The value relevance of exploration and evaluation expenditures

Description
This paper aims to investigate the value relevance of the various components of exploration
and evaluation expenditures in the Australian extractives industry. Whether exploration and
evaluation expenditures is more value relevant, following the adoption of AASB 6, and whether it
differs for firms engaged only in exploration when compared to those also engaged in mining
production is also examined.

Accounting Research Journal
The value relevance of exploration and evaluation expenditures
Teng Zhou J acqueline Birt Michaela Rankin
Article information:
To cite this document:
Teng Zhou J acqueline Birt Michaela Rankin , (2015),"The value relevance of exploration and
evaluation expenditures", Accounting Research J ournal, Vol. 28 Iss 3 pp. 228 - 250
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The value relevance of
exploration and evaluation
expenditures
Teng Zhou
Department of Accounting, Monash Business School, Monash University,
Melbourne, Australia
Jacqueline Birt
UQ Business School, University of Queensland, St Lucia, Australia, and
Michaela Rankin
Department of Accounting, Monash Business School, Monash University,
Melbourne, Australia
Abstract
Purpose – This paper aims to investigate the value relevance of the various components of exploration
and evaluation expenditures in the Australian extractives industry. Whether exploration and
evaluation expenditures is more value relevant, following the adoption of AASB 6, and whether it
differs for frms engaged only in exploration when compared to those also engaged in mining
production is also examined.
Design/methodology/approach – This paper uses a modifed Ohlson model as a benchmark
against which to compare an alternative valuation model featuring the disclosed components of
exploration and evaluation expenditures. A sample comprising 430 frm-year observations between
2003 and 2009 is utilised.
Findings – Written-off exploration and evaluation expenditures and the number of projects in which
frms are involved is relevant to investors when assessing the value of extractive frms. Further, the
implementation of AASB 6 has led to an improvement in the relevance of exploration and evaluation
information in assessing frm value.
Research limitations/implications – The sample is based on observations from the years
2003-2004 to the years 2006-2009. The authors do not incorporate 2005, as this is the frst year the new
standard was implemented, and there is the possibility of a settling in effect. The authors base our
sample on the top 100 extractive frms in 2009. As such, these companies may not represent the
accounting practices of smaller frms in the Australian extractive industry.
Originality/value – The authors address a gap in the literature by examining the value relevance of
the detailed line items of exploration and evaluation expenditure reported by extractives frms. The
authors also explore the effect of regulatory changes by examining the value relevance of exploration
and evaluation expenditures pre- and post-International Financial Reporting Standards (IFRS)
6/Australian Accounting Standards Board (AASB) 6 implementation. Finally, the authors contribute
useful fndings to the standard setters’ ongoing deliberations aimed at producing a comprehensive
standard on extractive activities by providing useful feedback on the relevance of accounting for
pre-production costs under a regime using the “area of interest” method.
Keywords Value relevance, IFRS, Extractives, Exploration and evaluation expenditures
Paper type Research paper
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1030-9616.htm
ARJ
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Received10 September 2013
Revised28 May2014
Accepted15 August 2014
Accounting Research Journal
Vol. 28 No. 3, 2015
pp. 228-250
©Emerald Group Publishing Limited
1030-9616
DOI 10.1108/ARJ-09-2013-0067
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1. Introduction
In this paper, we examine the value relevance of exploration and evaluation
expenditures of Australian frms engaged in the extractives industry. A diversity of
approaches to account for and report the results of extractive operations have evolved
across the world’s major mining regions of Australia, Canada, South Africa, the UKand
the USA (Cortese et al., 2010)[1]. Recognising a need for increased comparability of
fnancial information, the International Accounting Standards Committee (IASC)
commenced a project to address the measurement and disclosure issues faced by the
industry. Of particular concern was the method used to account for pre-production
costs – that is, exploration and evaluation expenditures[2] (IASC, 2000; Cortese et al.,
2010).
The International Accounting Standards Board (IASB) issued International
Financial Reporting Standards (IFRS) 6 Exploration for the Evaluation of Mineral
Resources in 2004, applicable fromJanuary 2005. This was subsequently adopted by the
Australian Accounting Standards Board (AASB) and issued as AASB6 Exploration for
the Evaluation of Mineral Resources, applicable the same year[3]. The accounting
standard represents an interim measure and focuses only on pre-production costs. The
attention on pre-production costs is likely to increase corporate focus on measurement
and disclosure of activities relating to these phases of operations, thus improving the
quality of disclosure. Further, AASB 6 provides greater detail on what should be
included in exploration and evaluation expenditure and the subsequent measurement of
capitalised exploration and evaluation expenditure. As a result, it could be argued that
AASB 6 takes a more “rules-based” approach than was evident in AASB 1022, and we
would anticipate an improvement in the disclosure and measurement of exploration and
evaluation expenditures, leading to more value-relevant information. Consequently, we
examine the relative value relevance pre- and post-adoption of AASB 6.
Investments in commodities are seen as attractive long-terminvestments, as they are
perceived to be a “safe haven” in times of economic crisis (Baurens, 2010, p. 7). Mining
and metals are amongst the best performing global equity sectors (Baurens, 2010).
However, valuing mining and exploration frms is complex. The sector is a dynamic
industry, which has an inherent high level of risk at each stage of activity (Wise and
Spear, 2002). Extractives frms experience the highest level of risk at the pre-discovery
or exploration stage. Exploration and evaluation costs can amount to hundreds of
millions of dollars, and for smaller exploration, frms can mean a signifcant drain on
resources during the exploration process (Cortese et al., 2010). In addition, expenditures
on exploration does not guarantee the discovery of a commercially exploitable reserve,
and in fact, only a small proportion of exploration programs ever culminate in a mine
development (Wise and Spear, 2002).
Knowledge about exploration activities is an important aspect in assessing frm
performance in the extractives sector. Exploration and evaluation activities can lead to
a range of possible outcomes for frms, from abandonment of the project, through to
development and production of an area of resource deposits. Therefore, due to the
uncertainty of exploration and evaluation, current earnings are unlikely to be indicative
of future earnings, thus conveying little information to assess the equity value of an
extractives frm (Wu et al., 2010).
