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Does the capitalization of development
costs affect the dispersion of forecasts
made by analysts?
Jeroen Pronk
11015977
25/06/2018 - Final version
Bsc Accountancy & Control
University of Amsterdam / Universiteit van Amsterdam
Supervisor: Dennis Jullens
Word count: 11177
2
Statement of Originality
This document is written by Jeroen Pronk who declares to take full responsibility
for the contents of this document. I declare that the text and the work presented
in this document are original and that no sources other than those mentioned in
the text and its references have been used in creating it. The Faculty of Economics
and Business is responsible solely for the supervision of completion of the work,
not for the contents.
3
Abstract
The introduction of IAS 38 requires entities to capitalize their development costs under certain
conditions. By capitalizing the costs of development, an entity is able to raise more assets and it can
spread the costs of development over multiple years. Standard setters in favor of IAS 38 claim that it
helps to reduce the amount of information asymmetry between entities and analysts. The new standard
also faces opposition that claim that it will lead to more earnings management by management of the
entities.
In this thesis I will perform a literature review to investigate whether capitalization of
development costs has a significant impact on the dispersion of analyst forecasts. I specifically
investigate the analyst forecast dispersion to see whether the financial statements become more useful
to its users. The conclusion in the end is that most of the literature finds the capitalization of
development costs disadvantageous for the users of financial statements and it would be more
beneficial to expense the costs.
Samenvatting
De introductie van IAS 38 leidt ertoe dat entiteiten hun onderzoeks- en ontwikkelingskosten
moeten kapitaliseren als deze aan bepaalde voorwaarden voldoen. Door deze kosten te kapitaliseren
kan een entiteit meer activa op zijn balans genereren en kan het de ontwikkelingskosten spreiden over
enkele jaren. De voorstanders van IAS 38 beweren dat het kapitaliseren het management van entiteiten
helpt om analisten beter te informeren over eventuele toekomstige ontwikkelingen en inkomsten.
Tegenstanders van de standaard beweren echter dat de standaard het management van entiteiten helpt
om de jaarrekeningen te manipuleren.
In deze scriptie zal ik aan de hand van een literatuuronderzoek proberen te onderzoeken of de
kapitalisatie van ontwikkelingskosten een significante invloed heeft op de spreiding van voorspellingen
van analisten. Ik doe specifiek onderzoek naar de spreiding van voorspellingen van analisten om te zien
of de jaarrekeningen meer bruikbaar worden of niet. De scriptie zal uiteindelijk laten zien dat het
kapitaliseren van ontwikkelingskosten vaak als nadelig wordt beschouwd in onderzoeken en dat het dus
voordeliger zou zijn om deze uitgaven als kosten te classificeren.
4
Table of contents 1. Introduction .................................................................................................................................... 5
2. Background ..................................................................................................................................... 7
2.1 What is an intangible asset? ..................................................................................................... 7
2.2 What is capitalization? ............................................................................................................. 9
2.3 What is earnings management? ............................................................................................. 11
2.4 Which conditions have to be met in order to capitalize research and development costs? ..... 13
3. Analysis ......................................................................................................................................... 15
3.1 How can entities send signals through capitalization? ............................................................ 15
3.2 What are the characteristics of entities that capitalize above-average? .................................. 16
3.3 What are the consequences for the quality of the financial statements? ................................ 19
3.4 Does the capitalization of development costs influence analysts’ forecast dispersion? ........... 21
4 Conclusion ..................................................................................................................................... 36
Reference list ........................................................................................................................................ 38
5
1. Introduction
In the search of a potential investment, an investor is likely to look for an entity that seems
reliable and profitable. While conducting his research on a certain entity, the investor is also likely to
analyse its financial statements. Large volatility in the profits of the entity over the years could have a
discouraging effect on his willingness to invest in the entity because the entity might seem unreliable.
A factor that could be the cause of this volatility in the profits are research and development
expenses (Lev & Zarowin, 1999). Companies that spend resources on research and development are
currently facing expenses of which they will potentially receive benefits in the future. This causes the
current profits to be relatively low compared to the future profits. This current situation leads to
different kinds of implications, including the underinvestment in research and development by
managers in some cases (Oswald & Zarowin, 2007).
The International Financial Reporting Standards therefore introduced a new accounting
standard in 2005 which could potentially help to avoid these problems. The new standard, called
International Accounting Standards 38 (IAS 38), requires entities to capitalize their development costs
under certain conditions. Entities are then able to amortize these costs over the years that follow. This
enables entities to match the expenses with the revenues from the developments that they are
conducting (Lev & Zarowin, 1999).
Capitalizing development costs is however subject to discussion by many standard setters.
Those in favor argue that there are multiple reasons why capitalization should be implemented in
accounting standards. It is stated that the capitalization has a positive influence on the performance of
the entity in Lev & Sougiannis (1996), or that capitalization is associated with greater stock price
informativeness (Osward & Zarowin, 2007). Standard setters opposed to the idea of capitalizing
development costs however state that capitalizing these costs provokes earnings management by
managers (Stewart, 2011), or that capitalization leads to overinvestment in research and development
(Seybert, 2010).
All these arguments implicate that the quality of the financial statements are affected by the
capitalization of development costs. In order to see whether the quality is really affected, it is possible to
look at the quality of the forecasts that are made based on these financial statements. If the quality of
the financial statements improves, it will benefit the forecasts that are made by analysts. If the quality
decreases, it works counterproductive for the forecasts. This leads us to the research question of this
6
thesis which is ‘Does the capitalization of development costs affect the dispersion of forecasts made by
analysts?’.
This thesis will have the following structure. In the first section there will be an explanation of
the various definitions that are used in the following sections of the thesis. The second section contains
the analysis. This analysis will first analyse the various advantages and disadvantages that the
capitalization of development costs has, and how it can be useful for the entity. Thereafter I will perform
a literature review to find a concrete answer to the research question. In the third section, I will
formulate this concrete answer and I will try to come to a conclusion about whether the capitalization of
development costs is beneficial for the dispersion in analysts’ forecasts.
7
2. Background
2.1 What is an intangible asset?
In order to understand what the capitalization
of intangible assets is, it is important to have a clear
understanding of what an intangible asset is. Intangible
assets are classified as a part of the assets on the
balance sheet. In order to explain what an intangible
asset is, it is therefore also important to have a clear
definition of an asset. IAS 38 states that in order to be
recognized as an asset, a resource should be able to
meet the following three different conditions.
The first condition that needs to be met by the resource is that it is identifiable. IAS 38 provides
a clear definition for the term identifiable; the resource should be able to be separated from the entity
itself, and should be able to be sold, transferred, licensed, rented or exchanged. Another condition for
identifiability is that the resource should arise from any contractual or legal rights that the entity owns,
this is regardless of whether these rights are transferable or separable. IAS 38 claims that identifiability
is important because the asset needs to be recognized in the financial statements on the balance sheet.
If an entity is unable to show what the exact extent of the asset is, it is unable to value it and the asset
can’t be recognized on the balance sheet.
