What determines the use of capital budgeting methods?

You are required to search at least FIVE (5) journal research articles related to capital budgeting and investment decision. Based on these research articles, you are required to answer the following questions: 1. In what way is the Net Present Value (NPV) consistent with the principle of shareholder wealth maximization? What happens to the value of a firm if a positive NPV is accepted? If a negative NPV project is accepted? (15 marks) 2. Discuss should capital budgeting decisions be made solely on the basis of a project’s NPV. (15 marks) 3. Explain how the expectation of changing costs of capital can be incorporated into the capital budgeting decisions. (15 marks) 4. In most situations, should firms use a constant or a changing project cost of capital. Why or why not? (15 marks) Assignment Format for Part B: a. Use single space and 12-point of Times New Roman font. b. The assignment should

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This is the published version of a paper published in Journal of Finance and Economics.
Citation for the original published paper (version of record):
Daunfeldt, S-O., Hartwig, F. (2014)
What determines the use of capital budgeting methods?: Evidence from Swedish listed
companies.
Journal of Finance and Economics, 2(4): 101-112
http://dx.doi.org/10.12691/jfe-2-4-1
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Journal of Finance and Economics, 2014, Vol. 2, No. 4, 101-112
Available online at http://pubs.sciepub.com/jfe/2/4/1
© Science and Education Publishing
DOI:10.12691/jfe-2-4-1
What Determines the Use of Capital Budgeting Methods?
Evidence from Swedish Listed Companies
Sven-Olov Daunfeldt1,*, Fredrik Hartwig2
1Department of Trade, Industry and Business, HUI Research and Dalarna University, Stockholm and Borlänge, Sweden
2Department of Trade, Industry and Business, Dalarna University, Borlänge, Sweden
*Corresponding author: [e-mail]
Received March 11, 2014; Revised March 18, 2014; Accepted March 27, 2014
Abstract Purpose: This paper aims to extend and contribute to prior research on the association between
company characteristics and choice of capital budgeting methods (CBMs). Design/methodology/approach: A
multivariate regression analysis on questionnaire data from 2005 and 2008 is used to study which factors determine
the choice of CBMs in Swedish listed companies. Findings: Our results supported hypotheses that Swedish listed
companies have become more sophisticated over the years (or at least less unsophisticated) which indicates a closing
of the theory-practice gap; that companies with greater leverage used payback more often; and that companies with
stricter debt targets and less management ownership employed accounting rate of return more frequent. Moreover,
larger companies used CBMs more often. Originality/value: The paper contributes to prior research within this
field by being the first Swedish study to examine the association between use of CBMs and as many as twelve
independent variables, including changes over time, by using multivariate regression analysis. The results are
compared to a US and a continental European study.
Keywords: investment decisions, capital budgeting methods, project valuation, Swedish listed companies, CFO,
sophisticated use
Cite This Article: Sven-Olov Daunfeldt, and Fredrik Hartwig, “What Determines the Use of Capital
Budgeting Methods? Evidence from Swedish Listed Companies.” Journal of Finance and Economics, vol. 2, no.
4 (2014): 101-112. doi: 10.12691/jfe-2-4-1.
1. Introduction
Management’s investment decision is pivotal for the
success of any company and over the years a number of
capital budgeting methods have evolved. The capital
budgeting method choice is not arbitrary, and textbooks in
financial management often recommend the net present
value method, while discouraging the use of other
techniques, such as the undiscounted payback method
(Brealey and Myers, 2003; Lumby and Jones, 2003; Smart
et al., 2004; Ross et al., 2005).
We use multivariate regression analysis on
questionnaire data from 2005 and 2008 to study which
factors determine the choice of capital budgeting methods
in Swedish listed companies. Our first question is to what
extent the recommended methods actually are used, i.e., is
there a gap between theory and practice? Second, we
investigate the average total use of capital budgeting
methods. Do Swedish listed companies typically use just
one method, or are two or even more used concurrently?
Third, we examine what factors determine the use of the
methods. For example, does size matter as suggested by
Stanley and Block, (1984), Pike (1988, 1996), Graham
and Harvey (2001), Sandahl and Sjögren (2003), and
Brounen et al. (2004)? The relation between size and
eleven other independent variables and eight capital
budgeting methods are analysed. Finally we compare our
results to studies of U.S. (Graham and Harvey, 2001) and
continental European (Brounen et al., 2004) listed
companies, which used data responding to the same
questionnaire as used here.
Capital budgeting decisions are very important for
financial managers, since they determine the choice of
investment projects that will affect company value. The
use of capital budgeting methods by U.S. and European
listed companies has been studied extensively (e.g.,
besides those already mentioned, Pike, 1988, 1989, 1996;
Pike and Sharp, 1989; Sangster, 1993; Block, 2007;
Hermes et al., 2007). [1] There have also been some
earlier studies of Sweden (Renck, 1966; Tell, 1978; Yard,
1987; Andersson, 1994; Segelod, 1995; Sandahl and
Sjögren, 2003; Holmén and Pramborg, 2009; Hartwig,
2012).