The paper makes three contributions. First, we address a number of gaps in the
extant literature exploring value relevance of accounting information in the extractives
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industry. Prior research examining value relevance of exploration expenditures has
primarily been conducted in the US oil and gas industry (Berry and Wright, 2001;
Bryant, 2003), where accounting is subject to a different regulatory environment[4].
Australian research examining the extractives sector focuses on research and
development expenditures (Ahmed and Falk, 2006; Wu et al., 2010) or disclosure of
fnancial instruments (Hassan et al., 2006; Birt et al., 2013). We extend this research by
examining the value relevance of the detailed line items of exploration and evaluation
expenditures reported by extractives frms.
Second, we examine accounting practices in an industry of primary importance to
both the Australian economy and globally. The industry is one of the largest in
Australia, contributing approximately 9 per cent to Australia’s gross domestic product
(GDP) in 2009-2010 (Australian Bureau of Statistics, 2012). Sector exports have
accounted for over 35 per cent of Australia’s total receipts over the past three decades
(ASX, 2010). Australia is the world’s largest exporter of coal and iron ore (Business
Monitor International, 2012). In the past decade, these exports have grown nearly
six-fold from $12 billion in 1999 to $69.4 billion in 2009 (DFAT, 2010).
Finally, fndings of this research will provide useful feedback on the relevance of
accounting for pre-production costs accounted for on the “area of interest” basis. The
IASB’s ongoing extractives project proposes one method for accounting for extractives
activities – the “area of interest” approach, consistent with that currently used in
Australia. Consequently, research examining the relevance of accounting data
generated by frms in the Australian extractives industry will assist standard setters in
their deliberations on the development of a comprehensive standard on extractive
activities[5]. We also contribute to the ongoing development of IFRS more generally, by
examining the effect of an accounting standard that could be argued to be more
“rules-based” than its precursor.
We fnd that written-off exploration and evaluation expenditure is positively and
signifcantly associated with share price for extractive frms. The number of
projects in which a frm is currently involved is also important in assessing frm
value. When we compare the results between pre- and post-adoption of IFRS 6/
AASB 6, we fnd that the introduction of IFRS 6/AASB 6 has resulted in an
improvement of the relevance of exploration and evaluation expenditure in valuing
frms in the sector. Finally, in additional analysis, we fnd the value relevance of
exploration and evaluation expenditure differs across frms involved in exploration
and production activities.
The results of this research provide evidence that investors perceive written-off
exploration and evaluation expenditure to be relevant in assessing frm value. It is
also evident that transfers of capitalised expenditure to reserves are value relevant
for frms that engage in a large number of projects. Investors perceive this transfer
to reserves as being a positive outcome of projects with which sample frms are
engaged.
The remainder of the paper is structured as follows. Section 2 briefy outlines the
regulatory background to AASB6 Exploration for and Evaluation of Mineral Resources.
Relevant research that has examined the value relevance of disclosures in the
extractives industry, and the development of hypotheses to test the relevance of
exploration and evaluation expenditure in valuing extractives frms, is presented in
Section 3. Section 4 discusses the research design and sample, while the results of
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statistical tests are presented in Section 5. Results of additional tests are discussed in the
penultimate section, with the paper concluding with limitations and suggestions for
future research.
2. Background: accounting for exploration and evaluation expenditure in
Australia
Entities operating in the extractives industry are involved in the search for, and
extraction of natural resources, such as “minerals, oil, natural gas and similar
non-regenerative resources” (Appendix A, AASB 6). As previously indicated, AASB 6
Exploration for and Evaluation of Mineral Resources is developed from IFRS 6
Exploration for and Evaluation of Mineral Resources and adopts an “area of interest”
accounting method. The “area of interest” is defned as “an individual geological area
that fows with natural resource minerals such oil and natural gas” (AASB 6,
Appendix A, p 208). This approach is consistent with the precursor standard AASB
1022 Accounting in the Extractive Industry, released in October 1989, following the
guidance in IFRS 6 permitting companies to continue to use their existing accounting
method. However, there have been changes to guidelines pertaining to disclosure and
measurement of exploration and evaluation expenditures.
First, AASB 6 provides clearer requirements regarding the recognition and
subsequent measurement of capitalised exploration and evaluation expenditures. It
requires that for each area of interest, the costs are either recognised as expenses as
incurred or capitalised if the conditions of AASB Paragraph 7 are met[6]. It also
requires that entities recognise the exploration and evaluation expenditure initially
at cost and in subsequent periods adopt either the cost or revaluation model. There
are also additional rules for subsequent reclassifcation of assets and also for testing
for impairment.
Second, AASB 6 provides greater detail on what should be included in exploration
and evaluation expenditure, including: acquisition of exploration rights, any expenses
directly relating to topography, geological, geochemical and geophysical studies,
drilling, trenching and sampling, any expenditure directly relating to evaluation and
extracting a mineral resource and any direct administrative expenses of the extractive
activities of the area of interest (AASB 6, Paragraph9). In summary, AASB 6 provides
additional detail on the recognition and subsequent measurement of the capitalised
asset and also the type of expenditure which would be classifed as exploration and
evaluation expenditure. The standard could be argued as being more “rules-based”
compared to its precursor AASB 1022, as it demonstrates larger volumes of
implementation guidance and higher levels of detail (Schipper, 2003; Bennett et al.,
2006).
The IASB’s project, aimed at developing a comprehensive standard for the extractive
industries, commenced with a discussion paper being issued in April 2010. The IASB
recognised the importance of the sector to the world economy and the major role
extractives frms play in the world’s capital markets (IASB, 2010a, 2010b)[7]. The
discussion paper provides results of the IASB’s research and proposes one consistent
method for accounting for minerals and oil and gas activities.
As indicated previously, the discussion paper proposes the “area of interest”
approach, consistent with that currently used in Australia. As such, research examining
the relevance of accounting data generated by frms in the Australian extractives
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industry will provide useful feedback to standard setters on their ongoing development
of a comprehensive industry standard. The IASB’s extractives project is currently
paused until it concludes deliberations on other accounting issues.