The second condition of an asset is that the entity has control over the asset (IAS 38). This
means that the entity is a beneficiary of the potential benefits of the asset, and that it has the capability
to choose the destination of these benefits. The most important part however is that the entity itself
can withhold others from gaining access to the benefits. They are able to withhold others from that
access because the entity is most likely to hold the legal rights over the asset (IAS 38).
The third condition was already cited in the paragraph before and is that any future economic
benefits that arise from the resource should flow towards the entity that is controlling it (IAS 38). These
economic benefits could vary a lot, it could mean the actual revenues that are generated by the
resource, but it could also mean that the intellectual property that was generated can now be used by
the entity. If the three conditions are met, the resource will be recognized as an asset.
Figure 1. The three different conditions to be recognized as an asset.
In order for a resource to be recognized as an asset, it
needs to meet three different conditions. The resource
needs to be identifiable, it needs to be controlled by the
entity itself, and the future benefits needs to flow
towards the entity that is controlling it.
Assets
Identifiable ControllableRecipent of
future benefits
8
Now that there is a clear definition of an asset, it is important to show how the intangible assets
distinguish themselves from the other assets. IAS 38 (p.2) defines the intangible assets as
“an identifiable non-monetary asset without physical substance”
The term non-monetary means that the value of the asset can change over time in response to
economic conditions (Bragg, 2017). What this means is that the intangible asset is defined as an asset
without any physical substance of which the value can change over time. There are other definitions for
the term but most sources are in accordance with the term given by IAS 38. Stolowy, Lebas & Yuan
(2012, p.290) defines the term intangible assets as
“Long lived (long-term) assets that lack physical substance and their acquisition and continued
possession represent rights to future economic benefits.”
Whereas Marshall, McMane & Viele (2014, p.216) defines the term as
“Long lived assets that differ from property, plant, and equipment that have been purchased
outright or acquired under a capital lease – either because the asset is represented by a
contractual right or because the asset results from a purchase transaction but is not physically
identifiable.”
All these sources agree on the fact that the asset is not physically identifiable, and that the value
of the asset is not fixed. The reason that the value of the asset is not fixed is because the intangible
assets are rarely traded on any active and transparent markets. Because of the non-tradability, it is
difficult to make an estimation of the true value of the asset (Gu & Wang, 2005). Stolowy, Lebas & Yuan
(2012) states some of the different types of intangible assets that could be included on the balance
sheet of an entity. According to them the intangible assets on the balance could comprise of goodwill,
patents, franchises, licenses, trademarks, brands, copyrights, and if the conditions are met, capitalized
development costs.
9
2.2 What is capitalization?
When an entity incurs development costs, it has two options on how to account for these costs
in the financial statements, the prudence principle and the matching principle (Stolowy, Lebas & Yuan,
2012).
According to the prudence principle, the costs should be expensed in the period that they are
incurred in. The principle states that there is an uncertainty about whether the intangible assets will
generate any future economic benefits, and they should therefore be treated as expenses for the
current period (Stolowy, Lebas & Yuan, 2012). What this means is that the operating income of that
period is directly negatively affected because of the expenses (Lu & Sivaramakrishnan, 2017). Oswald
and Zarowin (2007) shows that the mandatory expensing of research and development costs could lead
to an underinvestment in research and development costs, this is also confirmed by a study conducted
by Anagnostopoulou (2010). Jackson (2008) shows that the corporate culture has increased its focus on
external reporting, and that management has to carry the responsibility if the financial statements do
not meet requirements or forecasts. This finding is consistent with the behavior of managers to
underinvest in research and development if they need to meet a benchmark. These are negative
consequences of the prudence principle and it would be beneficial for some entities if there would be an
alternative.
The matching principle is another way of accounting for the development costs (Stolowy, Lebas
& Yuan, 2012). Another definition that is often used for the matching principle is capitalization. Entities
are required to capitalize their development costs if the development meets certain conditions.
Capitalization means that the initial costs of development are recognized as an intangible asset, and are
then amortized over the period in which the entity derives any economic benefits from the
development (IAS 38).
The costs that are eligible for capitalization are all the costs that are directly attributable and
necessary to create, produce and prepare the asset to be able to operate within the entity. These are
not only the costs for materials, but could also be costs of employee benefits, fees to register legal rights
or costs for patents and licenses that are used. The entity is required to start recognizing these costs as
intangible assets from the moment that the development meets the recognition criteria that are
discussed in the next section of this thesis.
10
IAS 38 states that the amortization of the intangible asset starts when the asset is available for
usage. However what is amortization exactly? Marshall, McManus & Viele (2014, p.230) defines
amortization as
“The process of spreading the cost of an intangible asset over its useful life.”
This means that instead of expensing the costs over one year, the costs are spread over the total useful
life of the intangible asset (Lu & Sivaramakrishnan, 2017). The useful life of the intangible asset is the
amount of time that the intangible asset can perform its operating tasks in the way that it was intended.
The entity then also has a decision to make about the pattern that the amortization amount should
follow. The amortization amount should follow a pattern in which the future economic benefits that the
entity will receive are reflected the best. What this means is that if most of the economic benefits are
received in the beginning of its useful life, most of the amortization should also take place in the
beginning of its useful life (IAS 38). There are different methods on which the amortization pattern can
be based, the straight-line method, diminishing balance method and the unit of production method (IAS
38).
The intangible asset can then be amortized until there is no value anymore, or up until the
residual value (IAS 38). The residual value is the value that the intangible asset has when it is done
performing its operating tasks. An entity is however only allowed to assume that there is a residual
value when there is commitment by a party to purchase it, or when there is an active market on which
the value can clearly be determined and the intangible asset later can be sold.
11
2.3 What is earnings management?
The capitalization of intangible assets can be used to narrow the amount of information
asymmetry between entities and analysts (Mohd, 2005). However the capitalization could also be used
to manipulate the earnings in the financial statements. In the previous section I showed that the
development costs are spread over multiple years when they are capitalized. This means that there is a
difference in the amount of earnings that an entity reports when it either expenses or capitalizes its
development costs. The capitalization could therefore allow managers to manage their earnings that are
received over a period. Why would management do this?
The earnings of an entity are one of the most important items in the financial statements. It
shows how much value the entity was involved in value-creating activities that year. For an analyst it
might be the starting point to begin when analyzing a company because the earnings hold information
about the past but also about the future. It is therefore important that the quality of important figures
such as the earnings are guaranteed in the financial statements.
According to Stolowy, Lebas & Yuan (2012), the quality of earnings can be influenced in three
different ways. By making use of accounting methods, accountings estimates, and by the classification of
exceptional items in the income statement. These three methods together are known as accounts
manipulation. Stolowy, Lebas & Yuan (2012) shows that there are four forms of accounts manipulation.
Earnings management is one of the forms of accounts manipulation (Stolowy & Breton, 2004). The
reason why management would participate in earnings-management is because they don’t want the
earnings to be volatile over the years. The share
price of an entity can be based on the future
earnings of an entity, which means that if the
earnings of the entity are volatile over the years,
the share price will be as well (Stolowy, Lebas &
Yuan, 2012). A stock that has an uncertain price
with a lot of volatility will simply attract less
investors because of the uncertainty. Analysts and
investors look for an entity which has a steady
income every year and which they can trust.
