Journal of Business Finance & Accounting, 32(3) & (4), April/May 2005, 0306-686X
Accounting, Valuation and Duration
of Football Player Contracts
ELI AMIR
AND
GILAD LIVNE*
Abstract: FRS 10 requires investments in player contracts by football companies to be capitalized and amortized. Given the high degree of uncertainty
associated with such contracts, it is not clear that this treatment is consistent
with asset capitalization criteria. The evidence provided in this paper does not
support inconclusively this capitalization requirement in that it indicates weak
association of investment in player contracts with three measures of future
benefits. In particular, the duration of this association is at most two years,
which is shorter than the duration implied by the amortization period reported
by sample companies. Nonetheless, other findings suggest that market participants seem to agree with the treatment prescribed by FRS 10. These results
should be of interest to practitioner and standard setters who (axiomatically)
regard intangibles acquired in an arm’s length transaction as assets.
Keywords: FRS 10, intangible assets, player contracts, capitalization versus
expensing, football industry
1. INTRODUCTION
Research on intangibles has primarily been concerned with
self-originated intangibles, such as research and development
*The authors are both from the London Business School. They thank an anonymous referee,
Andrew Stark (an editor), Elroy Dimson, Ron Kasznik, Maureen McNichols, Pat O’Brien,
Dennis Oswald, Tim Sutton, and seminar participants at the 2004 AAA annual meetings in
Orlando, the 2004 JBFA Conference, the BAA/AAA 2nd Globalization Conference at
Cambridge University, Cardiff University’s FRBC Conference, City University Business
School (London), the European Accounting Association meeting, the European Finance
Association annual meeting, London, the Hebrew University at Jerusalem, HEC Lausanne,
London Business School, MIT, Tel Aviv University, and the University of Toronto, for helpful
comments. They are especially grateful to Tal Amir, Francoise Husson and Anita Marijetic for
assisting in data collection and to Yanling Guan for research assistance.
Address for correspondence: Eli Amir, London Business School, Regent’s Park, London
NW1 4SA, UK.
e-mail: [email protected]
Blackwell Publishing Ltd. 2005, 9600 Garsington Road, Oxford OX4 2DQ, UK
and 350 Main Street, Malden, MA 02148, USA.
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(R&D) activities, advertising costs, goodwill, computer software
development costs and self-developed patents (see Hirschey
and Weygandt, 1985; Chauvin and Hirschey, 1993 and 1994;
Lev and Sougiannis, 1996; Green et al., 1996; and Aboody
and Lev, 1998, among others). Since the early 1990s, other
intangibles, such as brand names, licences, various legal and
intellectual property rights, began to gain prominence owing
to significant advances in information technology (Gates, 1999;
and Lev, 2001). These developments have created more active
markets for intangibles-based contracts, either directly or indirectly
through mergers and acquisitions activity. This new economic
reality also challenged the adequacy of the ‘old’ accounting model
to deal with financial transactions that involve acquired intangible
assets. In particular, the old rules (e.g., SSAP 22 in the UK) allowed
flexibility in the capitalization decision and were silent on treatment
of intangibles acquired through the acquisition of one entity
by another. The focus of this paper is on the adequacy of the
capitalization requirement of purchased intangibles, which is now
required by new rules in the UK and elsewhere.
In 1997, the Accounting Standard Board (ASB) issued
Financial Reporting Standard (FRS) 10, Goodwill and Intangible
Assets, which came into force in the UK in December 1998
(ASB, 1997). One important feature of FRS 10 is that it has
removed considerable reporting discretion in requiring that all
directly and indirectly purchased intangibles should be capitalized at cost. The International Accounting Standards Board
(IASB) soon followed by issuing International Accounting Standard
(IAS) 38, Intangible Assets (IASB, 1998).1 More recently, the
Financial Accounting Standards Board (FASB) issued SFAS
142 (FASB, 2001), superseding APB 17 that systematically
addresses the definition, initial measurement and subsequent
treatment of goodwill and other separable intangibles.
Common to all these new accounting standards is the presumption that assets acquired in an arm’s length transaction should be
capitalized. The rationale behind this presumption is that the
transaction price provides reliable evidence about the fair
value of the acquired assets (e.g., FASB, 2001, §B37 and FRS 10,
1 IASB has recently issued a revised version of IAS 38.
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Appendix III §26, IAS 38 (Revised 2004), §21–23).2 This line of
reasoning, however, overlooks the possibility that certain fixed
assets, tangible or intangible, represent speculative investments
in that their recoverability and association with future economic
benefits are highly uncertain. Nevertheless, lack of such certainty
in some other cases led practitioners and standard-setters to reject
asset recognition. For example, Statement of Position (SOP) 98–5
(AICPA, 1998) and UITF Abstract 24 (ASB, 2000), in the case of
start-up costs argue that since the relationship between expenditure
and future economic benefits is not sufficiently certain, overall criteria for asset recognition are not met. In addition, it is also possible
that the duration of certain fixed assets, although longer than one
year, does not justify the costly process of capitalization, amortization
and impairment reviews that are required by these standards.
In this paper we question the applicability of this presumption
by demonstrating that the relation between arm’s length investment in player contracts by football companies and future benefits
may be tenuous. We also demonstrate that the relatively short
duration of these investments may cast doubt on the applicability
of the capitalization rules. Our investigation is based on a
setting that has some special characteristics. While this setting is
interesting in its own right, evidence presented here should be
interpreted cautiously with respect to the more general case.
Nonetheless, we are able to provide here an example that seems
to raise some doubt for the abovementioned universal capitalization presumption. We believe that examining this issue, even
by the way of a specific example, has the power to illustrate some
potential shortcomings of existing standards.
Sums paid by UK football companies to acquire player contracts
in arm’s length transactions (a.k.a. transfer fees) under FRS 10 must
be capitalized. This provides a promising setting to explore our
research questions for a number of reasons. First, these specific
contractual rights constitute the main productive assets for member
firms indicating their economic importance. Second, accounting
information is available for a large portion of the industry, including
2 IAS 38 (Revised 2004), para 21 states: ‘An intangible asset shall be recognized if, and only
if: (a) it is probable that the expected future economic benefits that are attributable to the
asset will flow to the entity; and (b) the cost of the asset can be measured reliably.’ In para
25, the Standard states: ‘Therefore, the probability recognition criterion in paragraph
21(a) is always considered to be satisfied for separately acquired intangible assets.’
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both private and public companies. Third, the diversity in
accounting choice prior to FRS 10 allows us to devise marketbased tests that assess whether the association between share
prices and accounting information is stronger under
capitalization than under expensing.
While some other industries and fixed asset types may also be
characterized by a high degree of uncertainty, we know of no
other setting in which systematic data on trading activity in such
assets are available. Furthermore, in most cases it is prohibitively
costly to identify and collect data for private companies, as we do
here in order to construct a sample representative of a whole
industry. A study of a single, well-understood industry, and a
specific asset type, as opposed to a cross-section study of a number
of industries, also mitigates the problem of confounding effects
and the need to find suitable controls.
In the first analysis, we estimate the association between accounting-based measures of future economic benefits and current and
lagged investment in player contracts. This regression analysis
reveals that current and one-year lagged investments are associated with sales and operating profits, but that two-year lagged
investment is not associated with any benefit measure. For the cash
flow measure, investment in player contracts is positive and significant only for the current year, implying a weak relation between
investments in player contracts and future operating cash flows.
This analysis also suggests that the rate of economic decline in the
value of player contracts is higher than the rate of amortization and
impairment reported by sample firms under FRS 10.
Our second set of tests uses market-based analysis to assess the
association between transfer fees and market value of the firm’s
shares. We find that market values are positively and significantly
associated with investment in player contracts. As FRS 10 has
changed the way book value of equity and annual profits are
measured, we also examine whether the incremental explanatory
power of investment in player contracts has changed after the
Standard became effective. We therefore distinguish between
the period prior to FRS 10 and the one that followed the
standard’s effective date. Prior to FRS 10, investments in player
contracts exhibit explanatory power incremental to reported
equity and net income that is higher than in the post-FRS 10
period. This suggests that the market agrees with the prescribed
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treatment of this standard in that it regards reported accounting
figures as important inputs for valuation. In addition we contrast
the relative explanatory power of capitalization against a method
of full expensing. The evidence suggests that book value of equity
and net income under capitalization better explain share prices
than those measures under immediate expensing. This is consistent with the idea that the market regards payments for transfer
fees as assets. Nonetheless, we find that book value of equity and
net income under FRS 10 have differential valuation implications
for firms that expensed transfer fees prior to FRS 10 than to those
who capitalized. This suggests that the accounting choice itself is
correlated with information used by the market. Alternatively, to
the extent that the accounting choice itself is capable of conveying
useful (i.e., price-sensitive) information, removal of the choice by
FRS 10 may have had adverse informational effects.
The evidence on the whole is rather mixed with respect to the
adequacy of the presumption that the presence of an arm’s length
transaction is sufficient for capitalization in the specific case of
contractual rights in the football industry. By implication, uniform
requirement to capitalize all assets that were purchased in arm’s
length transactions may lead to the recognition of items that do
not fully meet the accounting definition of assets. However,
market-based analysis does seem to support the view that these
specific contractual rights are valued by the market as assets,
consistent with the requirements of FRS 10.
The remainder of the paper is organized as follows. Section 2
provides a brief review of institutional, legal and accounting backgrounds, and related literature. In Section 3, we discuss sample
selection, describe the data, and examine potential determinants
of the accounting choice prior to FRS 10. In Section 4, we investigate the association between future benefits and investment in
player contracts. In this section we also conduct our market-based
analysis. Section 5 provides a summary of the paper.
