An evaluation of asset impairment decisions by Australian firms and whether this was
impacted by AASB 136
David Bond, Brett Govendir and Peter Wells
Accounting Discipline Group, University of Technology Sydney
Abstract
Focussing on asset impairments recognised in financial reports, this paper evaluates how
managers of Australian firms are implementing the relevant regulation. This is undertaken
both before and after transition to IFRS to provide insights into whether the prescriptive
requirements of AASB 136 (IAS 36) impacted the recognition of asset impairments.
Evidence is provided that the incidence of asset impairments increased significantly for firms
where there were indicators of impairment subsequent to the transition to IFRS. However, the
majority of such firms are still not recognising impairments, and in most cases the asset
impairments recognised are not material or not of a magnitude suggested by the indicators of
impairment. This suggests there are potentially issues with either compliance with the
regulation or that additional disclosures are necessary for firms not making asset impairment.
Key words
:
Impairment of assets, AASB 136
JEL Classification
:
M41, G32
1
1.
Introduction
The objective of this paper is to evaluate the implementation of asset impairment
regulation by managers of Australian firms through an examination of asset impairment
recognised in financial reports. This is undertaken between 2000 and 2012 which includes
both the period when the requirement for asset impairment was addressed by AASB1010
Recoverable amount of non-current assets, and subsequent to transition to International
Financial Reporting Standards (IFRS) when it was addressed by AASB 136 Impairment of
assets.1Of particular concern is whether there is evidence of firms implementing the
regulation requiring the recognition of asset impairment in manner which is consistent with
the economic circumstances, financial performance and asset values of the firm. Furthermore,
are the regulations being complied with and is information being disclosed which would be
expected to reduce uncertainty about firm value? Additionally, did the recognition of asset
impairment change with transition to IFRS and the implementation of AASB 136 which is
much more prescriptive in the measurement of ‘recoverable amount’ and is central to the
determination of asset impairment?
The primary motivation for this paper is to enhance our understanding of the
recognition of asset impairment by Australian firms, and the extent to which this is consistent
with the regulations requiring asset impairment. This is important as there are a number of
high profile firms which ostensibly should have recognised asset impairments, and this was
either considerably delayed or has not occurred and there are scant disclosures of why.2 For
example, Qantas Ltd had a market value per share substantially less than book value for 5
years, by as much as 50%. This persisted from 2009 until 2013, a period where profitability
and operating cash flows were at best marginal and these would all be considered indicators
1
The Australian equivalents to IFRS were required to be adopted for financial years beginning on or after 1
January 2005. For most firms with 30 June year ends, 30 June 2006 was the first year of applying the Australian
equivalents to IFRS. Hence in the interests of simplicity we will refer to 2006 onwards as the IFRS period,
although it does include 31 December 2005 year ends.
2
There is no evidence the disclosures resulted in lowering the gap between book value and market value.
2
of impairment. In 2014 an impairment of $2.947b was recognised and there was finally an
alignment of book value with market value. Similarly, Fairfax Media Ltd reported poor
financial performance and a book value significantly in excess of market value for a number
of years before it recognised an asset impairment of $2.865b in its 30 June 2012 financial
report. Only after years with a book value considerably less than market value was there
finally an asset impairment and book value consistent with market value. While the above
firms eventually recognised an asset impairment, Seven West Media Ltd has had a market-tobook value of substantially less than one since 2011, and it is presently 0.64. This has not
been the catalyst for asset impairments and there have been scant disclosures to support the
decision not to impair assets, other than to say that the regulation was complied with (i.e.,
trust me). Concerns with how the regulation requiring asset impairment is being implemented
have also been expressed recently by the Australian Securities and Investments Commission
(ASIC), and they note problems with the mismatching of cash flows, the reasonableness of
cash flow assumptions, the identification of cash generating units and disclosure.3 However,
ASIC concerns are largely driven by anecdotal evidence rather than systematic empirical
analysis. This suggests an analysis of the financial statements of firms where asset
impairment is expected to provide insight into how the regulation is being implemented and
asset impairments recognised.
A second motivation for this study is to evaluate the impact of differences in the style
of regulation on its implementation. With transition to IFRS and the implementation of
AASB 136, the regulation requiring asset impairment while maintaining the same concepts
was much more prescriptive in the measurement of recoverable amount, and hence the
determination of asset impairments. Critically, did this impact the implementation of the
3
ASIC Media Release 13-160 ASIC’s area of focus for 30 June 2013 financial reports.
3
regulation and change the recognition of asset impairments? This is relevant for regulators
who may be concerned with how regulatory style impacts the implementation of regulation.
This paper complements a growing stream of research which evaluates asset
impairment. Asset impairment decisions have been the subject of extensive investigation
internationally (e.g., Riedl 2004; Jarva 2009) as well as in Australia (e.g., Cotter, Stokes and
Wyatt 1998). However, this research has generally focused on the identification of
opportunistic
motivations
impacting
the
recognition
of
asset
impairments.
The
implementation of AASB 136 has also been considered with respect to the impairment of
goodwill, and in particular the discount rates used and disclosed (e.g., Carlin and Finch 2009;
Bradbury 2010). However, the issue of how the regulation is being implemented more
generally has received little attention. Accordingly, this paper contributes to the asset
impairment literature and provides insights into whether the presence of external indicators of
impairment is manifesting in recognised asset impairment as required by the regulation. This
is of concern to standard setters, financial market regulators, auditors and financial statement
users alike.
From a sample of 5,839 Australian firm-years between 2000 and 2012 we find that
there are 543 (29%) firm-years where asset impairments is recognised, with the impact on the
book value of the firm generally being immaterial. Within this sample there are 1,857 firmyears (32%) that report at least one external indicator of impairment (i.e., book value
exceeding market value). Furthermore, for this subsample the majority reported poor
performance, suggesting more indicators of impairment are present. However, only 242 of
these firm years (13%) recognised asset impairment. There is some evidence that this
increased with the application of the more prescriptive requirements of AASB 136, but the
association between asset impairment and indicators of impairment remains weak. The first
contribution of this paper is that there is little evidence that firms are complying with the
4
regulatory requirements for recognising asset impairment, and there are limited disclosures
required where firms do not recognise asset impairment.Increased disclosures might be
considered by regulators and through this greater attention directed at the decision by the firm
not to impair assets. The second contribution of this paper is to suggest a review of the
disclosure requirements for firms recognising asset impairments to consider either the nature
of the information disclosed, or whether they extended beyond the cash generating unit where
the impairment is recognised which may be limiting the present disclosures.
Of the 543 firm-years where asset impairment is recognised, only 158 (29%) include an
impairment of goodwill. This is a consequence of the number of cash generating units in the
firms and how goodwill is allocated across the cash generating units. The third contribution
of this paper is to identify a limitation of the papers that consider impairment of goodwill
only, and that the impairment of assets should be considered more generally. Given the focus
on goodwill impairments in many studies and the subjectivity of goodwill valuation, the
strong findings for opportunistically motivated assets impairment are probably expected. For
the firms recognising asset impairment only 242 (45%) had a book value greater than market
value. A final contribution of this study is that the evaluation of asset impairments is
problematic as impairment decisions are evaluated at the cash generating unit level and this
may be obscured in aggregate firm level information.
The remainder of the paper is organised as follows. In the following section an
overview of the regulation and prior research into asset impairment are introduced. From this
hypotheses are developed. In Section 3, the research design is described and in Section 4 the
sample selection procedure and some preliminary descriptive statistics are provided. Section
5 sets out the main results of the analysis regarding asset impairment. Finally, the conclusions
are presented in Section 6.
5
2.