3. Literature review and hypothesis development
3.1 Prior research in the extractives sector
Several studies examining the extractives sector in the USAexplore the value relevance
of disclosures. Berry and Wright (2001) fnd a positive association between the market
value of US oil and gas frms and their resource exploration and mining feld
development disclosures. The authors examine whether disclosures under either the
“full cost” or “successful efforts” accounting methods convey relevant information
relating to oil and gas entities’ efforts and ability to discover reserves. The authors fnd
mining frms using the “full cost” approach provide value-relevant information on
proven developed reserves and undeveloped reserves to the market, concluding that
disclosed exploration costs under a “full cost” method appears to be a positive signal to
investors about the future investment opportunities available to these frms.
In a similar vein, Bryant (2003) applies a valuation model to examine the association
between oil and gas frms’ market value and exploration and development costs. The
author claims that the “full cost” method of accounting for exploration and development
expenditures provides more relevant information than the “successful efforts” method.
Both Berry and Wright (2001) and Bryant (2003) fnd that disclosures by extractive
frms under the “full cost” accounting method convey value-relevant information to the
stock market.
Australian extractive industry studies contribute to our understanding of the
relevance of research and development (R&D) (Goodwin, 2002; Ahmed and Falk, 2006),
the disclosure of fnancial instruments (Hassan et al., 2006; Birt et al., 2013) and reserves
disclosures (Taylor et al., 2012) to the assessment of frm value. However, there is little
research solely focusing on the value relevance of exploration and evaluation
expenditures.
Wu et al. (2010) offer one exception when they investigate how disclosures
relating to exploration expenditures and R&D investment assist investors to
evaluate the value of loss-making Australian mining frms. In doing so, they also
compare the value relevance of capitalised and expensed R&D and exploration
expenditures of loss frms to those reported by proft frms. The authors fnd that
capitalised and expensed exploration and R&D costs are positively and
signifcantly associated with the market value of the resource-based frms reporting
losses. However, neither capitalised exploration expenditures nor R&D costs are
found to have any signifcant impact on the market value of proftable frms.
Further, where frms have a positive market value despite current losses, this is due
to the information provided by exploration expenditures as an indication of
expected future value. The authors primarily focus on reporting during the period
before AASB 6 adoption, with only one full year of their study considering
accounting subject to AASB 6. As such, we seek to extend the period and undertake
a more detailed analysis of the association between the disclosure of the various line
items required pursuant to AASB 6 and frm value of extractives frms[8].
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3.2 Hypotheses development
3.2.1 Exploration and evaluation expenditures. Exploration and evaluation
expenditures contribute a large proportion of the total mining costs for companies
engaged in the exploration and evaluation phases of development. As previously
indicated, both Berry and Wright (2001) and Bryant (2003) fnd that exploration
expenditure disclosed by oil and gas frms that use the “full cost” approach is value
relevant to the market, which suggests that an oil and gas companies’ efforts
and ability to discover and extend proven reserves is useful in assessing frm
value.
Investors are likely to consider capitalisation of expenditures differently than those
that have been expensed (Aboody and Lev, 1998; Wu et al., 2010). Aboody and Lev (1998)
found that capitalising software development costs was more likely to reduce
information uncertainty for investors, leading to different relationships with share
returns. Mitrione et al. (2014) found differences in the value relevance of R&D expensed
and capitalised for Australian Health sector frms in the periods prior, during and post
the GFC. Consistent with Wu et al. (2010) it is expected that capitalised exploration and
evaluation expenditures will provide value-relevant information for investors of
Australian extractives frms. Current capitalised exploration and evaluation
expenditures[9] convey positive information about the continuing mining operations’
successful exploration for economic reserves and the likelihood of future development or
sale of mining projects, which are expected to recover the costs incurred during the
exploration and evaluation operations. Therefore, it is expected that the disclosure of
current capitalised exploration and evaluation expenditures will be value relevant to the
market.
Further, if capitalised exploration and evaluation expenditures are able to indicate
the extractive frm’s ability and efforts to discover proven mining reserves (Berry and
Wright, 2001), written-off exploration and evaluation expenditures[10] should also have
an impact on the value of these frms. The written-off expenditures are likely to be
considered as negative information indicating the likelihood of abandoning mining
tenements, oil and gas felds or mining projects, indicating the company sees little or no
value under present conditions. This provides a negative signal to investors about
future cash fows from these operations and is likely to be considered by investors in
valuing extractives frms. Prior research examining expensing of R&D (Ahmed and
Falk, 2006; Tsoligkas and Tsalavoutas, 2011) fnds a negative association between R&D
expense and share price and argues this is refective of non-proftable or unsuccessful
projects of the frm. This leads to our frst hypothesis:
H1. Current capitalised exploration and evaluation expenditures (written-off
exploration and evaluation expenditures) will be positively (negatively)
associated with the share price of an extractives frm.
3.2.2 Number of projects. We not only anticipate exploration and evaluation
expenditures to be value relevant. Consistent with Amir and Lev (1996) and Trueman
et al. (2001), other fnancial report information is also likely to provide useful information
in analysing and evaluating the extractive frm’s future development. The number of
mining or exploration projects a frm is engaged in could provide information on the
ability of the frm to undertake current and future projects. Evidence that some of the
entity’s projects have gone beyond the exploration and evaluation stage is a positive
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signal of the ability of the frm to successfully engage in the exploration process and
convert these projects to successfully mined tenements. Therefore, the second
hypothesis is:
H2. The number of mining projects will be positively associated with the share price
of an extractives frm.
3.2.3 Pre- versus post-AASB 6 adoption. Regulation is an important factor impacting on
the value relevance of publicly available information, and ultimately the usefulness of
fnancial information, in assessing current and future performance (Healy and Palepu,
2001). Compared to the previous standard (AASB1022), AASB6 provides more detailed
requirements for the disclosure of exploration and evaluation expenditures. Similarly,
Mitrione et al. (2014) found that after the implementation of tighter regulatory
requirements under IAS 38, reported R&D expenditure was more value relevant
compared to under AASB 1011. Based on the more extensive reporting guidelines of
AASB 6, we anticipate regulated entities place more focus on their reporting of
exploration and evaluation expenditures, leading to an improvement in the disclosure
of exploration and evaluation expenditure. As a result, we anticipate information
asymmetry to be reduced, leading to higher value relevance post-adoption of AASB 6.