2. INSTITUTIONAL BACKGROUND AND RELATED RESEARCH
(i) Trading in Player Contracts
Football clubs are engaged in three main activities. The first
activity is generating revenues from ticket sales, broadcasting,
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food services and sponsorships. The second activity is trading
(acquisition and disposal) of player contracts. The third activity
is developing and nurturing in-house talent.3 The focus of this
study is on the second activity. Still, football clubs may differ
substantially in their intensity of reliance on trading players and
on self-developed players. We attempt to control for such differences in our empirical analysis.
The main justification for the transfer system, which governs
player trading, is that clubs are entitled to recoup their investment in training and development of a player’s skill. There
are two types of player transfers between clubs: Transfers of
players under contract and transfers of players outside contract (i.e., when players are free agents). Until 1995, when a
player’s contract expired, the player could negotiate a new
contract with his holding club or with another club. If the
holding club offers terms that are rejected by the player, a
transfer fee must be negotiated between the holding and
the new clubs. If negotiations fail, the negotiating parties
must enter an arbitration process controlled by the Football
Association.
In December 1995, the European Court of Justice (ECJ)
ruled in the case of ‘Bosman’ that restricting the transfer of
players outside contracts is contrary to the provisions of the
European Economic Community (EEC), and therefore void.
Following the ‘Bosman’ ruling, players outside contracts
can move freely from one team to another provided both
teams reside within the EEC. All transfers of players whose
contracts are still effective must be arranged directly by the
clubs.
The ‘Bosman’ ruling was expected to reduce clubs’
investments in football talent (Antonioni and Cubbin, 1997).
However, as our study focuses on the association between
player transfer fees and future economic benefits, we do not
expect the ‘Bosman’ ruling to have a significant effect on our
analysis.4
3 See also Szymanski and Kuypers (1997) for a detailed discussion of the industry.
4 The results reported here are not time-sensitive, suggesting that the ‘Bosman’ ruling
had little effect on the association between players’ transfers and future economic
benefits. See also the discussion of Table 2 below.
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(ii) Accounting for Player Contracts Pre- and Post-FRS 10
The treatment of investments in players’ contracts by UK
football clubs has not been uniform until the issuance of FRS
10, which became effective in the UK in December 1998. This
standard governs accounting treatment of goodwill and other
intangible assets and equally applies to listed and private
companies. It requires that all purchased intangibles should be
capitalized separately from goodwill and that all intangibles
shall be amortized over their useful economic lives, unless
useful life is indefinite. Intangibles with indefinite useful life
should be reviewed for impairment every year. The transitional
arrangements of FRS 10 require the reinstatement of intangible
assets previously purchased separately, which were expensed
(e.g., previously expensed player contracts).
Prior to FRS 10, UK football companies could elect between
capitalization and amortization of players’ transfers and
immediate expensing of those transfers. Companies that elected
the capitalization method recognized player transfers as intangible fixed assets and amortized these intangibles over the
term of the contract. Also, gains and losses from sale of player
contracts were treated as capital gains similar to the gains that
arise on the sale of fixed assets.5 The second method was based
on immediate expensing of players’ contracts. When a player
contract was purchased (sold), expenses (revenues) were recognized
and reported separately.6
(iii) Related Research
Much attention has been directed in recent years at studying
value relevance of R&D and other intangible-related expenditures with particular focus on accounting valuation issues (e.g.,
Green et al., 1996; Amir and Lev, 1996; Aboody and Lev, 1998;
and Amir et al., 2003). Some of these studies focus on specific
industries, as we do here.
5 Cleveland Indians, a US Baseball Company, has adopted a similar treatment of
capitalizing and amortizing signing bonuses and player contracts.
6 One company in our sample revalued players’ contracts every period without
amortizing the assets. Differences from revaluation were presented in the
shareholders’ equity account until the contract is sold. Only then, gains and losses are
recognized. Our results are not sensitive to the inclusion of this company.
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Our main point of departure from the R&D literature in
accounting is the focus on purchased, as opposed to internally
developed, assets. Consequently, our paper is related to Deng
and Lev (1997) who examine the valuation of acquired R&D
expenditures. Our study is also related to Hirschey and
Weygandt (1985) and to Aboody and Lev (1998), though it should
be emphasized that their studies focus on internally-developed
intangibles rather than purchased intangibles. They demonstrate
that R&D and software development costs are associated with
market values as well as with future net and operating income.
Another relevant stream of research that is related to our
study is the economic consequences of the accounting choice
(Fields et al., 2001). Recently, Oswald and Zarowin (2003)
examine the incremental informativeness of share prices of
UK firms that elect to capitalize R&D expenditures.7 They
find that current stock returns exhibit greater association
with the future earnings of capitalizing firms and conclude that
capitalization is more informative.
Finally, the change brought about by FRS 10 provides an
opportunity to examine whether eliminating choice works to
enhance the informativeness of financial statements and assess
the consistency of new rules with the underlying fundamental
definition of an asset. This is also important because the ASB
and the FASB seem to believe that GAAP provides too much
choice (Fields et al., 2001). However, as Ball (1989) argues,
forcing dissimilar firms to report similarly may undermine the
usefulness of accounting numbers. We therefore distinguish
between pre- and post-FRS 10 periods to assess changes in
value relevance of reported income and book value of equity
across the two periods.
3. SAMPLE SELECTION, DATA SOURCES AND DESCRIPTIVE
STATISTICS
There are 92 English football clubs organized in four leagues –
the Premier League and Football League Divisions One, Two
and Three. In addition, there are 40 Scottish football clubs that
7 UK and international GAAP allow capitalization of development costs if certain
conditions are met.
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are organized in four leagues – the Scottish Premier and Divisions One, Two and Three. Our sample constitutes 58 football
companies for which we were able to obtain full financial statements over 1990–2003. In particular, our sample includes all
football companies that are listed on the London Stock
Exchange or the Alternative Investment Market (AIM). We
collected financial data from annual financial statements,
where financial statements of private companies were obtained
from Companies House, a government agency with which UK
companies have to file their annual reports.8 Share prices for the
24 listed companies are mainly retrieved from the London Stock
Prices Database (LSPD). League positions were retrieved from
the Football Yearbook, a software package marketed in the UK.
The list of sample firms appears in Table 1. The 58 firms are
ranked by median annual sales. The table also reports listing
status and the accounting method selected for investments in
player contracts. Companies with high (low) sales tend to be
public (private). Also, 13 out of the 24 listed companies had
their initial public offering (IPO) during or after 1995. In addition, 37 firms did not capitalize investment in player contracts at
any time prior to FRS 10 and only three switched between
expensing and capitalizing during 1990–1998. The latter observation suggests that most companies adopted a long-term view
with respect to their accounting policy.
Table 2 presents information on key financial variables for
three sub-periods: 1990–1995, the period prior to the ‘Bosman’
ruling (Panel A); 1996–1998, the period following the ‘Bosman’
ruling, but prior to the effective date of FRS 10 (Panel B);
1999–2003, the period during which FRS 10 is in effect (Panel
C). The distinction between the period prior to the ‘Bosman’
ruling and subsequent periods allows us to identify and assess
some economic implications, if any, of this change in the legal
environment. The table also presents data separately for listed
and private companies, as business fundamentals and investment
opportunities in player contracts may vary across those firm types.
8 In the UK, under Financial Reporting Standards for Small Entities (FRSSE), certain
small companies need only to prepare abbreviated financial statements that do not
include many of the data items required for this paper. Such Companies were not
included in our analysis.