Regulatory background and theory development
2.1
Regulatory Background
Since 2000 there has been a regulatory requirement in Australia for non-current assets
to be recognised at no more than recoverable amount. In the period immediately prior to
transition to IFRS this was addressed by AASB 1010 Recoverable amount of non-current
assets and when this standard was issued in 2000 there was the intention that it should be in
general conformity with IAS 36 as it was issued in 1998. This was reflective of a broad
strategy of convergence being followed at the time by the Australian Accounting Standards
Board (AASB)4 and this is evidenced by the terminology used. This includes the use of the
term ‘recoverable amount’ and the stated requirement for an asset to be written down to its
‘recoverable amount’ when the ‘carrying amount’ is greater than ‘recoverable amount’ (para
5.2). However, ‘recoverable amount’ was not precisely defined, and merely described as the
net amount of cash flows expected to be recovered from disposal and continued use of assets
together. Little explanation was provided for how this should be determined. Nor was the
discounting of cash flows specifically addressed, and there were anecdotes of net cash flows
not being discounted.
With transition to IFRS the requirements for asset impairment prescribed in IAS 36
were replicated in AASB 136 Impairment of assets, and in contrast to the prior standard it
was highly prescriptive of how decisions on asset impairment should be made, how
‘recoverable amount’ is measured and hence how asset impairment should be determined. In
terms of the volume of regulation, there are 40 paragraphs addressing the determination of
4
See Policy Statement 6 International Harmonisation Policy issued by the AASB and PSASB in 1996.
6
‘recoverable amount’, and of these 28 paragraphs address the estimation of value in use. It
included detailed requirements that where there are indicators of impairment such as
significant decline in firm value, significant changes in in technology, market, economic or
legal environments, changes in market interest rates, asset obsolescence or changes in asset
utilisation, firms should undertake impairment testing (AASB 136, para 12). Impairment
testing requires the determination of the ‘recoverable amount’ of the asset, which is defined
as the higher of ‘fair value’ or ‘value in use’ (AASB 136, para 6). For some assets where ‘fair
value’ is observable in an active market this will be relatively straightforward. For some
assets it will be much more problematic and ‘value in use’ will have to be estimated. Again,
guidance is provided describing the procedures for estimating future cash flows and discounts
rates (IAS 36, para 30). Impairment testing involves the comparison of carrying value with
‘recoverable amount’, and impairment is required to ensure that ‘carrying value’ does not
exceed ‘recoverable amount’ (AASB 136, para 59).
When implementing AASB 136 it will often be applied to groups of assets, referred to
as cash generating units, rather than individual assets. However, a process consistent with that
outlined above is applied to the cash generating unit, and an order is prescribed for the
impairment of assets within a group. Goodwill within a cash generating unit is impaired first,
and then subject to conditions the remaining assets are impaired on a pro-rata basis (AASB
136, para 104). This creates a number of issues when evaluating asset impairment if there is
more than one cash generating unit within a business.
First, determination of whether asset impairment is required may not always be
possible from aggregate firm level information.5 Where firm market value exceeds book
value it is possible that there will be no cash generating units where recoverable amount is
less that carrying amount and no impairment is necessary. However, there may be individual
5
This would require information about the relative size and loss of value within the separate cash generating
units which is not disclosed.
7
cash generating units where recoverable amount is less than carrying amount. Accordingly,
impairment may be necessary notwithstanding there being no externally identifiable
indicators.6 Where aggregate firm level recoverable amount is less than carrying amount, it is
expected that there will be at least one cash generating unit where recoverable amount is less
than carrying amount and impairment will be necessary. In this study the focus is on how
firms are implementing the regulation, so while considering all firms, particular attention is
focussed on those where market value is less than book value (an indicator of impairment,
AASB 136, para 12(d)) and an impairment decision is necessary.
Second, whether impairment within a cash generating unit is applied to goodwill or
other assets will depend on the allocation of goodwill across the cash generating units of the
firm. If no goodwill has been allocated to the cash generating unit for which impairment is
required, assets other than goodwill will be subjected to impairment. This is an issue for
studies that evaluate impairment of goodwill only (e.g., Ramanna and Watts 2012) and it is
for this reason that the focus is on impairment generally rather than goodwill alone.7
Critically, how this regulation is being implemented and whether asset impairment is
recognised, where necessary, is a major concern for standard setters, financial market
regulators and financial statement users. Furthermore, with transition to IFRS and the
adoption more prescriptive approach taken to the measurement of ‘recoverable amount’, was
there a change in the recognition of asset impairment?
2.2
Empirical research
There is a significant literature evaluating asset impairment. This has considered the
incidence of asset impairment (e.g., Strong and Meyer 1987) and there is evidence that asset
6
Consistent with this we observe that 301 observations where asset impairments are recognised (55% of those
recognising asset impairments) arise where market value exceeds book value.
7
In this regard we note that in our sample of firms recognising impairment, only 158 (29%) are impairing
goodwill. Most asset impairments relate to tangible assets (69%).
8
impairment is associated firm economic characteristics and performance (e.g., Cotter et al.
1998). However, evidence on price reactions to asset impairment is mixed and this has been
attributed to the nature of the assets being impaired and concerns about timeliness in the
recognition of asset impairment (e.g., Francis, Hanna and Vincent 1996; Collins and Henning
2004; Jarva 2009; Muller, Neamtiu and Riedl 2010). The determination of asset impairment
requires the exercise of considerable discretion and hence many studies consider whether
they are opportunistically motivated (e.g., Elliott and Shaw 1988; Francis et al. 1996; Cotter
et al. 1998; Riedl 2004; Beatty and Weber 2006; Christensen, Paik and Stice 2008; Garrod,
Kosi and Valentincic 2008; Jarva 2009, 2014). Results are consistent across different
countries and regulatory environments and suggest asset impairment is opportunistically
motivated. Furthermore, there is evidence that effective corporate governance mechanisms
may constrain opportunism (e.g., AbuGhazaleh, Al-Hares and Roberts 2011).8
In many of these studies controls are included for firm performance and this includes
many factors that would in terms of the current regulation be labelled as indicators of
impairment. However, this is not the focus of these prior studies and the relevance of these
factors to the recognition of asset impairment has received scant separate consideration.
Furthermore, sample firms have been broadly selected. This reflects concerns with
identifying the association between asset impairment and opportunistic motivations, rather
than the extent to which asset impairment is consistent with the requirements of the relevant
regulation. Hence, the focus of this study is whether there is evidence that financial
statements are being prepared in a manner consistent with the requirements of AASB 136,
and whether firms are recognising asset impairment where this is suggested by the presence
8
Much of this literature focuses on goodwill impairment as it is motivated by how SFAS 142 Goodwill and
other intangible assets was implemented, and how it impacted reporting behaviour. Notwithstanding, there are
exceptions such as AbuGhazaleh et al. (2011).
9
of indicators of impairment.9 This is considered important as the asset impairment
recognised, and the accompanying disclosures would provide information about expected
future performance and future cash flows. This would lead to lower parameter uncertainty in
estimating firm value (Lewellen and Shanken 2002; PÁstor and Pietro 2003) and reduce
uncertainty about firm value in the same manner as management earnings forecasts (Rogers,
Skinner and Van Buskirk 2009).
As discussed in section 2.1, between 2000 and 2012 there was a requirement for firms
to recognise asset impairment where the carrying amount of assets exceeded the recoverable
amount of the asset. This was addressed in the period prior to transition to IFRS by AASB
1010, and subsequent to transition with AASB 136. The initial concern in this paper is
whether there is evidence that for firms recognised asset impairment in a manner consistent
with the regulation. This is reflected in the following hypothesis.
H1:
Is evidence that firms are recognising asset impairment where
there are indicators of impairment.