Therefore, we hypothesise:
H3. Exploration and evaluation expenditure reported after the implementation of
AASB 6 is more value relevant than exploration and evaluation expenditure
reported under AASB 1022.
4. Data and research method
4.1 Sample and data
The sample constitutes the top 100 frms in the extractives industry, identifed fromthe
ASX, at January 2010. The market capitalisation of the top 100 frms ranges from $126
million to $132.23 billion, where the combined market capital of the sample is $270.03
billion, contributing 95.85 per cent of the total market capital ($282 billion) of the
industry. In total, 16 companies are excluded from the sample due to incomplete data.
Sample selection is summarised in Table I.
Table I.
Sample selection and
characteristics
Explanation Sample frms Firm-year observations
Top 100 companies in metals and mining sectors
in 2010 100 600
Less Companies/frm-years not following AASB
6 standards (9) (54)
Less Companies/frm-years with insuffcient
disclosures or missing data (7) (116)
Total companies/frm-year observations 84 430
Firm-years where engaged in exploration
activities only 247 (57.5%)
Firm-years where engaged in exploration and
production 183 (42.5%)
Firms-years with positive earnings 150 (35.9%)
Firm-years with negative earnings 280 (65.1%)
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We conduct our analysis using two specifc time periods. During the frst period
(2003-2004), sample frms are subject to the accounting requirements of AASB 1022
(pre-AASB 6). The second (2006-2009) represents the period post-implementation of
AASB 6. In total, there are 430 frm years in the sample, consisting of 112 frm years
from 2003 to 2004 and 318 frm years between 2006 and 2009.
Share price, earnings and earnings-per-share data are collected fromAspect Huntley Fin
Analysis. All other accounting data are hand-collected from annual reports retrieved
from Connect4 and Aspect Huntley Fin Analysis. The non-fnancial data are extracted
fromthe tenement statements, operation reviews, exploration and development reports,
director’s reports and extracting (mining) projects reports – all produced by sample
frms as part of their annual reports.
4.2 Research method
To test our hypotheses, we frst use the Ohlson (1995) model as a benchmark against
which to compare our alternative valuation model featuring the disclosed components of
exploration and evaluation expenditures. Model 1 represents the basic form of the
modifed Ohlson (1995)[11] model:
P
90
? ?
0
? ?
1
EPS
t
? ?
2
BVE
0t
? e (1)
where:
P
90
?the share price at 90 days after reporting date;
EPS
t
?earnings per share in fscal year t;
BVE
0t
?book value of equity per share in fscal year t; and
e ?error term.
To test our hypotheses, we include variables representing capitalised expenditures
EEE
t
and written-off exploration and evaluation expenditures WOFF
t
in an enhanced
model. Additionally, to test the value relevance of the number of mining projects (H2),
we include the variable (Projects
t
). To account for the time lag fromreporting date to the
fnancial report release date, consistent with prior research (Barth et al., 1996; Ahmed
and Falk, 2006; Hassan et al., 2006), the dependent variable is the share price 90 days
after reporting date (P
90
). We also incorporate a revised earnings per share measure with
the written-off exploration and evaluation expenses added back (denoted EBTBW
t
), and
a revised book value of equity per share after capitalised exploration and evaluations
expenditures are added back (BVE
1t
).
Valuation models are often criticised as suffering from scale effects, which arise
because large (small) frms tend to also have large (small) market capitalisation, large
(small) book values and large (small) earnings (Ota, 2003; Barth and Clinch, 2009). To
address this issue, consistent with Barth and Clinch (2009) and Mitrione et al. (2014), we
use a defated formof the model, where each variable is defated by the number of shares
outstanding. Further, we control for the potential that value relevance could be due to a
general rise in resources prices over the sample period, by including a commodities
index (Comm_Index
t
), calculated as the average Reserve Bank of Australia (RBA) Index
of Commodities Prices each year.
Therefore, our test model, used to evaluate whether market participants use
exploration and evaluation disclosures to value extractives frms, is:
235
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relevance
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P
90
? ?
0
? ?
1
EBTBW
t
? ?
2
BVE
1t
? ?
3
EEE
t
? ?
4
WOFF
t
? ?
5
Projects
t
? ?
6
Comm_Index
t
? e
(2)
where:
P
90
?the share price at 90 days after reporting date;
EBTBW
t
?earnings (per share) before income tax adding back written off
value of exploration and evaluation expenses in fscal year t;
BVE
1t
?balance of book value of equity per share excluding EEE
t
at the
reporting dates in fscal year t;
EEE
t
? capitalised exploration and evaluation expenditures per share
in fscal year t;
WOFF
t
? written off exploration and evaluation expenditures per share
in fscal year t;
Projects
t
? number of mining projects in fscal year t;
COMM_Index
t
? commodities index in fscal year t; and
e ? error term.
Easton and Sommers (2003) suggest that the best measure of scale is market
capitalisation because of the central role market prices play in market-based accounting
research. Consequently, an alternative to the above price model is to use a returns model,
where the variables used in the model are defated by the lagged market value of equity,
and are therefore scale-free (Ota, 2003). As such, we perform additional tests where we
use an alternative model, replacing the level variables with changes in these variables.
Aboody and Lev (1998); Tutticci et al. (2007) and Mitrione et al. (2014) also utilise this
method.
The model is presented in equation (3):
R
90
? ?
0
? EBTBW
MV
t
? ?
2
?EBTBW
MV
t
? ?
3
EEE
MV
t
? ?
4
WOFF
MV
t
? ?
5
ln Projects
t
? ?
6
Comm_Index
t
? e
(3)
where:
R
90
?market adjusted annual return at 90 days after reporting date;
EBTBW
MV
t
?earnings before income tax adding back written-off value of exploration
andevaluationexpenses infscal year t;
?EBTBW
MV
t
?change in earnings before income tax adding back written-off value of
exploration and evaluation expenses in fscal year t;
EEE
MV
t
?capitalised exploration and evaluation expenditures in fscal year t;
WOFF
MV
t
?written-off exploration and evaluation expenditures in fscal year t;
Ln Projects
t
?natural log of number of mining projects in fscal year t;
COMM_Index
t
?commodities index in fscal year t; and
e ?error term.