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AMIR AND LIVNE
Table 1
Sample Selection – Sales, Listing Status and Accounting for Transfer
Fees, 1990–2003
Listing Status
Name
Sales
Median
Chelsea Village
75,136
Manchester United 74,249
Liverpool
43,562
Newcastle United
41,134
Glasgow Rangers
31,186
Arsenal
27,158
Aston Villa
26,924
Tottenham Hotspurs 26,910
Leeds United
22,782
Celtic Glasgow
19,079
Everton
18,882
Sunderland
18,825
Westham United
15,256
Blackburn Rovers
14,302
Manchester City
12,713
Coventry City
12,265
Sheffield Wednesday 11,914
Derby County
10,738
Nottingham Forest 10,290
Leicester City
9,465
Southampton
7,648
Birmingham City
7,480
Bolton Wanderers
7,197
Wimbledon
7,094
Queens Park Rangers 7,070
Sheffield United
6,251
Ipswich Town
6,222
West Bromwich
6,073
Aberdeen Football
5,569
Heart of Midlothian 4,632
Charlton Athletic
4,330
Swindon Town
4,313
Millwall
4,055
Dundee United
4,028
Huddersfield Town
3,896
Burnley Football
3,670
Preston Northend
3,362
Reading Football
3,311
Bradford City AFC
3,251
Watford Football
3,110
Oldham Athletic
3,098
Listed
Private
96–03 92–95
94–03 92–93
91–03
97–02 90–96
91–03 90
91–03
92–03
92–03 90–91
90–03
90–03
91–03
97–03 93–96
91–03
91–03
95–03 90–94
91–03
89–03
91–03
97–01 91–96
97–03 90–96
94–03 91–93
90–03
97–03 90–96
91–01
97–00 90–96
91–02
91–03
95–03 92–94
91–03
97–03 90–96
97–03 91–96
91–98
90–03
91–03
91–01
91–03
95–03 90–94
91–03
98–02 91–97
91–03
91–01
Accounting for Transfers
Expensing
Capitalizing
92–94
95–03
92–98
99–03
91–98
99–03
90–91, 95–98 92–94, 99–02
90–93, 97–98 94–96, 99–03
91–98
99–03
92–98
99–03
90–03
90–96
97–03
90–93
94–03
91–98
99–03
93–03
91–98
99–03
91–98
99–03
90–98
99–03
91–98
99–03
89–98
99–03
91–03
91–97
98–01
90–98
99–03
91–98
99–03
90–98
99–03
90–98
99–03
91–98
99–01
90–98
99–00
91–02
91–98
99–03
92–94
95–03
91–94
95–03
90–03
91–97
98–03
91–98
90–95
96–03
91–98
99–03
91–97
98–01
91–97
98–03
90–93
94–03
91–98
99–03
91–98
99–02
91–98
99–03
91–98
99–01
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Table 1 (Continued)
Listing Status
Name
Peterborough United
Oxford United
The Motherwell
Barnsley Football
Southend United
Plymouth Argyle
Wrexham Football
Bury Football
Bristol Rovers
Dunfermline
Dundee Football
Cambridge United
Scunthorpe United
Roterham United
Hull City
Mansfield Town
Shrewsbury Town
Sales
Median
2,661
2,403
2,248
2,123
2,043
1,911
1,652
1,602
1,554
1,535
1,369
1,341
1,279
1,082
1,025
999
863
Listed
Accounting for Transfers
Private Expensing
91–03
91–03
91–03
91–00
91–01
91–03
91–02
91–03
91–03
91–01
91–01
91–03
91–03
91–03
91–99
91–01
90–03
Capitalizing
90–92, 94–98 93, 99–03
91–98
99–03
91–98
99–03
91–98
99–00
91–98
99–01
91–98
99–03
91–98
99–02
91–98
99–03
91–98
99–03
91–98
99–01
91–92
93–01
91–98
99–03
91–98
99–03
91–98
99–03
91–98
99
91–98
99–01
90–98
99–03
Notes:
The sample includes 58 UK football companies with available data covering 1990–2003.
The table reports median sales (£000s), years in the sample by listing status, and the
accounting method for player transfer fees during the sample period.
Sales figures have gradually increased over time, reflecting the
growth the industry has experienced during the sample period.
This growth is attributable to the increasing popularity of the
game among families as well as to the large amounts paid by
British Sky Broadcasting Group for exclusive live broadcasting
rights in the late 1990s. Listed companies’ median sales are uniformly higher than those for private companies and the difference
in sales is highly significant. In addition, operating profit margins
before transfer fees are larger in listed companies than in private
ones. Operating cash flow to sales is positive for listed companies
and significantly higher than that in private firms.9
9 In the UK, cash from operations excludes payments and receipts of interest and tax.
Since reported cash from operations is sensitive to accounting choice, we exclude transfer
fees (cost of player contracts) from cash flows for expensing firms to obtain comparability of
the cash flow numbers. Similarly, operating profits are measured before transfer fees to
obtain comparability between expensing and capitalizing companies.
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Table 2
Key Financial Variables by Period and Listing
All Companies
Private Companies
Listed Companies
p-Values4
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Mean
Median
N
Mean
Median
N
Mean
Median
t
W
Panel A – 1990–19951
Total Sales (£000s)2
Wages/Sales
Operating Profit/Sales
Cash From Operations/Sales
Transfer Fees Paid/Sales
Transfer Fees Received/Sales
Adjusted Leverage
302
302
283
285
302
285
303
5,299
0.68
0.12
0.04
0.25
0.29
0.91
2,969
0.64
0.07
0.00
0.18
0.19
0.76
173
173
154
166
173
156
174
3,253
0.75
0.19
0.13
0.21
0.30
0.91
1,946
0.73
0.13
0.06
0.14
0.19
0.74
129
129
129
129
129
129
129
8,044
0.58
0.04
0.07
0.30
0.28
0.92
5,431
0.55
0.02
0.09
0.25
0.18
0.78
0.00
0.00
0.00
0.00
0.01
0.68
0.88
0.00
0.00
0.00
0.00
0.00
0.97
0.29
Panel B – 1996–1998
Total Sales (£000s)
Wages/Sales
Operating Profit/Sales
Cash From Operations/Sales
Transfer Fees Paid/Sales
Transfer Fees Received/Sales
Adjusted Leverage
173
173
166
171
173
168
173
11,238
0.69
0.10
0.01
0.30
0.30
0.87
5,429
0.65
0.05
0.01
0.24
0.21
0.73
102
102
95
101
102
97
102
6,038
0.78
0.20
0.07
0.24
0.34
0.95
3,104
0.76
0.16
0.09
0.15
0.26
0.83
71
71
71
71
71
71
71
18,708
0.56
0.02
0.11
0.39
0.23
0.75
12,727
0.55
0.09
0.15
0.39
0.14
0.61
0.00
0.00
0.00
0.02
0.01
0.02
0.01
0.00
0.00
0.00
0.00
0.00
0.01
0.01
AMIR AND LIVNE
#
N
#
251
251
251
251
251
251
251
251
251
23,550
0.78
0.14
0.07
0.24
0.19
1.08
0.32
0.20
10,575
0.75
0.09
0.01
0.18
0.09
0.98
0.26
0.15
139
139
139
139
139
139
139
139
139
11,981
0.85
0.21
0.13
0.19
0.20
1.24
0.33
0.18
4,337
0.80
0.16
0.06
0.09
0.09
1.18
0.28
0.09
112
112
112
112
112
112
112
112
112
37,908
0.68
0.04
0.01
0.29
0.17
0.88
0.33
0.22
31,906
0.65
0.02
0.06
0.23
0.10
0.80
0.24
0.20
0.00
0.00
0.00
0.00
0.00
0.34
0.00
0.30
0.05
0.00
0.00
0.00
0.00
0.00
0.21
0.00
0.00
0.00
561
Notes:
1
Descriptive statistics for three periods: (a) 1990–1995 – prior to the ‘Bosman’ ruling; (b) 1996–1998 – prior to the effective date of FRS 10,
which required capitalization of players’ transfers; (c) 1999–2003 – FRS 10 is in effect. The table presents statistics separately for listed companies
and private companies.
2
Variable definitions:
. Total Sales – from all sources, including selling tickets, TV royalties, merchandizing, catering and sponsorships.
. Wages/Sales – Total wage expenses divided by current total sales.
. Operating Profit/Sales – Profit before net transfer fees, interest and taxes, divided by current total sales.
. Cash from Operations/Sales – Reported cash from operations divided by current sales before interest tax and transfer fees.
. Transfer Fees Paid/Sales – Cost of player contracts divided by current sales. For companies that capitalize the cost of players contracts, this
figure is the addition to intangible assets during the period. For companies that expense the cost of player contracts, this figure is taken from
the income statement.
. Transfer Fees Received/Sales – Revenues from selling player contracts divided by current sales. For companies that capitalize the cost of
player contracts, this figure is taken from the cash-flow statement. For companies that expense the cost of player contracts, this figure is taken
from the income statement.
. Adjusted Leverage – Total liabilities divided by total assets (after excluding capitalized players’ contracts).
. Contract amortization rate – (amortization of player contracts plus contract write-off, divided by the cost of players’ contracts.
. Intangible intensity – Cost of players’ contracts minus accumulated amortization, divided by total assets.
3
The last two variables are presented only for 1999–2003, the period FRS 10 was in effect.
4
P-values – two tailed t-test and Wilcoxon test for differences in means and medians, respectively.
ACCOUNTING & FOOTBALLERS’ CONTRACTS
Blackwell Publishing Ltd 2005
Panel C – 1999–2003
Total Sales (£000s)
Wages/Sales
Operating Profit/Sales
Cash From Operations/Sales
Transfer Fees Paid/Sales
Transfer Fees Received/Sales
Adjusted Leverage
Contract Amortization Rate3
Intangible Intensity3
562
AMIR AND LIVNE
More than a half of sales are devoted to wages and fringe
benefits. Wages, as a proportion of sales, has also gradually
increased over time. The table shows that listed firms pay
significantly less in wages than private firms in all three subperiods suggesting that the marginal contribution of players is
larger in listed companies.
The cost of player contracts constitutes the second largest
cost. This cost is measured as transfer fees paid to sales. In all
years this cost is significantly higher for listed companies than
for private ones. The difference in transfer fees received to
sales, however, is insignificant, except in 1996–1998. For these
years, private firms generated significantly more cash from selling player contracts than listed firms. Note that listed companies
are net investors in transfer fees in 1990–2003, whereas private
companies are net sellers of players in 1990–1998. Examining
the development in cost of player contracts over time we
observe that listed companies invested significantly more in
player contracts and received less from selling these contracts in
the period after 1995. That is, net investment in player contracts
(sums paid less sums received) is significantly higher in 1996–2003
than in 1990–1995 for listed firms (p-value of 1%, not tabulated).
We do not observe significant increase in net investment for
private firms. This can be explained in part by the impact of the
‘Bosman’ ruling that improved players’ bargaining positions,
especially vis-à-vis large clubs. The significant increase in net
investment in listed firms is also explained by the observation
(not reported) that listed firms tend to maintain a higher league
position. As broadcasting income is linked to league position,
listed firms have relatively greater incentives to invest in player
contracts to protect against relegation to a lower league.
We also calculate a measure of financial leverage, which is
comparable across the accounting treatment of player contracts.