The present study differs in one important respect from
previous similar studies, the majority of which are based
on purely descriptive statistics. [2] Most studies thus
explore only use or non-use, or the frequency of use, of
capital budgeting methods, and not the association
between use and independent variables. When
relationships between use and independent variables have
been studied (e.g., Hartwig, 2012), only descriptive
statistical methods such as correlation analysis and
independent-samples t-tests are utilised, so the results
cannot be interpreted causally [3].

102 Journal of Finance and Economics
Our results confirm previous findings that larger
companies tend to use capital budgeting methods more
often when deciding on investments. The choice of capital
budgeting methods is also influenced by financial leverage,
growth opportunities, dividend pay-out policies, the
choice of target debt ratio, degree of management
ownership, foreign sales, and the education and other
individual characteristics of the CEO. The total use of
capital budgeting methods is lower in Sweden than in the
U.S. (Graham and Harvey, 2001), and continental Europe
(Brounen et al., 2004).
The next section presents capital budgeting methods
and explains why some of them are recommended by
textbooks and others not. Data and descriptive statistics on
the use of capital budgeting methods in Swedish listed
companies are presented in Section 3. Section 4 then
presents the empirical method and hypotheses to be tested.
Results are presented and discussed in Section 5. Section
6 summarises and draws conclusions.
2. The Use of Capital Budgeting Methods
When evaluating investments, top managers can choose
among many capital budgeting methods, some
recommended in textbooks, others not. In accordance with
Graham and Harvey (2001), we distinguish twelve capital
budgeting methods (Table 1).
Table 1. Capital budgeting methods, recommended or not by
textbooks
Method Recommended or not
a) Net present value (NPV) Recommended
b) Internal rate of return (IRR) Not recommended
c) Annuity Recommended
d) Earnings multiple (P/E) Not recommended
e) Adjusted present value (APV) Recommended
f) Pay-back Not recommended
g) Discounted pay-back Not recommended
h) Profitability index Recommended
i) Accounting rate of return (ARR) Not recommended
j) Sensitivity analysis Recommended
k) Value-at-risk (VAR) Recommended
l) Real options Recommended
Method Recommended or not
a) Net present value (NPV) Recommended
b) Internal rate of return (IRR) Not recommended
c) Annuity Recommended
d) Earnings multiple (P/E) Not recommended
e) Adjusted present value (APV) Recommended
f) Pay-back Not recommended
g) Discounted pay-back Not recommended
h) Profitability index Recommended
i) Accounting rate of return (ARR) Not recommended
j) Sensitivity analysis Recommended
k) Value-at-risk (VAR) Recommended
l) Real options Recommended
As noted, methods such as net present value (NPV) that
discount cash flows, are often recommended in financial
management textbooks. Brealey and Myers (2003), for
example, has a chapter on “why net present value leads to
better investment decisions than other criteria”. NPV is
recommended since it incorporates all cash-flows that the
investment generates as well as the time value of money.
Other methods, such as the internal rate of return (IRR)
and pay-back methods are often criticised. IRR can be
misleading when a choice must be made among mutually
exclusive projects, and also because of so-called multiple
rates of return (Ross et al., 2005), yet it is often used
(Graham and Harvey, 2001; Sandahl and Sjögren, 2003;
Brounen et al., 2004; Bennouna et al., 2010).
Pay-back methods do not consider the time value of
money, and also ignores cash-flows that occur after the
maximum pay-back time (as defined by management), yet
it is also often used (Graham and Harvey, 2001; Sandahl
and Sjögren, 2003; Brounen et al., 2004; Bennouna et al.,
2010). Discounted pay-back does not ignore the time
value of money, but still ignores cash-flows after the
maximum pay-back point.
The earnings multiple or price/earnings (P/E) method is
a variation on pay-back methods since it calculates how
many years it will take until the initial investment (the
share price) will be paid back by earnings. It considers
earnings instead of cash-flows and only considers one
earnings figure (instead of many), and again does not take
the time value of money into consideration. On the other
hand, this relative valuation method has the advantage of
letting the more or less efficient capital market guide the
decision.
The main disadvantage with ARR is (as the name
suggests) that it uses accounting numbers (instead of cash-
flows) and again does not consider the time value of
money (Ross et al., 2005). Note that management can
affect accounting numbers positively through real actions
even though their actions may have negative effects on
long-term value (Graham et al. (2005).
In principal, sensitivity analysis has no drawbacks, and
should be applied to see whether an investment will still
be profitable if one or more variables are changed.
Another method with no obvious drawbacks is real
options. It has been suggested that the reason why many
projects which look unprofitable at first glance are made
nevertheless is that management explicitly or implicitly
incorporated the possibility of making subsequent
investments (conditioned on the current project) in the
project evaluation.
Value-at-risk (VAR), measuring “…the worst loss over
a target horizon that will not be exceeded with a given
level of confidence” (Jorion, 2006; page viii), is a rather
new method. A disadvantage is that is does not estimate
how bad the loss might be if market conditions turn
abnormal (such as happened widely in 2008-2009).
