated with goodwill amortization inevery year, and about 60% of capitalizers report a goodwill asset. Earnings level and earningschange are expected to be positive and significant, consistent with prior research. The changein amortization expense is used as a proxy for unexpected amortization, consistent with priorstudies (see Aboody & Lev, 1998). Since amortization expense is coded as a positive number, itscoefficient sign is expected to be negative. Amortization level is expected to be insignificant sinceunder naıve expectations last period’s value is expected for the current period. As some firmshave begun to amortize in recent years, amortization change (�Amort) is only calculated whenpositive values are reported for both t − 1 and t, resulting in a loss of 193 observations.

Results from estimating model 3 are presented in Table 7 and reveal that amortization level isinsignificant but amortization change is negative and significant for all intangibles. The table also

15 Accounting Interpretation A1 (non-legally binding), released in 1999 states that non-current intangible assets arecaught by AASB 1021 Depreciation, that requires depreciation to be recognized over a non-current asset’s estimateduseful life. Also, IAS 38 Intangible Assets released in 1998, requires amortization of all intangibles.16 Small sample sizes in earlier years for non-amortizers ruled out a matched design for a sample excluding losses.

Additionally, the matched results must be considered in light of reduced statistical power due to small numbers (fromabout 33 up to 92).


Table 7Regression results for returns on earnings, earnings change, amortization and amortization change for a pooled sample1992–1999

N E �E Amort �Amort R2 (F-statistics)

All 1007 0.395 (3.398)† 0.624 (9.545)† 0.467 (0.678) −0.283 (−3.014)† 0.235 (9.809)†

R&D 208 0.659 (2.318)† −0.089 (−0.540) 3.284 (2.714)† −10.596 (−6.777)† 0.336 (4.749)†

Deferred costs 445 0.652 (4.997)† 0.251 (3.645)† 9.323 (3.611)† −6.594 (−1.838)‡ 0.323 (7.224)†

Other 647 0.243 (1.435) 1.199 (10.637)† 0.624 (0.573) −0.317 (−2.701)† 0.249 (7.481)†

N = number of observations. E = earnings before all amortization, �E = change in earnings before all amortization,Amort = amortization expense, �Amort = change in amortization expense, all independent variables scaled by beginning-of-financial year market capitalization, t-statistics in parentheses in Panel A. Dummy variable results are suppressed forbrevity.† Significant at the 0.05 level (two-tailed).‡ Significant at the 0.10 level (two-tailed).

presents results for three asset groups that show amortization level to be positive and significantfor R&D (coefficient = 3.284, t = 2.714) and deferred costs (coefficient = 9.323, t = 3.611). Amor-tization change is negative and significant for all three asset groups, consistent with expectations.However, the significant, positive coefficient on amortization level is not expected. We leave thisobservation to future research.17

8. Conclusions

This paper reports evidence on the longitudinal returns–earnings and price–earnings–bookvalue relations for a representative sample of Australian firms over the 25-year period 1975–1999.It is motivated by recent U.S. studies reporting declining earnings value relevance and the ideathat the immediate expensing of intangibles is important in explaining this decline. Based on theearnings and earnings change model, the results suggest that earnings value relevance (measuredby R2 and ERC) has declined over this period. Since prior research has documented that profits aremore strongly associated with returns than are losses, the model was re-estimated excluding losses.After removing losses, the evidence on declining earnings value relevance is weak. Results fromestimating a levels model also provide no evidence that the value relevance of financial statementinformation has declined.

Further examination of intangible capitalizing firms reveals that for these firms, earnings valuerelevance has increased more compared with firms which did not capitalize intangibles over thesample period. The value relevance of earnings and book value has increased for capitalizersand there is no significant improvement for non-capitalizers. These results occur in a relativelyunregulated reporting regime for intangibles where, for example, one might expect a higher levelof earnings management. Furthermore, the value relevance of profitable capitalizers (excludinglosses) has considerably improved over time, while there is evidence of declining value relevancefor profitable non-capitalizers. Further specification tests that control for firm size, firm risk andgrowth options have not altered the above findings materially.

17 The model may be mis-specified for example. Specifically, growth in intangibles may be a correlated omitted variable.To provide some insight into this, we proxy for growth using, alternatively, the market-to-book ratio measured at the startof the financial year and the change in the intangible asset adjusted for amortization and write-offs scaled by beginning-of-financial year market value. The model was re-estimated including these variables. Results (unreported) did not changeinferences for amortization level or for amortization change.


As the longitudinal evidence is circumstantial, it is possible other factors are correlated withintangible capitalization and changing earnings value relevance that are not controlled for in thisstudy. Additionally, this study uses a previously-used design that suffers from the regression ofsample-specific R2s and ERCs on a time variable. Also, the design assumes that price qualityis unchanged in the sense it is unaffected by changes in market efficiency, for example. Ignor-ing these possible limitations, the evidence indicates capitalizers’ earnings reflect more relevantinformation for investors than non-capitalizers’ earnings in recent years. An unresolved questionis whether the arrest of declining earnings value relevance is only due to the intangible account-ing practised in Australia since there were groups of non-capitalizers that have little change inearnings value relevance. However, this study does report a cross-sectional difference in earningsvalue relevance between capitalizers and non-capitalizers, a difference that is bigger in recentyears and is unexplained by alternative reasons.

Focusing on the last 8 years of the sample, capitalizers that amortize generally have the highestearnings value relevance. Amortization level and change are more often significant for unregulatedintangibles, other than deferred costs, than for R&D and deferred costs. As expected, a negativesign for amortization change was observed. However, the positive sign for amortization levelpresent in most estimated equations was not expected. Future research might explore this finding.

Acknowledgments

The comments and suggestions of Kim Sawyer, Jayne Godfrey, Farshid Navissi, Raymondda Silva Rosa, seminar participants at La Trobe University and conference participants at theAccounting and Finance Association of Australia and New Zealand in Auckland are gratefullyacknowledged. The authors take the sole responsibility of the errors if any.

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