This measure is the ratio of total liabilities divided by adjusted
total assets, where adjusted total assets exclude capitalized player
contracts. In all years and for all company types this ratio is very
high, with private firms being more highly leveraged than listed
firms though the difference is insignificant in 1990–1995.
In Panel C of Table 2 we present the combined book rate of
amortization and impairment of player contracts for the post-FRS
10 period. The implied useful life of a contract is between three to
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ACCOUNTING & FOOTBALLERS’ CONTRACTS
563
four years although the median rate of amortization is larger for
private firms than for listed firms.10 Since FRS 10 requires all
previously expensed player contracts to be reinstated (i.e., restatement), we are also able to calculate the intangible intensity ratio on
a comparable basis in this panel. This ratio is defined as the cost of
player contracts net of accumulated amortization over total assets.
The average (median) ratio is 20% (16%) indicating the economic
importance of player contracts. Intangible intensity is higher for
listed companies, consistent with the observation that they pay
more for player contracts than private firms.
In sum, Table 2 shows that football companies are loss
makers and that wages and investment in player contracts are
very significant expenditures relative to sales, implying a high
degree of intangible intensity. The growth in the industry has
not translated into higher profitability. In addition, the table
shows that listed companies are larger, more profitable, generate
more cash flow from operations and spend more on acquisition
of player contracts, but relatively less on wages.
Table 3 provides descriptive statistics by League. Six different
leagues are represented in our sample: The English Premier
League; English National Divisions One, Two and Three; The
Scottish Premier League and the Scottish Division One. Clearly,
clubs in the English and the Scottish Premier leagues generate
more revenues than firms in lower divisions, due to revenues
from the media. For example, while the mean revenues for
English Premier League teams in the sample is about £28
million, the mean revenues for English Division One teams is
only about £6 million, and mean revenues for English Division 3
is a mere £1.5 million.
Furthermore, the share of wages from total sales is lower in
Premier Clubs than in clubs in lower divisions. For example, the
average wages-to-sales ratio in the English Premier League is
0.58, compared with 0.80 in the English National Divisions.
Premier League teams generate losses from trading players,
where losses are measured here as investments in players minus
revenues from selling players. Teams in lower divisions, however,
10 It is possible that private companies select higher amortization rates for contracts of
similar duration as listed companies, but it is also possible that private companies
purchase players on shorter-term contracts.
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564
Table 3
Key Financial Variables by League
English Premier
English Div-1
English Div-2
English Div-3
Scottish Premier
Scottish Div-1
Mean Median Mean Median Mean Median Mean Median Mean Median Mean Median
Total Sales (£000s)
Wages/Sales
Operating Profit/Sales
Cash From Operations/Sales
Transfer Fees Paid/Sales
Transfer Fees Received/Sales
Adjusted Leverage
28,231
0.58
0.08
0.07
0.39
0.25
0.88
17,632 6,319 4,733 2,322 1,931 1,548 1,326 11.054 4,896 1,491 1,012
0.56
0.80
0.79
0.80
0.79
0.79
0.74
0.68
0.68
1.07
0.98
0.09 0.25 0.21 0.25 0.22 0.22 0.13 0.12 0.08 0.47 0.26
0.07 0.09 0.03 0.05 0.03 0.05 0.01 0.05
0.00 0.35 0.42
0.36
0.30
0.23
0.17
0.10
0.06
0.03
0.28
0.23
0.12
0.14
0.17
0.36
0.22
0.27
0.15
0.18
0.10
0.19
0.13
0.29
0.21
0.80
0.95
0.90
1.03
0.99
0.96
0.75
0.87
0.68
0.93
0.88
#
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Notes:
1
Descriptive statistics for 6 leagues represented in the sample: English premier leagues (244 observations), English national divisions 1 (186
observations), 2 (128 observations) and 3 (67 observations), Scottish premier league (90 observations) and Scottish division 1 (13 observations).
2
See Table 1 for sample selection.
3
See Table 2 for variable definitions.
AMIR AND LIVNE
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ACCOUNTING & FOOTBALLERS’ CONTRACTS
565
generate profits from trading players. For example, English Premier League teams invest, on average, 39% of sales in new player
contracts and receive, on average, 25% of sales from selling
players. Teams in Division 3 invest only 6% of sales in new player
contracts and generate, on average, 18% of sales from selling
players. This result highlights two distinct strategies used by UK
football companies for utilizing talent: large companies seem to
heavily invest in player contracts to maintain league position
whereas smaller companies seem to trade in player contracts to
sustain their financial viability, which comes at a cost of staying in a
lower league. However, the cost of maintaining players on the
roster is relatively lower for teams in higher leagues.
As discussed earlier, prior to 1999 companies could elect
whether to expense the cost of player contracts or to capitalize
and amortize it. We also examine whether capitalizing and
expensing companies exhibit different financial characteristics
(not reported). As for listed companies, capitalization occurs in
32% of firm-year observations. Nonetheless, capitalizing and
expensing companies have similar sales volume, wages-to-sales
ratios, similar operating profit margins and operating cash flow.
Capitalizing companies have lower financial leverage than
expensing companies, suggesting that leverage is not a motivating factor behind the accounting choice. As for private companies, only 9% of the observations relate to capitalizing
companies and we find no significant difference between
capitalizing and expensing private companies in terms of
sales volume, wages-to-sales ratios, operating profit margins,
operating cash flows and leverage (not tabulated).
4. THE ASSOCIATION BETWEEN INVESTMENT IN PLAYER
CONTRACTS AND FUTURE BENEFITS
(i) The Association between Future Economic Benefits and Current and
Lagged Investments in Player Contracts – Regression Analysis
We next turn to examine the association between future economic
benefits and current and lagged investments in player contracts.
We postulate that a soccer firm’s production function is related
to its stock of tangible fixed assets (e.g., the stadium) and stock
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566
AMIR AND LIVNE
of intangible fixed assets (e.g., investment in players). The cost
of the latter comes in two forms: wages and transfer fees.
Thus, we postulate that the production function P can be
expressed as P ¼ f(Tangible assets, Intangible transfer fee assets,
Labour).
Ideally, we would like to use the balance of transfer fees at
the end of the year, as we do with tangible assets. However,
for most clubs this figure is not available prior to FRS 10.
Table 2 (Panel C) indicates that under FRS 10 most firms use
amortization rates of three to four years. We therefore
include three lags of investment in player contracts: current,
past year and the year before. Since the balance of transfer
fees is affected by ‘disposals’ of players, we also include three
lags of cash received for sale of contracts in the production
function. Note that the use of lagged investment in and
disposal of player contracts is also motivated directly from
the accounting definition of assets: current and past investments (disposals) of assets should be positively (negatively)
related to current benefits.
We use three accounting-based measures of economic
benefits – sales (SALESit), operating profit (OPROFit) and cash
flows from operations before interest, taxes and transfer fees
(ACFOit). Based on the discussion above, we construct the
following model:
Benefitit ¼
T
X
t¼1
0t YEARINDt þ
I
X
1i FIRMINDi þ 2 WAGESit
i¼1
þ 3 TASit þ 4 TFINVit þ 5 TFINVit1 þ 6 TFINVit2 ð1Þ
þ 7 TFRECit þ 8 TFRECit1 þ 9 TFRECit2 þ eit
where Benefitit is separately set equal to SALESit, OPROFit,
and ACFOit. WAGESit denotes total current wages. Year and
firm fixed effects are represented by the indicators YEARINDit
and FIRMINDit. Tangible fixed assets are represented by
TASit. The main variables of interest are TFINVit, the level
of gross investment in player contracts, and TFRECit, cash
received from selling player contracts. To control for scale
and heteroscedasticity effects, we deflate all variables by prior
year’s sales and estimate our model using Weighted Least
Squares (WLS). Employing lagged sales as a deflator may
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ACCOUNTING & FOOTBALLERS’ CONTRACTS
567
also control for possible simultaneity effects, as investments in
player contracts may be driven by higher sales.11
As discussed earlier, the competitive environment in this industry
may have changed over the sample period due to ‘Bosman’ ruling
and the introduction of large payments for broadcasting rights. In
addition, several companies are listed and others are private. To
control for possible firm and time specific differences, we add year
and company fixed effects to our regression model to ensure that
the regression results are not affected by such differences.
We also estimate a restricted version of an equation in which
we examine the relationship between future benefits and net
investment in player contracts:
Benefitit ¼
T
X
0t YEARINDt þ
t¼1
I
X
1i FIRMINDi þ 2 WAGESit
i¼1
þ 3 TASit þ 4 NINVit þ 5 NINVit1 þ 6 NINVit2
þ e0it
ð2Þ
where NINVit denotes net investment in players’ contracts,
measured as investment in players’ contracts minus revenues
from selling players’ contracts (TFINVit TFRECit). This model
restricts the coefficients on gross investments and revenues
from selling player contracts to be identical in absolute values.
We use this model as a sensitivity check for equation (1).
We expect a contemporaneous relation between economic
benefits and investments in player contracts. In particular,
investing in player contracts should be positively associated with
current economic benefits whereas selling player contracts should
be negatively associated with current economic benefits. Furthermore, if player contracts have a duration of more than one year – a
necessary condition for capitalization and amortization under FRS
10 – we would also expect lagged investments and disposals of
player contracts to be associated with current economic benefits.
Table 4 provides pairwise correlation coefficients across the
variables used in the regression. Observe that the correlation
11 We also considered other possible deflators. Market values are available for only a
subset of firms. Deflating by reported total assets or reported book values of equity
suffers from a consistency problem because prior to FRS 10 firms differed in the
treatment of transfer fees. In addition, because several clubs report negative equity,
book value of equity was also ruled out as a deflator.