All values (except the number of mining projects and commodities index) are defated by
lagged market capitalisation of the frm at 90 days after reporting date.
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5. Results
5.1 Descriptive statistics
The descriptive data for all variables included in the basic Ohlson (1995) model and our
price model are presented in Table II. Data reveal large variation across the sample.
Share prices (P
90
) range from $0.01 to $43.16 with a mean of $2.09; earnings per share
(EPS) range from ?$3.09 to $0.97; while earnings before tax, adding back written-off
exploration and evaluation expenditure (EBTBW
t
) ranges from?$0.39 to $5.24, with a
mean of $0.14. Capitalised exploration and evaluation expenditures (EEE
t
) ranges from
$0.00 to $0.87 per share. The mean is $0.05. Written-off exploration and evaluation
expenditures (WOFF
t
) range from$0.00 to $0.36 per share, with a mean of $0.02. Sample
frms engage in an average of 8 mining projects (mean 7.8), with a minimum of 1 and a
maximum of 69.
While tabulated statistics for capitalised (EEE
t
) and written-off (WOFF
t
) exploration
and evaluation expenditures (EEE
t
) are scaled by number of shares outstanding,
Figure 1 presents a graphical representation of total expenditures across the sample
frms. These refect unscaled data. Both categories of expenditure exhibited substantial
increases in the frst year AASB 6 was adopted (2006). Average written-off expenditure
(WOFF) increased from approximately $4 million in 2003 and 2004 to a high of over
$16million in 2006, declining thereafter. Capitalised expenditure (EEE) was more stable
across the sample period, but was generally higher after the adoption of AASB 6 than
prior.
Evidence of multicollinearity is determined by examining the correlations amongst
the independent variables. The correlation matrix, presented in Table III, shows that
almost all correlation coeffcients are below 0.80, indicating no evidence of
multicollinearity (Gujarati, 2003). We also evaluate variance infation factors (VIF) in
each regression model (unreported) and fnd that multicollinearity does not impact any
of our results[12].
Table II.
Descriptive statistics:
dependent and
independent
variables
Variables Mean Median Maximum Minimum SD
P
90
2.093 0.780 43.160 0.010 4.725
EPS
t
?0.012 ?0.014 0.996 ?3.069 0.282
BVE
0t
0.699 0.214 9.018 ?0.356 1.283
EBTBW
t
0.144 ?0.007 5.244 ?0.392 0.558
BVE
1t
0.587 0.141 8.415 0.591 1.175
EEE
t
0.054 0.024 0.871 0.000 0.096
WOFF
t
0.019 0.003 0.363 0.000 0.043
Projects
t
7.761 5.000 69.000 1.000 8.987
Comm_Index
t
81.565 81.200 111.0 49.6 20.925
Notes: n ? 430; variable defnitions: P
90
? share price at 90 days after reporting date; EPS
t
?
earnings per share in fscal year t; BVE
0t
?book value of equity in fscal year t; EBTBW
t
?earnings
(per share) before income tax, adding back written-off value of exploration and evaluation expenses in
fscal year t; BVE
1t
?balance of book value of equity per share excluding capitalised exploration and
evaluation expenditure at reporting date in fscal year t; EEE
t
?capitalised exploration and evaluation
expenditures per share in fscal year t; WOFF
t
?written-off exploration and evaluation expenditures
per share in fscal year t; Projects
t
? number of mining projects in fscal year t; Comm_Index ?
commodities index
237
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Aside from IFRS and Comm_Index, the highest correlation is between EBTBW
t
and
BVE
1t
, where we document a correlation coeffcient of 0.74. In further untabulated
results, we determine a correlation coeffcient of 0.66 between book value of equity and
positive earnings and ?0.49 between book value of equity and negative earnings. This
appears to be consistent with Collins et al. (1999) fndings.
5.2 Results of hypotheses tests
Cross-sectional regression results under the modifed Ohlson (1995) model and the price
models for exploration and evaluation expenditures are presented in Table IV. The
modifed Ohlson (1995) model (Table IV, Model 1) shows that while book value of equity
is positively associated with share price three months after fscal year-end for frms in
the mining sector (t-statistic 25.808), EPS are not (t-statistic ?0.209). This presents
evidence of the limited relevance of earnings in assessing the value of extractives frms
and, particularly, those engaged in exploration activities.
We run our analysis on pooled data (2003 to 2009) to test H1 and H2. We test
hypothesis three in two ways: frst, we run separate models on post-AASB6 (2006-2009)
-
2,000,000
4,000,000
6,000,000
8,000,000
10,000,000
12,000,000
14,000,000
16,000,000
18,000,000
2003 2004 2006 2007 2008 2009
EEE
WOFF
Figure 1.
Reported EEE and
WOFF over time
Table III.
Correlation matrix
Variable EBTBW
t
BVE
1t
EEE
t
WOFF
t
Projects
t
Comm_Index IFRS
EBTBW
t
1.000
BVE
1t
0.744 1.000
EEE
t
0.301 0.278 1.000
WOFF
t
0.363 0.286 0.115 1.000
Projects
t
0.452 0.304 0.010 0.226 1.000
Comm_Index 0.027 0.061 ?0.043 0.031 ?0.062 1.000
IFRS 0.050 0.040 ?0.028 0.012 ?0.072 0.860 1.000
Notes: n ? 430; Pearson’s correlation coeffcients are presented; variable defnitions: EBTBW
t
?
earnings (per share) before income tax adding, back written-off value of exploration and evaluation
expenses in fscal year t; BVE
1t
? balance of book value of equity per share excluding capitalised
exploration and evaluation expenditure at reporting date in fscal year t; EEE
t
?capitalised exploration
and evaluation expenditures per share in fscal year t; WOFF
t
?written-off exploration and evaluation
expenditures per share in fscal year t; Projects
t
? number of mining projects in fscal year t;
Comm_Index ?commodities index; IFRS ?dummy variable indicating pre(post) IFRS adoption
ARJ
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Table IV.