Accounts manipulation
Earnings management
Earnings smoothing
Big bath accounting
Creative accounting
Figure 2. The four forms of accounts manipulation.
Stolowy & Breton (2004) describes four different forms of
accounts manipulation. The two forms that are relevant to this
thesis are earnings management and earnings smoothing.
These two forms allow the management of an entity to reduce
the variance in their earnings over the years.
12
Another form of accounts manipulation is income smoothing, which can also be referred to as
earnings smoothing (Stolowy & Breton, 2004). Stolowy, Lebas & Yuan (2012) defines income smoothing
as a way of reducing the volatility in the earnings that are reported over several years. It’s objective is to
shift the date on which some costs or revenues are recognized, this is very similar to what is done by
amortizing the costs of development. Therefore the capitalization and amortization of development
costs can be referred to as both earnings management as earnings smoothing.
Pandit, Wasley & Zach (2011) shows that research and development is positively associated with
the volatility of its earnings. Graham, Harvey & Rajgopal (2005) shows that when management of the
entity smoothens the earnings, it benefits the entity. Graham, Harvey and Rajgopal (2005) also shows
that management of an entity prefers to smooth earnings, even if it is at the expense of value of the
entity. They find that 92,3% of the high-tech management in their study prefers smoothening of
earnings. This is also coherent with a study performed by Jackson (2008) which shows that corporate
culture over the years has increased its focus on external reporting. What these four studies imply is
that the smoothening of earnings is beneficial for the entities. Based on these studies, it is therefore
likely to say that management will use the capitalization of development costs to smoothen their
earnings if they have the possibility to.
This section discussed how earnings management works and the reason management could
have to participate in this kind of behavior, the consequences that earnings management and earnings
smoothing can cause are later discussed in this thesis.
13
2.4 Which conditions have to be met in order to capitalize development costs?
In the previous section we saw that entities use the capitalization of development costs to
practice earnings management. The standard setters of IAS 38 have tried to find a way to oppose these
practices and have therefore set certain criteria that need to be met in order to capitalize.
This thesis is focused on costs that are incurred while performing research and development. It
would therefore be irrelevant to look into the capitalization criteria of other forms of intangible assets.
In most studies research and development is seen as one process, but they fail to recognize that the two
activities actually differ in many ways. When analyzing intangible assets, it is also important to make a
distinction between the research phase and the development phase.
According to Goldense (2014), research means that you are either conducting basic research or
applied research. Basic research is targeted on a broad market or consumer need that needs to be
fulfilled and is focused on whether something would work to fulfil that need. Applied research focuses
on a known problem or opportunity in which certain improvements could be made. What this shows is
that during the research phase, only ideas are generated. This is important to understand because it has
effect on how the research phase is treated in IAS 38. According to IAS 38, an entity is not able to show
that the intangible asset is already able to generate potential benefits for the entity during the research
phase. Therefore the costs that are incurred during the research phase should not be capitalized. All
costs that are incurred will be expensed and will be shown on the income statement.
According to Goldense (2014), development can also be divided into two different kinds of
development. There is advanced development which focuses on feasible solutions to incorporate into
products or services. Or there is product development which is focused on creating products for the
marketplace. What this shows is that during the development phase, there is an actual development of
a product or idea. Since the purpose and extent of the development now can be identified, the entity is
able to capitalize intangible assets during this phase.
In order to capitalize costs that were incurred during the development phase, the intangible
asset must meet six set conditions by IAS 38. According to Hoegh-Krohn & Knivsfla (2000), the quality of
the financial statements is reduced if any doubtful or non-existing assets are recorded. According to
them the recognition of intangible assets is based on a trade-off between how the relevance and
reliability of the capitalization affects the informativeness of the financial statements. The conditions are
therefore set to ensure that the intangible assets that are recognized are relevant and reliable.
14
According to IAS 38, an entity needs to demonstrate
1. That it has the technical feasibility to complete the intangible asset so it is able to later use it or
sell it
2. That it has the intention to complete the intangible asset and use or sell it
3. That it has the ability to use or sell the intangible asset
4. How the intangible asset will generate probable future economic benefits. Among other things,
the entity can demonstrate the existence of a market for the output of the intangible asset or the
intangible asset itself or, it is to be used internally, the usefulness of the intangible asset
5. That it has the availability of adequate technical, financial and other resources to complete the
development and to use or sell the intangible asset
6. That it has the ability to measure reliably the expenditure attributable to the intangible asset
during its development
Several studies have shown that the future economic benefits that are derived from intangible
assets are more uncertain than the future economic benefits derived from tangible assets, which is why
there are more strict criteria (Kothari, Laguerre & Leone 2002; Amir, Guan & Livne, 2007). There are
however various ways in which entities can meet these requirements. According to IAS 38 the
availability of resources to complete, use and obtain the benefits can be demonstrated by writing a
business plan that demonstrates the technical, financial and other resources that are necessary to
obtain these resources.
15
3. Analysis
3.1 How can entities send signals through capitalization?
The problem that investors face when analyzing entities is that they don’t have the same
amount of information about the entity as the management of the entity has. Management might
withhold important information over organizational problems, as it wants to present itself in the best
way possible (Balakrishnan & Koza, 1993). The difference in the amount of information that is available
to both parties is called ‘information asymmetry’. Investors are aware of this problem and will try to find
ways to reduce this problem (Ghosh & Olsen, 2009). It is therefore important for the management of an
entity to find a way to send trustworthy positive signals about the financial condition of the entity to
investors. By sending these signals it tries to take a part of the uncertainty away and convince investors
to invest in the company, this is called signaling (Ghosh & Olsen, 2009).
Signaling can be done in various ways, it can be done by issuing or raising dividend that is paid to
the shareholders, it can also be done by repurchasing stocks (Ambarish, John & Williams, 1987). Some
studies however proof that by capitalizing development costs, management is also able to send signals
to investors and analysts (Aboody & Lev, 1998; Mohd, 2005).
Management of an entity is able to send signals through research and development costs via
two different ways. The first one is that by capitalizing development costs, the entity does not have to
expense the costs in the current period. This means that through capitalization of development costs
the profit of the current period is able to rise (Lu & Sivaramakrishnan, 2017). What this means for
signaling is that it can be either used to boost profits, or reduce the amount of losses. An, Gao & Lu
(2014) proved that managers use the capitalization of development especially to avoid losses.
The second way that the entity is able to send signals to the investors is by the capitalization
itself. By capitalizing the development costs, the entity shows that the development they are working on
a development that has technological and economic feasibility, as can be seen by the rules that were set
by IAS 38 (Aboody & Lev, 1998). It is a way for management to inform analysts and investors about the
progress that is being made by the development program (Aboody & Lev, 1998). Studies performed by
McNichols & O’Brien (1997), and Francis & Willis (2001) show that the analysts select entities based on
the expectations of the entity’s future performance. Matolscy & Wyatt (2006) and Peek (2005) therefore
prove that analyst following does increase when an entity reports more intangible assets because of the
potential future benefits that could originate from the intangible assets.