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AMIR AND LIVNE
Table 4
Correlation Matrix – Pearson (above diagonal) and Spearman (below
diagonal) Correlations
Variable SALES OPROF ACFO WAGES
TAS
SALES
OPROF
ACFO
WAGES
TAS
TFINV
TFREC
NINV
0.26
0.09
0.10
0.25
1.00
0.12
0.06
0.05
1.00
0.37
0.43
0.41
0.23
0.32
0.05
0.32
0.39
1.00
0.68
0.46
0.02
0.27
0.21
0.43
0.33
0.52
1.00
0.24
0.07
0.29
0.25
0.50
0.52
0.40
0.15
1.00
0.15
0.06
0.20
0.15
TFINV TFREC NINV
0.29
0.19
0.25
0.15
0.11
1.00
0.34
0.58
0.07
0.28
0.29
0.20
0.07
0.40
1.00
0.47
0.33
0.42
0.49
0.04
0.03
0.54
0.55
1.00
Notes:
The table contains simple correlations for the regression variables (see Tables 5–7). The
first three variables below represent benefit measures and the remaining variables
represent independent variables. All variables are deflated by lagged sales (subscript
time indicator is dropped for current period’s variables):
1
SALES ¼ Current sales divided by lagged sales (Salest/Salest 1).
2
OPROF ¼ Operating profit before transfer fees divided by lagged sales ([Salest –
Wages – Operating Expenses]/Salest 1).
3
ACFO – Adjusted Cash Flows from Operations, measured as cash from operations
before player contract (transfer fees), deflated by lagged sales (ACFOt/Salest 1).
4
TAS ¼ Total assets divided by lagged sales (Total Assetst/Salest 1).
5
WAGES ¼ Current wages divided by lagged sales (Wagest/Salest 1).
6
TFINV ¼ Current investment in player contracts (TFINV), measured as cash invested
in new contracts, deflated by lagged sales (TFINVt/Salest 1).
7
TFREC ¼ Current cash received from selling player contracts (TFREC), deflated by
lagged sales (TFRECt/Salest 1).
8
INV ¼ Current investment in player contracts (TFINV) minus current cash received
from selling player contracts (TFREC), deflated by lagged sales [(TFINVt-TFRECt)/
Salest 1)].
coefficients between the three benefit measures are generally
large. The largest one is for cash from operations and
operating profit (Pearson’s coefficient ¼ 0.52, Spearman’s
coefficient ¼ 0.68). The correlation coefficients between investments in player contracts and the three benefit measures are
positive, which demonstrate positive contemporaneous relations
between transactions in player contracts and benefits that accrue
to the companies. Nonetheless, from the moderate correlation
coefficients, it is clear that investments in player contracts are
just one factor that explains current performance. Wages are
positively related to sales, but negatively to operating profit and
operating cash flow, suggesting players extract some considerable
rents through their wages.
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ACCOUNTING & FOOTBALLERS’ CONTRACTS
569
The correlations between current and lagged investments
(not tabulated) are positive but not too large. This suggests
that multicollinearity is likely to have only a negligible effect
on the estimation procedure employed next.
Table 5 reports the coefficients from estimating equations (1)
and (2) for the three accounting-based benefit measures. When
SALESit is the dependent variable, results of estimating equation (1) show that the coefficient on current investments in
player contracts (TFINVit) is positive and significant at the 1%
level. In addition, the coefficient on the second lag of investments in player contracts (TFINVit2) is also positive and significant at the 10% level. The coefficients on both current and
first lag of disposals of player contracts (TFRECit and TFRECit1)
are negative, as expected, and significant at the 1% level. The last
lag is insignificantly different from zero. When equation (2) is
estimated, both current and first lag of net investment in player
contracts (NINVit and NINVit1, respectively) are positive, as
expected, and significant at the 5% level or better. But NINVit2
is not different from zero. These results suggest that investments
in player contracts are associated with current and future sales but
that the useful lives of these investments are limited to no more
than two years. Note that this contrasts with the accounting rate of
amortization that was calculated in Table 2, which implies useful
life of three to four years.
When operating profit (OPROFit) is the dependent variable, the
results are quite similar. In particular, results of estimating equation (1) show that the coefficients on current and the two lags of
investments in player contracts are significant at the 10% level or
better. However, the last lag is negative. The coefficients on
current and prior year’s disposals of player contracts are negative
and significant at the 1% level. When equation (2) is estimated, the
coefficients on NINVit and NINVit1 are positive, as expected,
and significant at the 1% level. These results suggest that investing
in player contracts, on average, increases current and next period’s
operating profit, but the effect ceases after two years.
Having cash from operations before transfers as the dependent
variable, estimation of equation (1) yields even weaker results.
The coefficients on current investments in player contracts
are negative, except for the current year’s investment, which
is significant and positive. Only the current disposal is negative
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Table 5
Equation 1 : Benefitit ¼
T
X
0t YEARINDt þ
t¼1
I
X
570
The Association between Future Economic Benefits and Current and Lagged Net Investments in Player Contracts
1i FIRMINDi þ 2 WAGESit þ 3 TASit þ 4 TFINVit
i¼1
þ 5 TFINVit1 þ 6 TFINVit2 þ 7 TFRECit þ 8 TFRECit1 þ 9 TFRECit2 þ eit
Equation 2 : Benefitit ¼
T
X
0t YEARINDt þ
t¼1
I
X
1i FIRMINDi þ 2 WAGESit þ 3 TASit þ 4 NINVit
i¼1
þ 5 NINVit1 þ 6 NINVit2 þ "0it
WAGES
TAS
TFINVt TFINVt1 TFINVt2 TFRECt TFRECt1 TFRECt2 NINVt
Sales
SALES
1.26
0.17
0.25
t-statistic 21.89*** 10.10*** 5.09***
0.09
1.47
0.12
1.94*
0.38
0.17
6.19*** 2.53***
0.01
0.07
SALES
1.18
0.16
t-statistic 24.23*** 9.73***
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Operating Profit
OPROF 0.04
t-statistic 0.87
0.05
0.23
3.94*** 5.60***
OPROF 0.10
t-statistic 2.47**
0.05
3.48***
Operating Cash Flows
ACFO
0.00
0.10
0.32
0.05
t-statistic 0.07
5.25*** 5.86*** 0.78
ACFO
0.08
t-statistic 1.49
0.09
4.83***
0.96
499
0.31
7.19***
0.12
2.59***
0.08
1.70*
0.28
0.19
5.63*** 3.63***
0.42
0.07
6.33*** 0.92
0.11
2.19**
0.01
0.09
0.08 0.96
1.46 499
0.55
499
0.26
7.29***
0.09
1.80*
NINVt1 NINVt2
Adj-R2
N
0.15
3.67***
0.10
1.23
0.06 0.54
1.27 499
0.54
499
0.37
0.01
7.77*** 0.17
0.02 0.54
0.33 499
AMIR AND LIVNE
Full
Sample
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Notes:
1
The dependent variable is measured as sales, operating profit before the effect of player contracts and cash flows from operations before the
effect of player contracts. Explanatory variables include current and lagged investment in player contracts and current and lagged cash received
from selling player contracts. Each model includes fixed year and company effects. Each model is regressed using WLS after deflation of
all variables and fixed effects by prior year’s sales. Reported results are for the deflated models. The sample contains 499 observations over
1990–2003.
2
Variables are defined as follows (subscript time indicator is dropped for current period’s variables):
SALES
¼ Current sales.
OPROF
¼ Operating profit before transfer fees.
ACFO
¼ Adjusted cash flows from operations, measured as cash from operations before interest, taxes and transfer fees.
WAGES
¼ Current wages.
TAS
¼ Total assets, excluding capitalized transfer fees.
TFINVi,t k ¼ Investment in player contracts in year t k k ¼ {0,1,2}, measured as cash invested in new contracts.
TFRECi,t k ¼ Cash received from selling player contracts in year t k k ¼ {0,1,2}.
NINVi,t k ¼ Net investment in player contracts, measured as the difference between the cost of player contracts the cash received from selling
player contracts ( ¼ DTFINV – DTFREC).
3
*, **, *** two-tail p-value < 0.10, <0.05 and <0.01, respectively.
571
572
AMIR AND LIVNE
and significant. Estimating equation (2) shows that the coefficient
on NINVit is positive and significant at the 1% level only for the
current period.
Altogether, we find a statistically reliable association between
cash paid and cash received on trading in player contracts, and
accounting-based measures of future economic benefits. However, the duration of this association is at most two years, depending on the benefit measure used, which is shorter than the
duration implied by the accounting amortization reported in
Table 2 (Panel C). It should be remembered, however, that this
comparison pertains to the post-FRS 10 period only, whereas the
analysis in Table 5 pertains to the entire sample period.
(ii) Market-based Analysis
We now turn our attention to listed companies to conduct a
market-based analysis using a valuation model based on Ohlson’s
(1995) framework. Our model relates market value of equity to
net income, book value of equity and investments in player contracts. Under the assumption that market values summarize all
available information regarding future net economic benefits, this
analysis is potentially useful in assessing aspects of the association
between investments in player contracts and future economic
benefits that is not captured by the previous fundamental analysis.