Price models
(
1
)
(
2
)
(
3
)
(
4
)
(
5
)
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i
e
s
i
n
d
e
x
;
I
F
R
S
?
d
u
m
m
y
v
a
r
i
a
b
l
e
i
n
d
i
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a
t
i
n
g
p
r
e
-
(
p
o
s
t
-
)
I
F
R
S
a
d
o
p
t
i
o
n
239
Value
relevance
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and pre-AASB 6 (2003-2004) data. We also incorporate a dummy variable (IFRS),
indicating post-AASB 6 adoption, and run the test on the pooled sample.
Our model on pooled data (Table IV Model 2) has greater explanatory power
(adjusted R
2
? 0.743) than the basic Ohlson (1995) model (adjusted R
2
? 0.623). This
provides initial support for our proposition that exploration and evaluation
expenditures, over and above fnancial earnings, are relevant to the market in assessing
frm value.
Confning our discussion to the test model, we fnd limited support for our frst
hypothesis that capitalised exploration and evaluation expenditure is value relevant in
explaining the market value of frms in the extractive industry. Consistent with Wu et al.
(2010) and Aboody and Lev (1998), we fnd that EEE
t
is negatively associated with share
price, but only at the 10 per cent level. Recall that AASB 6 requires a number of
conditions to be met before exploration and evaluation expenditure can be capitalised,
including the expectation of recoupment through successful development and
exploitation of the area of interest or by its sale (AASB 6 Paragraph Aus7.2).
Consequently, it is more likely that exploration expenditure will be expensed rather than
capitalised, particularly, during the exploration, as opposed to evaluation phase, where
frms face greater uncertainties pertaining to what resources might be underground.
Further, given the measure of EEE is a lagged measure indicating investment in
exploration and evaluation assets, the market may already have received and acted on
this information fromother sources prior to the release of the annual reports. If this is the
case, you would expect to fnd reduced value relevance for this accounting
information[13].
In relation to written-off exploration and evaluation expenditures (WOFF
t
), contrary
to expectations, we fnd a positive association between written-off expenditures and
share price (t-statistic 4.360). While we expected written-off expenditures to present a
negative signal to investors about the potential for abandoning mining tenements, oil
and gas felds or mining projects, this result supports previous research by Wu et al.
(2010), who also observe a positive relationship between share prices and expensed
exploration and evaluation costs. It also supports sub sector (i.e. health care) results in
the Mitrione et al. (2014) study where expensed R&D was considered important for the
manufacturing of health care equipment or providing health care related services. In the
current study, the results indicate that the amount of exploration and evaluation
expenditure could represent expenditure likely to relate to future earnings potential.
While the exploration has not reached a stage whereby it meets the criteria for
capitalisation, the expenditure signals the extent to which the frm is engaged in
activities that are likely to lead to future successful production activities.
The signifcant positive result for Projects
t
at the 1 per cent level (t-statistic 5.180)
offers support for our second hypothesis that the number of projects in which a frm is
engaged provides relevant information on the ability of the frm to generate future
income. Consistent with Amir and Lev (1996); Trueman et al. (2001) and Wyatt (2008),
this indicates that non-fnancial report information is likely to be value relevant if it is
suffciently salient to the frm’s economic reality and is informative about potential
future earnings[14]. The returns model (untabulated) shows that neither capitalised or
expensed exploration and evaluation expenditures are associated with share return
(t-statistics ?1.079 and ?1.056, respectively); however, consistent with the prices model
ARJ
28,3
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reported in Table IV(Model 2), the number of mining projects is signifcantly positively
associated with share returns (t-statistic 5.205).
To test H3, we frst compute our models on both post-AASB6 (Table IVModel 3) and
pre-AASB 6 implementation data (Table IV Model 4). The explanatory power of the
regression model is higher in the period after implementation of AASB 6 (adjusted R
2
78.3 per cent) than prior to its adoption (adjusted R
2
60.4 per cent). To determine whether
these models are signifcantly different from each other, we conduct a Chow (1960) test
to determine whether the coeffcients in the regression models pre- and post-adoption of
AASB6 are identical. We fnd that the coeffcients, and therefore the explanatory power
of the models, differ (F-value 142.298, p ?0.000).
We also test H3 by including a dummy variable representing pre- and post-AASB 4
adoption (IFRS) in the model and also interact this with EEE
t
and WOFF
t
(Table IV,
Model 5). The pre- and post-AASB 6 indicator variable is signifcant at the 1 per cent
level (t-statistic 3.783). Further, in support of our prior results, the interaction between
WOFF
t
and IFRS is signifcantly positive. This result shows that the association
between WOFF
t
and the dependent variable (P
90
) is signifcantly greater in the
post-AASB6 period than the pre-AASBperiod. The insignifcant result with EEEagain
refects the fact that possibly the market may have already priced the EEE from other
sources. Consistent with Cooper and Keim (1983); Kothari (2001) and Healy and Palepu
(2001), our results indicate that, based on the more extensive guidelines of AASB6, there
has been an improvement in the disclosure of exploration and evaluation expenditure,
leading to increased value relevance. This provides support for the third hypothesis.
Mitrione et al. (2014) fnd similar results regarding value relevance of R&D disclosures
in the Australian health-care industry.
5.3 Further tests
5.3.1 Proft and loss frms. Prior research has considered the value relevance of
accounting data for both proftable and unproftable frms. Wu et al. (2010) fnd that
exploration expenditures are more likely to explain the share price of loss-making
Australian mining companies. To identify the value relevance of exploration and
evaluation expenditures across proft and loss frms, we split the sample into
proft-making and loss frms based on their EPS.
Our data consists of 150 observations with positive EPS
t
and 280 observations with
negative EPS
t
. Table V (Models 1 and 2, respectively) presents the results of our
analysis, where we report the adjusted R
2
for the proftable frms (76.4 per cent) and loss
frms (31.5 per cent). Earnings (EBTBW
t
), book value BVE
1t
, and written-off (WOFF
t
)
exploration and evaluation expenditure are all signifcantly and positively associated
with the share price in both proft frmyears and loss frmyears. We fnd that capitalised
exploration and evaluation expenditure (EEE
t
) is more signifcantly and positively
associated with share price in loss frms (t-statistic 2.006) than for the pooled sample
presented in Table IV(Column 2). This is consistent with Wu et al.’s (2010) fndings, with
capitalised exploration and evaluation being able to explain the market value of
loss-making mining companies. Mitrione et al. (2014) fnd similar results for loss-making
frms in the Australian health-care sector. The number of mining projects (Projects
t
),
while positively related to share price of proftable frms, is not associated with the share
price of loss frms. This is likely to result fromthe fact that loss frms tend to be engaged
only in exploration activities, and thus have fewer, if any projects recorded.