When the highest net present value per monetary unit of
the initial outlay is calculated, a so-called profitability
index has been established. A potential limitation is that, if
applied carelessly and investment resources are
constrained, it can give bad advice (Brealey and Myers,
2003).
APV adds the value of any financial side-effects of an
investment to NPV, and should in principle have no
drawbacks (Ross et al., 2005). The annuity method is also

Journal of Finance and Economics 103
a variant of NPV. If you know the annuity of an
investment, and how many years it should generate net
cash-inflows or outflows, then you can easily calculate its
NPV by discounting the annuity with the relevant
weighted average cost of capital.
3. Data and Descriptive Statistics
To analyse what determines the choice of capital
budgeting methods in Sweden, a questionnaire (Appendix
1) was sent in 2005 and 2008 to the CFOs of all Swedish
companies listed on the Stockholm Stock Exchange. To
facilitate a comparison between the surveys, the questions
were the same as used by Graham and Harvey (2001) and
Brounen et al. (2004). [4] If no executive had the title
CFO, then the questionnaire was sent to another senior
executive (controller, treasurer, or CEO) responsible for
financial management.
In 2005, the questionnaire was sent to 244 companies
by postal mail three times, with response deadlines 8
January, 14 March, and 23 May. Non-respondents by the
first deadline were contacted by phone to encourage them
to respond. In the end, 112 questionnaires (45.9%) were
returned. However, seven were not useable and were
dropped, leaving an adjusted response rate of 43.0%.
In 2008, the questionnaire was sent to 249 companies
by postal mail four times, with response deadlines 18
February, 10 March, 3 April, and 16 June. Again, non-
respondents by the first deadline were contacted by phone.
In the end, 92 (36.9%) questionnaires were returned. Four
were not useable, leaving an adjusted response rate of
35.3%. The total adjusted response rate for the two
surveys was thus 39.1%, compared to 9% for Graham and
Harvey (2001) and 5% for Brounen et al. (2004).
In simple probit analysis of the response rate the
probability of response was statistically significantly
higher for larger companies, and the probability to answer
the survey was higher in 2005 compared to 2008. Industry
classification, P/E-ratio, degree of leverage, and dividend
pay-out level did not have statistically significant effects
on the probability of response (Table A1 in Appendix 2).
The questionnaire made clear that questions regarding
capital investment referred to all non-routine capital
investments accepted or rejected at group/parent-company
level. The reason for this framing was that otherwise, i.e.,
if questions were taken to refer to all investments in the
company (including investments accepted or rejected at
subsidiary level), then the respondents probably would not
be able to give credible answers.
3.1. Dependent Variables
The questionnaire (Appendix 1) consists of three main
questions regarding the use of capital budgeting and cost-
of-capital estimation techniques. [5] Data from question
one, “How often do you use the following capital
budgeting methods (on a scale of 0 to 4, with 0 = never
and 4 = always)?”, was used to construct our dependent
variables. The capital budgeting methods asked about
were:
a). Net-present value (NPV)
b). Internal rate of return (IRR)
c). Annuity
d). Earnings multiple
e). The adjusted present value (APV)
f). Pay-back
g). Discounted pay-back
h). Profitability index
i). Accounting rate of return (ARR)
j). Sensitivity analysis
k). Value-at-risk (VAR)
l). Real options
The number and share of respondents reporting that
they occasionally or never use or frequently or always use
each method are reported in Table 2. Annuity, adjusted
present value (APV), value-at-risk, and real options were
far less used than the other methods. We excluded them
from further analysis as not providing sufficient variation
to analyze.
Table 2. Number and proportion of companies that used each capital
budgeting Method never or occasionally (0-2) vs frequently or
always (3-4)
Capital budgeting method 0-2 % 3-4 %
(a) NPV 75 38.86% 118 61.14%
(b) IRR 135 69.95% 58 30.05%
(c) Annuity 187 96.89% 6 3.11%
(d) Earnings multiple approach 139 72.02% 54 27.98%
(e) APV 180 93.26% 13 6.74%
(f) Pay-back 88 45.60% 105 54.40%
(g) Discounted pay-back 160 82.90% 33 17.10%
(h) Profitability index 169 87.56% 24 12.44%
(i) ARR 147 76.17% 46 23.83%
(j) Sensitivity analysis 106 54.92% 87 45.08%
(k) VAR 180 93.26% 13 6.74%
(l) Real options 189 97.93% 4 2,07%
The recommended methods used frequently or always
by the most listed companies in Sweden were the net
present value (61%) and sensitivity analysis (45%), but
not recommended pay-back method was used frequently
or always by 54% of the respondents.
Mean values, standard deviations, and differences in
mean values for the most used capital budgeting methods
in 2005 and 2008 are reported in Table 3. Higher mean
values indicate more extensive use of the method.