By implication, this analysis can shed light on whether investors
expect investment in player contracts to result in better financial
performance in the future.12
We also attempt to understand if accounting choice is value
relevant as well as whether introducing FRS 10 has had any
effect on the value relevance of investments in player contracts,
reported income and reported book value of equity. Accordingly, we estimate four main specifications. First, we estimate
the relation between market values of equity three months after
12 We also conducted an event study of market reaction around 1,348 football games to
directly test the link between actual player performance and stock returns. (A regression
of share price on net investment in player contracts can be thought of as a test of the link
between market value and expected player performance.) We find a strong correlation
between game outcome and market reaction (not tabulated), consistent with the idea
that good player performance has positive effect on financial performance. For
example, the average 6-day return around games that were won was 1.4%, 1.7%
around games that are lost, and 0.07% around games that are tied.
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ACCOUNTING & FOOTBALLERS’ CONTRACTS
fiscal year-end (MV3it) and the two summary financial measures –
reported book value of equity (BVEit) and reported net income
(NETINCit) – for the 187 annual observations with complete
market and financial data.13 We obtain the following (undeflated)
model:
MV3it ¼
T
X
0t YEARINDt þ
t¼1
I
X
1i FIRMINDi þ 2 BVEit
i¼1
ð3Þ
þ 3 NETINCit þ !it:
Note that, as in the benefits equations, the model excludes an
intercept but includes year and company fixed effects (YEARIND and FIRMIND) to control for potential model mis-specifications and to compensate for omitted variables.14 This model,
as well as the remaining market-based models, is then estimated
using weighted least squares (WLS) where prior year’s sales
serves as the deflator for all variables.
To assess the value relevance of transfer fees, equation (3) is
extended to include gross investments in player contracts
(TFINVit) and cash received from selling player contracts
(TFRECit). The inclusion of cash received from disposal of
player contracts is motivated by the fact that such disposals
may fund acquisition of new contracts, resulting in potential
correlation between TFINVit and TFRECit. Since market values
may also be affected by disposals, exclusion of TFRECit may
result in a biased coefficient on TFINVit:
MV3it ¼
T
X
0t YEARINDt þ
t¼1
I
X
1t FITRMINDi þ 2 BVEit
ð4Þ
i¼1
þ 3 NETINCit þ 4 TFINVit þ 5 TFRECit þ
!0it :
13 Although UK listed firms are permitted to publish their annual financial statements
six months after fiscal year-end, many football companies do so much earlier. In
addition, the football industry is covered extensively by the media and game outcomes
are priced on a weekly basis. Using market values six months after fiscal year-end may
affect the results due to information released after the fiscal year-end. Nevertheless, we
repeated our analysis using share prices 6 months after fiscal year-end obtaining very
similar results.
14 Garrod and Rees (1998) use a similar framework to examine the valuation
implications of international diversification. Rees (1997) also uses a similar model to
examine the effect of dividends and capital investments on the market value of equity.
Football companies rarely pay any dividends and the magnitude of capital investments is
quite low. We therefore excluded these variables from our model.
#
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574
AMIR AND LIVNE
Note that the above model relies on reported values. One
problem with reported figures is that pre-FRS 10 the accounting treatment of transfer fees was not uniform. Since we do not
have sufficient information to estimate value of hypothetical
assets, we obtain a time-consistent and comparable basis by
excluding capitalized player contracts from book value of
equity, resulting in adjusted book value of equity, ABVEit, and
adjusting reported income as follows. For capitalizing firms we
add to net profit the amortization of any capitalized player
contracts and deduct (add) gain or loss on trading in player
contracts. For expensing firms, we add back transfer fees paid
and deduct transfer fees received. The adjusted profit figure,
denoted ANETINCit, is an income figure that is free of transfer
activity and thus is comparable over time.15 This yields the
following two modified regression models corresponding to
equations (3) and (4), respectively:
T
X
MV3it ¼
0t YEARINDt þ
t¼1
I
X
1i FIRMINDi þ 2 ABVEit
i¼1
ð5Þ
þ 3 ANETINCit þ it
and
T
X
MV3it ¼
t¼1
0t YEARINDt þ
I
X
1i FIRMINDi þ 2 ABVEit
i¼1
þ 3 ANETINCit þ 4 TFINVit þ 5 TFRECit þ
ð6Þ
it0 :
To assess the effect of FRS 10 on the value relevance of these
variables, we estimate all equations separately for 1990–1998, the
years prior to the effective date of FRS 10 in which accounting
choice was available (92 observations), and for 1999–2003, the
sample years during which FRS 10 was in effect (95 observations).
As Panel A of Table 6 shows, the coefficient on reported book
value of equity in equation (3) is positive and of similar magnitude in all time periods. The coefficient on net income is positive
but insignificant in all periods. The adj-R2 of equation (3)
15 We have not made any adjustment for income taxes as our interest is merely achieve
comparable basis across time. In addition, many firms in our sample have zero tax bill as
they run losses.
#
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#
Table 6
Panel A:
Equationð3Þ : MV3it ¼
T
P
0t YEARINDt þ
t¼1
Equationð4Þ : MV3it ¼
T
X
0t YEARINDt þ
t¼1
PI
i¼1
I
X
1i FIRMINDi þ 2 BVEit þ 3 NETINCit þ !it
1t FITRMINDi þ 2 BVEit þ 3 NETINCit þ 4 TFINVit
i¼1
þ 5 TFRECit þ !0it
Equationð5Þ : MV3it ¼
T
P
0t YEARINDt þ
t¼1
Equationð6Þ : MV3it ¼
T
X
0t YEARINDt þ
t¼1
PI
i ¼ 1 1i FIRMINDi
I
X
þ 2 ABVEit þ 3 ANETINCit þ it
1i FIRMINDi þ 2 ABVEit þ 3 ANETINCit þ 4 TFINVit
i¼1
þ 5 TFRECit þ it0
Sample
1.85
9.84***
1.59
6.68***
NETINC
(þ)
ABVE
(þ)
ANETINC
(þ)
0.95
1.39
1.29
1.83*
TFINV
(þ)
TFREC
(-)
AdjR2
F-test
(p-val)
0.44
1.14
1.56
1.88
6.33***
1.89
6.73***
3.04
3.62***
1.87
2.20**
0.32
0.28
0.45
1.61
(0.20)
0.41
2.29
3.61***
0.06
0.05
0.49
12.27
(0.00)
575
Full Sample (1990–2003)
Equation (3)
t-statistic (187 observ.)
Equation (4)
t-statistic (187 observ.)
Equation (5)
t-statistic (187 observ.)
Equation (6)
t-statistic (187 observ.)
BVE
(þ)
ACCOUNTING & FOOTBALLERS’ CONTRACTS
Blackwell Publishing Ltd 2005
The Association between Market Values of Equity and Book Values of Equity, Net Income, and Investments in
Player Contracts
576
Table 6 (Continued)
Sample
#
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1999–2003 (post-FRS 10)
Equation (3)
t-statistic (95 observ.)
Equation (4)
t-statistic (95 observ.)
Equation (5)
t-statistic (95 observ.)
Equation (6)
t-statistic (95 observ.)
NETINC
(þ)
1.67
5.24***
0.93
2.65***
1.60
1.16
2.59
1.91*
ABVE
(þ)
TFINV
(þ)
TFREC
(-)
AdjR2
F-test
(p-val)
0.39
5.66
3.61***
2.19
4.92***
1.46
3.32***
1.99
8.91***
2.23
7.11***
ANETINC
(þ)
1.92
1.31
2.25
1.68*
0.67
0.95
0.36
0.47
2.23
1.11
0.50
8.63
(0.00)
0.42
5.25
3.81***
1.69
0.93
0.53
9.60
(0.00)
0.51
0.41
0.55
1.58
3.93***
1.78
4.47***
3.77
3.84***
2.60
2.23**
0.95
0.74
0.52
0.89
(0.41)
0.42
1.34
1.71*
0.83
0.55
0.48
5.17
(0.01)
AMIR AND LIVNE
1990–1998 (pre-FRS 10)
Equation (3)
t-statistic (92 observ.)
Equation (4)
t-statistic (92 observ.)
Equation (5)
t-statistic (92 observ.)
Equation (6)
t-statistic (92 observ.)
BVE
(þ)
#
Equationð4aÞ : MV3it ¼
T
P
t¼1
Equationð6aÞ : MV3it ¼
T
P
t¼1
Sample
Full sample (1990–2003)
Equation (4a)
t-statistic (187 obs.)
Equation (6a)
t-statistic (187 obs.)
1990–1998 (pre-FRS 10)
Equation (4a)
t-statistic (92 obs.)
Equation (6a)
t-statistic (92 obs.)
0ot YEARINDt þ
0
0t
YEARINDt þ
BVE (þ)
NETINC (þ)
1.65
7.19***
1.23
1.75*
I
P
i¼1
I
P
i¼1
01t FIRMINDi þ 02 BVEit þ 03 NETINCit þ 04 NINVit þ it0
0
1i
FIRMINDi þ 20 ABVEit þ 30 ANETINCit þ 40 NINVit þ it0
ABVE (þ)
1.93
6.77***
1.02
2.84***
1999–2003 (post-FRS 10)
Equation (4a)
2.08
t-statistic (95 obs.)
7.20***
Equation (6a)
t-statistic (95 observ.)