241
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Table V.
Additional tests
(
1
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5.3.2 Production frms versus exploration frms
Our initial sample consists of both production and exploration frms. The extent to
which exploration frms maintain a capitalised exploration and evaluation assets
balance is likely to present signifcant information to investors relating to the imminent
discovery of viable reserves. However, we would expect both capitalised and written-off
exploration and evaluation expenditure to be more value relevant for production frms
than for exploration frms, given the uncertainty associated with exploration
activities[15]. To test this, we split our sample into production and exploration frms.
Results presented in Table V (Models 3 and 4) show that our model comprising
production frms (adjusted R
2
80.6 per cent) signifcantly exceeds that for exploration
frms (adjusted R
2
22.4 per cent). A Chow (1960) test indicates the models are
signifcantly different (F-value 148.795, p ?0.000). We also note that for our exploration
frm model, only earnings and book value provide information relevant in valuing
shares of sample frms. This result points to the diffculty in valuing exploration frms,
which often operate under differing objectives than frms that develop mining
tenements through to production.
5.3.3 Sensitivity tests
We also conduct a number of sensitivity tests including: assessing the impact of
transfers to reserves on share price, using the share price at reporting date as the
dependent variable, examining the sub-sample of frms that engage in write-offs of
exploration and evaluation expenditure, and substituting original values of EPS and
BVE. While we discuss each of our sensitivity results below, results are untabulated.
An important consideration for any extractives frmis the number of mining projects
it is currently engaged in. These projects can involve both risks and returns for the frm.
In this paper we have already shown a positive and signifcant association between the
number of mining projects and share price. If an extractives frm is successful with its
projects, it will transfer the capitalised amount to reserves. These transfers are expected
to have a positive impact on share price. We did not consider transfers to reserves in our
main tests, as AASB 6 does not govern the requirements for measurement and
disclosure of this fgure. Taylor et al. (2012) note reporting of reserve information is
value relevant, particularly given the importance of reserves to resource frms in
achieving forecasted cash fows, meeting debt covenant terms and in achieving growth
forecasts. Disclosure of reserve estimates is important to investors in making informed
economic decisions about the underlying value of extractives frms (Taylor et al., 2012).
Therefore, as a sensitivity test, we introduce an interaction variable, where we interact
the number of mining projects with transfers of capitalised expenditure to reserves. We
fnd positive and signifcant results for our interaction variable. It appears that investors
do value information regarding the number of projects in which a frm is engaged, and
this combined with transferring capitalised amounts to reserves, further highlights
investor confdence in the frm.
We also rerun our models and substitute the 90-day share price with share price at
reporting date as the dependent variable. All variables except EEE
t
are highly
signifcant in the regression model with pooled sample data. The substitution of current
share price does not appear to have an impact on the explanatory power of the model. In
all tests, the model that features exploration and evaluation variables still performs
better than the basic modifed Ohlson (1995) model using share price at reporting date.
243
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Finally, we substitute alternative proxies for EPS and BVE in the model featuring
exploration and evaluation expenditures. Recall, the original model incorporated an
adjustment to both EPS and BVE where we add back write-offs to earnings, and subtract
capitalisedexplorationandevaluationexpenditures fromBVE. Therefore, inthis sensitivity
test, the original values of EPS and BVE are used. The explanatory power (adjusted R
2
)
under this model is slightly lower than the explanatory power of the regression model
without using the normal EPS
t
and book value equity (unreported results).
6. Conclusion
Valuingminingandexplorationfrms is complex. The sector is dynamic, withaninherently
high level of risk at each stage of activity (Wise and Spear, 2002). Extractives frms
experience the highest level of riskat the pre-discoveryor explorationstage. Explorationand
evaluation costs can amount to hundreds of millions of dollars, and for smaller exploration
frms canmeanasignifcant drainonresources duringthe explorationprocess (Cortese et al.,
2010). Knowledge about exploration activities is important when assessing frm
performance in the extractives sector. Mining companies invest heavily in exploration
activities, which is likely to add value to the frm. Exploration and evaluation can lead to a
range of possible outcomes, fromabandonment of the project, through to development and
production of an area of resource deposits. Therefore, due to the uncertainty of exploration
and evaluation activities, current earnings are unlikely to be indicative of future earnings,
thus conveying little information to assess the equity value of an extractives frm(Wu et al.,
2010).
This paper investigates the value relevance of disclosed exploration and evaluation
expenditures. The paper makes three contributions. First, we address a gap in the
literature by examining the value relevance of the detailed line items of exploration and
evaluation expenditure reported by extractives frms. Second, we explore the effect of
regulatory changes (Healy and Palepu, 2001) by examining the value relevance of
exploration and evaluation expenditures pre- and post-IFRS 6/AASB6 implementation.
Finally, we contribute useful fndings to the standard setters’ ongoing deliberations
aimed at producing a comprehensive standard on extractive activities by providing
useful feedback on the relevance of accounting for pre-production costs under a regime
using the “area of interest” method.
The paper contributes three main fndings to the value relevance literature on
Australian extractive industries. First, we show that exploration and evaluation
expenditures (both capitalised and written-off exploration and evaluation expenditures)
are relevant to investors when assessing the value of extractive frms. While capitalised
expenditures are marginally signifcant, expensed exploration and evaluation costs
exhibit a strong positive signifcant association with frm valuation. While contrary to
our predicted direction, this result supports Wu et al.’s (2010) fndings of a positive
association between exploration and evaluation expenses and share price. Rather than
signalling abandonment of mining tenements and projects, our results indicate that the
expenditure signals the extent to which the frmis engaged in activities that are likely to
lead to future successful production activities.