Table 3. Mean values, standard deviations, and differences in mean
values for the most used capital budgeting methods in 2005 and 2008
2005 2008
Dependent variable Mean Sd Mean Sd Difference
(a) NPV 2.50 1.38 2.55 1.38 0.05
(b) IRR 1.57 1.58 1.27 1.45 -0.30***
(d) Earnings multiple 1.36 1.61 1.41 1.57 0.05
(f) Pay-back 2.39 1.41 2.20 1.47 -0.19
(g) Discounted pay-back 1.08 1.42 0.74 1.31 -0.34***
(h) Profitability index 0.69 1.26 0.72 1.20 0.03
(i) ARR 1.14 1.55 1.05 1.45 -0.10
(j) Sensitivity analysis 1.92 1.63 2.05 1.53 0.12
Note: *** indicates that the difference is statistically significant at the
1% level.
The differences between 2005 and 2008 are small,
usually not significantly different from zero. The biggest
differences are that IRR and the discounted pay-back

104 Journal of Finance and Economics
(both not recommended) were less used in 2008 than in
2005.
Figure 1 compares the total use of capital budgeting
methods by listed Swedish companies (287%) to U.S.
results (413%, Graham and Harvey, 2001) and continental
European results (308-388%, Brounen et. al, 2004). Total
use was calculated as the sum of column 3 on Table 2, and
was thus much lower in Sweden compared to the U.S. and
continental Europe.
The differences between Sweden and the U.S. or
continental Europe are surprising since our data only is
from listed companies, which should mean more use of
capital budgeting methods (since listed companies are
presumably more sophisticated, gathering more
information before making investments).
Figure 1. The total stated use of capital budgeting techniques in Swedish
Figure 2 compares use of each method across countries.
A recommended method that is very uncommon in
Sweden compared to the U.S. and continental Europe is
incorporation of real options. But other recommended
methods such as NPV and sensitivity analysis were used
more frequently by Swedish listed companies than by
most continental European ones.
Figure 2. The stated use of different capital budgeting techniques in Swedish companies compared to companies in the US and continental Europe
3.2. Independent variables
We use information on company size, company
leverage, growth opportunities, dividend payout levels,
industry classification (manufacturing or not), target debt
ratio, proportion of foreign sales, proportion of shares
owned by the management, changes over time (a year
dummy), as well as the age, educational attainment and
the tenure of the CEO to analyze which variables
influence the reported use of capital budgeting methods.
Definitions, means, and standard deviations are presented
in Table 4. The variables included are further discussed in
Section 4.
Data on target debt-ratio, proportion of foreign sales,
proportion of shares owned by management, and
characteristics of the CEO are obtained from the
questionnaire, while data on company size, growth
opportunities, leverage, industry classification, and
dividend payments come from Datastream. [6] Data was
intentionally obtained from Datastream for 2004 and 2007
to prevent a possible endogeneity problem, since previous
year's values are predetermined.

Journal of Finance and Economics 105
Company size is approximated by revenues adjusted for
inflation using the Swedish Consumer Price Index
published by Statistics Sweden. Growth opportunities are
proxied by the price-earnings (P/E) ratio because high
P/E-ratios are thought to mean that the capital market
expects the company to have high future growth, and
leverage is measured by the debt-to-asset ratio. Even
though it may be the CFO who chooses the capital
budgeting method, questions regarding the CEO were
asked since the CFO is seen as the CEO’s agent.
Table 4. Means, standard deviations, definitions and sources of independent variables
Independent
variable
Mea
n SD Definition and source
SIZE (millions) 13.1 31.8 Deflated revenues in SEK. Source: Datastream.
LEVERAGE 0.21 0.19 Total debt to total assets ratio. Source: Datastream.
DIVPAY 0.24 0.96 Dividend pay-out ratio. Dividend divided by net income. Source: Datastream.
GROWTH 9.20 66.44 P/E ratio. Source: Datastream.
DMAN 0.40 0.49 Dummy taking the value one if the company could be classified as manufacturing. Source: Datastream.
TARGET_DEBT 2.24 1.02 Whether the company had no (1) or a strict (4) target debt-ratio. Source: Survey (question 9).
FSALES 3.30 0.98 The proportion of total sales that took place outside Sweden, ranging from 0% (1) to > 50% (4). Source:
Survey (question 12)
MAN_OWN 1.38 0.93
Share of the company that would be owned by the top three officers if all options had been exercised,
ranging from
< 5% (1) to > 20% (4). Source: Survey (question 12).
CEO_AGE 2.43 0.73 Age of the CEO ranging from < 40 years (1) to > 60 years (4). Source: Survey (question 12).
CEO_EDUC 1.82 0.84 Dummy taking the value one if the CEO had a Masters inBusiness and/or Economics. Source: Survey
(question 12).
CEO_TENURE 1.61 0.75 Number of years the CEO had been CEO in the company, ranging from < 4 year (1) to > 9 year (3).
Source: Survey (question 12).
DYEAR 0.46 0.50 Dummy, taking the value one in 2008, zero in 2005.
The relationships among the independent variables were
investigated using Pearson product-moment correlation
coefficients (Table A2 in Appendix 3), with multicollinearity
found to be limited. The highest correlation coefficient
was 0.48, while most were far lower.