16
3.2 What are the characteristics of entities that capitalize above-average?
In the previous section I explained how capitalization can be used to signal information to
analysts and potential investors. It is however important to realize that some entities have the habit of
capitalizing more intangible assets than other entities. If an analyst would not be aware of these factors
that influence the capitalization decision, it might interpret the financial statements of an entity wrong.
Aboody & Lev (1998) shows that there are five attributes an entity can hold that has a significant impact
on the decision to capitalize. Three out of these five attributes are later confirmed to be significant in
other studies conducted by Cazavan-Jeny, JeanJean & Joos (2011) and Oswald & Zarowin (2007), and will
therefore be discussed in the following section.
Entity size
When analyzing different entities, it is important to realize that the size of the entity in
comparison to other entities in the market has influence on the amount of development costs that the
entity will capitalize.
Several studies have found that the amount of development that is capitalized is negatively
correlated with the actual size of the entity (An, Gao & Lu, 2014; Oswald & Zarowin, 2007; Cazavan-Jeny,
JeanJean & Joos, 2011; Aboody & Lev, 1998). This results implies that a smaller entity is more likely to
capitalize a higher percentage of their development costs compared to a larger entity. This is consistent
with a study that was performed by Skinner (1993). This study showed that large entities are more likely
to choose accounting procedures that decrease the income for that period. This would imply that a
larger entity would not try to meet the requirements of capitalization as soon as possible.
According to Aboody & Lev (1998), this is the opposite of what you would expect from the
smaller entities in the first place. They expect that the developments that young and small companies
are conducting have not reached the technological feasibility stage yet that is required for the
capitalization of development costs. Since there is also a discussion about whether the capitalization
affects the quality of the earnings, you could also expect that young companies would want to establish
a strong reporting credibility at the beginning of their operations and would therefore not capitalize any
development costs (Aboody & Lev, 1998).
However the opposite is claimed by multiple studies. The lead cause that relatively smaller
entities capitalize a higher percentage of their development costs is the actual sort of development that
is conducted itself. Gu & Wang (2005) shows that the technology portfolios of a large and a small entity
17
are different on average. Aboody & Lev (1998) shows that the smaller entities in an industry are more
likely to spend their research and development on innovative technologies that innovate the current
market. Larger entities are more likely to spend a large part of their development costs on basic
research, maintenance, and upgrades of their own products. Basic research and maintenance is not
eligible for capitalization which means that it is expensed (Aboody & Lev, 1998; Cazavan-Jeny, JeanJean
& Joos, 2011). The development that is conducted by the smaller entities is the opposite of this. Oswald
(2007) calls these entities the ‘early life cycle’ entities because they are trying to break into the market
by innovating in a way that the larger entities are not doing. Since they want to innovate the market and
are not looking to make large losses in the beginning of their operations, they are eager to meet the
requirements for capitalization (Aboody & Lev, 1998; Cazavan-Jeny, JeanJean & Joos, 2011).
Profitability
A study performed by Aboody and Lev (1998) shows that entities that make a profit would avoid
to capitalize their development costs. Studies performed by An, Gao & Lu (2014), and Oswald & Zarowin
(2007) confirm that leverage has a significant negative impact on development capitalization. The
reason that leverage has a negative impact on development capitalization can be explained fairly simple.
As was shown in the previous section, management would like to signal to analysts that the entity is
doing well. According to a study performed by Aboody and Lev (1998), capitalization would have a
negative effect on the willingness of an analyst to invest in the entity. According to them, many analysts
still believe that the capitalization of development costs has a negative impact on the quality of the
earnings that are reported. This means that if an entity is doing well and is actually making profits, it
doesn’t want to send a negative signal to the analysts, therefore they will try to not capitalize since they
do not want to affect the quality of the earnings that they report (Aboody & Lev, 1998)
Since profits and capitalization are negatively correlated, it could mean that losses and
capitalization are positively related. Several studies (DeFond & Jiambalvo, 1994; Rosner, 2003) show that
troubled companies have a large motive to practice earnings management in order to keep up a positive
image for external analysts. A study performed by Stewart (2011) shows that it is correct that the
amount of capitalization of intangible assets increases sharply in the years leading up to declaring
bankruptcy. This shows that if an entity is financially troubled, they prefer to capitalize a higher
percentage of their intangible assets instead of expensing it. Stewart (2011) shows that management of
these entities have different incentives to show this kind of behavior. Management of the entities would
want to avoid to report any net income losses because of the potential signal it can send to the analysts.
18
This is also confirmed by Oswald (2007), which shows that management likes to use the capitalization to
spread costs over future years in order to reduce the amount of losses they declare.
Leverage
Another characteristic that has influence on whether entities capitalize development costs or
not is the relative amount of leverage an entity has compared to its equity. A higher percentage of debt
would lead to more capitalization of development costs.
The first reason are the financial ratios that an entity reports at the end of the year. The studies
that were used use different ratios but the results are very similar. Aboody & Lev (1998) calculates it by
dividing long-term debt by the book value of equity (minus software asset). Other studies like Stewart
(2011) study the leverage ratio which is the total debt divided by total assets. The leverage ratio is what
can be influenced by the management of an entity. A recent study performed by Chalamandaris &
Vlachogiannakis (2018) shows that the financial ratios are used by CDS traders in the decision-making
process. By capitalizing development costs, the amount of assets go up, and the amount of leverage
could potentially go down since income rises as well. The outcome of this is that the leverage ratio will
go down, making the entity more attractive for investors since it seems to be more capable to pay off its
debts (Cazavan-Jeny, JeanJean & Joos, 2011).
Another reason why managers might prefer to capitalize development costs are the debt
covenants (Wang, Yang, & Zong, 2009). A debt covenant is a restriction that a lender might put on a
lending agreement. Most of the times this restricts the amount of debt a lender can attract until he has
paid the loan back. Stewart (2011) shows that highly leveraged entities could be close to the debt
restrictions imposed on them. When these entities would capitalize their development costs, they would
be able to lower their leverage ratios and therefore attract more debt.
What this shows is that young entities that make losses and have a high percentage of leverage
are more willing to capitalize in comparison to other entities. This does suggest in a way that
capitalization is used by entities to manage their earnings so the financial statements might show a
better image than is actually true. Whether this is true and what the implications of that capitalization
are, is discussed in the following sections.
19
3.3 What are the consequences for the quality of the financial statements?
Although income smoothing and earnings management has been widely documented for
decades, its effect on earnings informativeness is unknown. Income smoothing could improve earnings
informativeness if managers use it to communicate their assessment of future earnings. On the other
hand, income smoothing makes the financial statements less trustworthy if management wants to
intentionally distort the truthful earnings.
It is therefore in the best interest of standard setters and analysts that the quality of these
earnings are guaranteed. Stolowy, Lebas & Yuan (2012) shows that the quality of earnings can be
influenced by three different factors: accountings methods, accountings estimates and judgements, and
the classification of exceptional items in the income statement. These three factors are known together
as accounts manipulation. Stolowy, Lebas & Yuan (2012) shows that account manipulation can have four
different forms, of which earnings management and earnings smoothing are two. The book shows that
these two forms can be used by management to inform investors about their assessment of future
earnings. They can however also be used to generate noise because management wants to intentionally
improve the earnings. Stolowy, Lebas & Yuan (2012) shows that the capitalization is primarily used to
generate a negative effect on the quality of earnings, but what do other researchers say about the
quality of the earnings?