Additional report information, in the form of the number of projects also assists in
providing relevant information for investors. Consistent with Amir and Lev (1996),
Trueman et al. (2001) and Wyatt (2008), this result indicates that non-fnancial
information is likely to be value relevant if it is suffciently salient to the frm’s economic
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reality and is informative about potential future earnings. Third, the implementation of
AASB 6 has led to an improvement in the relevance of exploration and evaluation
information in assessing frm value. Consistent with Cooper and Keim (1983); Kothari
(2001) and Healy and Palepu (2001) our results indicate that, based on the more extensive
guidelines of AASB 6, there has been an improvement in the disclosure of exploration
and evaluation expenditure, leading to increased value relevance. In additional analysis,
we fnd that exploration and evaluation data is more relevant in valuing production
frms than those purely engaged in exploration. This result points to the diffculty in
valuing exploration frms, which often operate under differing objectives than frms that
develop mining tenements through to production.
The disclosure of exploration and evaluation expenditure appears to assist users
in making decisions about extractives frms in terms of the assessment of current
fnancial performance and fnancial position, and also in forecasting future
performance and fnancial position. This is particularly important in the extractives
sector, where book values and earnings provide limited information with which to
assess the future success of a frm. It also supports previous research observing that
changes in accounting regulation have consequences for value relevance (Cooper
and Keim, 1983; Healy and Palepu, 2001; Goodwin, 2002; Ahmed and Falk, 2006;
Mitrione et al., 2014).
As with all such research, our study suffers from some limitations. The sample is
based on observations from the years 2003-2004 and the years 2006-2009. We do not
incorporate 2005 as this is the frst year the newstandard was implemented and there is
the possibility of a settling in effect. We base our sample on the top 100 extractive frms
in 2009. As such, these companies may not represent the accounting practices of smaller
frms in the Australian extractive industry.
We offer several suggestions for future research. Future research could address
the previously identifed limitations by increasing the observation period and
sample size. Studies could specifcally look at smaller mining frms versus larger
frms and examine the respective value relevance of different exploration and
evaluation variables. In addition, future studies could examine the value relevance
of the impairment of capitalised exploration and evaluation assets. One alternative
explanation for the difference in value relevance pre- and post-IFRS adoption could
be that this period coincides with a mining boom, resulting in increases commodity
prices from 2006-2008. While we have partially controlled for this by incorporating
a resources index in our models, future research could more comprehensively
examine this event.
Finally, a comparison with practices in other countries that have implemented IFRS
6 would usefully add to our understanding of the value relevance of exploration and
evaluation expenditures on a global scale, and thus contribute to the standard setters’
future development of a comprehensive extractives activities standard.
Notes
1. While there is a range of methods used, the two main methods that have developed over
time are referred to as the successful-efforts method and the full-cost method (IASB,
2010a, 2010b).
2. Firms in the extractives sector engage in activities across four phases – exploration or
searching for natural resources, evaluation of the quality, quantity and economic viability of
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explored resources, development of infrastructure necessary to extract resources and
production of resources (IASB, 2010a, 2010b).
3. Our study examines accounting for exploration costs by Australian frms. Consequently, any
further references to the standard will be to the Australian AASB 6 Exploration for the
Evaluation of Mineral Resources rather than IFRS 6.
4. One recent study examines the infuence of IFRS regulation on fnancial reporting by
companies in the Turkish extractives industry (Zarapinar et al., 2012). In an effort to assess
the impact of differences in accounting culture on disclosure, the authors compared the degree
of comparability between the top fve Turkish and the top fve global extractives frms. The
studyreveals that the global frms are more likelyto adhere to the requirements of IFRS6 than
their Turkish counterparts (Zarapinar et al., 2012).
5. The IASB’s extractives project is currently on hold until decisions are made concerning a
range of other accounting issues.
6. Capitalised expenditures should only be allocated to mineral resources in the areas of
interest in which the legal rights to tenure are current and a least one of: (i) the exploration
and evaluation expenditures are expected to be recouped through successful
development and exploitation of the area of interest, or alternatively, by its sale; and (ii)
exploration and evaluation activities have not reached a stage which permits a reasonable
assessment of the existence or otherwise of economically recoverable reserves, and active
and signifcant operations in, or in relation to, the area of interest are continuing (AASB
6, 2004, para.7).
7. The discussion paper addresses the following issues (IASB, 2010a, 2010b): how to estimate
and classify the quantities of minerals or oil and gas discovered, howto account for minerals
or oil and gas properties, howminerals or oil and gas properties should be measured and what
information about extractive activities should be disclosed.
8. As previously indicated, Wu et al. (2010) examine only the net value of exploration and
evaluation expenditures and do not consider the current capitalised or written-off line items.
9. Current capitalised exploration and evaluation expenditures constitute those expenditures
capitalised in the current period.
10. The written-off exploration and evaluation expenditures is recognised in the income
statement as “exploration and evaluation expenses” or similar. These constitute either direct
write-off of expenses in the current operating period or disposal of assets previously
capitalised to the exploration and evaluation expenditure asset account.
11. The modifed Ohlson (1995) model is used in prior value-relevance studies (Berry and Wright,
2001 and Tsoligkas and Tsalavoutas, 2011) to test the value relevance of exploration costs.
12. Kutner et al. (2004) note that a variance infation factor of ten or above indicates that
multicollinearity may be present, but levels over four should be investigated. VIFs range
between 1.131 and 1.294. Accordingly, multicollinearity is not deemed to be an issue in our
models.
13. We thank an anonymous referee for highlighting this potential reason for our lack of a
substantive result here.
14. A limitation with measuring the number of mining projects as “other fnancial report
information” is the measure could be proxying for frm size. In additional tests, we defate
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Projects
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by the number of shares outstanding and the results still hold. Further, when
Projects
t
is removed from the regression, our main results for H1 still hold.
15. We differentiate frms engaged in production activities from those only engaged in
exploration in two ways. First, we examine the segment reports for information indicating
engagement in both production and exploration activities, and those only engaged in
exploration. We confrm these by following Ferguson et al. (2011) and identifying sales
revenue greater than 5 per cent of market capitalisation.
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Corresponding author
Jacqueline Birt can be contacted at: [email protected]
For instructions on how to order reprints of this article, please visit our website:
www.emeraldgrouppublishing.com/licensing/reprints.htm
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