The second concern of this paper is whether the nature of the regulation impacted its
application. As discussed in section 2.1 there was considerable discretion in the application of
AASB 1010 and this is in stark contrast with the requirements of AASB 136 which would be
considered detailed and prescriptive.
While regulators might argue that this is likely to increase compliance with regulatory
intent, the actual impact is less certain. Shaw (1995) and Beresford (1999) both express
concerns about whether practitioners are able to critically understand and apply complex
regulations, which are likely to contribute to ‘standards overload’. These concerns are echoed
by Bonner (1994) in relation to auditors. She suggests that more complex tasks, or in this case
regulations, are likely to adversely impact auditors judgement performance and this likely
9
This should be distinguished from where firms are recognising impairment, or excessive impairment for
entirely opportunistic reasons.
10
reflects an increasing concern with strict regulatory compliance at the expense of the exercise
of professional judgment. This conclusion is supported by Bennett, Bradbury and Prangnell
(2006) who, based on an analysis of specific regulation, find that more prescriptive
regulations require less professional judgement. It is therefore not surprising that Nelson,
Elliott and TarpIey (2002) provide evidence that managers are more (less) likely to attempt
earnings management, and auditors are less (more) likely to constrain it, where accounting
regulations are more (less) precise and earnings management actions can be structured to
demonstrate compliance with the regulation.
This suggests that the change in the regulation relating to asset impairment with
transition to IFRS, and the adoption of a more prescriptive regulation, may not have led to
greater adherence to the intent of the regulators. We test the following hypothesis to
determine if there was a change in the recognition of asset impairments across the two
regulatory regimes.
H2:
3.
With the adoption of a more prescriptive regulation there was
an increase in the recognition of asset impairment by firms
where there is evidence that asset impairment decisions are
necessary.
Research design
The primary concern in this paper is whether there is evidence of firms recognising
asset impairment in response to deteriorating economic circumstances, financial performance
and asset values in accordance with the requirements of the regulation. This is reflected in the
research design.
The determination of asset impairment requires the exercise of judgement by
management, but as a safeguard against over-optimism the regulation identifies detailed
indicators of impairment and if any of these are present impairment testing is required to be
11
undertaken (AASB 136, para 12, IAS 36 BCZ24). This would be expected to lead to asset
impairment being recognised. While these indicators are not explicitly identified in AASB
1010, they would have been equally relevant to the determination of whether impairment is
necessary and they are included in the initial version of IAS 36 (issued in 1998) which would
have been considered authoritative. Accordingly, these factors will be used to identify firms
where impairment is likely necessary, and the extent to which impairment is necessary.
While primarily concerned with evaluating how firms are implementing the regulation,
it is recognised that financial reports are a joint statement of management and auditors (Antle
and Nalebuff 1991, p. 31). Auditors are a source of accounting expertise and will review
critical accounting decisions, such as impairment testing. Hence consideration is also given to
how auditors impact the recognition of asset impairment, but this is on the basis of their
direct involvement in the financial reporting process rather than as a corporate governance
mechanism.
This suggests the estimation of the following model to evaluate how the regulation
prescribing asset impairment is being implemented:
𝐼𝑚𝑝𝑎𝑖𝑟𝑖𝑡 =∝0 +∝1 𝐵/𝑀𝑖𝑡 +∝2 𝑌𝑟𝑠𝑖𝑡 +∝3 𝐸𝑎𝑟𝑛𝑖𝑡 +∝4 𝐶𝐹𝑖𝑡 +∝5 𝐵𝐻𝑅𝑖𝑡 +
∝6 𝐴𝑢𝑑𝑖𝑡𝑄𝑢𝑎𝑙𝑖𝑡 +∝7 𝐴𝑢𝑑𝑖𝑡𝐸𝑓𝑓𝑖𝑡 + 𝜀𝑖𝑡
(1)
To determine whether the recognition of asset impairment changed across the regulatory
periods, equation (1) is re-estimated with an indicator variable to distinguish the two
regulatory periods to capture any change in impairments generally, and with interaction terms
to capture changes in the extent to which there is a change in the extent to which any of the
indicators of impairment are deterministic of asset impairment.
12
𝐼𝑚𝑝𝑎𝑖𝑟𝑖𝑡 =
𝛽0 + 𝛽1 𝐵/𝑀𝑖𝑡 + 𝛽2 𝑌𝑟𝑠𝑖𝑡 + 𝛽3 𝐸𝑎𝑟𝑛𝑖𝑡 + 𝛽4 𝐶𝐹𝑖𝑡 + 𝛽5 𝐵𝐻𝑅𝑖𝑡 +
𝛽6 𝐴𝑢𝑑𝑖𝑡𝑄𝑢𝑎𝑙𝑖𝑡 +𝛽7 𝐴𝑢𝑑𝑖𝑡𝐸𝑓𝑓𝑖𝑡 + 𝜀𝑖𝑡
(2)
And:
𝐼𝑚𝑝𝑎𝑖𝑟𝑖𝑡 = 𝛽0 + 𝛽1 𝐵/𝑀𝑖𝑡 + 𝛽2 𝑌𝑟𝑠𝑖𝑡 + 𝛽3 𝐸𝑎𝑟𝑛𝑖𝑡 + 𝛽4 𝐶𝐹𝑖𝑡 + 𝛽5 𝐵𝐻𝑅𝑖𝑡 +
𝛽6 𝐴𝑢𝑑𝑖𝑡𝑄𝑢𝑎𝑙𝑖𝑡 +𝛽7 𝐴𝑢𝑑𝑖𝑡𝐸𝑓𝑓𝑖𝑡 + 𝛽8 𝐼𝐹𝑅𝑆𝑖𝑡 + 𝛽9 𝐵/𝑀𝑖𝑡 ∗ 𝐼𝐹𝑅𝑆𝑖𝑡 + 𝛽10 𝑌𝑟𝑠𝑖𝑡 ∗ 𝐼𝐹𝑅𝑆𝑖𝑡 +
𝛽11 𝐸𝑎𝑟𝑛𝑖𝑡 ∗ 𝐼𝐹𝑅𝑆𝑖𝑡 + 𝛽12 𝐶𝐹𝑖𝑡 ∗ 𝐼𝐹𝑅𝑆𝑖𝑡 + 𝛽13 𝐵𝐻𝑅𝑖𝑡 ∗ 𝐼𝐹𝑅𝑆𝑖𝑡 + 𝛽14 𝐴𝑢𝑑𝑖𝑡𝑄𝑢𝑎𝑙𝑖𝑡 ∗ 𝐼𝐹𝑅𝑆𝑖𝑡 +
𝛽15 𝐴𝑢𝑑𝑖𝑡𝐸𝑓𝑓𝑖𝑡 ∗ 𝐼𝐹𝑅𝑆𝑖𝑡 + 𝜀𝑖𝑡
(3)
The variables in these regressions are measured as follows.
Impair
The focus of this paper is the incidence of asset impairment (Impair) and this is measured in
the first instance as continuous variable being the asset impairment per share recognised in
the income statement in accordance with the disclosure requirements of AASB 136.
Recognising that indicators of impairment may lead to asset impairment but the magnitude of
the asset impairment may be highly variable, as a sensitivity the analysis is undertaken with
Impair measured as a dichotomous variable. As impairments are negatively signed, to ensure
consistency in the results from regressions with the continuous variable, this assumes the
value 0 if an asset impairment is recognised, otherwise 1.
Indicators of Impairment
The initial concern in this study is whether the presence of indicators of impairment is
associated with the recognition of asset impairment. Consistent with the requirements of the
13
regulation we identify external factors which are indicators of impairment, and which
externally observable.