ANETINC (þ)
0.45
1.75
2.03**
0.46
2.32
1.68*
5.25
3.28***
4.77
3.38***
0.58
0.79
1.84
4.54***
Adj- R2
1.12
1.54
2.55
3.99
3.01
2.18**
1.63
3.63***
NINV (þ)
2.15
1.84*
0.36
0.48
1.85
2.43**
0.46
0.49
0.51
ACCOUNTING & FOOTBALLERS’ CONTRACTS
Blackwell Publishing Ltd 2005
Panel B:
0.46
577
Notes:
1
Variables: MV3 is market value of equity (share price multiplied by the number of shares outstanding) 3 months after fiscal year-end. BVE is
book value of equity. ABVE denotes book value of equity less capitalized transfer fees. NETINC denotes net income. ANETINC is net income
before transfer fees. NINV is net investment in players’ contracts, measured as investments in player contracts (TFINV) minus cash received
from selling player contracts (TFREC). Each model is regressed using WLS after deflation of all variables and fixed effects by prior year’s sales.
Reported results are for the deflated models.
2
*, **, *** denote 2-tail p-value below 0.10, 0.05 and 0.01, respectively.
578
AMIR AND LIVNE
increases to 0.51 from 0.39 when FRS 10 comes into effect,
providing preliminary indication of the improved information
content under this standard as all companies provide comparable
information.
When transfer fees paid and received are added (equation
(4)), reported income turns significant at the 10% level in the
pre-FRS 10 period, but not in the late period. Since reported
income in many cases is calculated under the expensing method
before 1999, we conclude that transfer activity enhanced the
value relevance of reported profits prior to FRS 10. Indeed
when FRS-10 is in force, this effect is not present, suggesting
that reported numbers under FRS 10 better capture information in transfer fees than in the previous period. Note that the
coefficient on transfer fees received is positive and significant
during 1990–1998, but not in the later period. Furthermore,
the p-value of the F-test of 0.00 indicates that transfer fees
received and paid collectively have incremental explanatory
power over reported book value of equity and net income in
1990–1998. This is not the case under FRS 10, indicating that
the capitalization requirement in the Standard resulted in
reported values that efficiently summarize information in transfer fees. Consistent with this, we also note that the adj-R2 is
roughly similar in the two sub-periods.
Estimation of equations (5) and (6) again shows that adding
transfer fees received and paid, work to enhance the value
relevance of reported earnings. We can also reject the null
that TFINV and TFREC do not jointly offer incremental
explanatory power over adjusted book value of equity and
adjusted net income. This can be seen from the high values
for the F-tests. Consistent with the argument that transfer fees
paid should be treated as assets, the coefficient on TFINV is
positive and significant at 10% or better in all periods. Nevertheless, the coefficient on TFREC is not significantly different
from zero in any time period.
As an alternative specification, we also estimate the association
between net investment in player contracts (NINV), instead of
gross investments and disposal of player contracts (TFINV and
TFREC), and market values of equity. Equations (4a) and (6a)
restrict the coefficients on TFINVit and TFRECit to be identical
in absolute values.
#
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ACCOUNTING & FOOTBALLERS’ CONTRACTS
MV3it ¼
T
X
0ot YEARINDt þ
t¼1
þ
03 NETINCit
þ
I
X
01t FIRMINDi þ 02 BVEit
i¼1
04 NINVit
þ
579
ð4aÞ
it0
and
MV3it ¼
T
X
0
0t
YEARINDt þ
t¼1
þ
30 ANETINCit
þ
I
X
0
1i
FIRMINDi
i¼1
40 NINVit þ it0 :
þ 20 ABVEit
ð6aÞ
The results of estimating equations (4a) and (6a) are reported in
Table 6, Panel B. For the entire sample period, NINV is not
significantly different from zero, regardless of model specification.
However, it is positive and significant in 1990–1998 for equation
(4a) and in each sub-period for equation (6a). This is generally
consistent with the earlier findings whereby transfer fees are
regarded by the market as assets. It also confirms the informational
effects of FRS 10.
The positive association between investment in player contracts
and market values stands in some contrast to the findings of the
previous analyses, which showed only weak association between
investment in player contracts and future benefits. However,
the results are not entirely comparable as the previous analysis
included listed as well as unlisted companies. Also, market participants may focus on benefit measures not captured in our
previous analyses. In addition, it is not possible to infer from the
market-based tests the useful life of the investment, nor is it
possible to infer the likelihood of a successful investment.
In the last set of tests we examine the valuation implications of
accounting choice. For the period when FRS 10 is in effect, we
calculate book value of equity and net income under immediate
expensing, the alternative method to capitalization. Specifically,
we exclude capitalized player contracts from book value of equity
to obtain book value of equity under immediate expensing. We
also replace amortization, gains/losses and impairments of player
contracts with net cash invested in player contracts to obtain
net income under expensing. This yields two alternative variables
for book value of equity, BVE(EXP), and for net income,
NETINC(EXP). We then run two tests. First, to provide
#
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580
AMIR AND LIVNE
additional evidence on the informativeness of FRS 10-based variables, we examine whether BVE and NETINC have incremental
explanatory power over BVE(EXP) and NETINC(EXP). Second,
we compare the relative explanatory power of capitalization vs.
expensing. A test of relative explanatory power is a test of the
ability of one set of variables to explain the dependent variable
better than another set of variables. In this case, we are interested
in learning whether reported book value of equity and income
under capitalization better summarise the information in prices
than book value of equity and net income under expensing.16
The incremental explanatory power test is performed by an
F-test on the null that 4 ¼ 5 ¼ 0 in the following equation:
MV3it ¼
T
X
I
X
0t YEARINDt þ
t¼1
i¼1
1t FIRMINDi þ 2 BVEðEXPÞit
ð7Þ
þ 3 NETINCðEXPÞit þ 4 BVEit þ 5 NETINCit þ !it :
Relative explanatory power is performed using the test in
Voung (1989) by contrasting two sub-models of (7):
MV3it ¼
T
X
a
0t
YEARIND þ
t¼1
I
X
a
1i
FIRMIND þ 2a BVEðEXPÞit
ð7aÞ
i¼1
þ 3a NETINCðEXPÞit þ !ait
and
MV3it ¼
T
X
b
0t
YEARINDt þ
t¼1
þ
3b BVEit
I
X
b
1i
FIRMINDi
i¼1
þ
4b NETINCit
þ
ð7bÞ
!bit :
Note that equation (7a) essentially forces the coefficients on
BVE and NETINC in equation (7) to be zero. Similarly, equation
(7b) forces the coefficients on BVE(EXP) and NETINC(EXP) in
equation (7) to be zero. Also note that equation (7b) is identical
to equation (3), but we have relabeled it for the ease of exposition.
The results are reported in Panel A of Table 7. The F-test is
highly significant, suggesting that book value of equity and net
16 See Francis et al. (2003) for detailed discussion of tests of relative and incremental
explanatory power.
#
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#
The Association between Market Values of Equity and Book Values of Equity
and Net Income: Capitalization vs. Expensing of Investments in Player Contracts
Panel A:
Equation ð7Þ : MV3it ¼
T
X
0t YEARINDt þ
t¼1
I
X
1t FIRMINDi þ BVEðEXPÞit þ 3 NETINCðEXPÞit
i¼1
þ 4 BVEit þ 5 NETINCit þ !it
T
I
X
X
a
a
Equation ð7aÞ : MV3it ¼
0t
YEARIND þ
1i
FIRMIND þ 2a BVEðEXPÞit þ 3a NETINCðEXPÞit þ !ait
Equation ð7bÞ : MV3it ¼
t¼1
T
X
b
0t
YEARINDt
t¼1
i¼1
I
X
þ
b
1i
FIRMINDi þ 3b BVEit þ 4b NETINCit þ !bit
i¼1
Equation (7a)
Sample
1999–2003 (FRS
10 in effect)
t-statistic (95
observations)
Equation (7b)
NETINC (EXP)
(þ)
Adj-R2
2.23
0.36
0.34
7.11***
0.47
BVE (EXP)
(þ)
BVE
(þ)
NETINC
(þ)
1.99
0.67
8.91***
0.95
Adj-R2
0.51
F-test of
Incremental
Explanatory
Power (p-value)
Vuong’s Z-test of
Relative Explanatory
Power (p-value)
4 ¼ 5 ¼ 0
in Eq. (7)
(7b) vs. (7a)
17.98
3.39
(0.00)
0.00
ACCOUNTING & FOOTBALLERS’ CONTRACTS
Blackwell Publishing Ltd 2005
Table 7
581
582
Table 7 (Continued)
Panel B:
Equation ð8Þ : MV3it ¼
T
X
0t YEARINDt þ
t¼1
I
X
1t FIRMINDi þ 2 BVEit þ 3 EXP BVEit þ 4 NETINCit
i¼1
þ 5 EXP NETINCit þ #it
BVE (þ)
EXP BVE
NETINC (þ)
EXP NETINC
Adj-R2 Obs.
1990–1998 (prior to FRS 10)
t-statistic
1999–2003 (FRS 10 in effect)
t-statistic
1.35
3.99***
1.17
4.29***
1.38
2.65***
1.18
3.74***
0.81
0.34
1.20
1.47
2.71
1.03
3.48
2.82***
0.45
92
0.61
95
#
Blackwell Publishing Ltd 2005
Notes:
1
Variable definitions: MV3 is market value of equity (price per share multiplied by the number of shares outstanding) 3 months after fiscal yearend. BVE denotes reported book value of equity. BVE(EXP) denotes book value of equity assuming player contracts are expensed. NETINC
denotes reported net income. NETINC(EXP) is net income assuming player contracts are expensed. EXP is an indicator variable that obtains the
value of ‘1’ if the company elected to expense transfer fees during 1990–1998, and ‘0’ if the company elected to capitalize transfer fees. Each
model is regressed using WLS after deflation of all variables and fixed effects by prior year’s sales. Reported results are for the deflated models.