4. Empirical Method and Hypotheses
To analyze what determines the reported use of capital
budgeting method, the following equation is estimated
using ordinary least square (OLS):
jit 0 1 it 2 it
3 it 4 it
5 it 6 it
7 it 8 it
9 it 10 it
11 it 12 t it
CBT SIZE GROWTH
LEVERAGE TARGET _ DEBT
DIVPAY FSALES
MAN _ OWN CEOEDUC
CEOAGE CEOTENURE
DMAN DYEAR e
α α α
α α
α α
α α
α α
α α
= + +
+ +
+ +
+ +
+ +
+ + +
(1)
where CBTjit is the reported use of capital budgeting
method j (j=1,2,...,8) by company i (i=1,2,...152) during
year t (t=2005, 2008). As noted earlier, SIZE it is deflated
revenues (for company i during year t); LEVERAGE is the
debt-to-assets ratio; GROWTH is the price-earnings ratio;
TARGET_DEBT reflects a survey question whether the
company had a strict or flexible debt target; MAN_OWN
reflects a survey question on the proportion of shares
owned by management; CEOEDUC reflects the
educational attainment of the CEO; CEOAGE reflects
CEO’s age; CEOTENURE reflects how long the CEO has
had that position; DMAN is a dummy taking the value one
if the company can be classified as a manufacturing
company, and zero otherwise; DIVPAY is company i’s
dividend payout ratio; FSALES reflects a survey question
on the proportion of foreign sales; and DYEAR is a
dummy taking the value zero in 2005, and one in 2008.
When estimating Equation (1), we expect size to be
related to the use of recommended capital budgeting
methods (Pike, 1988, 1996; Graham and Harvey, 2001;
Sandahl and Sjögren, 2003; Brounen et al., 2004;
Verbeeten, 2006) because large companies tend to deal
with larger projects, making the use of more sophisticated
methods less costly (Payne et al., 1999; Hermes et al.,
2007).
We expect high leverage to be related to the use of the
non-recommended pay-back method, which has been
found to be positively associated with economic
uncertainty (Schall and Sundem, 1980; Binder and Chaput,
1996). Simpler rules (such as pay-back) can be more
attractive in an uncertain setting, since the costs of
accurately estimating the inputs for more complicated
discounting-based calculations are higher (Binder and
Chaput, 1996). An alternative explanation as to why high
leverage companies might be expected to use pay-back
more often is that they are under more financial pressure
and might therefore feel a need to find investments that
quickly “pay back” the initial investment.
We expect growth companies to use two recommended
methods more frequently. First, finance textbooks teach
that IRR should not be used to rate mutually exclusive
projects [7], which growth companies might have more of
than mature companies. Growth companies might also be
more likely to calculate the profitability index, because if
they have more potential new investment projects [8], and
thus reject more, it would be important that the accepted
ones give the highest possible NPV per unit invested, and
the only way to establish that is through calculating the
profitability index.
We expect companies with strict debt targets to use the
non-recommended ARR method more often. Companies
which are closer to violating accounting-based debt
covenants have been found more likely to choose income
enhancing accounting solutions which reduce the risk of
“costly” technical default (Watts and Zimmerman, 1990).
The same thing might happen with regard to “internal debt
covenants” (i.e., debt targets); the higher the “cost” of
violating the accounting based debt target, the more the
company might consider how an investment would affect
accounting numbers. Companies with a stricter target
might thus tend to consider an investment’s impact on the

106 Journal of Finance and Economics
accounting debt-ratio to a higher extent (so that the target
debt-ratio is not “violated”). The accounting rate of return
indicates how an investment is expected to affect the debt
ratio, and could therefore be employed more extensively
in strict debt-target companies.
We expect companies with greater management
ownership to use recommended methods more often.
Ownership structure can have an impact on managerial
decisions and company performance (Warfield et al., 1995;
Klassen, 1997), and companies with greater managerial
ownership have been found to be less likely to experience
financial distress (Donker et al., 2009), perhaps because
managers then have more to lose if the company goes
bankrupt. Management ownership may thus reduce
management opportunism and increase use of
recommended capital budgeting methods.
On the other hand, with greater separation of ownership
(principals) and management (agents) incentives can arise
for managers to pursue non-value maximising behaviour
(Jensen and Meckling, 1976). To remedy this, contracts
often stipulate that management’s remuneration should be
based on accounting numbers. Top managers’ discretion
over both business activities and accounting choices
makes it possible for them to manage earnings upwards, to
maximise their own bonus payments (Healy, 1985).
Managers can thus take either accounting actions or
realactions to manage earnings or other accounting
figures (Dechow and Skinner, 2000). [9] Managers
focused on meeting accounting figures might reject a
profitable investment (with positive NPV) if the calculated
accounting rate of return is too low. [10] Graham et al.
(2005) showed that top management was willing to
sacrifice long-term value just to meet accounting targets.
[11] We believe that this focus on accounting numbers is
more profound in companies with low levels of
management ownership, and we therefore expect that
management owned companies use ARR less frequent.
We expect more educated and younger CEOs to use
recommended methods (Hermes et al., 2007), with which
they might be more familiar and to which they might be
more open. We also expect new CEOs to use more
“socially acceptable” (often recommended methods),
whereas CEOs with more company-specific experience
might be more relaxed and choose simpler methods,
perhaps viewing them as “good enough”. But more
experienced CEOs might choose more recommended
methods if taught their value by experience.