A book value in excess of market value is an indicator that the market has determined
that the value of assets is less than book value (AASB 136, para 12(d)). Hence B/M is
included as an independent variable and is measured as the ratio of the book value of equity
over the market value of equity at the end of the financial year. This is included as a
continuous variable as the greater the excess the stronger the indication that an asset
impairment should be recognised. If book value has been greater than market value for more
than one year this suggests that the decline in value that the firm has experienced is not
transitory. Hence, Yrs is included in the regression and this is a dichotomous variable
assuming the value one if B/M has been greater than one for two years (current and
preceding), and zero otherwise.
An increase in the B/M may have occurred because of a substantial decline in market
value, however this may not have resulted in a value greater than one. There may be
individual cash generating units to which the decline in market value can be attributed and
this doubtless contributed to the identification of declines in market value as an indicator of
impairment (AASB 136, para 12(a)). Therefore, we complement B/M with BHR, which is the
buy-hold return for the stock over the financial year, as a further indicator of impairment.
Other indicators of impairment may be observable internally during the financial year,
and these would become observable externally at year end when the financial statements are
prepared. Where economic performance of an asset is worse than expected asset impairment
is necessary (AASB 136, para 12(g)). Evidence of this would include actual cash flows and
profitability being worse than expected (AASB 136, para 14(b)-(d)). Accordingly, we include
earnings before impairment charges per share (Earn) and aggregate cash flow from operating
and investing per share (CF) as further indicators of impairment.
14
Audit
Recognising that audit quality may be relevant to decisions relating to the
implementation of the regulation we include AuditQual as an independent variable which
assumes the value one if the firm is audited by a Big 4 auditor, and zero otherwise.
Evaluating impairment decisions may also impact the requisite audit effort and hence we in
∆AuditEff as an independent variable measured as the percentage change in audit fees for the
firm.
Regulatory change
With the change in regulation on transition to IFRS this may have changed the
incidence of asset impairments. To evaluate this we consider differences in the magnitude or
frequency of asset impairment (reflecting the dependent variable used) by including a
dichotomous variable, IFRS, which has the value one if the financial reports are from the
post-transition period (i.e., prepared under AASB 136) and zero otherwise. This variable is
also interacted with the other independent variable to determine whether there any changes in
the association with those variables and asset impairment in the post-transition period.
4. Sample selection and data description
Sample observations for this paper were chosen in the first instance between 2000 and
2012 so as to include firm-years from periods both before and after the adoption of IFRS in
Australia. Financial report information was obtained from the Morningstar Datanalysis
database, stock price information was obtained from SIRCA SPPR database and audit data
was obtained from the UTS Audit database. Financial information was supplemented where
necessary with hand collected information from financial reports where asset impairments
15
were potentially aggregated in abnormal items in the Morningstar database. Firms in the
agriculture, financial services, real-estate investment sectors were excluded because changes
in asset values may not be recognised as impairment due to the application of fair value
accounting (e.g., AASB 140 Investment Property; AASB 141 Agriculture). While there is
provision in other standards such as AASB 116 Property Plant and Equipment and AASB
138 Intangible Assets for the recognition of assets at other than cost (i.e., the revaluation
model), in practice very few firms avail of this choice and it is reasonable to assume that
remaining firms have significant assets recognised at cost and for which AASB 136
Impairment of Assets would be relevant.10 This ensured that sample firm-years are more
likely to be recognising assets at cost and decrements in asset value would be recognised as
impairment in accordance with AASB 136 Impairment of Assets or an equivalent. This
identified a final sample of 5,839 firm year observations where all necessary information was
available.
Descriptive statistics for sample firms are provided in Table 1. This shows that for the
full sample of firms the mean (median) book value of equity per share was $1.279 (0.424),
and the mean (median) of stock price was $0.977 (0.663). The mean asset impairment was
$0.010 per share and this represents less than 0.4% of mean total assets. Doubtless
influencing this is limited number of firms recognising asset impairments, with only 543
firms (9.3%) of firms recognising asset impairment. For firms recognising asset impairment,
mean impairment is $0.105. Of the firms recognising asset impairment, 158 firms recognised
an impairment of goodwill, while 196 recognised an impairment of an identifiable intangible
asset and 374 recognised an impairment of tangible assets. This reaffirms the decision to
address asset impairment generally rather than focus on goodwill in particular, and suggests
10
Asset impairments could be recognised for assets measured at fair value between the years where revaluation
is undertaken. Accordingly, changes in asset values may be recognised as both impairments and revaluations.
However, these circumstances are rare and unlikely to influence the results.
16
that studies focusing on goodwill impairment may be missing a significant proportion of
impairments.
5. Results
To provide insights into the full extent of the recognition of asset impairments we
provide descriptive statistics for the full sample in Table 1. For these firm year observations
the mean (median) B/P ratio is 0.977 (0.663) and this indicates considerable skewness in the
distribution of this variable. This is confirmed by the 75th percentile being 1.187, and there
are a significant number of firms with a B/P ratio of greater than one and for which asset
impairment is ostensibly an accounting issue. We identify 543 (9.3%) firm-year observations
where asset impairments are being recognised, and for these firms the mean (median)
impairment per share is -0.105 (-0.026). Again this identifies considerable skewness and most
asset impairments are economically small. Of the firm-years where asset impairment is
recognised, 158 (29%) include an impairment of goodwill, while 196 include impairment of
identifiable intangible assets and 374 impairment of tangible assets. This confirms the
concerns expressed above about focussing on goodwill impairments only, and assuming the
goodwill is allocated to the cash generating units where impairment is required to be
recognised.
In Table 2 attention is directed at firms where the firm has a book value greater than
market value (B/P>1). This is undertaken to focus attention of firms where there is at least
one indicator that impairment is necessary. This identifies 1857 firm-year observations (32%
of the full sample) with a book value in excess of market value. Furthermore, for these firms
it is also notable that while the mean values of earnings per share and cash flows per share
(CFOPS+CFINV) are 0.066 and 0.042 respectively, the median values were economically
little different from zero. Accordingly, for a majority of this subsample the existence of
17
indicators of impairment is likely not limited to book value being greater than market value.
Hence, it is somewhat surprising that only 242 (13%) of these firms-year observations are
recognising asset impairment, there is little support for H1. Of these impairments, only 85
(35%) include an impairment of goodwill and this highlights the problem of assuming
goodwill is allocated across the cash generating units where impairments are being
recognised. For firms-years where asset impairment is recognised (Panel B) it is clear that
while some firms are recognising material impairments and the mean impairment per share is
-0.122, most asset impairment is relatively small and the median asset impairment per share
is only -0.033. Whether this is sufficient, or commensurate with the indicators of impairment
will be addressed in the subsequent analysis.
In combination these tables suggest that the incidence of asset impairment is relatively
low, and this is particularly so for firm-years where there is at least one indicator of
impairment. Furthermore, the magnitude of recognised asset impairment is low, and the
majority are economically immaterial. This initial analysis provides little support for H1.
To provide further insight into the nature of firm-years with at least one indicator of
impairment we further partitioned them on the basis of size, with the results presented in
Table 3. This reflected concerns that smaller firms may not be subject to the same level of
scrutiny and this may impact the results. Included in our subsample of firm-years there are
1,212 firm-years with a market capitalisation of greater than $10m and 197 (16%) of these
firms recognised an asset impairment (Panel A). This contrasts with only 45 (7%) of firmyears with a capitalisation below $10m recognising an asset impairment. This may be a
consequence of smaller firms being subjected to less scrutiny by directors, auditors,
regulators and investors. It is also notable that firm performance, measured as earnings and
cash flows are poorer for smaller firms, but the median values of earnings and cash flow for
the larger firms indicates that the majority of the larger firms are still experiencing poor
18
performance. Hence, while there is evidence of more asset impairment is being recognised by
larger firms, concerns about lack of recognition of asset impairment persist for all firms.