A study performed by Tucker & Zarowin (2006) investigates whether earnings management
improves the informativeness of current earnings. By analyzing entities between 1988 and 2000 they
find interesting results. The first result from the study is that they find that entities with better
performances do indeed smooth income to a larger degree. Furthermore they show that income
smoothing enhances the FERC that they are investigating. This supports the hypothesis that income
smoothing improves the informativeness of past and current earnings about future earnings. Therefore,
Tucker & Zarowin (2006) are supportive of the capitalization of development costs in the financial
statements. This statement is supported by several other studies as well. A study performed by Aboody
& Lev (1998) did not show that the capitalization of software development significantly increases the
informativeness, but it did show that there is no evidence to think that it would reduce the earnings
quality. An, Gao & Lu (2014) showed results from studies that the development cost capitalization
enhanced the earnings information that was reported by the entities, and is therefore positive about the
usage of capitalization for development. All these studies therefore indicate that the informativeness of
current earnings improves if the development costs are capitalized.
20
Oswald and Zarowin performed a study in 2007 on how the capitalization of development costs
could affect the informativeness of earnings and stock prices. This study is performed in the UK and uses
data from the 1990-1999. They were able to use data from the 1990s because capitalization was
optional according to UK GAAP at that time. What this study showed is that capitalization in fact
increases the informativeness of earnings, but also the increases the informativeness of stock prices.
The increase in informativeness of stock prices is a consequence of capitalization that other studies
show as well. Chen, Gavious & Lev (2017) also showed that the stock informativeness increases. It
showed that due to the capitalization, the confidence of the analysts in the entity rises, and therefore
the stock price rises as well.
So far this section showed that the capitalization of development costs is associated with more
current earnings informativeness, and that current stock prices are likely to rise as well. This seems
advantageous to the users of the financial statements, but what does the capitalization say about the
future earnings of the entity?
Cazavan-Jeny, JeanJean & Joos (2011) performed a study based on French entities to examine
whether the capitalization of development costs has a correlation with certain future performance.
What they found is that there is in fact a correlation, but this is negative one. The entities that would
capitalize would show a decline in performance in the years that followed. What is even more surprising
however is that entities that would expense and capitalize their development costs would show an even
harder decline in performance. What this would imply is that management of the entities are not able to
truthfully convey information about the future performance of the entity. This is quite contradicting to
the supporting studies that we saw so far, however Cazavan-Jeny, JeanJean & Joos (2011) is not the only
study to show these kind of results. An, Gao & Lu (2014) states that the capitalization of development
costs is related to lower returns in future years, which confirms the results of Cazavan-Jeny, JeanJean &
Joos (2011). Stewart (2011) performed a study on Australian entitie that were listed on the Australian
Stock Exchange between 1989 and 2004 and proved that the capitalization of development costs is
associated with the failure rate of an entity. All these studies therefore imply that the capitalization of
development costs is used for earnings management and will eventually lead to poor future
performance of the entity.
21
3.4 Does the capitalization of development costs influence analysts’ forecast dispersion?
The analysis section so far showed; how capitalization can be used to signal information to
investors, what the characteristics are of entities that capitalize relatively more development costs, and
what the possible consequences could be for the quality of the financial statements. The section so far
did however not provide significant prove that is able to answer our research question. This is why I
decided that in order to answer that research question, a literature review on the direct effect on
forecast dispersion was necessary.
At first I will analyze studies that provide evidence that is in favor of the capitalization of
development costs, after that I will analyze studies that provide evidence that opposes the capitalization
of development costs. The conclusion of this literature review is discussed in the fourth section.
Figure 3. The literature review. This figure shows the different studies that are analysed in the literature review. The studies are arranged in two groups, these two groups indicate whether the study was in favour of the capitalization of development costs or whether it was opposed to the capitalization of development costs.
In favor of capitalization
Matolscy & Wyatt (2006)
Anagnostopoulou (2010)
Opposes capitalization
Dinh, Eierle, Shultze & Steeger
(2015)
André, Dionysiou & Tsalavoutas
(2018)
Gu & Wang (2005)
Barron, Byard, Kile & Riedl
(2002)
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In favor of capitalization
Capitalized intangibles and financial analysts - Matolscy & Wyatt (2006)
Hypothesis development
This study is performed in 2006 by Zoltan Matolscy and Anne Wyatt. The study examines
whether the capitalization of intangible assets leads to a higher analyst following, lower dispersion of
analysts’ earnings forecasts and more accurate earnings forecasts.
The study starts building its hypothesis by analyzing similar studies. It shows evidence that
analyst following is higher for firms with higher unrecognized intangible assets, and it shows that
analysts look for entities that provide good performance prospects. According to Matolscy & Wyatt,
these two statements taken together indicate that analysts prefer to follow entities with a high amount
of intangibles because they expect the future performance of these entities to be better. The study then
finds complementary evidence which shows that in some cases, it is in fact true that a high amount of
intangibles can in fact predict better future entity performance. Therefore analysts’ expectations should
be higher for firms that capitalize relatively more intangible assets, the first hypothesis is therefore
Capitalization of intangible assets relative to total underlying intangible assets is positively
related to analyst following.
Evidence that was provided by an Australian study (Wyatt, 2005) specifically suggests that
relatively higher intangible assets lead to more predictable earnings. This is the opposite of what an US
study performed by Gu & Wang (2003) states, this study found a negative correlation between the
forecast errors made by analysts, and the amount of underlying intangibles. This means that in this US
study, higher intangibles would lead to less predictable earnings. The second hypothesis of this study is
therefore
Capitalization of intangible assets relative to total underlying intangible assets is associated with
lower absolute analyst earnings forecast error and lower earnings forecast dispersion.
Sample and method
The sample that was used consisted of entities that were enlisted on the Barclays Australasia
Consensus Earnings Profile (BARCEP) file between 1990 and 1997. These entities were scattered across
twenty-three industries which makes the sample versatile although it were only Australian and Asian
entities. The Australian GAAP allowed the capitalization of development costs long before 2005.
23
Australia is therefore a well-known source when it comes to research on the capitalization of
development costs since they were already allowing it before IAS 38.
The dependent variable that is used to test the first hypothesis is FOLLOW. This is the average
number of analysts following the firm i in fiscal year t. The first of the two dependent variables that were
used to test the second hypothesis was LG(DISP/TA). This is the natural logarithm of the amount of
analyst earnings forecast dispersion divided by the total amount of assets. The second dependent
variable was the absolute forecast error, noted as LG(|FE|/TA). This is the natural logarithm of the
absolute value of the earnings minus the mean forecast of earnings, divided by the total assets of the
entity. In order to be consistent with previous studies, the forecasts error and the forecast dispersion
were deflated in order to facilitate comparisons across firms.