There might also be industry-specific differences when
it comes to the use of methods. We expect manufacturing
companies to use more recommended methods because
they are often larger, more capital intensive with higher
sunk costs.
We expect that companies with a higher dividend
payout ratio use profitability index calculations methods
less often because (apart from expectations about future
positive cash flows and profits) a higher dividend payout
indicates that the company is liquid, making capital
rationing less likely.
We expect a positive relation between foreign sales,
presumably reflecting a higher proportion of foreign
investments, with attendent currency and political risks,
and use of sensitivity analysis. Moreover, we expect that
foreign sales is positively associated with the pay-back
method. [12] Holmén and Pramborg (2009) documented
that the use of the payback method increases with political
risk. The suggested reason for the observed positive
relation (between political risk and the pay-back method)
is that political risk is difficult to estimate (i.e. rendering
high deliberation costs).
Finally, we expect more use of recommended methods
in 2008 than in 2005, because the use of capital budgeting
methods has become more sophisticated over time
(Klammer and Walker, 1984; Pike, 1996; Ryan and Ryan,
2002; Sandahl and Sjögren, 2003;Singh et al., 2012;
Bennouna et al., 2010).
5. Results and Discussion
Company size has generally been positively correlated
with the use of recommended capital budgeting methods
(Graham and Harvey, 2001; Brounen et al., 2004). We
find that large companies use NPV (recommended), IRR
(not recommended), pay-back (not recommended), and
sensitivity analysis (recommended) more than small
companies; results for the other methods were smaller and
less statistically significant (Table 5).
Contrary to our results, Graham and Harvey (2001)
found a statistically significant negative relation between
size and pay-back in particular in the U.S., while Brounen
et al. (2004) found no statistically significant relation
between size and pay-back in any of their four continental
European countries (Germany, France, Netherlands, and
UK).
Contrary to our expectations, Swedish listed companies
with higher growth opportunities (which we measured by
their P/E ratio) used IRR (not recommended) more often
but profitability index (recommended) less often. Possibly
the P/E ratio is a bad proxy for growth opportunities, or
maybe “growth companies” actually have or assess fewer
investment opportunities than do mature companies.
High-leverage companies employed the pay-back
method more frequent, confirming our hypothesis that
companies with a high level of financial risk are more
likely to use the non-reommended, and non-discounting
based, pay-back method. However, high leveraged
companies also had a tendency to utilise NPV and IRR,
which both are discounting based methods, more
extensively than low leveraged companies, supporting
results presented previously by Graham and Harvey (2001).
Confirming our expectations, companies with stricter
debt targets used ARR (not recommended) more often.
Companies with stricter debt targets also employed the
profitability index (recommended) more, a result also
found by Graham and Harvey (2001).
Contrary to what we expected, companies with a higher
dividend pay-out level utilised profitability index more
extensively, as well as using IRR (not recommended) and
sensitivity analysis (recommended) more. Companies with
more foreign sales used profitability index less. Moreover,
foreign sales was not significantly positively related to the
use of the pay-back method. The latter result thus fails to
support the findings in Holmén and Pramborg (2009).
Management-owned companies used ARR (not
recommended) and sensitivity analysis (recommended)
less often, supporting previous findings that ownership
structure influence management decisions (Gul et al.,
2002; Hutchinson and Leung, 2007; Siregar and Utama,

Journal of Finance and Economics 107
2008). Management-owned companies might use ARR
because of greater goal-congruence between agent and
principal, with owners more interested in the economic
than accounting returns of an investment. There may also
be other (preferred) communicative and monitoring tools
than formal accounting numbers in companies with high
management (Eng and Mak, 2003), making an investment’s
impact on accounting rate of return not as important.