Recognising the regulatory change that occurred in 2006, firm-years were partitioned
on the basis of whether the historic Australian regulation applied (i.e., ASB 1010) or whether
the post transition to international accounting regulations applied (i.e., AASB 136). The
sample includes more firms from the post-transition period (1,137 compared to 720), and
there was proportionately greater recognition of asset impairment in the post-transition period
(195 or 17% compared to 47 or 7%). However, it is notable that there are still less firms
recognising asset impairment than would otherwise be expected given presence of indicators
of impairment. Again, there is little support for H1.
To evaluate the association between impairment and indicators of impairment,
equation 1 was estimated with the results presented in Table 5. Focusing initially on
impairment measured as a continuous variable (Panel A) and firm-years where the book
value is greater than market value (and firms most likely need to undertake impairment
testing and recognise asset impairments) it is notable that the model has an adjusted R2 of
15.2%. While this is statistically significant given the regulatory prescription there is an
expectation this might be greater. The co-efficient on the indicators of impairment are
generally as expected given that impairment is negatively signed. While B/P is not significant
this is likely a consequence of firms already being partitioned on the basis of B/P. The coefficient on YRS (α2=-0.092, t-stat=-3.326) is negative and significant while the co-efficient
on Earn is positive and significant (α3=0.595, t-stat=18.343) suggesting that the magnitude of
impairment is greater if book value has been greater than market value for two years and if
the firms is less profitable. The co-efficient on CF is not significant and this is likely a
consequence of this measure being confounded by higher investing cash flows where firms
are able to raise debt and equity to finance asset acquisition. Finally the co-efficient on BHR
19
is negative and significant (α5=-0.090, t-stat=-3.498) and while surprising this may simply
reflect a poor stock return not being an indicator of impairment if it follows historic high
market values and high profitability. When the equation was estimated for the full sample of
firms the model lost explanatory power and this would have been adversely impacted by
difficulties assessing asset impairments in cash generating units on the basis of aggregate
firm level information.
The results when impairment is measured as a dichotomous variable are presented in
Panel B. For both the B/P>1 subsample and the full sample the model has minimal
explanatory power (2.1% and 2.2% respectively). For both samples the decline in explanatory
power is consistent with the limited number of material asset impairments receiving less
weight in the analysis (and many asset impairments recognised being small), together with a
high proportion of firm-years where there are indicators of impairment but asset impairment
is not recognised. Furthermore, when the full sample is considered many of the co-efficients
have a different sign from that expected and this is likely a consequence of the high
proportion of firms recognising asset impairment within a cash generating unit when there are
no aggregate firm level indicators of impairment. It is also notable that the co-efficient on
AuditQual Changes between Panels A and B and this suggests that Big 4 auditors are more
likely to require a large impairment where necessary, but generally their clients are larger,
more profitable and less likely to need to make an asset impairment.
In summary the results for tests of hypothesis one are weak and while there is some
evidence that firms with indicators of impairment are recognising asset impairment, this is
not pervasive and many are recognising either small impairments which are not
commensurate with the magnitude of the indicators of impairments or not recognising asset
impairment. This result is consistent with extant literature which provides strong evidence of
opportunistic incentives being a major determinant of asset impairments (e.g., Elliott and
20
Shaw 1988; Francis et al. 1996; Cotter et al. 1998; Riedl 2004; Beatty and Weber 2006;
Christensen et al. 2008; Garrod et al. 2008; Jarva 2009, 2014). Further weakening these tests
are the number of firms recognising impairment where there is no externally identifiable
indicator of impairment at the aggregate firm level.
Finally, the proportion of firms
recognising impairment of goodwill is relatively low, and this is inconsistent being
distributed across all cash generating units as is assumed in many impairment studies.
In Table 6 we commence our evaluation of whether there are differences in the
recognition of asset impairment subsequent to the transition to IFRS and the implementation
of AASB 136, and this is undertaken with the inclusion of an indicator variable, IFRS. In
Panel A asset impairment is measured as a continuous variable and the results are little
changed from those in Table 5. Critically, for the subsample where book value exceeds
market value the co-efficient on IFRS is not significant (α?=0.023, t-stat=0.792), and for the
full sample the model has literally no explanatory power. These results contrast with those in
Panel B where asset impairment was measured as dichotomous variable, and for both the
samples of firms the coefficient on IFRS was negative and significant which is indicative of
a greater incidence of impairments subsequent to the transition to IFRS and more prescriptive
regulations.
This result complements those provided in Table 5 and suggests that both before and
after transition to IFRS and more prescriptive regulations some firms recognised
economically material asset impairment. However, subsequent to transition to impairment
there was an increased incidence of small asset impairment which may not have been
commensurate with the indicators of impairment observed. Furthermore, many firms with
indicators of impairment are not recognising asset impairments. Hence, there is at best
limited support for H2, in that while there may have been an increase in the recognition of
asset impairment, they may not have been fully reflective of the economic circumstances.
21
Finally, in Table 7 we consider whether there was a change in the relation between the
recognition of asset impairment and the various indicators of impairment in the post-IFRS
period. The results across Panels A (continuous) and B (dichotomous) and for the sample
with book value greater than market value and the full sample provide few additional
insights. First, the models have poorer than expected explanatory due to the low incidence of
firm-years recognising impairment where there are indicators, and firms recognising
impairment where there are no externally observable indicators. Second, a significant
proportion of the asset impairment recognised is economically insignificant. In combination
this causes considerable instability on the regression results, including co-efficients not being
significant or changing sign across the different regressions. Accordingly, while there may
have been an increased recognition of asset impairment subsequent to transition to IFRS, the
associations with indicators of impairment are still tenuous and there is again little support for
H2.
6. Conclusion
The objective of this paper was to evaluate how the regulation prescribing asset
impairment is being implemented by managers through an examination of asset impairment
being recognised in financial reports. Of particular concern was whether evidence could be
found that the regulations are being complied with and whether information about expected
future performance and future cash flows is being provided through the recognition of asset
impairment and the associated disclosures. Furthermore, did this result change with transition
to IFRS and implementation of the more prescriptive AASB 136.
We provide evidence that for 1,857 (32%) of our sample firms book value exceeds
market value and there is at least one indicator of impairment. For these same firms there is
also evidence of poor performance with reported earnings and cash flows being economically
22
immaterial for the majority of these firms. Furthermore, for many firms these circumstances
persisted for a number of years. However, only 242 (13%) recognised asset impairment and
the association of asset impairment with indicators of impairment is weak. There is some
evidence that this improved with the more prescriptive requirements of AASB 136 but the
association between asset impairments and indicators of impairment remains weak. Hence,
the first contribution of this paper is that there is little evidence that firms are complying with
the regulatory requirements for recognising asset impairment. Problematically, where there
are external indicators of impairment present but asset impairment is not recognised, the
mandated disclosures are minimal. Given the proportion of firms in this circumstance,
regulators might consider increased disclosure for firms not impairing assets thereby
directing greater attention at the decision by the firm not to impair assets. The majority of
asset impairments recognised are economically immaterial, and the association with
indicators of impairment is weaker than would be expected. The second contribution of this
paper is to suggest a review of the disclosure requirements for firms recognising asset
impairment to consider either the nature of the information disclosed or whether the
disclosures are extended beyond the cash generating unit where the impairment is recognised.
Of the 543 firm-years where asset impairment is recognised, only 158 (29%) include an
impairment of goodwill. This is a consequence of the number of cash generating units in the
firm and how goodwill is allocated across the cash generating units. The third contribution of
this paper is to identify a limitation of the papers that consider impairment of goodwill only,
and that the impairment of assets should be considered more generally. Given the focus on
goodwill impairment in many studies, the strong findings for opportunistically motivated
asset impairment is probably expected. For the firms recognising asset impairment only 242
(45%) had a book value greater than market value. A final contribution of this study is that
23
the evaluation of asset impairment is problematic as impairments are evaluated at the cash
generating unit level and this may be obscured in aggregate firm level information.