All these three dependent variables were later used in an equation to estimate the dependent
variable INTANG/MVAD. INTANG/MVAD is the amount of capitalized intangible assets divided by
‘market value added’. Market value added is the outcome of the equation: market value equity – (Book
value of equity – intangible assets). By making use of previous studies (Alford and Berger 1999, Demers
2002), several control variables were used in the equations to make sure the intended results were
achieved. The three equations were all computed by using ordinary least square (OLS) estimators. When
the estimates were made, an endogeneity problem arose. To evaluate how much impact this
endogeneity problem would cause, the study decided to also conduct two stage least squares (2SLS)
estimates.
Results
The results for the first hypothesis were significant in the OLS equation but not in the 2SLS
equation. This shows that there is a positive association between analyst following and the amount of
capitalized intangibles, although it might not be a strong one. The results for the second hypothesis are
similar to the first one. The OLS regressions show that there is a significant relationship between a lower
earnings forecast dispersion and earnings forecast error, and the amount of reported intangible assets.
This result is however not significant in the 2SLS equation. What this shows is that there is a
relationship, but it is not strong enough to show significance on both the tests. The study therefore
concludes that the capitalization of development costs could lead to lower forecast error and lower
forecast dispersion, but it is unclear how strong that influence is.
24
Does the capitalization of development costs improve analyst forecast accuracy – Anagnostopoulou
(2010)
Hypothesis development
This is a study performed by Seraina Anagnostopoulou in 2010. By focusing on the UK market
this study provides a different insight than other studies that were analyzed.
The study develops its hypothesis by showing evidence that was generated by older studies. It
starts by showing evidence from Amir, Guan & Livne (2007) and Gu & Wang (2005). These studies
demonstrate that forecasting errors are greater for US analysts when there is a significant investment in
research and development costs. Lev (2001) shows that this is mainly due to the uncertainty of the
economic future benefits.
These studies are all performed in the US market, this study therefore tries to examine whether
the capitalization of intangible assets has influence on the forecasts made by analysts in the UK market.
This market is interesting because the accounting rules already allowed the capitalization of
development costs under certain conditions before the introduction of IAS 38 in 2005.
The study then argues that capitalization is also positive because entities are able to provide
users of the financial statements with information of the developments they are currently working on
(Oswald & Zarowin, 2007). The hypothesis of the study therefore is
There is a positive association between R&D capitalization and reduction in forecast inaccuracy
Research method
The data that is used is derived from all UK non-financial entities that were listed on the London
Stock Exchange and the Alternative Investment Market from the years 1990 to 2003. A total of 5.401
firm-year observations were derived from the data. Out of these 5.401 firm-years, 873 firm-years
involved entities that capitalized development costs during that year, which is roughly 16,16%. To test
whether the capitalization of development costs has influence on forecasting errors, a regression
analysis is performed of which ‘Signed/Unsigned Errors or Revisions’ is the dependent variable. Several
control variables were tested for significance in the study and then added to the regression analysis to
ensure that the intended result was achieved.
25
Results
Important to realize is that the study makes a distinction between signed and unsigned forecasting
errors of analysts. The study finds that the expensing of research and development is significantly
related to signed forecasting errors and accuracy. What this shows is that if more development costs are
expensed, the accuracy of the forecasts made by the analysts goes down. In contrast to this finding, they
find that when the development costs are capitalized, it does not significantly influence the signed
forecasting errors or accuracy. This would mean that it is more beneficial to capitalize development
costs for the forecasts that are made by analysts. When the study analyzes whether the two methods
affect the unsigned forecasting errors, no significance was found.
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Opposing the capitalization
Research and development, uncertainty and analysts’ forecasts: the case of IAS 38 – Dinh, Eierle,
Schultze & Steeger (2015)
Hypothesis development
This study was conducted in 2015 by Tami Dinh, Brigitte Eierle, Wolfgang Schultze and Leif
Steeger. This study is one of the newer studies that was analyzed and is therefore based on several
other studies that were used in this section.
The study starts to develop its hypothesis by analyzing previous studies. It shows that prior
research finds that analysts have strong incentives to provide investors with correct information about
future earnings (Barron et al, 2002; Amir, Guan & Livne, 2003; Gu & Wang 2005). The study shows that
previous studies have found results that indicate that capitalization of development costs improves the
forecasting accuracy (Peek, 2005), but that there were also studies that found that capitalization of
development costs decreases the forecasting accuracy (Gu & Wang 2005).
Several reasons are given for these contradicting results. Gu & Wang (2005) shows that
intangible assets lead to more complex information, of which Aboody & Lev (1998) claims that the
intangible assets will only cause more noise in the analysts’ earnings forecasts. Wyatt (2005) shows that
the reason for this complexity is mainly due to the uncertainty of the future benefits from these
intangible assets. Matolscy & Wyatt (2006) then however also show that the capitalization is only
positive and can be used to signal private information of future benefits to the market.
Given that all these studies provide contracting information, the study therefore decides to
analyze whether the capitalization of development costs does have influence on the accuracy of
forecasts by analysts. The first two hypothesis therefore are
Capitalized development expenditures under IAS 38 are not associated with individual analysts’
forecast errors.
and
Capitalized development expenditures under IAS 38 are not associated with dispersion of
analysts’ forecasts.
27
These two hypothesis will refer to the entire sample, the study however also wants to analyze
whether there are certain conditions in which the capitalization of development costs may be more
favorable for the forecasts made by analysts. The two additional hypothesis that are examined therefore
are
For firms with high underlying environmental uncertainty, capitalized development expenditures
under IAS 38 are negatively associated with analysts’ forecast errors.
and
For firms with high underlying environmental uncertainty, capitalized development expenditures
under IAS 38 are negatively associated with analysts’ forecast dispersion.
Sample and method
The sample that was used by this study were 150 of the largest entities that were listed on the
German Stock Exchange during the period of 2000-2007. The condition that the entities had to meet
was that the entities had to use IFRS during one or several of the years that were researched. The period
of 2000-2007 was taken on purpose to avoid any effects that could be caused by the financial crisis that
started in 2008.
Two regression equations were generated of which the forecasting errors (BFE) and analysts’
forecast dispersion (SDF) were the dependent variables. The main variable that could influence the
dependent variables was the annual amount of capitalized development costs (DCAP). All the other
variables in the equation were meant as control variables in order to obtain the result that was
intended.
Results
The first results showed that there are only a few variables that have a significant influence on
the amount of development costs that are capitalized by an entity. A firm will capitalize more
development costs when it has a higher leverage, it is in a mature state, when it has previously
capitalized development costs, and when it has not adopted IFRS for a while. After these results were
obtained, the researchers were able to analyze the association between the capitalization of
development costs with the forecasting errors and forecasting dispersion.
The results show that the relationship between the forecasting errors and the capitalization of
development costs is highly significant. The relationship between the forecasting dispersion and
28
capitalization of development costs also proved to be significant. What this implies is that the
capitalization of development costs certainly leads to more forecasting errors, and it also leads to more
dispersion in the forecasts made by analysts.