2
*, **, *** denote 2-tail p-values below 0.10, 0.05 and 0.01, respectively.
AMIR AND LIVNE
Sample
ACCOUNTING & FOOTBALLERS’ CONTRACTS
583
income under capitalization provide information incremental to
that in book value of equity and net income under expensing.
In that panel we also report the results of the two alternative
models (7a) and (7b). Under both alternatives the coefficient on
book value of equity is positive and significant. This is expected,
as expensing is more conservative in that it understates
potential economic assets. The coefficient on net income is
positive in both cases, but insignificant. The adj-R2 for full
expensing is 34%, whereas that for capitalization is 51%.
Voung’s test confirms that capitalization has greater ability to
summarize information in prices than expensing. We also
conducted a Wald test, as an alternative to Voung’s test.
Wald’s 2 statistic is 7.53 with p-value of 0.01 (not tabulated).
Thus, our result is robust to the type of test used. We conclude
from this table that a method of immediate expensing is value
relevant. However, capitalization seems to better capture information used by market participants in setting share prices.
Does the last result imply that expensing is unwarranted
altogether? To assess this, we re-estimate equation (3) allowing
the coefficients on reported book value of equity and reported
net income to vary according to the accounting method used by
the company to account for player contracts prior to fiscal 1999.
We do this in order to see whether a standard like FRS 10,
which removes accounting choice, could have some detrimental
effect on the flow of information from firms to the market.
Thus, we estimate equation (8):
MV3it ¼
T
X
0t YEARINDt þ
t¼1
I
X
1t FIRMINDi þ 2 BVEit
i¼1
þ 3 EXP BVEit þ 4 NETINCit
ð8Þ
þ 5 EXP NETINCit þ #it
where EXP is an indicator variable which obtains the value of ‘1’
if the company elected to expense player contracts prior to fiscal
1999 (the year FRS 10 became effective), and ‘0’ otherwise. This
approach helps us to test whether the market assesses differently reported income and book value of equity of capitalizing
firms than previously expensing firms. In addition, if 3 and 5
are significant for the 1999–2003 period, when accounting
choice is not available and treatment of player contracts is
#
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584
AMIR AND LIVNE
identical, one can conclude that past accounting choice is still
value relevant. This, in turn, would be consistent with the general idea that lack of accounting choice, may be detrimental if it
conveys information otherwise not known to the market.
The figures in Panel B of Table 7 show that prior to 1999 the
coefficient on book values of equity is 1.35 for capitalizing
companies (t ¼ 3.99) and 2.73 (1.35 plus 1.38) for expensing
companies. In addition, the coefficient on net income is 0.81
for capitalizing companies (t ¼ 0.34) and 1.9 (0.81 plus 2.71)
for expensing companies, not significantly different from zero
for both firm types. The finding that net income is irrelevant for
valuing capitalizing companies during 1990–98 suggests that
book value of equity was sufficient for valuing equity. Turning
to 1999–2003, the results show that, under FRS 10, book value
of equity is sufficient for valuing equity for companies that used
to capitalize player contracts. As for companies that used to
expense player contracts prior to 1999, the coefficient on book
value of equity is larger (by 1.18, t ¼ 3.74) and the coefficient on
net income is larger by 3.48 (t ¼ 2.82). This result suggests that,
after FRS 10, net income became value-relevant for companies
that used to expense player contracts. To the extent that the
accounting choice conveys information not otherwise known to
the market, this supports the idea that, had no choice been allowed
throughout, the market would potentially have been deprived
from information embedded in the accounting choice itself.
That the coefficients on BVE and NETINC are larger for
expensing firms is also suggestive of off-balance sheet assets.
This is a plausible explanation, as many of the firms that elected
to expense prior to FRS 10 rely more heavily on unrecorded
home-grown talent (these firms are relatively small, private and
maintain low league position). In the future, as accounting
choice is not available anymore, companies may find it harder
to convey their ‘type’ through the financial statements.
5. SUMMARY
This study examines whether investment in player contracts
warrant capitalization, as is now required by FRS 10 and similar
international standards. We also take advantage of this recent
change in accounting regulation in the UK to examine the effects
#
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ACCOUNTING & FOOTBALLERS’ CONTRACTS
585
of introducing a uniform capitalization requirement. By focusing
on the UK football industry we are able to provide a specific
example that illustrates potential shortcoming of a capitalization
requirement that is based on the presence of arm’s length
transactions. The evidence presented in this paper does not
support inconclusively the capitalization requirement in that it
indicates weak association of intangibles with future benefits.
Other findings, nevertheless, suggest that market participants
seem to agree with the treatment prescribed by the new accounting requirement. Specifically, we find that transfer fees paid are
positively related to market values.
Past accounting choice seems to be value relevant and may
help investors to assess the value of companies. In that regard,
removal of the choice may prevent the market from making
efficient assessments.
We believe that further research is needed in this area. The
relatively weak results of the association between transfer fees
and future benefits are in our opinion intriguing given the
results of the market-based tests. It will be interesting to see
how other traded intangibles are related to future benefits and
what are their relations with share prices.
REFERENCES
Aboody, D. and B. Lev (1998), ‘The Value Relevance of Intangibles: The Case
of Software Capitalization,’ Journal of Accounting Research (Supplement)
pp. 161–91.
Accounting Standards Board (1997), Financial Reporting Standard No. 10,
Goodwill and Intangible Assets (December, London: ASB).
——— (2000), UITF No. 24, Accounting for Start-up Costs (June, London: ASB).
AICPA (1998), SOP 98-5, Reporting on the Costs of Start-Up Activities (No.
014906CLC5).
Amir, E. and B. Lev (1996), ‘Value-relevance of Nonfinancial Information:
The Wireless Communications Industry,’ Journal of Accounting and
Economics, Vol. 22, Nos. 1–3, pp. 3–30.
——— ——— and T. Sougiannis (2003), ‘Do Financial Analysts Get Intangibles?’
European Accounting Review, Vol. 12, Nos 4, pp. 635–61.
Antonioni, P. and J. Cubbin (1997), ‘The Bosman Ruling and the Emergence
of the Single Market in Football Talent,’ Working Paper (City University,
London).
Ball, R. (1989), ‘The Firm as a Specialist Contracting Intermediary:
Application to Accounting and Auditing,’ Working Paper (University of
Rochester).
#
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AMIR AND LIVNE
Chauvin, K.W. and M. Hirschey (1993), ‘Advertising, R&D Expenditure and
the Market Value of the Firm, Financial Management, Vol. 22, No. 4, pp.
128–40.
——— ——— (1994), ‘Goodwill, Profitability, and the Market Value of the
Firm, Journal of Accounting and Public Policy, Vol. 13, pp. 159–80.
Deng, Z. and B. Lev (1997), ‘Flush-Then-Flush: The Valuation of Acquired
R&D-In-Process, Working Paper (New York University).
Fields, T., T. Lys. and L. Vincent (2001), ‘Empirical Research on Accounting
Choice,’ Journal of Accounting and Economics, Vol. 31, pp. 255–307.
Financial Accounting Standards Board (2001), Statement of Financial Accounting
Standards No. 142: Goodwill and Other Intangible Assets (June, Norwalk, CT:
FASB).
Francis, J., K. Schipper and L. Vincent (2003), ‘The Relative and Incremental
Explanatory Power of Earnings and Alternative (to Earnings) Performance Measures for Returns,’ Contemporary Accounting Research, Vol. 20,
pp. 121–64.
Garrod, N. and W. Rees, (1998), ‘International Diversification and Firm
Value,’ Journal of Business, Finance & Accounting, Vol. 25, No. 9, pp.
1255–81.
Gates, B. (1999), ‘Business @ the Speed of Thought,’ Business Strategy Review,
Vol. 10, pp. 11–18.
Green, J.P., A.W. Stark and H.M. Thomas (1996). ‘UK Evidence on the
Market Valuation of Research and Development Expenditures,’ Journal
of Business Finance & Accounting, Vol. 23, No. 2, pp. 191–216.
Hirschey, M. and J.J. Weygandt (1985), ‘Amortization Policy for Advertising
and Research and Development Expenditures, Journal of Accounting
Research, Vol. 23, No. 1, pp. 326–35.
International Accounting Standard Board (IASB) (1998), International Accounting
Standard No. 38: Intangible Assets (London, UK).
Lev, B (2001), Intangibles: Management, Measurement, and Reporting (Brookings
Institution Press).
——— and T. Sougiannis (1996), ‘The Capitalization, Amortization, and
Value-Relevance of R&D,’ Journal of Accounting and Economics (February),
pp. 107–38.
Ohlson, J. (1995), ‘Earnings, Book Values and Dividends in Equity Valuation,’
Contemporary Accounting Research, Vol. 11, No. 2, pp. 661–87.
Oswald, D. and P. Zarowin (2003), ‘Capitalization of R&D and the Informativeness of Stock Prices,’ Working Paper (London Business School and
New York University).
Rees, W.P. (1997), ‘The Impact of Dividends, Debt and Investment on Valuation Models,’ Journal of Business Finance & Accounting, Vol. 24, No. 7, pp.
1111–40.
Szymanski, S. and T. Kuypers (1997), ‘Winners and Losers: The Business
Strategy of Football’ (City University of London).
Voung, Q. (1989), ‘Likelihood Ratio Test for Model Selection and Non-nested
Hypotheses,’ Econometrica, Vol. 57, pp. 307–33.
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