Not addressed in this study, but which might be considered in future studies is how
investors respond to asset impairment decisions and what evidence is there of share price and
market impacts.
24
7. References
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Beatty, A. & Weber, J. 2006, 'Accounting Discretion in Fair Value Estimates: An
Examination of SFAS 142 Goodwill Impairments', Journal of Accounting Research,
vol. 44, no. 2, pp. 257-88.
Bennett, B., Bradbury, M. & Prangnell, H. 2006, 'Rules, principles and judgments in
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Beresford, D.R. 1999, 'It's Time to Simplify Accounting Standards', Journal of Accountancy,
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Bonner, S.E. 1994, 'A model of the effects of audit task complexity', Accounting,
Organizations and Society, vol. 19, no. 3, pp. 213-34.
Bradbury, M.E. 2010, 'Commentary: Discount Rates in Disarray – Evidence on Flawed
Goodwill Impairment Testing', Australian Accounting Review, vol. 20, no. 3, pp. 3136.
Carlin, T.M. & Finch, N. 2009, 'Discount Rates in Disarray: Evidence on Flawed Goodwill
Impairment Testing', Australian Accounting Review, vol. 19, no. 4, pp. 326-36.
Christensen, T.E., Paik, G.H. & Stice, E.K. 2008, 'Creating a Bigger Bath Using the Deferred
Tax Valuation Allowance', Journal of Business Finance & Accounting, vol. 35, no. 56, pp. 601-25.
Collins, D. & Henning, S. 2004, 'Write-Down Timeliness, Line-of-Business Disclosures and
Investors’ Interpretations of Segment Divestiture Announcements', Journal of
Business Finance & Accounting, vol. 31, no. 9-10, pp. 1261-99.
Cotter, J., Stokes, D. & Wyatt, A. 1998, 'An analysis of factors influencing asset writedowns',
Accounting & Finance, vol. 38, no. 2, pp. 157-79.
Elliott, J.A. & Shaw, W.H. 1988, 'Write-Offs As Accounting Procedures to Manage
Perceptions', Journal of Accounting Research, vol. 26, pp. 91-119.
Francis, J., Hanna, J.D. & Vincent, L. 1996, 'Causes and Effects of Discretionary Asset
Write-Offs', Journal of Accounting Research, vol. 34, pp. 117-34.
Garrod, N., Kosi, U. & Valentincic, A. 2008, 'Asset Write-Offs in the Absence of Agency
Problems', Journal of Business Finance & Accounting, vol. 35, no. 3-4, pp. 307-30.
Jarva, H. 2009, 'Do Firms Manage Fair Value Estimates? An Examination of SFAS 142
Goodwill Impairments', Journal of Business Finance & Accounting, vol. 36, no. 9-10,
pp. 1059-86.
Jarva, H. 2014, 'Economic consequences of SFAS 142 goodwill write-offs', Accounting &
Finance, vol. 54, no. 1, pp. 211-35.
Lewellen, J. & Shanken, J. 2002, 'Learning, Asset-Pricing Tests, and Market Efficiency', The
Journal of Finance, vol. 57, no. 3, pp. 1113-45.
Muller, K., Neamtiu, M. & Riedl, E.J. 2010, 'Information asymmetry surrounding SFAS 142
goodwill impairments', Harvard Business School Accounting & Management Unit
Working Paper, no. 1429615.
Nelson, M.W., Elliott, J.A. & TarpIey, R.L. 2002, 'Evidence from Auditors about Managers'
and Auditors' Earnings Management Decisions', Accounting Review, vol. 77, no. 4, p.
175.
PÁstor, Ľ. & Pietro, V. 2003, 'Stock Valuation and Learning about Profitability', The Journal
of Finance, vol. 58, no. 5, pp. 1749-90.
25
Ramanna, K. & Watts, R. 2012, 'Evidence on the use of unverifiable estimates in required
goodwill impairment', Review of Accounting Studies, vol. 17, no. 4, pp. 749-80.
Riedl, E.I. 2004, 'An Examination of Long-Lived Asset Impairments', The Accounting
Review, vol. 79, no. 3, pp. 823-52.
Rogers, J.L., Skinner, D.J. & Van Buskirk, A. 2009, 'Earnings guidance and market
uncertainty', Journal of Accounting and Economics, vol. 48, no. 1, pp. 90-109.
Shaw, J. 1995, 'Audit failure and regulatory overload', Accountancy, vol. 115, no. 1219, p. 82.
Strong, J.S. & Meyer, J.R. 1987, 'Asset Writedowns: Managerial Incentives and Security
Returns', The Journal of Finance, vol. 42, no. 3, pp. 643-61.
26
Table 1: Descriptive Statistics
All firms listed on the ASX with data available between 2000 and 2012
Panel A:
3.161
1.883
1.279
2.541
0.977
Std.
Dev
10.997
9.889
2.545
6.102
1.385
0.000
0.000
0.000
0.001
0.000
0.150
0.027
0.095
0.130
0.352
5839
5839
5839
5839
5839
5839
5839
5839
5839
-0.003
-0.002
-0.004
-0.010
0.136
0.127
0.205
-0.219
-0.015
0.038
0.027
0.047
0.073
0.505
0.490
0.547
1.361
1.353
-1.281
-0.952
-2.251
-2.251
-6.802
-4.015
-5.733
-32.540
-33.230
158
196
374
543
-0.121
-0.071
-0.064
-0.105
0.201
0.129
0.177
0.218
-1.281
-0.952
-2.251
-2.251
Obs.
Mean
5839
5839
5839
5839
5839
Min
p25 Median
p75
Max
0.790
0.286
0.424
0.600
0.663
2.910
1.393
1.401
2.460
1.187
234.927
224.359
42.398
119.950
57.979
0.000
0.000
0.000
0.000
-0.014
-0.019
-0.007
-0.168
-0.054
0.000
0.000
0.000
0.000
0.021
0.017
0.033
-0.029
-0.005
0.000
0.000
0.000
0.000
0.175
0.166
0.248
-0.002
0.084
0.000
0.000
0.000
0.000
13.986
11.621
13.933
34.542
35.291
-0.126
-0.081
-0.054
-0.104
-0.041
-0.018
-0.016
-0.026
-0.010
-0.003
-0.004
-0.006
-0.000
-0.000
-0.000
-0.000
Assets
Liabilities
BV
P
B/P
Impairment type:
Goodwill
Identifiable Intangibles
Tangibles
Total
NPAT
NPAT+Spec
CFOPS
CFINV
CF
Panel B:
Impairment type:
Goodwill
Identifiable Intangibles
Tangibles
Total
Where:
Assets
Liabilities
BV
P
B/P
Impairment
B/P^
:
:
:
:
:
:
:
Total assets per share for firm i in year t
Total liabilities per share for firm i in year t
Book value or Net Assets per share for firm i in year t
Price per share at year end for firm i in year t
BV/P
Impairment expense per share for firm i in year t
(BV + Impairment) /P
NPAT
NPAT+Spec
CFOPS
CFINV
CF
:
:
:
:
:
Net profit after tax before special items per share for firm i in year t
Net profit after tax including special items per share for firm i in year t
Net cash flow from operations from cash flow statement per share for firm i in
year t Investment cash flow from the cash flow statement per share for firm i in
Total
year tcash flow per share for firm i in year t (CFOPS+CFINV)
Free
27
Table 2: Descriptive Statistics
B/M>1 firms listed on the ASX with data available between 2000 and 2012
Panel A:
Obs.
Mean
Std.