Table 5. Estimation results
Variable (a) NPV (b) IRR (d) EM (f) PB (g) DPB (h) PI (i) ARR (j) SA
SIZE Coef. 0,00598** 0,00975*** 0,00261 0,00623* 0,00131 -0,00146 -0,00172 0,00742**
t-value 2.28 2.72 0.85 1.94 0.38 -0.75 -0.46 2.61
GROWTH Coef. 0,0033 0,0034** -0,0004 0,0010 0,0015 -0,0021*** 0,0016 0,0022
t-value 1.64 2.00 -0.27 1.06 1.12 -2.76 1.59 1.28
LEVERAGE Coef. 1,15* 1,52** -0,34 1,37** 0,59 -0,11 0,45 0,34
t-value 1.78 2.32 -0.48 2.16 0.89 -0.17 0.61 0.49
TARGET_DEBT Coef. 0,02 0,13 0,00 0,12 -0,06 0,16* 0,30** 0,11
t-value 0.17 1.12 0.04 1.06 -0.60 1.69 2.45 0.89
DIVPAY Coef. -0,12 -0,35*** -0,04 -0,01 -0,19 0,13* 0,05 -0,20*
t-value -1.13 -3.40 -0.24 -0.15 -1.08 1.73 0.41 -1.88
FSALES Coef. 0,06 0,06 -0,05 0,18 0,30 -0,27** -0,09 0,20
t-value 0.54 0.49 -0.32 1.41 0.28 -2.16 -0.70 1.41
MAN_OWN Coef. -0,03 -0,04 -0,24 -0,06 -0,11 0,03 -0,26** -0,33**
t-value -0.18 -0.25 -1.59 -0.45 -0.76 0.30 -2.16 -2.04
CEO_EDUC Coef. 0,01 0,36** 0,22 0,17 0,29** -0,09 0,17 0,25
t-value 0.08 2.34 1.28 1.04 2.14 -0.46 1.09 1.42
CEO_AGE Coef. -0,04 -0,04 -0,13 -0,13 0,11 -0,05 0,34* -0,32*
t-value -0.22 -0.22 -0.63 -0.79 0.67 -0.32 1.95 -1.68
CEO_TENURE Coef. -0,07 0,25 0,05 0,11 0,08 -0,10 -0,13 0,33*
t-value -0.37 1.43 0.25 0.63 0.49 -0.72 -0.80 1.78
DMAN Coef. -0,18 0,25 -0,47* 0,14 0,25 -0,47** -0,13 -0,14
t-value -0.73 1.08 -1.69 0.59 1.11 -2.37 -0.59 -0.51
DYEAR Coef. -0,13 -0,82*** -0,31 -0,41 -0,64*** -0,05 -0,23 -0,33
t-value -0.54 -3.23 -1.08 -1.55 -2.77 -0.24 -0.91 -1.18
CONSTANT Coef. 2,38*** 0,14 2,16** 1,154 0,32 1,88 0,28 1,52*
t-value 3.61 0.17 2.43 1.56 0.50 3.07 0.38 1.80
R2 0.08 0.19 0.08 0.10 0.08 0.15 0.15 0.12
The reduced use of sensitivity analysis (recommended)
by management-owned companies could be interpreted as
contradicting the argument that owner-managers would
tend to use more sophisticated methods. But it could also
be that non-owner managers estimate how sensitive ARR
(rather than, say NPV) is to changes in the assumptions
(thus not necessarily leading to increased shareholder
value). And it could be that non-owner managers make
ARR estimations “internally” (to see how the accounting
numbers are affected), but show NPV-based sensitivity
analyses to other executives/board members to legitimise
their investment choice (Dowling and Pfeffer, 1975; Gray
et al., 1996).
As expected, older CEOs used the accounting rate of
return (not recommended) more often, but sensitivity
analysis (recommended) less. On the other hand, CEOs
with long tenure used sensitivity analysis more often.
Contrary to expectations, more educated CEOs used both
IRR (not recommended) and discounted pay-back (not
recommended) more. A positive association between CEO
education and use of IRR has also been found in the U.S.
(Graham and Harvey, 2001), and the Netherlands,
Germany and France, though not in the UK (Brounen et al.
2004).
Confirming our expectations, manufacturing companies
used earnings multiple approach (not recommended) less,
but also used profitability index (recommended) less,
contradicting our expectations. Finally, IRR (not
recommended) and discounted pay-back (not recommended)
were used less often in 2008 than in 2005. Thus, the use of
recommended methods may not have increased, but the use
of non-recommended methods seems to have decreased.
6. Summary and Conclusions
We analysed what determined the use of capital
budgeting methods in Swedish listed companies in 2005
and 2008. Data on the use of capital budgeting methods
were obtained from a survey sent out to all Swedish
companies listed on the Stockholm Stock Exchange. The
survey is a replica of that used by Graham and Harvey
(2001) and Brounen et al. (2004).
Previous studies have found size to be positively
correlated with the use of some capital budgeting methods.
However, most of these studies were based on descriptive
methods such as correlation analysis and independent
sample t-tests, which are not sufficient to establish
causality. Using multivariate regression analysis, we
found that large companies used net present value
(recommended), internal rate of return (not recommended),
pay-back (not recommended), and sensitivity analysis
(recommended) more than small companies.
Other company-specific variables that seemed to
influence the choice of method were growth opportunities
of the company, leverage, the dividend pay-out ratio,
target debt ratio, the degree of management ownership,
foreign sales, industry and individual characteristics of the
CEO. Our results supported hypotheses that Swedish
listed companies have become more sophisticated over the
years (or at least less unsophisticated); that companies
with greater leverage used payback more; and that
companies with stricter debt targets and less management
ownership employed ARR more.
Surprisingly, companies with more educated CEOs
used non-recommended methods such as IRR and
discounted pay-back more than others. Possibly it is the
characteristics of the CFO (not the CEO) that influence
the choice of capital budgeting methods, which is thus a
topic for further study.

108 Journal of Finance and Economics
The reported use of capital budgeting methods was
compared to U.S. and continental European studies. Total
use of capital budgeting methods was higher in the U.S.
(Graham and Harvey, 2001) and in continental Europe
(Brounen et al., 2004) than in Sweden. This is surprising
since data only is from listed companies, whereas both
non-listed as well as listed companies were included in
Graham and Harvey (2001) and Brounen et al. (2004). It
can be assumed that listed companies are more
sophisticated, gathering more information before making
investments, which should mean more extensive use of
capital budgeting methods.