After that, the third and fourth hypothesis were tested to see how much the impact of
environmental uncertainty is on the association between the capitalization of development costs and
forecasts accuracy and dispersion. To do this, they used stock price volatility. The results were consistent
with their expectations, both the forecast errors and forecast dispersion proved to significantly increase
with a higher stock volatility. This meant that the forecast errors and dispersion were in fact positively
associated with environmental uncertainty. What the results did show was when the uncertainty
became high, the negative effect on forecast accuracy and dispersion was reduced. Which shows that if
the uncertainty reaches a certain level, forecast errors and dispersion is less affected.
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Mandated disclosures under IAS 36 impairment of assets and IAS 38 intangible assets: value relevance
and impact on analysts’ forecasts – André, Dionysiou & Tsalavoutas (2018)
Hypothesis development
This study is performed in 2018 by Paul André, Dionysia Dionysiou and Ioanis Tsalavoutas. Since
it is published in 2018, it is the most recent study that is used in this literature review.
While developing the hypothesis, the study starts by focusing on the relevancy of items in the
financial statement. According to them, the item is only relevant if it capable of influencing any potential
decisions made by the financial statement users. The item should not only be relevant but it should also
be faithfully represented in the books so the users are able to make decisions based on them. A
structured framework with set accounting rules like IFRS enables a financial statement users to do this
since all the entities have to disclose their financial statements in the same way. A change in these
frameworks could therefore also potentially influence the decisions and the forecasts that are made by
analysts.
By introducing IAS 38, the IFRS introduced a set of rules concerning the reporting of intangible
assets. Intangible assets are assets without physical substance and are not traded on an any active
markets. The valuation of the intangible assets could therefore lead to problems, and could influence
decisions and forecasts made by analysts. This study therefore wants to analyze whether the disclosure
of intangible assets is informative for forecasting earnings and valuation purposes. Therefore the
following hypothesis are formed
IFRS mandatory disclosure levels (for each individual standard as well as in aggregate) are value
relevant
and
IFRS mandatory disclosure levels (for each individual standard as well as in aggregate) increase
analysts’ forecast accuracy
and
IFRS mandatory disclosure levels (for each individual standard as well as in aggregate) reduce
analysts’ forecast dispersion
The study also analyzes the influence of the introduction of IAS 36, since this is not relevant to this thesis
I have decided to not include it.
30
Sample and method
The data that was used in this study was first derived from non-financial entities that were part
of the S&P Europe 350 index. In addition, more data was added from other large European firms in
order to increase the sample size. Any firms that did not apply either IAS 36 or IAS 38 in their financial
statements were excluded from the sample. The total sample at the end included 373 different
companies, of which the data from the reporting year 2010/2011 was derived.
The model of Ohlson (1995) was used to provide a framework for the analysis that was
performed. The study did include other independent variables to control for potential influences that
Ohlson (1995) oversaw. In the end, the study had three different regression models to test the three
hypothesis.
Results
The first results concerned the level of compliance of the standards that the entities had. A high
variation in the results was observed which meant that financial statements all had different levels of
compliance to the IAS 38 standards. This meant that the users of the financial statements would also
receive different amounts of information from the financial statements. The results for IAS 38
specifically showed that a large percentage of the entities did not share all the information that was
relevant for future earnings forecasts. This was mainly due to the fact that they did not share
information about the useful lives of the intangible assets or the amortization rates.
The most important result from the study was that IAS 36 did improve the accuracy of analysts’
forecasts and that it decreased the amount of forecast dispersion of analysts. The results of IAS 38
however were not significant. This means that IAS 38 does neither increase of decrease the accuracy of
analysts’ forecasts and does not affect the forecast dispersion either.
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Intangible Assets, Information Complexity, and Analysts’ Earnings Forecasts - Gu & Wang (2005)
Hypothesis development
This is a study performed in 2005 by Feng Gu and Weimin Wang. The study focuses on the
effects of the capitalization of intangible assets on the forecasts made by analysts.
While developing the hypothesis, the study starts by focusing on the effect of information
complexity on the value of intangible assets. According to them, there are greater errors in the analysts’
earnings forecasts if a firm is associated with more complex information. Intangibles are associated with
more complex information because of the higher uncertainty, and because they are rarely traded on
active markets. They would therefore lead to greater errors in the analysts’ earnings forecasts.
According to Mowery (1983) and Cohen & Levinthal (1989), an entity will invest in intangible
assets for two reasons: to develop new knowledge, and to learn and benefit from the research of others.
An entity needs to keep up with the other firms in its industry and therefore a certain level of research
and development is necessary. However some firms also plan to innovate even further and work on
pioneering developments. These pioneering developments are higher in risk, are non-tradeable, and the
value is likely to not be estimated reliably. They also represent the costs that other entities in the
industry are not spending. The first hypothesis that the study forms is therefore
Analysts’ forecasts errors with respect to future earnings are greater for firms that have higher
intangible intensity than industry peers.
The study then claims that the information complexity increases with the diversity of the firm’s
technology. The analysts are constrained by the amount of time and expertise that they have, so to
analyze different kinds of technologies will increase the difficulty of the analysis of the entity. The
second hypothesis therefore is
There is a positive association between analysts’ forecast errors and the diversity of the firm’s
technology investment portfolio.
. A study performed by Mansfield & Wagner (1977) showed newer innovations are associated with more
uncertain prospects. This means that newer innovations are also related to more information
complexity. The third hypothesis that was formed is
Analysts’ forecast errors are greater for firms investing in more original technologies and firms
with an increasing speed of innovation
32
The amount of information complexity could also be related to the firm’s regulatory
environment. If the research process is more regulated and transparent, it will lead to more identifiable
changes in the intangible assets and therefore decreasing the amount of information complexity. The
study therefore expects biotech entities, pharmaceutical entities, and entities manufacturing equipment
used in medical treatment to have less complex information, which will lead to more accurate forecasts.
The fourth and last hypothesis therefore is
Analysts’ forecast errors are significantly smaller for firms from the biotech, pharmaceutical, and
medical equipment industries, which are subject to regulatory review of product development
Sample and method
The data that used in this study originated from entities that had to meet certain conditions. The
entities needed to have their data published on the 1999 Compustat merged annual files, and their
analyst earnings forecasts needed to be provided by I/B/E/S. The period that the firm-years were
retrieved from was 1981-1998. This ultimately lead to 18,803 different firm-years that met the two
conditions and were available to the researchers.
To test the first hypothesis, a regression model is generated. Dependent variable of this model is
the analysts’ forecast error for a year. Dependent variables are R&D expenditures, advertising
expenditures, and the amount of intangibles recognized on the balance sheet. There were also several
control variables added to ensure that the intended result was achieved, these control variables were
later also tested for significance. To test the other three hypothesis, another regression analysis is
generated that also has analysts’ forecast error as dependent variable. The difference is that this
regression analysis has more complex control variables.
Results
The results from the first analysis show that the control variables are indeed significant.
Volatility of historical earnings, status of loss, and the firm size are all significantly positively or
negatively associated with analysts’ forecast errors.
The results for the second hypothesis are as predicted. The results indicate that the errors in
analysts’ forecast of future earnings are larger if an entity has higher intangible intensity than its
industry peers. Especially the coefficient of R&D expenditures is the most significant here and therefore
has the most influence.