Dev
8.571
7.311
2.971
2.533
2.050
Min
p25
Median
p75
Max
Assets
1857
2.721
0.003
Liabilities
1857
1.386
0.000
BV
1857
1.335
0.002
P
1857
0.942
0.001
B/P
1857
2.050
1.000
Impairment type:
Goodwill
1857 -0.006
0.050 -1.243
Identifiable Intangibles
1857 -0.004
0.035 -0.952
Tangibles
1857 -0.006
0.068 -2.251
Total
1857 -0.016
0.097 -2.251
NPAT
1857
0.066
0.412 -1.787
NPAT+Spec
1857
0.040
0.442 -4.015
CFOPS
1857
0.124
0.360 -4.498
CFINV
1857 -0.082
1.519 -28.401
CF
1857
0.042
1.559 -27.571
Panel B:
Impairment type:
Goodwill
85 -0.127
0.198 -1.243
Identifiable Intangibles
88 -0.083
0.138 -0.952
Tangibles
170 -0.068
0.214 -2.251
Total
242 -0.122
0.243 -2.251
Where: All variables as previously defined
0.229
0.045
0.152
0.077
1.225
0.887
0.353
0.495
0.270
1.534
2.738
1.232
1.408
0.905
2.164
200.469
188.024
42.398
42.370
57.979
0.000
0.000
0.000
0.000
-0.017
-0.030
-0.006
-0.118
-0.044
0.000
0.000
0.000
0.000
0.009
0.005
0.024
-0.021
-0.003
0.000
0.000
0.000
0.000
0.083
0.076
0.157
-0.001
0.071
0.000
0.000
0.000
0.000
11.621
11.621
4.225
34.542
35.291
-0.138
-0.107
-0.046
-0.124
-0.042
-0.028
-0.018
-0.033
-0.013
-0.005
-0.003
-0.007
-0.001
-0.000
-0.000
-0.000
28
Table 3: Descriptive Statistics
Firms listed on the ASX with data available between 2000 and 2012
Panel A: Market Capitalisation>10m and BTM>1
Std.
Obs.
Mean
Min
p25 Median
Dev
Assets
1212
3.686
10.167
0.010
0.582
1.783
Liabilities
1212
1.971
8.987
0.000
0.154
0.670
BV
1212
1.715
2.672
0.010
0.351
0.945
P
1212
1.228
2.360
0.004
0.210
0.560
B/P
1212
1.731
1.004
1.000
1.186
1.436
Impairment type:
Goodwill
1212
-0.008
0.060
-1.243
0.000
0.000
Identifiable Intangibles
1212
-0.005
0.033
-0.505
0.000
0.000
Tangibles
1212
-0.009
0.083
-2.251
0.000
0.000
Total
1212
-0.022
0.115
-2.251
0.000
0.000
NPAT
1212
0.104
0.490
-1.787
-0.005
0.040
NPAT+Spec
1212
0.069
0.527
-4.015
-0.019
0.028
CFOPS
1212
0.176
0.406
-4.498
0.001
0.074
CFINV
1212
-0.145
0.716 -10.150
-0.190
-0.052
CF
1212
0.031
0.779
-9.961
-0.064
0.004
Impairment type:
Goodwill
68
-0.143
0.214
-1.243
-0.197
-0.043
Identifiable Intangibles
71
-0.084
0.108
-0.505
-0.111
-0.035
Tangibles
144
-0.076
0.231
-2.251
-0.056
-0.021
Total
197
-0.135
0.257
-2.251
-0.139
-0.038
Panel B: Market Capitalisation<10m
Assets
645
0.907
3.507
0.003
0.086
0.219
Liabilities
645
0.285
0.557
0.000
0.008
0.052
BV
645
0.622
3.351
0.002
0.061
0.132
P
645
0.405
2.753
0.001
0.030
0.064
B/P
645
2.650
3.109
1.000
1.362
1.823
Impairment type:
Goodwill
645
-0.002
0.018
-0.297
0.000
0.000
Identifiable Intangibles
645
-0.002
0.038
-0.952
0.000
0.000
Tangibles
645
-0.001
0.010
-0.190
0.000
0.000
Total
645
-0.005
0.043
-0.952
0.000
0.000
NPAT
645
-0.004
0.179
-0.764
-0.029
-0.006
NPAT+Spec
645
-0.016
0.194
-1.277
-0.041
-0.008
CFOPS
645
0.027
0.223
-0.530
-0.011
-0.002
CFINV
645
0.035
2.379 -28.401
-0.023
-0.004
CF
645
0.062
2.422 -27.571
-0.028
-0.006
Impairment type:
Goodwill
17
-0.064
0.092
-0.297
-0.071
-0.028
Identifiable Intangibles
17
-0.077
0.230
-0.952
-0.019
-0.005
Tangibles
26
-0.021
0.048
-0.190
-0.012
-0.004
Total
45
-0.065
0.153
-0.952
-0.053
-0.010
Where: All variables as previously defined
29
p75
Max
4.079
1.853
2.037
1.410
1.901
200.469
188.024
42.398
42.370
14.874
0.000
0.000
0.000
0.000
0.138
0.124
0.246
-0.006
0.127
0.000
0.000
0.000
0.000
11.621
11.621
3.266
12.642
12.858
-0.018
-0.015
-0.005
-0.011
-0.001
-0.000
-0.000
-0.000
0.690
0.273
0.364
0.160
2.892
38.660
4.280
38.108
38.000
57.979
0.000
0.000
0.000
0.000
0.007
0.006
0.019
0.000
0.008
0.000
0.000
0.000
0.000
1.808
1.808
4.225
34.542
35.291
-0.008
-0.001
-0.002
-0.004
-0.002
-0.000
-0.000
-0.000
Table 4: Descriptive Statistics
Firms listed on the ASX with data available between 2000 and 2012
Panel A: Pre-IFRS and BTM>1
Std.
Obs.
Mean
Min
p25 Median
Dev
Assets
720
3.073
5.061
0.011
0.353
1.376
Liabilities
720
1.264
2.007
0.000
0.069
0.544
BV
720
1.808
4.136
0.007
0.225
0.724
P
720
1.324
3.578
0.003
0.125
0.400
B/P
720
1.828
1.144
1.000
1.207
1.468
Impairment type:
Goodwill
720
-0.001
0.020
-0.469
0.000
0.000
Identifiable Intangibles
720
-0.002
0.019
-0.330
0.000
0.000
Tangibles
720
-0.005
0.085
-2.251
0.000
0.000
Total
720
-0.009
0.091
-2.251
0.000
0.000
NPAT
720
0.099
0.550
-1.787
-0.011
0.019
NPAT+Spec
720
0.068
0.595
-4.015
-0.026
0.014
CFOPS
720
0.156
0.361
-1.561
-0.003
0.049
CFINV
720
-0.075
2.316 -28.401
-0.152
-0.031
CF
720
0.080
2.363 -27.571
-0.054
0.001
Impairment type:
Goodwill
12
-0.087
0.129
-0.469
-0.104
-0.046
Identifiable Intangibles
15
-0.090
0.104
-0.330
-0.165
-0.053
Tangibles
27
-0.139
0.428
-2.251
-0.139
-0.016
Total
47
-0.131
0.336
-2.251
-0.155
-0.038
Panel B: Post-IFRS
Assets
1137
2.498
10.183
0.003
0.187
0.721
Liabilities
1137
1.462
9.207
0.000
0.035
0.239
BV
1137
1.036
1.833
0.002
0.122
0.405
P
1137
0.700
1.494
0.001
0.060
0.210
B/P
1137
2.191
2.447
1.000
1.237
1.587
Impairment type:
Goodwill
1137
-0.009
0.062
-1.243
0.000
0.000
Identifiable Intangibles
1137
-0.005
0.041
-0.952
0.000
0.000
Tangibles
1137
-0.007
0.053
-1.186
0.000
0.000
Total
1137
-0.021
0.100
-1.439
0.000
0.000
NPAT
1137
0.046
0.292
-0.984
-0.020
0.006
NPAT+Spec
1137
0.022
0.308
-1.904
-0.034
0.002
CFOPS
1137
0.104
0.358
-4.498
-0.008
0.014
CFINV
1137
-0.087
0.611 -10.150
-0.095
-0.017
CF
1137
0.017
0.661
-9.961
-0.041
-0.005
Impairment type:
Goodwill
73
-0.134
0.207
-1.243
-0.175
-0.042
Identifiable Intangibles
73
-0.081
0.145
-0.952
-0.093
-0.024
Tangibles
143
-0.054
0.141
-1.186
-0.041
-0.018
Total
195
-0.120
0.215
-1.439
-0.122
-0.033
Where: All variables as previously defined
30
p75
Max
3.636
1.689
1.884
1.310
1.987
43.961
19.049
42.398
42.370
11.886
0.000
0.000
0.000
0.000
0.112
0.110
0.208
-0.000
0.110
0.000
0.000
0.000
0.000
11.621
11.621
4.225
34.542
35.291
-0.019
-0.016
-0.007
-0.007
-0.002
-0.000
-0.000
-0.000
2.236
0.956
1.174
0.680
2.297
200.469
188.024
26.021
22.650
57.979
0.000
0.000
0.000
0.000
0.070
0.056
0.124
-0.001
0.046
0.000
0.000
0.000
0.000
7.164
7.164
3.266
12.642
12.858
-0.013
-0.005
-0.003
-0.007
-0.001
-0.000
-0.000
-0.000
Table 5:
All firms listed on the ASX with data available between 2000 and 2012
Panel A: Continuous Impairment
All
BTM>1
Firms
Coef.