Our study measured only reported use of capital
budgeting methods, not actual use; i.e., we measured
beliefs rather than actions. We cannot be sure what
methods were actually used. But our survey nevertheless
enabled a broad and rich overview of capital budgeting
methods in Sweden, facilitating comparisons between
countries and over time.
Notes:
1. The use of capital budgeting method has also been
studied in other parts of the world, including Australia
(Truong et al., 2008) and Asia (Kester et al., 1999; Kwong,
1986), but not to the same extent.
2. Hermes et al. (2007) is an exception, but was mainly
interested in exploring country differences in the use of
capital budgeting methods. Silvola (2006) is another
exception, but only investigated whether small high-tech
companies in Finland used other capital budgeting
methods than did small companies in other industries.
Finally, Holmén and Pramborg (2009) used logit
regression to investigate whether the use of capital
budgeting methods for foreign direct investments was
related to the political risk in the host country.
3. Hartwig (2012) found a positive correlation between
company size and use of the net present value method,
with two possible non-causal explanations: (i) the use of a
more sophisticated methods such as net present value
could lead to better growth opportunities and thus to larger
companies; or (ii) an omitted variable, such as CEO
education, could cause both better growth opportunities
and choice of capital budgeting method.
4. Graham and Harvey (2001) - declared the best paper
published in the Journal of Financial Economics in 2001 –
is very often referred to in both academic journals and
textbooks.
5. The questionnaire also includes questions regarding
financing decisions. Those answers are analysed in a
separate study.
6. In a few instances, when data was not available from
Datastream, it was obtained directly from the company.
7. Investment projects are said to be mutually exclusive
if only one could be accepted.
8. In mature companies, a larger portion of the total
capital investment budget might consist of reinvestments.
Since the business activities to a higher extent are given in
a mature company (at least in the short to medium run),
one could expect that the number of potential investment
projects are fewer.
9. “Real actions” refers to actions that affect cash flows.
10. Calculating accounting rate of return on investments
gives an approximate estimate of how accounting ratios
(like return on assets) would be affected.
11. The fact that top managers in general do not believe
that the capital market is able to see through managed
financial statements (Collison et al., 1996; Tzovas, 2006),
is probably a contributing factor as to why they focus on
accounting numbers.
12. Naturally, we do not know how much political risk
companies with foreign sales (which is a proxy for foreign
investments) are exposed to. It is, however, probable that
companies with a lower proportion of foreign
sales/investments, all other things held constant, are
exposed to less political risk.
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Appendix 1
The questionnaire (English translation of questions)
Instructions:1) The survey concerns investment- and
financing issues that are decided at top management or
board level in the parent company/group. This is a top
management perspective and the survey questions do not
apply to small routine decisions. 2) When questions are
asked about investments below, tangible (e.g. properties)
as well as intangible (e.g. R&D) and financial investments
(e.g. corporate acquisitions) are referred to. The questions
regarding investments apply to all non-routine
investments decided at top management or board level in
the parent company/group.

110 Journal of Finance and Economics

Journal of Finance and Economics 111

112 Journal of Finance and Economics
Appendix 2
Table A1. Non-response analysis. Probit regression. Dependent variable equals one if the company respondedto the survey, otherwise zero
Independent variable Estimate z-value
SIZE 6.66e-09** 2.78
LEVERAGE -0.00092 -0.31
DIVPAY -0.00029 -0.57
GROWTH 0.00047 0.54
DMAN 0.014 0.12
DYEAR -0.20* -1.70
Pseudo R2 0.02
Number of obs. 493
***=significant at the 1% level, **=significant at the 5% level, *=significant at the 10% level.
Appendix 3
Table A2. Pearson correlation coefficients of independent variables used in the empirical analysis
SIZE LEVERAGE GROWTH TARGET_DEBT MAN_OWN CEOEDUC CEOAGE CEOTENURE DMAN DIVPAY FSALES DYEAR
SIZE 1
LEVERAGE 0,058 1
GROWTH 0,026 0,026 1
TARGET_DEBT -0,038 0,240*** 0,197*** 1
MAN_OWN -0,161** 0,023 -0,049 -0,122 1
CEOEDUC 0,002 0,077 -0,037 -0,060 0,040 1
CEOAGE 0,210*** -0,003 0,054 -0,016 0,113 -0,228*** 1
CEOTENURE -0,006 0,105 -0,064 -0,035 0,426*** -0,150** 0,277*** 1
DMAN 0,112 0,028 0,014 -0,099 -0,048 -0,053 -0,074 0,098 1
DIVPAY 0,165** 0,046 0,321 0,089 -0,111 0,065 0,045 0,007 0,058 1
FSALES 0,166 -0,0125 -0,149 -0,129* 0,001 -0,095 0,020 0,118 0,378*** 0,026 1
DYEAR 0,090 0,086 -0,073 -0,002 -0,010 0,480*** -0,118 -0,061 0,035 0,037 -0,111 1
***=significant at the 1% level, **=significant at the 5% level, *=significant at the 1% level.