33
The same results were achieved for the third and fourth hypothesis. At first the results showed
that the diversity and innovativeness of an entity’s technology does have an association with the
amount of forecast errors that are made. If an entity’s portfolio becomes more diverse, the amount of
forecast errors made by analysts increases. What the study also showed was that if the intangibles are
more regulated, the amount of forecast error made by analysts decreases. Therefore the fourth
hypothesis is proven to be right as well.
34
High-technology Intangibles and Analysts’ Forecasts – Barron, Byard, Kile & Riedl (2002)
Hypothesis development
This is a study performed by Orie E. Barron, Donal Byard, Charles Kile and Edward J. Riedl and
was published in 2002.
While developing the hypothesis, the study argues that by capitalizing development costs, an
entity implies that it is confident that the development will generate future economic benefits. By
expensing the costs, it would imply that there is a lower probability that the development will generate
future economic benefits. The study therefore argues that by expensing the costs, the entity seems
more uncertain about the future economic benefits of the development.
A study by Barth, Kasznik and McNichols (2001) shows that analysts favor firms that have high
amounts of intangible assets instead of low amounts, which confirms the statements that were made in
the previous section according to Barron et al. According to Barth, Kasznik and McNichols (2001) the
reason for this extra following is because the intangible assets provide earnings forecasts which are
informative to the analysts. The study performed by Barron et al. wants to provide insight into why this
is, and also whether the capitalization of intangible assets is actually beneficial for the forecasts by the
analysts.
The study then continues to argue that by making use of intangible assets, an entity is able to
match their expenses with their revenues in the future. However, the problem is that the expenses and
revenues associated with the intangible assets are classified as non-recurring by some analysts. This
means that these revenues and expenses are excluded when the analysts calculate the ‘core earnings’.
There is no method for calculating the core earnings, which implicates that all the analysts have to come
up with their own method to exclude the expenses and revenues. This leads to differences in the
valuations made by analysts, and therefore also to differences in the forecasts made by analysts.
Based on this assumptions, the thesis therefore forms the following hypothesis
A lower degree of consensus exists among analysts forecasting earnings for high-intangible firms
than for low-intangible firms.
Sample and method
The sample that was originally derived were 77.420 potential firm-years derive from Compustat
quarterly files. The researchers however had certain conditions set which the firm-years had to meet.
The first condition was that each firm-year’s earnings announcement date needed to be available. The
second condition was that each firm-year had to have a minimum of three forecasts made by individual
35
analysts within 30 days. Only 1103 firm-years consisting of 451 separate entities met those
requirements and were used.
The empirical analysis that was conducted focused on two dependent variables. The first was a
consensus measure which was based on the observed values of the forecast dispersion and the squared
error in the mean forecast. The second variable was a measure of the benefits of aggregating individual
analysts’ forecasts. These variables were tested by regression analysis. There were several equations
that tested whether there was a significant influence of intangible assets on the dependent variables,
these equations also included control variables that were derived from other studies in order to get the
desired result.
Results
The tests that were conducted indicated a significant negative association between the
consensus measure and R&D expenses. It also indicated a negative association between the consensus
measure and the balance sheet intangibles. These first results are therefore not helpful to make an
distinction in results between capitalization and expensing, however later the study provided evidence
that the consensus is lower for high-intangible firms than for low-intangible firms. This difference is
mainly due to costs that were incurred for research and development, the advertising expenses were
insignificant.
The study then provides an alternative interpretation about the negative association between
the consensus and firm’s intangibles, it could be due to the high levels of uncertainty and low across-
analyst correlations in forecast errors. A study performed by Barron, Byard and Kim (2002) provides
evidence that makes this is not true, however the study then still re-estimates the equation to
accommodate any firm characteristic that could potentially lead to greater uncertainty. This should
oppose the effect that could potentially be created by the uncertainty.
The study then finds direct evidence that shows that a lower degree of consensus among the
analysts forecast is measured when a firm has a high amount of intangibles. The study also finds that the
earnings are more difficult to forecast, and the individual forecast errors are also larger for a firm with a
high amount of intangibles. Additional analysis then shows that these effects are mainly attributable to
the amount of R&D investments that an entity has.
36
4 Conclusion
The management of an entity is able to use the capitalization of development costs in two
different ways. Management can use the capitalization to reduce the amount of information asymmetry
between the entity and analysts. They are able to do this by showing the analysts what kind of
developments they are currently working on. The second option for management is to use the
capitalization to manage their earnings. By making use of amortization, it can portray the financial
statements in a better way than it really is. Current earnings are improved significantly, while future
earnings are only decreased slightly.
The sections prior to the literature review did not provide significant evidence that could lead to
an answer for the research question. I therefore conducted the literature review to see whether the
capitalization of development costs has an effect on the analysts’ forecast dispersion. The reason that I
decided to choose the influence on forecast dispersion is to see whether the analysts benefitted and the
information asymmetry was reduced, or that the capitalization only caused more uncertainty and the
information asymmetry was increased.
The literature review did provide an answer, although it was not convincing. I started the
analysis with literature that was in favor of the capitalization of development costs. The study
performed by Matolcsy & Wyatt (2006) showed that there was a positive association between the
capitalization of development costs, and forecast error and forecast dispersion. However this
relationship was only significant in the OLS equation that they conducted. It was not significant in the
2SLS equation. What this shows according to the results in the study is that there is an association
although it is not strong. Anagnostopoulou (2010) was another study that was in favor of capitalization
but was not able to generate convincing results either. They showed that the expensing of research and
development costs is negatively associated with the forecasting errors and accuracy. This means that if
development costs are expensed, the amount of forecast errors increases and the accuracy of the
forecast decreases. The study then showed that there is no significant relationship between the
capitalization of development costs, and the forecast errors and accuracy. The study therefore did show
that capitalization is more favorable, but it did show that with convincing results.
I continued my literature review with studies that were opposed to the capitalization of
development costs, these studies did provide more convincing results. Dinh et al. (2015) showed
convincing evidence that the capitalization of development costs has a significant impact on forecast
errors and forecast dispersion. According to them the capitalization will lead to more forecast errors and
37
to more forecast dispersion as well. Gu & Wang (2005) and Barron et al (2002) showed results that were
very similar. They both showed that the forecast error and accuracy are both affected in a negative way
by the capitalization of intangible assets. The last study that I reviewed was André, Dionysiou &
Tsalavoutas (2018), this study showed that IAS 36 has a negative effect on the forecast error and
dispersion, but that IAS 38 had no significant effect, this makes the result of this study similar to
Anagnostopoulou (2010).
The studies in favor of the capitalization were not able to show evidence that had significant
prove. The studies that were opposed to capitalization of intangible assets did show evidence that was
significant. I therefore conclude that based on the studies that were analyzed, I can say that there is
evidence to conclude that the capitalization of intangibles leads to more dispersion in the forecasts of
analysts. This makes the capitalization of development costs unfavorable for users of the financial
statements compared to the expensing of development costs. Additional research is however required
to show that there is a convincing difference.
38
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