t-stat.
Coef.
t-stat.
B/P
-0.005
-0.818
-0.009
-1.363
Yrs
-0.092
-3.326 ***
-0.028
-1.185
Earn
0.595 18.343 ***
0.000
0.104
CF
-0.003
-0.337
-0.001
-0.190
BHR
-0.090
-3.498 ***
0.006
0.778
AuditQual
-0.058
-2.136 *
-0.017
-0.975
ΔAuditEff
-0.013
-0.594
0.004
0.648
Constant
0.107
3.614 ***
0.019
1.242
Observations
1857
5839
Adjusted R2
0.152
0.000
F-Stat.
48.59
1.140
Panel B: Dichotomous Impairment
B/P
0.005
1.186
0.011
3.808 ***
Yrs
-0.001
-0.092
0.030
2.817 **
Earn
-0.011
-0.591
-0.000
-0.319
CF
0.002
0.474
0.002
0.765
BHR
-0.028
-1.867
-0.011
-3.107 **
AuditQual
0.101
6.463 ***
0.075
9.760 ***
ΔAuditEff
-0.005
-0.366
-0.001
-0.190
Constant
0.064
3.787 ***
0.034
4.960 ***
Observations
1857
5839
Adjusted R2
0.021
0.022
F-Stat.
6.762
20.09
Where: All variables as previously defined
* = p-value < 0.05; ** = p-value < 0.01, *** = p-value < 0.001
31
Table 6:
Analysis with Post-IFR indicator variable, excluding interactions All firms listed on the
ASX with data available between 2000 and 2012
Panel A: Continuous Impairment
All
BTM>1
Firms
Coef.
t-stat.
Coef.
t-stat.
B/P
-0.005
-0.769
-0.009
-1.320
Yrs
-0.094
-3.399 ***
-0.030
-1.256
Earn
0.594 18.320 ***
0.000
0.116
CF
-0.003
-0.347
-0.001
-0.187
BHR
-0.092
-3.565 ***
0.006
0.742
*
AuditQual
-0.061
-2.230
-0.019
-1.107
ΔAuditEff
-0.014
-0.638
0.004
0.582
IFRS
0.023
0.792
0.018
1.025
Constant
0.100
3.288 **
0.014
0.843
2
Adjusted R
0.152
0.000
F-Stat.
42.580
1.129
Observations
1857
5839
Panel B: Dichotomous Impairment
B/P
0.003
0.742
0.010
3.428 ***
Yrs
0.014
0.859
0.037
3.543 ***
Earn
-0.008
-0.433
-0.000
-0.436
CF
0.003
0.575
0.002
0.744
BHR
-0.015
-1.014
-0.010
-2.790 **
AuditQual
0.119
7.620 ***
0.085
11.103 ***
ΔAuditEff
0.001
0.067
0.001
0.425
IFRS
-0.123
-7.627 ***
-0.076
-9.830 ***
Constant
0.098
5.678 ***
0.057
7.912 ***
Adjusted R2
0.051
0.038
F-Stat.
13.370
29.950
Observations
1857
5839
Where: All variables as previously defined
* = p-value < 0.05; ** = p-value < 0.01, *** = p-value < 0.001
32
Table 7:
Analysis with Post-IFR indicator variable, including interactions All firms listed on the
ASX with data available between 2000 and 2012
Panel A: Continuous Impairment
All
BTM>1
Firms
Coef.
t-stat.
Coef.
t-stat.
B/P
-0.007
-0.948
-0.008
-1.069
Yrs
-0.130
-3.767 ***
-0.044
-1.449
Earn
0.668
19.501 ***
0.000
0.175
CF
-0.024
-0.894
-0.003
-0.324
BHR
-0.119
-3.552 ***
0.013
1.371
*
AuditQual
-0.086
-2.496
-0.028
-1.283
ΔAuditEff
-0.019
-0.557
0.027
1.523
IFRS
-0.125
-1.853
0.000
0.004
B/P * IFRS
0.004
0.209
-0.001
-0.038
YRS * IFRS
0.113
1.948
0.035
0.689
Earn * IFRS
-0.627
-6.066 ***
-0.023
-4.817 ***
CF * IFRS
0.024
0.852
0.003
0.247
BHR * IFRS
0.118
2.219 *
-0.023
-1.258
AuditQual * IFRS
0.083
1.469
0.026
0.729
ΔAuditEff * IFRS
0.015
0.334
-0.027
-1.371
Constant
0.139
4.025 ***
0.016
0.844
2
Adjusted R
0.167
0.004
F-Stat.
25.780
2.533
Observations
1857
5839
Panel B: Dichotomous Impairment
B/P
0.001
0.253
0.009
2.912 **
Yrs
0.019
0.990
0.064
4.693 ***
Earn
-0.009
-0.468
-0.000
-0.469
CF
0.027
1.728
0.003
0.639
BHR
-0.010
-0.505
-0.012
-2.843 **
AuditQual
0.167
8.486 ***
0.112
11.686 ***
ΔAuditEff
-0.020
-1.036
0.009
1.180
IFRS
-0.072
-1.869
-0.023
-1.514
B/P * IFRS
0.016
1.321
0.007
0.789
YRS * IFRS
-0.017
-0.531
-0.068
-2.985 **
Earn * IFRS
-0.026
-0.436
0.001
0.524
CF * IFRS
-0.027
-1.638
-0.002
-0.291
BHR * IFRS
-0.005
-0.166
0.006
0.747
***
AuditQual * IFRS
-0.129
-3.998
-0.073
-4.556 ***
ΔAuditEff * IFRS
0.037
1.402
-0.010
-1.160
***
Constant
0.078
3.979
0.038
4.649 ***
Adjusted R2
0.060
0.042
F-Stat.
8.829
18.150
Observations
1857
5839
Where: All variables as previously defined
* = p-value < 0.05; ** = p-value < 0.01, *** = p-value < 0.001
33